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Simplified adenine base editors improve adenine base editing efficiency in rice

Summary Adenine base editors (ABEs) have been exploited to introduce targeted adenine (A) to guanine (G) base conversions in various plant genomes, including rice, wheat and Arabidopsis. However, the ABEs reported thus far are all quite inefficient at many target sites in rice, which hampers their applications in plant genome engineering and crop breeding. Here, we show that unlike in the mammalian system, a simplified base editor ABE‐P1S (Adenine Base Editor‐Plant version 1 Simplified) containing the ecTadA*7.10‐nSpCas9 (D10A) fusion has much higher editing efficiency in rice compared to the widely used ABE‐P1 consisting of the ecTadA‐ecTadA*7.10‐nSpCas9 (D10A) fusion. We found that the protein expression level of ABE‐P1S is higher than that of ABE‐P1 in rice calli and protoplasts, which may explain the higher editing efficiency of ABE‐P1S in different rice varieties. Moreover, we demonstrate that the ecTadA*7.10‐nCas9 fusion can be used to improve the editing efficiency of other ABEs containing SaCas9 or the engineered SaKKH‐Cas9 variant. These more efficient ABEs will help advance trait improvements in rice and other crops.

Introduction
The clustered regularly interspaced short palindromic repeat (CRISPR)-CRISPR-associated protein (Cas) is an immune system of bacteria and archaea that can protect them from infectious nucleic acids or other foreign genetic elements (Hille et al., 2018). Owing to its simplicity, the class 2 CRISPR-Cas system has been repurposed for genome editing in a wide range of organisms, including many plant species (Chen et al., 2019;Komor et al., 2017;Mahfouz et al., 2014;Mao et al., 2017). The endonuclease Cas9 (or Cas12a or Cas12b) proteins from class 2 type II (or V) CRISPR-Cas systems can target a specific DNA sequence under the guidance of an sgRNA (or crRNA), where they generate a DNA double-stranded break (DSB) (Cong et al., 2013;Mali et al., 2013;Teng et al., 2018;Zetsche et al., 2015). The DSB is mainly repaired through the non-homologous end joining (NHEJ) pathway in most eukaryotic cells, which can induce random insertions or deletions (indels) at the DNA cleavage site (Carroll, 2014). In contrast, base editing, a newly developed genome editing tool based on the CRISPR-Cas9 system, enables targeted base conversions without inducing DSBs or requiring exogenous repair template DNA (Gaudelli et al., 2017;Komor et al., 2016;Rees and Liu, 2018). Therefore, base editing is a promising tool for precision molecular breeding because the varietal differences in many important agronomic traits in crops are determined by one or a few base changes . Cytosine base editor (CBE), the first member in the base editing toolbox, can convert cytidine (C) to thymidine (T) (or G to A) at specific genomic sites in an sgRNA-dependent manner (Komor et al., 2016). The most commonly used CBEs in plants consist of a Cas9 nickase (nSpCas9 (D10A)) fused with a cytidine deaminase and a uracil glycosylase inhibitor (UGI) Lu and Zhu, 2017;Qin et al., 2019a;Shimatani et al., 2017;Zong et al., 2017). Although the CBEs have been shown to be functional in many plant species, the narrow target range and low editing efficiency considerably limit their application in crop breeding. Recently, the target scope of CBEs in plants was expanded by constructing new CBEs with different Cas9 variants (Hua et al., 2019;Qin et al., 2019b). Moreover, the editing efficiency of CBEs in plants was improved by exploiting different cytidine deaminases, such as human AID and APOBEC3A Zong et al., 2018).
In addition to the CBEs, adenine base editors (ABEs) were recently developed that can introduce targeted A to G (or T to C) substitutions in a programmable manner (Gaudelli et al., 2017). The ABEs consist of a Cas9 nickase (or nuclease dead Cas9, dCas9) fused with an evolved adenine deaminase TadA from E. coli (Gaudelli et al., 2017). Of note, the adenine base editors used for genome editing in bacteria and mammalian cells are different. The ABEs that work efficiently in bacteria contain the evolved TadA variant ecTadA* fused to the dCas9 protein. However, in mammalian cells, providing the ecTadA*-nSpCas9 (D10A) fusion with a wild-type ecTadA or an additional evolved ecTadA* monomer is necessary for efficient base editing (Gaudelli et al., 2017). This difference is attributed to the biochemical property of tRNA deaminase TadA as a homodimer (Losey et al., 2006). The E.coli genome encodes a wild-type ecTadA that can assist adenine base editing of the ecTadA*-dCas9 fusion. But the human genome lacks an ecTadA homolog, thus necessitating the in-cis tethering of a wild-type ecTadA to support base editing of the ecTadA*-nSpCas9 (D10A) fusion (Gaudelli et al., 2017). The ABE architecture used for human genome editing has since been adopted to perform adenine base editing in other eukaryotes (Liang et al., 2018;Liu et al., 2018a,b;Ma et al., 2018;Ryu et al., 2018;Yang et al., 2018), including various plant species (Hua et al., 2018;Kang et al., 2018;Li et al., 2018;Negishi et al., 2019;Wang et al., 2019;Yan et al., 2018). However, results from several groups indicated that ABEs containing the ecTadA-ecTadA*7.10-nSpCas9 (D10A) fusion are quite inefficient at many target sites in plants, especially in rice (Hua et al., 2018;Li et al., 2018;Yan et al., 2018). It is not known whether the ABE architecture used for E.coli genome editing may work more efficiently in plants.
In this study, we used the ecTadA*7.10-nSpCas9 (D10A) fusion to perform adenine base editing in rice and found that it has much higher editing efficiency compared to the widely used ABEs consisting of the ecTadA-ecTadA*7.10-nSpCas9 (D10A) fusions. Moreover, we demonstrate that this strategy can also be used to improve the editing efficiency of other ABEs containing SaCas9 or the engineered SaKKH-Cas9 variant.

Results and discussion
To test whether the ABE architecture used for E. coli genome editing may work in plants, we fused ecTadA*7.10 to the Nterminus of nSpCas9 (D10A), generating a simplified adenine base editor, ABE-P1S ( Figure 1a). In order to test the editing activity of ABE-P1S in rice, we first targeted the OsSPL14 and SLR1 genes in the rice variety Nipponbare. In our previous study, both genes could be modestly edited by ABE-P1, which contained the widely used ecTadA-ecTadA*7.10-nSpCas9 (D10A) fusion ( Figure 1a) (Hua et al., 2018). At the sgRNA1 target site in OsSPL14 (Figure 1b), we surprisingly found that the base editing efficiency of ABE-P1S (70.6%, 12/17) was 1.9-fold higher than that of ABE-P1 (37.5%, 18/48) (Table 1). We also found that the base editing window of ABE-P1S at the OsSPL14 target site was expanded ( Figure 1c). Adenines at positions 1, 3, 5, 7, 10 and 12 in the protospacer region of OsSPL14 could be efficiently edited by ABE-P1S (Figure 1c), whereas ABE-P1 only edited adenines at positions 5, 7 and 10 ( Table S1). The base editing efficiency of ABE-P1S at the sgRNA2 target site SLR1 (35%) was twice of that of ABE-P1 (17.5%) (Table 1). Then, we designed an sgRNA (sgRNA3) that targets OsSERK2 (Figure 1d), which was previously reported to be edited by the pUbi:rBE14 editor containing the ecTadA-ecTadA*7.10-nSpCas9 (D10A) fusion (editing efficiency 32.1%; Yan et al., 2018). Our base editor ABE-P1 with a similar architecture as pUbi:rBE14 achieved a much higher editing rate at this site (66.6%, 26/39) (Table 1), a 1.1-fold increase compared to pUbi:rBE14. Interestingly, ABE-P1S further improved the editing efficiency to 77.8% (21/27) (Table 1), a 20% increase compared to ABE-P1. Importantly, we found that thymines at positions 6 and 8 in the protospacer of OsSERK2 could be efficiently edited by both ABE-P1 and ABE-P1S ( Figure 1e and Table S1), whereas the previous study showed that only the thymine at position 6 in the protospacer could be edited . The above results suggest that the simplified base editor ABE-P1S has much higher editing efficiency in rice compared to the widely used ABEs containing the ecTadA-ecTadA*7.10-nSpCas9 (D10A) fusion.
To test whether ABE-P1S has a higher editing efficiency in other rice genetic backgrounds, we also chose the rice variety Kitaake for transformation. We designed an sgRNA (sgRNA4) that targets Tms9-1 (Figure 1f), which failed to be edited by the pUbi: rBE14 editor in the Kitaake background in a previous report . However, using our ABE-P1 base editor, we identified one editing event from 22 transgenic lines (Table 1). Thus, the adenine base editor ABE-P1 used in our study was more efficient than the previously reported pUbi:rBE14 editor at the Tms9-1 target site, although they have a similar architecture. We note that the nuclear localization sequence and the codon usage of SpCas9 and ecTadA in ABE-P1 and pUbi-rBE14 are different, which may affect their nuclear targeting efficiencies and expression levels. The different base editing rates between ABE-P1 and pUbi-rBE14 at the same target site may be a reflection of these differences. Using the ABE-P1S base editor, 4 out of 36 lines were found to harbour a T-C conversion at the 5th position in the protospacer of Tms9-1, with the Line 2 having a homozygous substitution ( Figure 1g and Table S1). Next, we selected three target sites with base editing efficiencies ranging between 15% and 40% from the study of Li et al. (2018). Interestingly, both ABE-P1 and ABE-P1S gave very high editing rates at these three target sites (Table 1). At the sgRNA5 target site OsNRT 1.1B, the base editing efficiency of ABE-P1S was up to 96.3% (52/54), 1.3fold higher than that of ABE-P1 (72.9%, 27/37; Table 1). We observed comparable base editing efficiencies at the sgRNA6 target site OsACC1 for ABE-P1 (69.4%) and ABE-P1S (73.8%) ( Table 1). However, the editing efficiency of ABE-P1S at the sgRNA7 target site OsDEP1 (71.4%) was slightly lower than that of ABE-P1 (80%) ( Table 1). Since ABE-P1 already has high editing rates at the three target sites in the Kitaake background (averaging 74%), it seems difficult to improve the editing efficiencies further using ABE-P1S.
To evaluate the specificity of ABE-P1 and ABE-P1S in rice, we sequenced the potential off-target sites of sgRNA1 and sgRNA6. ABE-P1 and ABE-P1S did not induce any mutation at the potential off-target sites of sgRNA6 in the Kitaake background (Table S4). Consistent with our previous study (Hua et al., 2018), ABE-P1 was highly specific when guided by sgRNA1 (Table S3). However, we found that ABE-P1S could induce base conversion at offtarget site 1 of sgRNA1, which has one mismatch to sgRNA1 at the fifth position upstream of the PAM sequence ( Figure S1a, b and Table S3). As ABE-P1 and ABE-P1S both rely on SpCas9 to recognize target sites, we speculate that the base conversion at off-target site 1 by ABE-P1S may be due to its higher editing activity.
Since simplifying the adenine base editor ABE-P1 containing SpCas9 can significantly improve base editing efficiency in rice, we hypothesized that this effect might extend to other adenine base editors containing different Cas9 proteins. So we sought to simplify the adenine base editor ABE-P2 (Figure 2a), which relies on SaCas9 to recognize target sites. We have previously demonstrated that ABE-P2 can edit endogenous genes in rice (Hua et al., 2018). We fused ecTadA*7.10 to the N-terminus of nSaCas9 (D10A) to obtain the adenine base editor ABE-P2S ( Figure 3a). We first designed sgRNA8 to target the OsmiR827 binding site in SPX-MFS2 (Figure 3b) to compare the editing efficiencies between ABE-P2 and ABE-P2S in rice. For the base editor ABE-P2, 4 out of 41 transgenic lines were found to have a single T-C substitution at the target site ( Table 2). The thymine at position 1, 9 or 15 in the protospacer region could be edited (Table S2), but no transgenic line showed a homozygous substitution. The base editing efficiency of ABE-P2S at the SPX-MFS2 target site was 14.9% (7/47) (Table 2), which was 1.5-fold higher than that of ABE-P2 (9.8%). Base conversions were found at position (s) 3, 6, 9 or 15 in the protospacer region of SPX-MFS2 (Table S2), with one transgenic line, Line 38, showing a homozygous T-C substitution at position 6 in the protospacer of SPX-MFS2 ( Figure 2c). In addition, we designed sgRNA9 and sgRNA10 to test whether ABE-P2S may outperform ABE-P2 when multiple sites in the rice genome are simultaneously targeted. The sgRNA9 was designed to simultaneously target the OsmiR156 binding  (Table 2). Among the edited plants, 15 lines were simultaneously modified at both sites ( Table 2). The base editing efficiency of ABE-P2S at the OsSPL17 target site was 30% higher than that achieved by ABE-P2 (61.1% vs 46.4%) ( Table 2). At the OsSPL14 target site, the base editing efficiency of ABE-P2S was 1.4-fold as high as that of ABE-P2 (55.6% vs 39.3%; Table 2). The sgRNA10 targets the OsmiR156 binding sites in OsSPL16 and OsSPL18 (Figure 3e). The base editing efficiencies of ABE-P2S at these two target sites were 30.3% (10/33) and 39.4% (13/33) (Table 2), respectively, which were 78% and 68% higher compared to that achieved by ABE-P2 in our previous work (17% at OsSPL14 and 23.4% at OsSPL18; Hua et al., 2018). Moreover, 5 lines were simultaneously edited at both sites (Table 2). Interestingly, we found that compared to ABE-P2, the base editing window of ABE-P2S at some target sites was also expanded, as even the thymine at position 17 in the protospacer region of OsSPL14 or OsSPL18 could be efficiently edited (Figure 2d, e and Table S2). Taken together, these results show that ABE-P2S has a higher editing efficiency compared to ABE-P2 in rice and the deamination window of ABE-P2S is also expanded at some target sites. To evaluate the specificity of ABE-P2S, we amplified and sequenced the potential off-target sites of sgRNA9 and did not detect any off-target editing at these sites, suggesting that ABE-P2S is highly specific at the sgRNA9 target site (Table S5).
Previously, we showed that the base editing efficiencies of ABE-P4 (containing the VRER-Cas9 variant) and ABE-P5 (containing the SaKKH-Cas9 variant) at all selected target sites were lower than 10% (Hua et al., 2019). We wondered whether the simplified ecTadA*7.10-nCas9 fusion can also improve the base editing efficiency of these adenine base editors with engineered Cas9 variants. We chose ABE-P5 (Figure 2a) to test this hypothesis in rice. We constructed the simplified base editor ABE-P5S by fusing ecTadA*7.10 to the N-terminus of nSaKKH-Cas9 (D10A) (Figure 2a). In order to directly compare the base editing efficiencies of ABE-P5 and ABE-P5S in rice, we first selected OsSPL13 as a target. The sgRNA11 was designed to target the OsmiR156 binding site in OsSPL13 followed by an TTAGGT PAM sequence (Figure 2f). This site was totally resistant to editing by ABE-P5 in our previous work (Hua et al., 2019). Here, we obtained 46 transgenic lines for ABE-P5 and only one line was identified to have a slight fraction with T-C substitution at position 11 in the protospacer of OsSPL13 (Figure 2g). For the base editor ABE-P5S, 2 out of 33 lines were found to harbour an T-C substitution at position 7 or 9 in the protospacer of OsSPL13 (Figure 2h and Table S2). Thus, the base editing efficiency of ABE-P5S at OsSPL13 target site is 2.8-fold as high as that of ABE-P5 (6.1% for ABE-P5S vs 2.2% for ABE-P5; Table 2). To further compare the efficacy between ABE-P5 and ABE-P5S, we designed sgRNA12 that targets the OsmiR172 binding site in SNB. The ABE-P5 achieved a base conversion rate of 9.1% (2/22) at this site, and only the adenine at position 4 in the protospacer region could be modestly edited (Table 2 and Table S2). In contrast, the base editing efficiency of ABE-P5S was increased to 33.9% (21/62), a 2.7-fold increase compared to ABE-P5 (Table 2), and the adenine at position 4, 8, or 9 in the protospacer of SNB could be efficiently edited (Table S2). Collectively, these results suggest that simplifying ABE-P5 to ABE-P5S can also improve the adenine base editing efficiency in rice.
Our findings here appear to contradict previous adenine base editing results in mammalian and plant systems because it has been widely accepted that eukaryotic cells need an additional ecTadA monomer to assist ecTadA*7.10-nSpCas9 (D10A) for efficient base editing (Gaudelli et al., 2017). However, it should be noted that this inference was based on an early-stage evolved ecTadA* variant (ecTadA*2.1), which showed relatively low adenine base editing activity even when provided with an additional ecTadA monomer (Gaudelli et al., 2017). Whether the later-stage evolved ecTadA* monomers, especially the highly active ecTadA*7.10 variant, alone can support efficient base editing when fused with nSpCas9 (D10A), had not been tested.
The native TadA deaminase functions as a homodimer (Losey et al., 2006). Therefore, it is possible that the ecTadA*2.1-nSpCas9 (D10A) relies on intermolecular dimerization to support a low efficiency adenine base editing in mammalian cells (Gaudelli et al., 2017). This dimerization may occur between two ecTadA*2.1 monomers. We speculated that ecTadA*7.10-nSpCas9 (D10A) may intermolecularly dimerize in the nuclei of plant cells. Bimolecular fluorescence complementation (BiFC) assays suggested that ecTadA*7.10-nSpCas9 (D10A) indeed can dimerize in the nuclei of tobacco leaf cells and the intermolecular dimerization is mediated by ecTadA*7.10 (Figure 3a and b).
Although the ecTadA*7.10-nSpCas9 (D10A) can self-dimerize to support adenine base editing, the underlying reasons for its higher base editing efficiency was not known. Recent studies in mammalian cells and plants suggested that the protein levels and nuclear targeting efficiencies of base editors are highly correlated with their editing efficiencies (Koblan et al., 2018;Wang et al., 2019;Zafra et al., 2018). The ABE-P1S and ABE-P1 used the same nuclear localization signal (NLS) from the Agrobacterium VirD2 protein (Data S1). BiFC assays indicated that the NLS from VirD2 is highly efficient for nuclear targeting as ecTadA*7.10-nCas9 (D10A) dimerizes only in the nucleus, as evidenced by the yellow fluorescence signal exclusively in the nucleus (Figure 3b). Therefore, we believe that ABE-P1S and ABE-P1 both have a high nuclear targeting efficiency, although we cannot exclude that an additional wild-type ecTadA at the N-terminus of ABE-P1 may compromise its nuclear targeting. Since the nucleotide sequence of wild-type ecTadA is nearly the same as the ecTadA*7.10 variant (97.2% identity, see Data S1), we wondered whether the tandem repeat of ecTadA sequences at the N-terminus of ABE-P1 may reduce its expression levels in rice due to potential gene silencing. Therefore, we examined the protein levels of ABE-P1 and ABE-P1S in rice calli after a 1-month selection. In the Nipponbare background, we found that the protein level of ABE-P1S was much higher than that of ABE-P1 (Figure 3c). In the Kitaake background, ABE-P1S also accumulated to a much higher level than ABE-P1 (Figure 3d). To exclude the position effect of T-DNA random insertion on the expression level of the different base editors, we transiently expressed ABE-P1S and ABE-P1 in rice protoplasts and compared their protein levels. We found that the protein level of ABE-P1S was also substantially higher than that of ABE-P1 in rice protoplasts (Figure 3e). Collectively, our results suggest that removing wild-type ecTadA from ABE-P1 helps to improve the protein level of the base editor, which may account for the higher editing efficiency of the simplified base editor in rice.
In summary, we have demonstrated that the ecTadA*7.10-nCas9 fusion is a general strategy that can be used to improve the base editing efficiency of ABEs containing different Cas9 proteins or variants in rice. The newly developed ABEs can achieve base conversion rates over 50% at many target sites, with the highest ones up to 96.3% (Tables 1 and 2). Moreover, our improved ABEs showed expanded base editing window at some target sites and did not induce any unintended base changes or indels at any  (c, d, e, g, h). Arrows point to the positions with an edited base (c, d, e, g, h). of the tested target sites. The improved efficiencies of the simplified adenine base editors may be explained at least in part by their improved protein levels (Figure 3c-e). It would be worth to test whether the simplified ABEs may also have higher protein levels and base editing efficiencies in Arabidopsis and other plants. Our findings will boost the application of adenine base editing in crop trait improvements. Nevertheless, we note that some target sites in rice were still inefficiently edited (Tables 1  and 2), implying a need for further optimization of these ABEs. In mammalian and plant systems, it has been reported that the base editing efficiency is highly correlated with the expression levels of adenine and cytosine base editors (Koblan et al., 2018;Wang et al., 2019;Zafra et al., 2018). Through changing the codon usage of base editors, modifying the number and position of the nuclear localization signals (NLS) and using ancestral deaminase component, the expression level and nuclear targeting of base editors can be significantly improved to increase the base editing efficiency ( 2018). The TadA deaminase and different Cas9 proteins used in this study were human-codon optimized (Data S1), indicating that there are opportunities for further codon optimization to improve the editing efficiency of adenine base editors in plants.

Plasmid construction
The nucleotide sequences of key components in the new adenine base editors developed in this study have been published (Hua et al., 2019) and are provided in the Data S1. The simplified base editors ABE-P1S and ABE-P2S were constructed based on our previous reported vectors pRSp-OsU6 and pRSa-OsU6 (Hua et al., 2018). The ecTadA*7.10 coding sequence with a 96 bp linker was inserted between two AarI sites of pRSp-OsU6 and pRSa-OsU6 by the Golden Gate method, leading to the pRSABESp-OsU6 (ABE-P1S) and pRSABESa-OsU6 vectors. A PCR fragment comprised of the OsU6 promoter, two BsaI sites and the sgRNA Figure 3 Detection of the self-dimerization of ecTadA*7.10-nSpCas9 (D10A) in tobacco leaf and protein levels of ABE-P1 and ABE-P1S in rice. a, Schematic diagrams of different coding sequences used in the BiFC assay. NLS, nuclear localization signal from the Agrobacterium VirD2 protein. b, BiFC assay testing interactions between TadA7.10-nSpCas9 and TadA7.10nCas9, and between TadA7.10 and nCas9 in tobacco leaves. BF, bright field; nYFP, Nterminal portion of enhanced yellow fluorescent protein; cYFP, C-terminal portion of enhanced yellow fluorescent protein. Scale bars, 50 lm. c, Detection of ABE-P1 and ABE-P1S proteins in transgenic calli from Nipponbare. ABE-P1 and ABE-P1S vectors contain sgRNA1 that targets OsSPL14. Upper panel, ABE-P1 and ABE-P1S were immunoblotted with an anti-SpCas9 antibody. Lower panel, actin was immunoblotted with an anti-actin antibody and was used as a loading control. d, Detection of ABE-P1 and ABE-P1S proteins in transgenic calli from Kitaake. ABE-P1 and ABE-P1S vectors contain sgRNA5 that targets OsNRT1.1B. e, Protein levels of ABE-P1 and ABE-P1S in rice protoplasts. ABE-P1 and ABE-P1S vectors containing the sgRNA1 or sgRNA5 were transformed into the protoplasts isolated from the leaf sheaths of Nipponbare seedlings grown in the dark. All the sgRNAs used in this study were selected from previous reports (Hua et al., 2018(Hua et al., , 2019Li et al., 2018;Yan et al., 2018), except the sgRNA8 that targets to SPX-MFX2. The sgRNAs inserted into the binary vectors through Golden Gate method. Before rice transformation, the accuracy of sgRNA sequences was confirmed by Sanger sequencing. Primers for sgRNAs used in this study are shown in Table S6.

Rice transformation
Two rice varieties Nipponbare (Oryza sativa L. japonica. cv. Nipponbare) and Kitaake (Oryza sativa L. japonica. cv. Kitaake) were used for Agrobacterium-mediated rice transformation. The embryogenic calli were induced from mature seeds of these two varieties and infected by Agrobacterium tumefaciens strain EH105 at 22°C in the dark for 3 days. After repeat washing the infected calli with water containing 250 mg/L carbenicillin, rice calli were selected on the selection medium (containing 40 mg/L hygromycin and 250 mg/L carbenicillin) for 2 weeks at 30°C in the dark. Then, the hygromycin-resistant calli were transferred to the regeneration medium (also containing 40 mg/L hygromycin and 250 mg/L carbenicillin) for shoot induction at 30°C under cold fluorescent light. To examine the protein level of ABE-P1s and ABE-P1 in rice calli, these hygromycin-resistant calli were selected for another 2 weeks on the fresh selection medium. All resistant calli derived from one infected callus were pooled together for protein extraction. The young plantlets that grew vigorously on the regeneration medium were transferred to rooting medium for root induction. Two weeks later, the plantlets were ready for transplanting to soil and grew in glasshouseunder the standard conditions for rice (12-h light 28°C and 12-h darkness at 22°C). The tissue culture medium that we used for rice transformation was previously reported (Nishimura et al., 2007).

BiFC assay
The coding sequences of ecTadA*7.10-nCas9 (D10A)-NLS, ecTadA*7.10 and nCas9 (D10A)-NLS were PCR amplified from the pRSABESp-OsU6 vector and in-frame cloned into p2YN and/ or p2YC vectors by Gibson assembly. The accuracy of all recombinant vectors was confirmed by Sanger sequencing. The empty and recombinant vectors were then transformed into A. tumefaciens GV3101 by the freeze-thaw method. Single clone of Agribacterium was first inoculated into 5 mL LB medium with antibiotics and grown overnight at 28°C in the dark, and then, 100 lL of the culture was transferred to fresh 5 mL LB medium containing antibiotics. The fresh culture was kept growing at 28°C until the OD600 reaches 3.0. The Agrobacteria cells were harvested by centrifugation, and the pellets were resuspended in the infiltration buffer (10 mM MgCl 2 , 10 mM MES, pH5.6, 100 lM acetosyringone) to an OD600 of 0.8. All p2YN/p2YC combinations were mixed in equal volume and incubated at room temperature for 2 h. The prepared suspensions were infiltrated into N. benthamiana leaves with a needleless syringe. Three days after infiltration, the yellow fluorescence signals were monitored using a confocal scanning laser microscopy (Leica SMD FLCS Confocal System).

Rice protoplast isolation and transformation
The de-husked Nipponbare seeds were surface-sterilized in 2% sodium hypochlorite for 30 min followed by rinsing with sterile water. The healthy seeds were selected for germination on 1/2 MS medium and then grown at 28°C in the dark for 10 days. Fifty rice seedlings were used for protoplast isolation. Rice protoplast isolation was performed as previously described (He et al., 2016). For protoplast transformation, 10 lL (1 lg/lL) plasmid DNA was mixed with 200 lL protoplasts and 210 lL PEG solution (40% w/ v PEG4000, 0.2 M mannitol and 0.1 M CaCl 2 ). The mixture was incubated at room temperature for 20 min, and the transformation reaction was quenched by adding 1 mL W5 solution. Protoplasts were harvested by centrifugation at 183 g for 5 min and resuspended in 1 mL W5 solution. The protoplasts were incubated at 28°C in the dark for 24 h before harvesting for protein extraction.

Protein extraction and Western blotting
Total proteins of rice calli or protoplasts were extracted using the protein extraction buffer (50 mM Tris-HCl pH 8.0, 150 mM NaCl, 10 mM MgCl 2 , 1 mM EDTA pH 8.0, 10% glycerol) with Protease inhibitor cocktail (sigma). Equal amount of total proteins from different samples were resolved on an 8% SDS-PAGE gel and then transferred to a PVDF membrane. ABE-P1S and ABE-P1 proteins were immunoblotted with an anti-Cas9 antibody (1 : 5000) (Active motif), whereas the actin was immunodetected with an anti-actin antibody (1 : 5000) (Sangon Biotech, Shanghai). The membranes were rinsed three times with TBST buffer and then blotted with secondary antibodies. The signals were detected using High-signal ECL Western Blotting Substrate from Tanon (Shanghai).
Genotyping at on-target and off-target sites Rice genome DNA was extracted from the young leaves of all T 0 transgenic lines. The on-target sites for sgRNA1-sgRNA12 were amplified by PCR, and the PCR products were purified for Sanger sequencing by a nest primer. Primers for on-target sites amplification and sequencing are listed in Table S7. The potential off-target sites for sgRNA1, sgRNA6 and sgRNA9 were predicted by the online tool CRISPR-GE (Xie et al., 2017). We chose sequences with up to 4 or 5 bp mismatches to target sites in the rice genome as potential off-target sites. All the potential off-target sites were each amplified from eight randomly selected base edited lines and sequenced by a nest primer. Primers for potential off-target sites amplification and sequencing are listed in Table S8.

Supporting information
Additional supporting information may be found online in the Supporting Information section at the end of the article.

Figure S1
Off-target editing at OsSPL17 by ABE-P1S. Table S1 The base editing windows of ABE-P1 and ABE-P1S at different target sites. Table S2 The base editing windows of ABE-P2, ABE-P2S, ABE-P5 and ABE-P5S at different target sites. Table S3 The base editing frequencies of ABE-P1 and ABE-P1S at potential off-target sites of sgRNA1. Table S4 The base editing frequencies of ABE-P1 and ABE-P1S at potential off-target sites of sgRNA6. Table S5 The base editing frequencies of ABE-P2S at potential off-target sites of sgRNA9. Table S6 The target sites and primers for all sgRNAs used in this study. Table S7 Primers for on-target site amplification and sequencing. Table S8 Primers for potential off-target site amplification and sequencing. Data S1 The DNA sequences of key components in the different adenine base editors.


extfieldsofstudy: Chemistry Medicine

provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2019.jsonl.gz.gz

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Improvement of the aroma of lily rice wine by using aroma-producing yeast strain Wickerhamomyces anomalus HN006

A fruity aroma-producing yeast strain was isolated with the aim of improving the aroma of fermented lily rice wine, and identified as Wickerhamomyces anomalus HN006. In addition, the effects of adding solid residues of previous fermentation cycles, and of fungus α-amylase and W. anomalus HN006 supplementation on the biochemical parameters of lily rice wine were evaluated. The optimum quality of the wine, in terms of ethanol and residual sugar content, acidity levels and aroma, was obtained with 5% (w/v) solid residue addition, and supplementation with 10 U/g fungal α-amylase and 2% (v/v) W. anomalus inoculum on the 4th day of fermentation. Volatile compound profiles, the total amount of amino acids and the sensory characteristics of the lily rice wines produced by the two fermentation processes were also evaluated and compared. The lily rice wine obtained from our optimized experimental technology produced higher amounts of some esters, free fatty acids, alcohols, aldehydes, ketones, alkenes, volatile phenol and thiazole, in addition to higher total amino acid content and sensory scores compared to the traditionally brewed wine. Our process resulted in an intensification and improvement of lily rice wine aroma. Electronic supplementary material The online version of this article (10.1186/s13568-019-0811-8) contains supplementary material, which is available to authorized users.

Introduction
Lilies are perennial bulbous plants belonging to the monocotyledonous family Liliaceae. It has been a valuable medicinal plant in China for centuries, and modern pharmacological studies have shown several benefits of the lily bulb, such as improvement of lung function and cough relief, anti-fatigue and hypoxia tolerance, increase in peripheral white blood cell, protection of gastric mucosa, inhibition of delayed hypersensitivity reaction etc. (Rong et al. 2011). Lily bulbs are rich in nutrients like carbohydrates, proteins, vitamins B 1 , B 2 and C, magnesium, calcium, iron, potassium, carotene and various alkaloids like colchicines (Gao et al. 2012). Cancer cells treated with colchicine extracted from the lily bulb showed significant in vitro growth inhibition (Chen et al. 2014). Lilies are widely cultivated in China, mainly for food and medicinal purposes, and improvements have been made in recent years in processing the lilies into powder form (Francis et al. 2004), and in the production of compound beverages ) and soft sweets containing this ingredient (Shang et al. 2016). However, the current processing techniques still have a narrow application range and therefore low economic benefit. Therefore, it is imperative to develop new processing technologies, especially for high value products such as lily rice wine.
Rice wine is one of the most popular alcoholic beverages in China, and has a long history of brewing. With economic globalization, Chinese rice wine has now entered the international market. In addition, the improvement in the standard of living of Chinese people has led to demands of higher quality wine, with additional pro-health effects. Lily bulbs are suitable for rice wine brewing due to their high starch content. Although the process of rice wine brewing retains the nutrients of the lily bulbs, the resulting lily rice wine has suboptimal fragrance and a weak aftertaste. Therefore, it is necessary to improve the aroma in order to promote the rapidly developing lily rice wine industry.
We isolated an aroma-producing yeast strain and used it in brewing lily rice wine, in addition to optimizing the brewing process. The volatile flavor substances obtained from the traditional and modified brewing processes were detected and quantified by solid phase microextraction-gas chromatograph-mass spectrometry (SPME-GC-MS). The sensory characteristics of the final product were also evaluated. Our findings may not only provide a new strategy for enhancing the overall quality of lily rice wine, but also provide a basis for the brewing, quality evaluation and application of other rice wines.

Materials
Dried lilies and debranned polished glutinous rice from the 2016 crop were obtained from the Anhui Yingjia Distillery Group Co. Ltd. (LuAn, Anhui province, China). Wheat Qu was purchased from Angel Yeast Co. Ltd. (Yichang, Hubei province, China). Fermented Zaopei samples of Chinese strong-flavor liquor was obtained from a brewing plant of Anhui Yingjia Distillery Group Co. Ltd., LuAn, Anhui province. Fungal α-amylase solution was purchased from Shan-dong Longda Bio-Products Co. Ltd. (China). According to the information sheet of the manufacturer, the optimum temperature and pH for fungal α-amylase is in the range of 50-60 °C and 4.0-6.5, respectively. The specific activity of fungal α-amylase is 5000 U/mL, where one unit is defined as the amount of enzyme that hydrolyzes 1 mg of water soluble corn starch per minute under the assay conditions.

Isolation of aroma-producing yeast strain
Fermented Zaopei samples were inoculated into 90 mL yeast extract peptone dextrose medium (YEPD) containing 50 g/L glucose, 5 g/L yeast extract and 10 g/L peptone, in a 250 mL flask. The broth was incubated at 30 °C with constant shaking at 200 rpm for 24-48 h, and the resulting yeast culture was serially diluted with sterile water and spread onto YEPD agar plates. The plates were incubated at 30 °C for 48 h, and the colonies were picked and streaked several times to obtain pure isolates. Each isolated yeast strain was maintained on YEPD agar slants at 4 °C. To further propagate the pure strains, the seed colonies of each were inoculated in the liquid medium and cultured aerobically at 30 °C for 24 h with constant mixing at 200 rpm. The suspension culture was inoculated into 90 mL YEPD at 2% inoculum size (v/v, approximately 1 × 10 7 CFU/mL), and incubated at 30 °C and 200 rpm for 48 h. Both the liquid and solid cultures were evaluated through smelling (with non-inoculated YEPD agar and liquid medium as control), and the strains producing strong pleasant aroma were selected for further analysis.

Identification of the aroma-producing yeast strain
The screened strain was identified based on 26S rRNA gene sequencing. Yeast cells at the exponential growth phase were harvested by centrifugation at 12,000 rpm, 4 °C for 10 min and washed with sterile water. Genomic DNA was extracted as described by Gadanho et al. (2003). A fragment of the 26S rRNA gene was amplified by PCR using the forward primer ITS1 (5′-TCC GTA GGT GAA CCT GCG -3′) and the reverse primer ITS4 (5′-TCC TCC GCT TAT TGA TAT GC-3′). The 50 µL reaction mix consisted of approximately 100 ng of total DNA, 5 µL 10× buffer, 3 µL 25 mM MgCl 2 , 1 µL 2.5 mM dNTPs, 2 µL of each 10 pM primer and 1 µL 5 U/µL Taq polymerase. The PCR conditions were as follows: initial denaturation at 95 °C for 5 min, followed by 25 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s and primer extension at 72 °C for 1 min, followed by a final extension at 72 °C for 10 min. The purified PCR products were then sequenced by Sangon Biotech Company (Shanghai, China). The sequences were submitted to GenBank for BLAST analysis. A phylogenetic tree was constructed by the neighbor-joining method using the MEGA 4.0 program.

W. anomalus HN006 inoculum preparation for lily rice wine fermentation
The W. anomalus HN006 inoculum was prepared in YEPD medium. Pre-cultivation was performed aerobically at 30 °C for 24 h with constant shaking at 200 rpm. The concentration of the yeast cells was adjusted to 1 × 10 7 cells/mL, and used as the inoculum.

Traditional lily rice wine brewing
The traditional method of brewing lily rice wine is shown in Additional file 1. The dried lilies and glutinous rice were mixed at the ratio of 1:4 (w/w), washed, and soaked in 1.5 times the amount of water for about 6-8 h. After soaking, the mixture was cooked with steam for 30 min, and naturally cooled to 30 °C before mixing with wheat Qu. The raw material preparation was transferred into a jar and fermented at 30 °C for 7 days.

Optimization of lily rice wine brewing
The effects of solid residue addition, time of adding fungal α-amylase and W. anomalus HN006, and different concentrations of both on the quality parameters of the lily rice wine (ethanol and residual sugar content, acidity levels and aroma) were evaluated. Residue-addition fermentation refers to mixing a portion of solid residues of the previous fermentation batch with the fresh raw material.
In the present study, various amounts of the solid residues (0%, 5%, 10%, 15% and 20%, w/w) were added to the soaked raw materials, cooked with steam and then mixed with wheat Qu for simultaneous saccharification and fermentation. In addition, fungal α-amylase (10 U/g of raw material) and W. anomalus HN006 (2% v/v inoculum corresponding to 1 × 10 7 CFU/mL) were simultaneously added to the broth, and the effect of adding them at 0, 2, 4 and 6 days of fermentation were analyzed. In addition, different W. anomalus HN006 inoculum sizes (2%, 4%, 6% and 8%), and fungal α-amylase concentrations (5 U/g, 10 U/g, 15 U/g and 20 U/g of raw materials) were tested. Fermentation broth samples were taken at regular intervals for analysis, and results represent the averages. All the experiments were performed in triplicates.

Analysis of the biochemical parameters of lily rice wine
During the fermentation process, broth samples were withdrawn at specific intervals and centrifuged at 5000g for 20 min to remove the cellular debris. The concentrations of ethanol, total acids, amino acids and reducing sugars in the supernatant wine were then measured. Ethanol concentration (% v/v at 20 °C) and total acid were determined as described by Yan et al. (2015). Reducing sugar was directly determined by 3,5-dinitro-salicylic acid colorimetry (Miller 1959). Amino acid content was analyzed by HPLC with an ODS HYPERSIL (Agilent Tech Inc., Santa Clara, CA) column and a diode array detector (DAD) at 40 °C with a mobile phase of 20% sodium acetate (0.2 M), 40% acetonitrile and 40% methanol at a flow rate of 1.0 mL/min (Shen et al. 2010).

Extraction of volatile flavor compounds by HS-SPME
Volatile flavor compounds of lily rice wine were extracted using the headspace solid-phase micro-extraction technique (HS-SPME). The volatile compounds of the fermentation broth were extracted using a 75 mm CAR-PDMS (Supelco, Bellefonte, PA, USA). Each lily rice wine sample (1 mL) was placed in the headspace bottle together with 10 µL of the internal standard 2-octanol (70.2 mg/L in absolute ethanol). The vial was tightly capped, and then equilibrated by ultrasonic vibration in a 60 °C water bath for 10 min. The extraction head was then inserted into the vial and the sample was extracted for 30 min at 60 °C. The extraction head was then introduced into the injection port of the GC-MS system (250 °C for 3 min) and the analytes extracted from the fiber were thermally desorbed.

GC-MS analysis
Agilent 6890 GC equipped with an Agilent 5975 mass selective detector (Agilent, USA) was used. Helium was used as the carrier gas at a constant flow rate of 1 mL/ min. The temperature of the injector and detector were both set at 250 °C. The analytes were separated through a DB-Wax column (60 m length, 0.25 mm i.d., 0.25 mm film thickness, Agilent) with an oven temperature program of 40 °C (1 min), 5 °C/min to 180 °C (1 min), and 8 °C/min to 230 °C (7 min). The Agilent 5975 MSD was used for identifying the unknown compounds. The electron impact energy was 70 eV, and the ion source and quadruple temperatures were both set at 230 °C. Electron impact (EI) mass spectra was recorded in the 20-550 amu range. All samples were analyzed in triplicates. The mass spectrum data were compared against NIST mass spectral database (Agilent Technologies Inc.) to identify the volatile flavor compounds in lily rice wine samples. The volatile compounds were quantified by comparing their peak areas to that of the 2-octanol internal standard. The amounts of individual constituents present in the sample were calculated and expressed as milligram per liter of wine.

Sensory evaluation of lily rice wine
The sensory characteristics of taste, smell, aftertaste, acidity and overall acceptability of the final lily rice wine were evaluated by 10 well trained experts working at the Anhui Yingjia Distillery. Four experts were females aged 30-40 years old, and six experts were males and were 28-45 years old. The sensory scores were determined by a 9-point hedonic scale: 1-dislike extremely; 2-dislike very much; 3-dislike moderately; 4-dislike slightly; 5-neither like nor dislike; 6-like slightly; 7-like moderately; 8-like very much; 9-like extremely. The mean intensity scores of all the attributes were calculated and plotted.

Statistical analysis
The data of volatile compounds was processed using the SPSS version 21.0 statistical package for windows (SPSS Inc., Chicago, IL, USA). Principal component analysis (PCA) was used to investigate the possible differences between the lily rice wine samples.

Characterization and identification of aroma-producing yeast strain HN006
Several yeast strains were isolated from fermented Zaopei, and after subjecting both their liquid and solid cultures to direct sensorial tests, one strain that produced a strong fruity aroma was selected. The strain was named HN006, and it formed small, spherical, raised, milk-white colonies with no pigmentation on solid medium after 24 h of incubation. The HN006 cells were oval measuring 6 × 10 µm, and multiplied by budding. This aerobic strain grew between 10 and 40 °C with optimum temperature range 28-32 °C, 0-2% NaCl (w/v) with optimum salinity 0-0.5% NaCl (w/v), and pH 6-8 with optimum growth at pH 5. HN006 hydrolyzed casein but not gelatin, starch, Tween 40 and urea, and could utilize glucose, sucrose, maltose, glycerol and d-galactose as sole carbon sources for growth.
The D1/D2 domain of 26S rRNA gene is highly conserved and is used for the phylogenetic analysis of higher taxa. The HN006 D1/D2 sequences comprising of 608 nucleotides were submitted to GenBank (http://www. ncbi.nlm.nih.gov), and displayed 100% similarity to that of Wickerhamomyces anomalus (GenBank accession KT883963.1 and KX253664.1). A phylogenetic tree was constructed based on the 26S rRNA coding gene sequences of the isolate and the nearest relatives ( Fig. 1). Based on the morphological, physiological and molecular data, the fruity-aroma producing strain isolated from Zaopei was identified and named as W. anomalus HN006.

The effect of different amounts of solid residues on the characteristics of lily rice wine
The levels of ethanol, reducing sugars and acidity, and the sensory evaluation scores of the lily rice wine relative to different amounts of solid residues are summarized in Fig. 2. Ethanol concentration remained unchanged as the proportion of solid residues was increased from 0 to 5% (w/v), but decreased significantly at amounts over 5% (w/v). The concentration of reducing sugars gradually increased in the wine with increasing amount of solid residues. This could be due to the presence of acidic substances in the solid residues, which accelerate the hydrolysis of starch in the fermentation media. In addition, a certain level of acidity aids the growth and metabolism of both Rhizopus and yeast that are used in rice wine brewing. However, high levels of acidity normally inhibit microbial growth and decreases the efficiency of ethanol fermentation. The acidity levels of the media had expectedly similar trends as that of reducing sugars with increasing solid residue addition. The highest sensory evaluation score was obtained at 5% (w/v) solid residues. Taken together, the optimum amount of solid residues vis-à-vis wine quality was 5% (w/v).

The effect of the addition time of fungal α-amylase and W. anomalus HN006 on lily rice wine quality
The process of hydrolyzing starch into fermentable sugar requires the liquefaction of α-amylase, which converts the starch into dextrin that is subsequently broken down by glucoamylase into fermentable sugars. However, as wheat Qu is mainly produced from pure cultures of Rhizopus and yeasts in rice flour, its liquefaction power is normally low. To improve the liquefaction efficiency of rice starch, fungal α-amylase (10 U/g raw material) was added to the fermentation broth. In addition, W. anomalus HN006 (2% v/v, initial viable cell number 1 × 10 7 CFU/ mL) was also inoculated to improve the sensory properties and ethanol content of lily rice wine, and fermentation was conducted under the optimum conditions mentioned above. Figure 3 illustrates the effect of the different addition times of fungal α-amylase and W. anomalus HN006 on the biochemical parameters of lily rice wine. Both ethanol concentration and sensory evaluation scores were the highest when the amylase and yeast inoculum were added on the 4th day of fermentation, while the reducing sugar content was relatively low for that addition time. In contrast, the addition time had no effect on the acidity level. Therefore, simultaneous addition of fungal α-amylase and W. anomalus HN006 on the 4th day of fermentation resulted in optimum quality of the lily rice wine.
Rice wine is mainly produced by the saccharification of Rhizopus and the ethanol fermentation of yeast. Rhizopus produces glucoamylase which converts starch into glucose, which is partly used for maintaining microbial growth and metabolism, and partly as the raw material for ethanol fermentation. During the initial stages of fermentation, the growth of Rhizopus is dominant due to the availability of oxygen and nutrients. With the continuous consumption of oxygen and the accumulation of ethanol and organic acids during fermentation, the growth of Rhizopus gradually ceased. The optimum growth of Rhizopus in the initial stages led to more efficient saccharification of starch, which increased the ethanol concentration.
The aroma-producing yeasts not only produce aromatic compounds, but also organic acids like acetic acid, which has a strong inhibitory effect on Rhizopus. Therefore, the presence of aroma-producing yeast at the initial fermentation stage would inhibit Rhizopus growth and reduce starch conversion rate, resulting in low ethanol levels in the wine. On the 4th day of lily rice wine fermentation, the simultaneous addition of fungal α-amylase and W. anomalus HN006 not only enhanced the wine flavor but also increased its ethanol concentration. The likely reason is that the large amounts of glucoamylase that had already accumulated in the first 4 days of fermentation rendered any effect of the aroma-producing yeast on glucoamylase production redundant. In addition, the supplementation with fungal α-amylase also promoted the transformation of residual starch into glucose.

The effect of fungal α-amylase concentration on lily rice wine quality
Alpha amylase (enzyme EC 3.2.1.1) hydrolyzes the α-1,4-glycosidic bond in starch to produce maltose and oligosaccharides. This enzyme is widely used for starch liquefaction in various industries, such as textiles, brewing, baking, detergents, paper etc. The common bacterial α-amylase mainly acts at high temperatures (95-105 °C) and near neutral conditions (pH 5.8-6.8), while fungal α-amylase is suitable for liquefying starch at low temperatures (50-60 °C) and acidic conditions (pH 5-5.5). Therefore, fungal α-amylase is more suitable for lily rice wine brewing. The effect of fungal α-amylase concentration on lily rice wine fermentation is summarized in Fig. 4. The acidity of the wine increased slightly with increasing concentration of fungal α-amylase, and was not significant. The ethanol concentration increased from 10.35% (v/v) to 11.63% (v/v) as the fungal α-amylase concentration was raised from 5 to 10 U/g of the raw materials, which again was not a significant increase. Similarly, the concentration of reducing sugars also did not change appreciably relative to the fungal amylase. The maximum overall sensory evaluation scores was obtained with the supplementation of 10 U/g fungal α-amylase. Therefore, this concentration of the enzyme was chosen for subsequent fermentation.

The effect of the inoculum size of W. anomalus
Aroma-producing yeast synthesize volatile flavor substances, mainly consisting of esters and higher alcohols, as part of its metabolism, which give a more harmonious and mellow taste to the wine. Therefore, supplementing the fermentation broth with aroma-producing yeast can improve the flavor of the wine. Figure 5 summarizes the ethanol and reducing sugar content, acidity levels, as well as overall sensory evaluation at different inoculum sizes. The optimum inoculum concentration for maximum ethanol production and overall sensory evaluation was 4% (v/v), and was thus used for all subsequent experiments.

Volatile flavour compounds in lily rice wine
In contrast to the raw materials, a variety of volatile components which contribute to the fragrance and the flavor of the wine were detected in the lily rice wine, regardless of the fermentation process. The lily rice wine samples from both fermentation processes were mainly composed of alcohols, acids, esters and alkane compounds Esters, which impart the fruity and floral odors to Chinese rice wine (Fan and Qian 2006), are formed either by the esterification of alcohols with fatty acids, or through de novo synthesis in the microbial cells by alcohol acetyltransferase using acetyl-CoA and higher alcohols as substrates during fermentation (Mo and Xu 2010). Most aroma-producing yeasts can synthesize esters during fermentation. While only 11 esters were detected in the lily rice wine from traditional brewing,  (Table 1). In addition, the total amount of esters obtained from the optimized fermentation process was 105.278 mg/L, compared to 37.58 mg/L in the traditional method. Ethyl palmitate was the most abundant ester obtained from the optimized experimental process, accounting for 39.74% of all esters in the lily rice wine. In addition to its influence on the organoleptic characteristics of lily rice wine, ethyl palmitate also imparts a pleasant, fruity fragrance to the wine.
Acids constitute a fairly large group of volatile compounds in rice wine, whose content and types can influence the quality of the final product. An appropriate amount of organic acids inhibit the growth of contaminating bacteria, and improve the mellow aftertaste and the flavor of the wine. The organic acids can also promote the formation of esters during fermentation. The lily rice wine obtained from our optimized fermentation process had higher content of different organic acids, except that of butanoic acid, compared to that of traditionally brewed wine. Acetic acid, butanoic acid, n-decanoic acid, linoleic acid, myristic acid, pentadecanoic acid, hexadecanoic acid and n-hexadecanoic acid were identified in the two lily rice wine samples, of which n-hexadecanoic acid, a product of lipid oxidation, was the most abundant in both. Acetic acid affects the aroma and flavor of wines due to its pungent smell (Soufleros et al. 2004). However, only 0.65 mg/L and 2.649 mg/L acetic acid was detected in the final lily rice wine product obtained from traditional-and modified fermentation respectively. This contradicts the observation that acetic acid is the dominant organic acid in alcoholic beverages (Satora et al. 2008). The low concentration of acetic acid in the rice wines could be due to its transformation into fatty acids during the fermentation process. Two unsaturated fatty acids, oleic acid and linoleic acid, were detected in the rice wine obtained from the optimized fermentation process (Table 1), which contributed to the soapy texture, green color and fatty odor of the wine. Higher alcohols are among the most important flavor compounds in rice wine and contribute to the aroma and clean-taste of the wine. The higher alcohols are predominantly formed by the yeast from α-keto acids, either via the degradation of amino acids (valine, leucine, isoleucine, threonine, phenylalanine) by the Ehrlich pathway or de novo biosynthesis from the carbon source. In this study, the main higher alcohols identified in the lily rice wine obtained from the optimized fermentation were isoamyl alcohol (5.331 mg/L), 2-nonanol (2.186 mg/L), 2,3-butanediol (2.373 mg/L), 1-octanol (0.664 mg/L), 2-(2-ethoxyethoxy)-ethanol (0.482 mg/L), 2-tetradecanol (5.858 mg/L), phenylethyl alcohol (39.518 mg/L), 2-dodecanol (0.561 mg/L), isoborneol (0.625 mg/L), and glycerin (0.668 mg/L). Isoamyl alcohol, 2-nonanol, 2,3-butanediol and phenylethyl alcohol were the main higher alcohols detected in both lily rice wine samples, but their amounts were  (Table 1). Isoamyl alcohol imparts a strong banana flavor, and also reduces the amount of bitter-tasting amino acids like leucine which improves the wine taste. Isobutanol has a faint smell of allyl alcohol with bitter notes, while 2,3-butanediol has a unique bitter taste and a buttery odor note (Bartowsky and Henschke 2004). Phenylethyl alcohol, which contributes to rosy and honey aroma, is usually present in high concentration in Chinese rice wines (Fan and Qian 2006). Two aldehydes and five ketones were identified in the lily rice wine obtained from the optimized fermentation, with total amounts of 6.007 mg/L and 14.104 mg/L respectively, both of which were higher than that in the traditionally brewed wine. The most potentially important aldehyde was 4-methyl benzaldehyde, which imparts a bitter almond aroma. It could be formed by the oxidation of benzyl alcohol, by the microbial decomposition of aromatic amino acids, or from phenyl acetic acid. Furthermore, aldehydes and ketones might also be the oxidation products of linoleic acid (Liu et al. 2015).
Three alkenes (1,3,5-(3E,5Z)-1,3,5-undecatriene, 2-tetradecene, and 1,15-hexadecadiene) were detected in the lily rice wine obtained from our modified fermentation process, while only one alkene was present in the traditionally fermented rice wine. The contribution of the alkenes to rice wine aroma and flavor are not clear so far. One volatile phenol (4-vinylguaiacol) was detected in both lily rice wines samples (Table 1), and imparts spicy, smoky, and clove-like odors. The volatile phenols detected in the samples can originate from p-coumaric and ferulic acids by enzymatic or thermal decarboxylation (Ye et al. 2014). In addition, low amounts of one thiazole (2-mercapto-4-phenylthiazole) was identified in the lily rice wine obtained from the optimized fermentation, but its contribution to rice wine aroma and flavor needs further investigation.

Amino acids content of lily rice wine
Amino acids are not only essential for yeast nutrition, but are also the precursors of the aroma compounds in Chinese rice wine, and therefore an important quality  parameter (Shen et al. 2010). Amino acids are mainly derived from the enzymatic degradation of proteins in the raw material by the wheat Qu proteases, as well as autolysis of yeast and other microbes. During fermentation, some amino acids are used by yeast as nutrients, some are transformed into higher alcohols, and the remaining become part of the rice wine (Ye et al. 2014).
The amino acid content in the lily rice wine samples are summarized in Table 2. Seventeen amino acids were identified, the total amount and that of each amino acid was higher in the rice wine obtained from optimized fermentation process (total content 4282.6 ± 40.26 mg/L) compared to the traditionally brewed wine (total content 2777.4 ± 38.9 mg/L), with an increase of 54.2%. This may be due to the increased acidity in our modified process which helps in protein digestion. Furthermore, some organic acids that are produced by the aroma-producing yeast may accelerate microbial autolysis.

Discussion
In present study, the volatile flavor substances in the wines obtained from the traditional and novel brewing technologies were identified by SPME-GC-MS. The lily rice wine obtained from the optimized fermentation process had higher amounts of some esters, free fatty acids, alcohols, aldehydes, ketones, alkenes, volatile phenol and thiazole, in addition to higher total amino acid content compared to the traditionally brewed wine. The optimized fermentation process resulted in an intensification and improvement of lily rice wine aroma. Additionally, SPSS version 21.0 was used to analyze the data of volatile compounds of the brewing raw materials and the two lily rice wine samples by the principal component analysis (PCA), and the results are shown in Fig. 7. A two dimensional analysis of the principal components was attempted using the component data matrix shown in Table 1.
The first and second principal components accounted for 92.5% and 3.79% of the variance respectively. The first principle component of the lily rice wine obtained from the optimized fermentation was located on the positive side of the factor, and characterized mainly by esters, fatty acids and the volatile phenol 4-vinylguaiacol. The esters were isoamyl butyrate, ethyl heptanoate, ethyl caprylate, hexyl formate, ethyl nonanoate, ethyl caprate, phenethyl acetate, ethyl laurate, ethyl palmitate, ethyl oleate, ethyl linoleate, ethyl and 9-cis, 11-trans-octadecadienoate. The fatty acids were acetic acid, n-decanoic acid, linoleic acid and myristic acid. In contrast, the principal component of the traditionally brewed lily wine was on the negative side of the factor, distinguished by the production of butanoic acid, alkene 2-tetradecene and ketone 2-nonanone. Hexadecanoic acid that originated from fatty acids was also found on the negative region of the factor.
PCA results indicated that the two lily rice wine samples correlating with particular groups of volatile compounds were clearly discriminated in the loading plot (Fig. 7), and the wine obtained from the optimized fermentation process had a long distance with the traditionally produced wine and the raw materials. The main flavor components of the lily rice wine obtained from the modified process were isoamyl butyrate, ethyl oenanthate, ethyl caprylate, hexyl formate, ethyl pelargonate, ethyl caprate, phenethyl acetate, ethyl laurate, ethyl palmitate, ethyl oleate, ethyl linoleate, ethyl, 9-cis, 11-trans-octadecadienoate, acetic acid, n-decanoic acid, linoleic acid, myristic acid and 4-vinylguaiacol, which were clearly distinguishable from those of the traditional wine and raw materials. The lily rice wine obtained from traditional brewing was located on the positive semi axle region of the second principle component and far from other samples. The main flavor components distinguishing the traditionally brewed lily rice wine were butanoic acid, 2-tetradecene and 2-nonanone. Hexadecanoic acid was the main flavor component that distinguished raw materials from the lily rice wine samples. These observations demonstrated the relationship between the volatile compounds and the fermentation process.
The sensory evaluation of lily rice wine was also investigated (Fig. 8) and the lily rice wine obtained from the optimized fermentation process scored better in all quality parameters such as acidity, taste, aroma, aftertaste and overall sensory evaluation, increasing specifically by 1.3, 2.4, 2.1, 2.6 and 1.5 points respectively compared to the traditionally brewed wine. This could be due to the higher concentration of esters, especially ethyl palmitate, in the lily rice wine brewed by the modified process. In addition, high concentrations of fatty acids, such as n-hexadecanoic acid, pentadecanoic acid, linoleic acid, myristic acid etc., may also contribute to the enhanced flavor and taste of the wine. A previous study has reported that organic acids harmonize the flavor and taste of wine and increase its softness (Ye et al. 2014). Taken together, sensory evaluation indicate better quality of the wine obtained by the optimized fermentation. Volatile aroma compounds play an important role in the quality of rice wine, and are influenced by factors such as raw materials, wheat Qu and the fermenting microbes, especially yeast. During rice wine brewing, yeast transforms the fermentable sugars into ethanol and carbon dioxide, along with producing higher alcohols, acids, esters, aldehydes etc., which greatly influence the wine aroma. Different yeast species produce different kinds and amounts of volatile substances, which contributes to the different flavors. Therefore, it is necessary to screen new, aroma-producing yeast strains to increase the levels of volatile flavor substances in rice wine. Addition of the aroma-producing yeast strain of W. anomalus HN006 resulted in significantly higher amounts of aroma substances, a more complex volatile profile, and higher sensory scores than those obtained using traditional rice wine brewing methods. This strain can be tested in starters or adjunct cultures of other types of rice wine as well.

Additional file
Additional file 1. Flow diagram of lily rice wine production.


extfieldsofstudy: Medicine Chemistry

s2fieldsofstudy:
Agricultural And Food Sciences
Biology

text:
Agastache honey has superior antifungal activity in comparison with important commercial honeys

There is an urgent need for new effective antifungal agents suitable for the treatment of superficial skin infections, since acquired resistance of fungi to currently available agents is increasing. The antifungal activity of mono-floral Agastache honey and commercially available honeys were tested against dermatophytes (T. mentagrophytes and T. rubrum) and C. albicans (ATCC 10231 and a clinical isolate) by agar well diffusion and micro-dilution (AWD and MD). In AWD and MD assays, Agastache honey was effective at 40% concentration against dermatophytes (zone diameter, 19.5–20 mm) and C. albicans with the same MIC and MFC values indicating fungicidal activity. Tea tree honey was effective at 80% concentration (zone diameter, 14 mm) against dermatophytes and at 40% concentration against T. mentagrophytes and C. albicans. Manuka was effective at 80% concentration only against T. mentagrophytes (zone diameter, 12 mm) and at 40% against T. rubrum and C. albicans with fungistatic activity. Similar to the AWD results, Jelly bush, Super Manuka, and Jarrah showed no activity against dermatophytes but showed some activity against C. albicans. Headspace volatiles of six honeys were isolated by SPME and identified by GC-MS. The characteristic chemical markers for each honey were as follows: Agastache- Phenol, 2,4-bis(1,1-dimethylethyl) and Estragole; Manuka and Tea-tree- Acetanisole and Methyl 3,5-dimethoxybenzoate; Jelly bush- Linalool and Nonanal; Super Manuka- Methyl 3,5-dimethoxybenzoate and Nonanal; Jarrah- Isophorone and Nonanoic acid. Overall, analysis of the bioactive compound content and antifungal activity of Agastache honey indicated possible use as an antifungal agent for management of superficial fungal infections.

Honey source (species)
Agar well diffusion (zone size in mm) Micro-dilution (MIC, % honey)   Table 2. Antifungal activity of honey at different concentrations, hydrogen peroxide content and major volatile compounds of honeys. The antifungal activity of honey was assessed against dermatophytes and C. albicans. The hydrogen peroxide content of honeys was determined at a concentration of 40%. Data represent the mean of triplicate readings ± standard deviations (SD).

Figure 1.
Antifungal activity of honey against T. mentagrophytes determined by agar well diffusion. Honeys were tested in the range of 80-10% (w/v). Agastache honey exhibited the largest zone of inhibition at 40% concentration (20 mm) followed by tea-tree honey and Manuka honey at 80% concentration (14 mm and 12 mm, respectively).
rubrum in the presence of tea tree honey. However, at 40% honey concentration, all strains with the exception of T. rubrum/tea tree honey, showed some inhibition. Agastache honey was consistent in inhibiting growth of dermatophytes and yeasts at this honey concentration. The MIC and MFC values were the same for all the strains/ isolates, indicating the fungicidal activity of honey. Among Leptospermum origin honeys, Manuka honey (40%) was effective against T. rubrum and C. albicans but only partially effective (45% inhibition) against T. mentagrophytes. Manuka honey showed only fungistatic activity. Tea tree honey (40%) inhibited the growth of T. mentagrophytes and C. albicans and exhibited fungicidal activity but was partially (50% inhibition) effective against T. rubrum and C. albicans clinical isolates. Other honeys such as Jelly bush (<50% inhibition), Super Manuka (60-70% inhibition), and Jarrah (75-80% inhibition) showed variable activity against dermatophytes whilst, Jelly bush and Jarrah showed only fungistatic against C. albicans clinical isolate. Statistical analysis showed that interaction between three parameters, honey concentration, honey type and fungal strains were significant and affected the growth of all fungal isolates/strains and the C. albicans reference strain (ATCC 10231). The main influence on activity was honey concentration, which explained 33% of the variation, fungal strain/isolate (25% of the variation), while honey concentration and fungal strain/isolate interaction explained 16% of variation (Table 3). The non-parametric Kruskal-Wallis test also showed that honey concentration had a significant effect on fungal growth (p = 0.001).
Head space-solid phase microextraction gas chromatography-mass spectroscopy (HS-SPME GC-MS). The volatile compounds in six honey samples were isolated by SPME and identified by GC-MS.

Figure 2.
Antifungal activity of honey against T. rubrum determined by agar well diffusion. Honeys were tested in the range of 80-10% (w/v). Agastache honey exhibited the largest zone of inhibition at 40% concentration (19.5 mm) followed by tea-tree honey at 80% honey (14 mm).
Of the 80 different species of Leptospermum origin native to Australia, honey was available from the following: Jelly bush, Super Manuka and Tea-tree honeys. Manuka is derived from Leptospermum genus found in New Zealand. The common major compounds were benzaldehyde, benzacetaldehyde, Linalool, Nonanal and Methyl 3, 5-dimethoxybenzoate. Acetanisole was the major marker compound found in Manuka and Tea tree, whilst it was detected in low amounts in Jelly bush and not in Super Manuka honey. Methyl 3,5-dimethoxybenzoate was detected in all honeys at variable percentages and can be described in the descending order as follows: Super Manuka > Manuka > Tea tree > Jelly bush. Linalool was the marker compound found in Jelly bush honey and a minor compound in Tea tree honey but was detected in trace amounts in other honeys. Benzene    www.nature.com/scientificreports www.nature.com/scientificreports/ Volatile compounds in Jarrah honey. Jarrah tree (Eucalyptus marginata) is native to Western Australian.

Discussion
The most common dermatophytes causing skin infection in humans are T. mentagrophytes and T. rubrum 30 . Tinea pedis or athletes foot, tinea cruris or jock itch, tinea corporus or ringworm of the body (face, scalp, nail and hand) are the major infections caused by dermatophytes 31 . Candidiasis is most commonly caused by C. albicans. Currently, there are many anti-mycotic agents available over the counter and some have become only partially effective 7 . Moreover, some patients prefer to use natural products instead of commercially available antimycotic agents. Therefore, we evaluated honey as an alternative to available antifungal agents. The antifungal activity was assessed by two methods, agar well diffusion (AWD) and micro-dilution (MD).
Based on the AWD assay, Agastache honey was the most effective honey against T. mentagrophytes and T. rubrum, closely followed by Tea tree honey, with Manuka honey showing some activity. The other honeys examined (Jelly bush, Super Manuka, and Jarrah honeys) showed no activity in the AWD assay (Fig. 1, Table 2). The more sensitive MD assay reflected these results, with only Agastache honey showing inhibition against both dermatophytes at 40% concentration, while Tea tree honey and Manuka were active against T. mentagrophytes and T. rubrum respectively. The other honeys examined were less active or showed no anti-dermatophyte activity; indeed T. rubrum was able to grow in the presence of Tea tree honey ( Table 2). The MIC and MFC values of Agastache honey against the two dermatophytes indicated fungicidal activity. Tea tree honey was also fungicidal, but only against T. mentagrophytes. No other honeys displayed fungicidal activity against the dermatophytes. The lower sensitivity of the AWD assay compared with MD could be explained by the need for the active components to diffuse across agar; however, AWD is considered to be an appropriate model to assess agents applied topically 32 . Furthermore, the observed zones of inhibition of honey at 80% for Agastache honey were smaller than at 40% concentration (Table 2). Generally, the production of hydrogen peroxide increases over the serial dilutions. However, for most of the honeys, accumulation of hydrogen peroxide is maximum at 30-50% 33 . Therefore, the inhibition size variation may be a result of less hydrogen peroxide production at highest concentration (80%).
In general C. albicans was more susceptible to all honeys than the dermatophytes (Fig. 3c,d), the only exception being Super Manuka honey that showed no activity against either Candida strain ( Table 2). Only Tea tree honey showed fungicidal activity against C. albicans. The highest concentration of honey used for MIC determination in the present study was 40%. It is possible that honeys such as Jelly bush, Super Manuka and Jarrah might show activity at higher concentration. Notably, Agastache honey was effective at 40% concentration against both dermatophytes and both strains of C. albicans. The control antifungal, fluconazole failed to inhibit T. mentagrophytes in both assays but strongly inhibited T. rubrum (21 mm), as well as C. albicans, ATCC 10231 and a clinical isolate at a concentration of 128 µg/ml.
The few reports in the literature on antifungal activity of honey against dermatophytes and yeasts partially agree with the findings of the present study. Suhana et al. 34 reported that Manuka honey (UMF 10+) has antifungal activity against C. albicans (25% v/v) and dermatophytes (50% v/v), while Brady et al. 24 also reported activity of Manuka honey against T. mentagrophytes, although the zone of inhibition (18.4 mm) was wider than found in the current study (12 mm). Koc et al. 35 found that fluconazole-resistant C. albicans required 40-80% (MIC values) concentration of Turkish honey (Rhododendron, Orange and Eucalyptus) for inhibition. Another honey, Jujube honey (Zizyphus spina-christi) was active against C. albicans ATCC 10231 at 40% (w/v) (MIC), with the MFC at 50% 36 . In another study, Carter et al. 11 found that Manuka honey was less effective for treatment of fungal skin infections caused by C. albicans and dermatophytes than for bacterial skin infections. This finding was attributed the observation that Manuka honey lacks hydrogen peroxide, which is responsible for the antifungal activities of some honeys 11,24 . However, our results do not support this view since Agastache honey, which showed the most antifungal activity according to the assays we used, produced lower amounts of H 2 O 2 (5.13 µm) than Jarrah and Super Manuka honeys (115 µm and 41 µm respectively), which displayed weak antifungal activity. On the other hand, Tea tree honey produced the highest amount of H 2 O 2 (155 µM) and showed antifungal activity. These findings clearly indicate that other factors than H 2 O 2 production, for example, volatile and phenolic compounds, contribute to the antifungal activity. In this study, therefore, we have identified volatile compounds in the honeys and their possible relation to the antifungal activity.
In order to investigate the source of the volatile compounds in Agastache honey, we compared the findings of the present study with an earlier study from our laboratory 38  www.nature.com/scientificreports www.nature.com/scientificreports/ percentage in leaves (94.35%), flower (96.74%), and flower with nectar (97.16%). In contrast, our present findings that Agastache honey contained only 12.31% estragole suggests that the nectar contained only a low amount of the compound compared to flower and leaves. However, this needs to be further confirmed by analyzing volatile compounds of nectar separately. Jerković and Marijanović 39,40 reported that the volatile compound composition of nectar, honey-sac and Satsuma Mandarin honey were significantly different. The authors suggested these differences could be due to hive conditions and bee-enzyme activity. Other compounds found in the flower nectar, such as Bicyclo undec-4-ene, 4,11,11-trimethyl-8-methylene-an isomer of caryophyllene (4.67%) and D-limonene (0.38%) were detected in Agastache honey confirming that major compounds of nectar were transferred to the honey. Estragole was also detected in Australian Super Manuka honey, but in low amounts (1.92%). Estragole was also identified as the most abundant compound in A. rugosa and A. foeniculum arial parts (18.6% to over 98%) 41 .
Other major compounds identified only in our Agastache honey could be the result of transformation of plant compounds by the metabolism of a bee, microbial and environmental contaminations 12,40 . The Agastache honey was produced in the greenhouse to ensure that bees forage onto the single flower species. However, the bees store their food inside the honey-sac, honey could be sourced from other plants before the hive was introduced into the glasshouse. Therefore, some compounds could be introduced from the different plant sources. Moreover, bees interact with plants trichome and carry loads of volatile compounds on the wings and transfer them into the honey. Considering different factors, the above-mentioned compounds were identified in the significant amount in samples, hence they can be nominated as chemical markers of Agastache honey.
The volatile compound profile of Agastache honey identified many antifungal compounds which could be correlated with the activity demonstrated in the present study. These include estragole, the major volatile component, which was effective against Trichophyton species, when used at 1.25 mg/ml concentration in combination with ketoconazole (12.5 µg/ml) 42 . In addition, phenol-2, 4-bis (1, 1-dimethylethyl) (100 µg/ml) has activity against Aspergillus indicated by reduction in the germ tube length and presence of an inhibition zone in agar dilution studies 43 . Moreover, 2, 4-di-tert-butylphenol (100 µg/ml) inhibited the growth of fungal cells and biofilm formation of C. albicans 44 .
Several studies have also reported that oils containing high concentrations of estragole have antifungal activity. For example, croton zehntneri oil, which contains 84.7% estragole produced significant zones of inhibition against fungi (C. albicans and B. dermatitidis) 45 . The essential oil extracted from Foeniculum vulgare, which contains a major fraction of estragole, demonstrated antifungal activity against C. albicans 46 . In addition, other components identified in Agastache honey in the present study were reported to have antifungal activity. For example, nonanoic acid, was identified as the antifungal compound in the roots of Hibiscus syriacus which has been used successfully to treat tinea pedis 47 . Moreover, 2-propenoic acid, 3-phenyl, ethyl ester (ethyl cinnamate) were effective against A. niger and C. albicans than E. coli and S. aureus 48 . Finally, ethyl cinnamate is also active against C. albicans 49 .
The study conducted by Kim J. H. reported that several benzaldehydes (such as 2-hydroxy-3 -methoxybenzaldehyde, 2-hydroxy-5-methoxybenzaldehyde) have antifungal activity and structure-activity analysis revealed the presence of hydroxyl group increases the antifungal activity 50 . A promising class of bioactive heterocyclic compounds that exhibit a range of biological activities is benzimidazole. Khabnadideh S. studied the derivatives of benzimidazole (such as 1-Nonyl-1 H-benzo[d]imidazole and 1-Decyl-1 H-benzo[d]imidazole) and evaluated the antifungal activity against C. albicans and dermatophytes 51 .
As expected, there were differences in the major volatile compounds identified in the different honeys of Leptospernum origin (Table 2, Fig. 6). In agreement with other reports 52-54 the major compound identified in Manuka honey was Acetanisole (O-Methoxyacetophenone). This compound was also observed in highest amount in Tea-tree honey (31.3%) but was present in only low amounts in Jelly bush honey and was absent in Super Manuka honey. These findings are consistent with the Leptospermum species origin of the various honeys; since Manuka honey and Tea-tree honey are derived or partially derived from Leptospermum scoparium, while Jelly bush and Super Manuka honeys are derived from Leptospermum polygalifolium.
In the present study, methyl 3,5-dimethoxybenzoate was identified for the first time in all Leptospermum-origin honeys; however, Kirkpatrick et al. 55 detected methyl syringate as the characteristic antioxidant in Leptospermum-origin honeys, using GC-MS and HPLC, Methyl 3,5-dimethoxybenzoate could be formed due to a loss of an oxygen atom from methyl syringate. The percentages of this compound among total volatiles in the different honeys was as follows: Manuka (26.67%), Tea tree (14.47%), Jelly bush (11.7%) and Super Manuka (40%). Since Methyl 3,5-dimethoxybenzoate constituted the highest percentage of volatile compounds of Super Manuka honey it could be nominated as a chemical marker of the honey.
Nonanal was identified in all Leptospermum-origin honeys and has not been reported previously in Manuka honey. The concentrations of nonanal in the different honeys of Leptospermum-origin were as follows; Manuka (3.87%), Tea tree (8.25%), Jelly bush (12.4%) and Super Manuka (11.3%). It was reported to be present in Chilean Ulmo honey (7.97%) 56 . Also, as found in the present study, Jelly bush was reported to contain Cis-linalool and Nonanal 52 , which were nominated chemical markers for Jelly bush.
Several authors have reported on the anti-Candida albicans and antibacterial activity of compounds of Leptospermum origin that were identified in this study. These include Methyl 3,5-dimethoxybenzoate (Benzoic acid, 3,5-dimethoxy, methyl ester), which has activity against Candida albicans 57 . Linalool, the major component (54.4%) of the essential oil of Ocimum basilucum, had antimicrobial effects on eight bacteria and three fungi tested, giving inhibition zones ranging from 7 to 19 mm in agar dilution studies 58 . Acetanisole was found to be antimicrobial 59 . Nonanal was found to be antimicrobial against P. vulgaris when isolated from the olive oil 60 . The major compounds of Leptospermum honeys with bioactivity against C. albicans, lacked activity against dermatophytes. A correlation was clearly observed between the presence of antifungal compounds in honey samples and the activity shown in the present study.

Scientific RepoRtS |
(2019) 9:18197 | https://doi.org/10.1038/s41598-019-54679-w www.nature.com/scientificreports www.nature.com/scientificreports/ The major compounds detected in Jarrah honey were Isophorone (40.06%) and Nonanoic acid (5.62%). Isophorone is an antioxidant 19 , which has been detected by others in three other Australian Eucalyptus honeys as well as Sunflower honey 61 . In contrast, Spanish Eucalyptus honeys contained two major chemical marker compounds (2-hydroxy-5-methyl-3-hexanone and 3-hydroxy-5-methyl-2-hexanone), but Isophorone was absent 62 . In another study, Fir, Thyme and Orange blossom honeys from Greece were reported to have Isophorone in significant amounts. The compound was detected in Spanish Citrus, Rosemary, Eucalyptus, Lavender, Thyme and Heather honeys as reported by 63 . In addition, Alpha Isophorone was identified in Corsican strawberry-tree honey and defined as a chemical marker for that honey. Jarrah honey is derived from Jarrah tree which belongs to Eucalyptus species. Other countries such as Italy, Spain, Portugal and Israel also produce Eucalyptus honey, but these have different tastes and aromas due to different floral varieties and climate conditions, which affect volatile compound composition. Isophorone has been declared floral marker for Heather honey 64 and Ulmo Chilean honey 13 . Another major compound observed in the present study was Nonanoic acid. This compound was also detected in other Australian Eucalyptus honeys 14 .
In summary, Agastache honey (40%) exhibited antifungal activity against dermatophytes and C. albicans in both the AWD and MD assays. The activity was fungicidal. Tea-tree showed fungicidal activity against T. mentagrophytes and C. albicans, but activity against T. rubrum was less than activity against the other fungal species tested. Manuka honey was active against C. albicans and showed some activity against dermatophytes. The activity was only fungistatic. Jelly bush, Super Manuka and Jarrah showed no activity against dermatophytes, but Jelly bush and Jarrah showed some activity against C. albicans. The volatile compound of all honeys were analysed by HS-SPME-GC-MS. This is the first time the volatile compounds of Agastache honey have been reported and screened for compounds possibly responsible for antifungal activity. Agastache honey contained several volatile compounds which have been reported to have antifungal activity whereas other honeys contained few antifungal compounds confirming the higher antifungal activity of Agastache honey than other honeys. The source of the volatile compounds were elucidated by detecting same compounds in both honey and flower. The study also identified chemical markers in each honey and identified common compounds in honey samples from different origin, for instance Leptospermum origin honeys contained Methyl 3,5-dimethoxybenzoate and Nonanal at variable percentages (Fig. 6). Based on higher abundance in each honey, the nominated chemical marker for honeys were: Agastache-Phenol-2, 4-bis (1, 1-dimethylethyl), Estragole and Nonanoic acid, ethyl ester; Manuka and Tea tree-ortho-Methoxyacetophenone, and Methyl 3,5-dimethoxybenzoate; Jelly bush-Linalool and Nonanal; Super Manuka-Methyl 3,5-dimethoxybenzoate and Nonanal; Jarrah honey-Isophorone and Nonanoic acid. The present findings that Agastache honey has greater antifungal activity than Leptospermum honeys, suggests that Agastache honey products could be developed for the topical application against skin-infections caused by fungi. However, this needs to be further confirmed by assessing honey in-vivo studies.

Methods
Sample preparation. Mono-floral Agastache honey was produced in a closed glass house as described by Antifungal activity of honey. Two different methods were used to evaluate antifungal activity of honey: well-diffusion (dermatophytes), broth dilution (dermatophytes and C. albicans). The well-diffusion and micro-broth dilution methods were performed according to the guidelines of National Committee for Clinical Laboratories Standards 65 and as described by the Alio S. et al. 66 .

Inoculum size preparation.
A clinical isolate of C. albicans (obtained from nail infection, Dorevitch pathology, Melbourne) and a reference strain of C. albicans (ATCC 10231) were maintained on Sabouraud Dextrose Agar (SDA, Oxoid, Australia) plates at 4 °C and sub-cultured prior to each experiment. C. albicans was suspended in sterile RPMI 1640 (Sigma Chemicals, St Louis, MO) and turbidity was adjusted to 0.5 McFarland, then suspensions were further diluted 1:100. T. mentagrophytes and T. rubrum, obtained from RMIT culture collection, were sub-cultured on SDA plates and incubated at 28 °C for 7 to 15 days. Both isolates sporulated well after this period. Stock conidial suspensions were prepared by covering the fungal colonies with 5 ml of sterile MilliQ water and gently rubbing with the tip of a sterile pipette tip. The suspensions were collected in sterile centrifuge tubes, counted using a haemocytometer. Conidial suspensions were adjusted to the desired density by adding RPMI 1640 medium with 10 g/l glucose (Sigma Chemicals, St Louis, MO) without sodium bicarbonate, to obtain a final concentration of 2 × 10 4 to 6 × 10 4 CFU/ml in 0.165 mol/l MOPS buffer (Gibco, Grand Island, NY), pH 7.0. Conidial concentration was verified by plating 10 ul of the adjusted conidial suspensions on SDA plates.
Agar well diffusion assay. The agar well diffusion assay was used to assess the antifungal activity of T. mentagrophytes and T. rubrum. To perform the assay, SDA plates were flooded with 100 µl of RPMI media containing conidial suspensions (2 × 10 4 to 6 × 10 4 CFU/ml) of either T. mentagrophytes or T. rubrum and the suspensions were evenly spread. The plates were dried for 20 mins followed by punching four holes (10 mm) with a sterile cork borer at different sites. Diluted honey samples (80%, 40%, 20%, and 10% w/v) were placed in each well. Fluconazole was included as control. Fluconazole was dissolved in water and tested in the range of (128-0.05 ug/ml). Plates were allowed for pre-diffusion for 10-15 min before incubation at 28 °C for 7 days. The growth of dermatophytes was observed each day and diameters of zones of inhibition were recorded after 7 days. www.nature.com/scientificreports www.nature.com/scientificreports/ Broth micro-dilution assay. The minimal inhibitory concentration (MIC) and minimal fungicidal concentration (MFC) were determined for the honey samples against C. albicans and the two dermatophyte isolates according to the method described in Nature protocol 67 with some modifications. The assays were performed in sterile, 96-well, flat-bottom, polystyrene microtiter plates (Corning Coster Ltd., NY). Briefly, C. albicans was streaked onto SDA plates and incubated for 24-48 hrs. Colony suspensions were prepared by touching 3-5 colonies with a sterile loop and transferring the inoculum into sterile 3-5 ml RPMI 1640. Turbidity was adjusted to 0.5 McFarland with sterile RPMI 1640, then suspensions were further diluted 1:100. Honey suspensions at variable concentrations (10%, 20%, 40% and 80%) were prepared in sterile RPMI, filtered through 0.45 µM filters and ten two-fold dilutions were made. Spore suspensions of the two dermatophytes were prepared as described in the previous section. 100 µl volumes of the diluted yeast or spore suspensions were inoculated into wells containing the honey dilutions resulting in the final inocula of ~5 × 10 5 cfu/ml C. albicans or 2 × 10 3 to 6 × 10 3 cfu/ml dermatophyte suspension.
Sterility controls containing media only and growth controls containing yeast/dermatophytes only were included in the assay. Inoculum size was validated by removing 10 µl volumes from the growth control well and performing viable counts. To control for the colour of different honey samples, OD 600 measurements were taken at 0 hrs and after 24-48 hrs incubation at 37 °C in the dark. Growth of yeast in the presence of honey was assessed by the following formula: OD honey treated wells /OD negative control well × 100, where the control well was assigned 100% growth. To assess fungistatic activity, 10 µl samples from the first 2 wells containing no visible growth were plated onto the SDA plates and incubated for 24 hrs. The fungistatic end point was defined as the highest dilution showing growth inhibition. The fungicidal end point was defined as the highest dilution showing no growth on the inoculated plates. Since the hydrogen peroxide and glucose oxidase are light-sensitive, samples were incubated in the dark. All experiments were performed in triplicate.
Hydrogen peroxide assay. Honey dilution initiates the production of hydrogen-peroxide since the glucose oxidase, an enzyme present in honey, is inactive in undiluted honey. Honeys used in this study were diluted to 40% and the production of hydrogen peroxide were measured as described in the protocol of OxiSelect ™ Hydrogen Peroxide Assay Kit (Fluorometric) (catalogue number STA-344, Cell Biolabs, VIC, Australia). The H 2 O 2 concentrations in the samples were calculated from the standard curve obtained by testing H 2 O 2 in the concentration range of 0 µM -200 µM. A fluorescence micro plate reader (Omega BMG LabTech, Australia) was used with an excitation of 544 nm and an emission of 590 nm. Experiments were performed three times in duplicate.

HS-SPME/GC-MS analysis. Extraction of volatiles.
The volatile compounds of honeys were determined according to the method described in Bianchi et al. 68 with minor modifications. Briefly, honey samples (4 g) were dissolved in 2 ml of Milli Q water in a 10 ml vial hermetically capped with PTFE/silicon septum (Chromatographic Specialties Inc.). Diluted honey samples were equilibrated for 20 mins using a heating block and volatiles were extracted for 50 min at 60 °C. Samples were agitated by magnetic stirring to accelerate the transfer of analyte from the sample matrix to the coating fibre. An 85-µm polyacrylate (PA) fibre was fitted to the manual sampling fibre holder (Supelco, Bellefonte, PA). The precondition PA fibre (270 °C, 1 h) was inserted into the headspace of the vial containing the sample and vial was placed on the heating blocks. The extraction process was performed in triplicate.
Gas chromatography-mass spectrometry. The extracted volatiles were desorbed by placing the fibre into the gas chromatography injection port for 5 min. The identification of volatile compounds was performed as described by Yamani et al. 38 using an Agilent 5973 MSD fitted with a DB-5 MS (5%-phenyl)-methylpolysiloxane fused silica column (Agilent) (30 m × 250 µm i.e. film thickness 0.25 µm). The analytical conditions were as follows; carrier gas helium (He 99.99%), flow rate 1.5 ml/min, split ratio 50:1. Initially, the oven temperature was 40 °C for 3 min, and it was raised later from 40 °C to 250 °C at 6 °C/min, where it was held for 5 min. The temperatures for injection port, transfer line and source temperatures were set at 250 °C, 280 °C, and 230 °C respectively. The samples were scanned in the mass range of 41-415 m/z as per Adams: Essential oil components by Quadrupole GC/MS 69 .
Spectra were acquired and processed using MSD ChemStation (E02.00.493). Compounds were identified with GC-MS reference libraries (Adams, Wiley 7th and NIST 2.0) using a 70% similarity match cut-off value. The peak area in the total ion chromatograms was the basis of calculations of concentration of studied compounds. The relative abundance was determined by integrating measurements obtained from three replicates. Statistical analysis. Minitab 18 (MiniTab Inc., PA, USA) was used to compare the fungal growth after treatment with different concentrations of honey. Analysis of variance (ANOVA) was followed by post hoc Tukey test and Kruskal-Wallis (KW) tests. Each experiment was conducted in triplicate and data were calculated from three different experiments. Significance was accepted as p ≤ 0.05.