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Screening novel genes by a comprehensive strategy to construct multiple stress-tolerant industrial Saccharomyces cerevisiae with prominent bioethanol production

Screening novel genes by a comprehensive strategy to construct multiple stress-tolerant... ENA5 Functional KF-7-ENA5 vs KF-7 genes E-158-ENA5 vs E-158 ASP3 KF-7 Mutagenesis Crz1p Transcription and factors Tos8p hybridization YOL162W Genes of unknow function YOR012W Transcriptome under five stress E-158 conditions Fermentation Expression regulation Background of S. cerevisiae [13, 14]. Such environmental stresses Bioethanol, an eco-friendly renewable biofuel, is one of possibly cause lipid peroxidation, protein denaturation, the alternatives of fossil gasoline [1]. Bioethanol produc- DNA damage, cell apoptosis, etc., of S. cerevisiae [15, tion is based on the fermentation of starchy (cassava, 16]. Extensive improvements of the multiple stress-toler- corn, microalgae, etc.), sugary (molasses, sweet sorghum/ ance and robustness of S. cerevisiae are of paramount to sugarcane juice, etc.), or lignocellulosic (straw, corn achieve high bioethanol production. cob, etc.) biomass [1, 2]. Species including Saccharomy- However, breeding multiple stress-tolerant industrial ces cerevisiae, Kluyveromyces marxianus, Zymomonas S. cerevisiae strains that perform well when using which- mobilis, and Pichia stipites are bioethanol producers ever feedstocks is still challenging [17]. Presently, some [3–5]. S. cerevisiae is the main species used for indus- studies have reported that stress-tolerance of strains can trial ethanol production due to its good fermentation be improved by random mutagenesis [18], genome shuf- performance and stress resistance [6–8]. However, S. cer- fling [19], and genetic engineering [17]. Compared with evisiae is commonly exposed to different kinds of envi - random mutagenesis and genome shuffling, genetic engi - ronmental stresses in the industrial fermentation process neering is of great significance because of short breeding with different feedstocks. For example, in simultaneous time, clear gene targeting and clear relationship between saccharification and fermentation (SSF) with lignocel - gene and phenotype. Over the past decades, studies have lulosic or starchy biomass as feedstock, S. cerevisiae is reported that a number of genes were closely related to expected to resist high temperatures (since the optimal ethanol, heat, or osmosis stress tolerance of S. cerevisiae enzymatic saccharification temperature is 45–50  °C) [9, 20–22], which can be used as the potential targets to and high ethanol concentration [9–11]. Similarly, during improve stress tolerance of the strains. Based on these very high gravity (VHG) fermentation using sugar-based findings, a number of trials have been performed. For raw materials (molasses, concentrated sweet sorghum example, overexpression of ISU1 and JAC1 increased the juice, and sugarcane juice), strains should withstand the ethanol tolerance [23] and overexpression of HSF1 and high concentration of sugar at the early stage and high MSN2 promoted cell growth and high temperature fer- ethanol concentration at the later stage [12]. Moreover, mentation [24]. Salt tolerance can be enhanced by over molasses without acid pretreatment has high salt con- expressing CDS1 and CHO1 [25]. However, these stud- tent, which notably impedes the fermentation efficiency ies mainly focused on the improvement of resistance to 9% Ethanol 44°C 43°C+3% (v/v) ethanol 28% Glucose 1.5 M NaCl Increased percentage of ethanol concentration (%) W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 3 of 19 single stress (high ethanol or high temperature). To our of RNA-seq data, hundreds of DEGs were found under knowledge, none of the genes linking to multiple stress- each kind of stress condition (Fig. 2A). tolerance has been reported to date. Since S. cerevisiae Twenty-eight DEGs were found shared under all five strains are forced to face diverse environmental stresses stress conditions via Venn diagram (Fig.  2B, Addi- during the industrial fermentation, it is vital to identify tional file  1: Table  S1), suggesting their potential con- gene targets that could be engineered to improve multi- tributions to multiple stress-tolerant phenotypes. GO ple stress-tolerance of S. cerevisiae. and KEGG analyses revealed that these DEGs were In our previous study, a S. cerevisiae strain E-158 was involved in multiple biological processes. The func - obtained by random mutagenesis and hybridization, tional gene ASP3, whose expression largely decreased which shows higher capability of multiple stress-toler- (log FC: − 10 ~ − 12), was involved in both processes ance than its original strain KF-7 [18]. To identify poten- of response to stress (GO: 0006950) and cellular nitro- tial target genes related to multiple stress-tolerance, in gen compound metabolism (GO: 0034641) (Fig.  2C). the present study, the comparative transcriptome analy- ASP3 was also involved in cyanoamino acid metabo- sis was performed between strain E-158 and its original lism (KEGG Pathway: sce00460), the only pathway strain KF-7 under five stress conditions. Six target genes significantly enriched by the KEGG analysis, suggest - which possibly contribute to the multiple stress-tolerant ing ASP3 may be one of the key genes regulating mul- phenotypes of S. cerevisiae were mined by a comprehen- tiple-tolerant phenotypes of S. cerevisiae (Fig.  2D). To sive strategy. CRISPR/Cas9 technology was used to reg- reveal the relationship among DEGs and to find the ulate the expression of these six target genes to explore core regulatory target genes, protein–protein interac- their impacts on the multiple stress-tolerance pheno- tion network analysis was performed for the 28 shared types of S. cerevisiae. Moreover, the stress tolerance of DEGs. As shown in Fig. 2E, gene ENA5 (log FC: 2 ~ 16) the engineered strains was assessed using three kinds of was located at the core of the network and had strong typical industrial feedstocks. relationships with other DEGs. ENA5 encodes a P-type + + ATPase (extrudes Na probably in exchange for H ), which may assist the efflux of sodium ions, thus reduc - ing cytotoxicity [26]. It could be one key functional Results gene responsible for regulating multiple-tolerant phe- Fermentation performance of original strain KF‑7 notypes of S. cerevisiae. and resistant strain E‑158 Six DEGs with unknown function (putative pro- In our previous study, an excellent multiple stress-tol- tein with unknown function in Saccharomyces erant strain E-158 was obtained by using a strategy of Genome Database) in 28 shared DEGs were all sig- random mutagenesis and hybridization [18]. The strain nificantly down-regulated (Fig.  2F). Among these E-158 showed higher ethanol production and glucose six DEGs, the expression of DEGs named YOL162W consumption rates than the original strain KF-7 under (log FC: − 8 ~ − 11), YOL163W (log FC: − 8 ~ − 10) 2 2 five stress conditions. The final concentrations of etha - and YOR012W (log FC: − 8 ~ − 10) decreased more nol produced by E-158 during batch fermentations were than other three DEGs, suggesting they may have a 66.89%, 33.37%, 81.02%, 10.14%, and 35.98%, respectively, greater impact on the tolerance phenotype [27]. Genes higher than those of KF-7 under five stress conditions: YOL162W and YOL163W have high sequence similar- (1) 8.0% (v/v) initial ethanol, (2) 44 °C, (3) 43 °C and 2.6% ity and were proposed to have similar function [28]. (v/v) initial ethanol, (4) 27% glucose, (5) 1.25  M NaCl Hence, YOL162W and YOR012W were selected as can- (Fig. 1). didate genes to explore their effects on multiple-toler - ant phenotypes of S. cerevisiae. Crz1p (log FC: 1 ~ 2) and Tos8p (lo g FC: − 9 ~ − 13) 2 2 Comprehensive strategy of mining key genes regulating were two transcriptional factors (TFs) found in the stress‑tolerant phenotypes of S. cerevisiae 28 shared DEGs (Fig.  2G). The regulatory relation - To mine the potential key genes governing the multiple ship between these two TFs and the 28 shared DEGs stress-tolerant phenotypes of S. cerevisiae, transcrip- was explored through YEASTRACT database. The tional profiles of strains KF-7 and E-158 under five stress results showed that the DEGs including SPO24, ENA5, conditions were investigated based on RNA-seq with WSC2, HSP150, YOL162W, and YOL163W among the three biological replicates (the RNA extraction times 28 shared DEGs were potentially regulated by Crz1p. were shown in Fig.  1, and the gene expression levels of DEGs of GEX2 and YDR222W were potentially regu- KF-7 under same stress conditions were taken as the con- lated by Tos8p. Therefore, Crz1p and Tos8p may be trol group). According to differential expression analysis Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 4 of 19 60 120 140 160 44°C 8.0% Ethanol 130 140 50 100 120 120 RNA: 16 h 40 80 110 100 30 60 100 80 90 60 20 40 80 40 10 20 70 20 RNA: 48 h 0 0 60 0 Time (h) Time (h) 160 320 70 120 270 g/L Glucose 43°C + 2.6% Ethanol 140 280 60 100 120 240 50 80 100 200 RNA: 30 h 40 60 80 160 60 120 30 40 40 80 20 20 20 40 RNA: 12 h 10 0 0 0 01020304050607080 0102030405060708090 100 Time (h) Time (h) 70 210 1.25 mol/L NaCl 60 180 50 150 RNA: 48 h 40 120 30 90 20 60 10 30 0 0 Time (h) Fig. 1 Fermentation characteristics under five stress conditions. Fermentation kinetics (A–E) of KF‑7 (open squares: glucose; closed squares: ethanol) and E‑158 (open circles: glucose; closed circles: ethanol) were shown. Data are averages of three independent experiments (error bars represent SD) (See figure on next page.) Fig. 2 A comprehensive selection of key genes potentially related to the multiple stress‑tolerant phenotypes. A DEGs under five stress conditions; B Venn diagram of DEGs under the five stress conditions, including 28 shared DEGs; C GO enrichment analyses of 28 shared DEGs; D the pathway of cyanoamino acid metabolism; E protein–protein interaction network of 28 shared DEGs. In the plot, the bluer the circle, the greater the contribution of the gene, the thicker the line, the stronger the interaction between the two genes; F Relative expression level of the DEGs of unknown function in 28 shared DEGs; G DEGs regulated by the two identified TFs in 28 shared DEGs Ethanol concentration (g/L) Ethanol concentration (g/L) Ethanol concentration (g/L) Glucose concentration (g/L) Glucose concentration (g/L) Ethanol concentration (g/L) Ethanol concentration (g/L) Glucose concentration (g/L) Glucose concentration (g/L) Glucose concentration (g/L) W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 5 of 19 A A Down-regulated genes B Up-regulated genes 28 shared DEGs 300 404 200 133 122 112 C D Transport L-isoleucine Response to stress N-Hydroxy-L-isoleucine Cellular nitrogen compound metabolic process L-Aspartate APS3 Functional gene L-Asparagine Reproduction Cell wall organization or biogenesis Log2FC E F SPO24 YOL163W MF(ALPHA)2 GEX2 AAD15 ASP3-3 YOL162W AGA1 HSP150 PHO12 ASP3-2 ASP3-4 BDS1 Log2FC ASP3-1 ENA5 FLO9 VTH2 VTH1 CRZ1 Functional gene Node color (degree): TOS8 LowHigh CRZ1 Transcriptional factor TOS8 Transcriptional factor Positive Negative Unspecified SPO24 HSP150 YOL162W WSC2 GEX2 ENA5 YOL163W YDR222W Fig. 2 (See legend on previous page.) EE vs KE ET vs KT ETE vs KTE EG vs KG ES vs KS Differentially expressed genes (DEGs) Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 6 of 19 key TFs regulating multiple-tolerant phenotypes of S. not grow when the temperature was 44 °C. However, the cerevisiae. growth of other strains was significantly better than that of KF-7. When the spot assay was respectively performed Growth and fermentation abilities of engineered strains under the osmotic stress conditions, i.e., 400 g/L glucose using original strain KF‑7 as host and 3  mol/L sorbitol, strains KF-7-CRZ1, KF-7-ENA5, To experimentally verified whether the identified key KF-7ΔASP3, KF-7ΔTOS8, and KF-7ΔYOR012W grew DEGs are responsible for the multiple-tolerant pheno- better than KF-7, but there was no significant difference types in strain E-158, using its original strain KF-7 as a between KF-7ΔYOL162W and KF-7. host, genes CRZ1 and ENA5 were over expressed, and To evaluate the ability of ethanol tolerance of the genes ASP3, TOS8, YOL162W, and YOR012W were engineered strains, batch fermentations were per- knocked out to result in strains KF-7-CRZ1, KF-7-ENA5, formed using YPD150 media with 8.0% (v/v) initial KF-7ΔASP3, KF-7ΔTOS8, KF-7ΔYOL162W, and ethanol concentration (Fig.  4A). Except for KF-7-CRZ1 KF-7ΔYOR012W, respectively. The growth of these engi - and KF-7ΔYOL162W, the other strains produced sig- neered strains under different stress conditions was com - nificantly (P < 0.05) more ethanol than KF-7 (Table  1). pared with that of KF-7 through the spot assay (Fig.  3). After 96-h fermentation, the order of the final ethanol Under the condition without stress, strains showed simi- concentrations produced by these strains was as fol- lar growth capacities. When exposed to 13% (v/v) etha-lows: K F-7 -EN A 5 > KF- 7 Δ ASP 3 > KF- 7 ΔYO R01 2 W > nol, all strains, except strain KF-7-CRZ1, grew better than KF- 7ΔTO S8 > K F -7Δ YOL 162W > KF-7 > KF- 7-C RZ1 . Th KF-7. Under the heat stress, strain KF-7ΔYOL162W did e e tha nol concentration of KF- 7-ENA5 was the highest Fig. 3 Growth abilities of engineered strains using original strain KF‑7 as the host under different stress conditions W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 7 of 19 Fig. 4 Fermentation abilities of engineered strains using original strain KF‑7 as the host under five stress conditions. A 8.0% initial ethanol; B 44 °C; C 43 °C with 2.6% initial ethanol; D 270 g/L glucose; E 1.25 mol/L NaCl; F 1.5 mol/L NaCl. Data are averages of three independent experiments (error bars represent SD) Meanwhile, the ethanol concentration of KF-7ΔASP3 (23.96 ± 0.73 g/L), which was 27.57% higher than that of (25.91 ± 2.24  g/L) was 99.31% higher than that of KF-7 KF-7 (18.79 ± 2.11 g/L) (Table 1). (13.00 ± 1.84 g/L) under two stresses of ethanol and heat During the batch fermentations at 44  °C, the etha- (Fig. 4C, Table 1). nol concentration of KF-7ΔYOL162W was only 56.39% VHG fermentations were conducted using YP of that of KF-7, but the ethanol concentrations of other medium with 271.09  g/L glucose concentration. strains were significantly (P < 0.05) higher than that Except for strain KF-7ΔYOL162W, the ethanol con- of KF-7 (Fig.  4B, Table  1). Among them, KF-7ΔASP3 centrations of other strains were increased by 2.45% (44.37 ± 1.86  g/L) had the highest ethanol production, (KF-7ΔYOR012W ) ~ 6.24% (KF-7-ENA5) compared which was 41.35% higher than KF-7 (31.39 ± 2.54  g/L). Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 8 of 19 Table 1 Comparisons of fermentation performance of engineered strains using original strain KF‑7 as the host Indexes Strains 8.0% (v/v) 44 °C 43 °C + 2.6% (v/v) 27% Glucose 1.25 M NaCl Initial ethanol (YPD100) Initial ethanol (YPD270) (YPD150) (YPD150) (YPD100) KF‑7 18.79 ± 2.11c 31.39 ± 2.54c 13.00 ± 1.84b 123.92 ± 0.79c 43.78 ± 1.37d Final generated ethanol concentration KF‑7‑ CRZ1 14.82 ± 1.48d 40.11 ± 2.42ab 21.93 ± 1.49a 128.99 ± 1.05b 63.66 ± 1.50a (g/L) KF‑7‑ENA5 23.96 ± 0.73a 41.69 ± 0.66ab 22.50 ± 1.70a 131.65 ± 0.99a 64.26 ± 1.12a KF‑7ΔASP3 22.76 ± 1.12ab 44.37 ± 1.86a 25.91 ± 2.24a 128.19 ± 0.69b 45.16 ± 1.17d KF‑7ΔTOS8 20.26 ± 1.57ab 36.58 ± 2.19bc 14.63 ± 1.79b 129.40 ± 0.96ab 54.78 ± 0.81bc KF‑7ΔYOL162W 19.49 ± 0.94bc 17.70 ± 3.60d 4.24 ± 1.26c 122.80 ± 1.19c 57.77 ± 1.62b KF‑7ΔYOR012W 22.45 ± 1.11ab 37.63 ± 1.54bc 16.94 ± 1.43b 126.95 ± 1.99bc 51.16 ± 1.33c KF‑7 100.12 ± 4.07ab 29.51 ± 3.57b 71.80 ± 3.41b 25.09 ± 1.49a 40.18 ± 4.81a Residual glucose (g/L) KF‑7‑ CRZ1 105.01 ± 3.12a 13.75 ± 3.78 cd 50.59 ± 2.80d 13.48 ± 2.58c 0.00 ± 0.00c KF‑7‑ENA5 86.88 ± 1.55d 12.62 ± 4.69 cd 50.10 ± 3.37d 10.90 ± 1.88c 0.00 ± 0.00c KF‑7ΔASP3 89.53 ± 1.29 cd 5.89 ± 2.90d 41.76 ± 4.16d 15.05 ± 1.31bc 34.11 ± 2.72a KF‑7ΔTOS8 95.74 ± 2.71bc 19.88 ± 3.72bc 67.85 ± 3.33bc 13.74 ± 1.91c 9.76 ± 1.88b KF‑7ΔYOL162W 98.98 ± 1.86ab 57.75 ± 5.06a 85.36 ± 2.35a 29.66 ± 2.92a 1.36 ± 0.53c KF‑7ΔYOR012W 90.97 ± 1.13 cd 18.56 ± 2.63c 61.66 ± 2.84c 19.48 ± 1.17b 14.66 ± 3.09b Ethanol yield (g ethanol/g consumed KF‑7 0.45 ± 0.01a 0.45 ± 0.01bc 0.47 ± 0.01a 0.50 ± 0.01a 0.42 ± 0.02ab glucose) KF‑7‑ CRZ1 0.41 ± 0.01b 0.46 ± 0.00ab 0.46 ± 0.01a 0.50 ± 0.00a 0.44 ± 0.02ab KF‑7‑ENA5 0.44 ± 0.00a 0.48 ± 0.02a 0.46 ± 0.01a 0.50 ± 0.01a 0.45 ± 0.01a KF‑7ΔASP3 0.44 ± 0.00a 0.47 ± 0.00ab 0.46 ± 0.01a 0.50 ± 0.00a 0.41 ± 0.00bc KF‑7ΔTOS8 0.44 ± 0.02a 0.46 ± 0.01ab 0.47 ± 0.01a 0.49 ± 0.01a 0.41 ± 0.00bc KF‑7ΔYOL162W 0.46 ± 0.01a 0.42 ± 0.01c 0.32 ± 0.02b 0.49 ± 0.01a 0.41 ± 0.01bc KF‑7ΔYOR012W 0.45 ± 0.01a 0.46 ± 0.01ab 0.45 ± 0.02a 0.50 ± 0.01a 0.39 ± 0.01c The data in the table are those at the end of fermentation. Values indicate mean ± standard deviation of three biological replications. Values followed by different lowercase letters in the same column indicate significant differences at the level of P < 0.05 (Tukey-test) among strains. Same lowercase letters, no difference. KF-7-CRZ1: overexpression of TF Crz1p in KF-7; KF-7-ENA5: overexpression of ENA5 in KF-7; KF-7ΔASP3: Knockout ASP3 in KF-7; KF-7ΔTOS8: Knockout TOS8 in KF-7; KF-7ΔYOL162W: Knockout YOL162W in KF-7; KF-7ΔYOR012W: Knockout YOR012W in KF-7 with that of KF-7 (Fig.  4D, Table  1). All strains had that of E-158 in the presence of 13% (v/v) ethanol, while improved fermentation performance when ferment- the growth of E-158-CRZ1 was poor (Fig.  5). E-158- ing YPD150 medium supplemented with 1.25  mol/L CRZ1 and E-158-ENA5 grew better than E-158 under (7.31%) NaCl (Fig.  4E). Especially, after 96-h fermenta- heat stress at 44  °C. Under the high osmotic conditions tion, strains KF-7-CRZ1 and KF-7-ENA5 utilized all of 400  g/L glucose, 3  mol/L sorbitol, or 2  mol/L NaCl, glucose, but the residual glucose was 43.78 ± 1.37  g/L the growths of E-158-CRZ1 and E-158-ENA5 were bet- for KF-7 (Table  1). When the concentration of NaCl ter than that of E-158. Particularly, under 2  mol/L NaCl was increased to 1.5  mol/L, strains KF-7-CRZ1 and KF- stress, both the engineered strains showed excellent 7-ENA5 showed high ethanol production and glucose growth capacities. consumption rates (Fig. 4F). The final ethanol concentra - Batch fermentations of E-158-CRZ1 and E-158-ENA5 tions were 52.48 ± 0.97  g/L and 44.93 ± 1.58  g/L, which were conducted under five stress conditions. Overex - were 121.42% and 89.56% higher than those of KF-7, pression of ENA5 further increased the ethanol toler- respectively. ance of E-158. The ethanol produced by E-158-ENA5 (32.39 ± 1.02  g/L) was 13.09% higher than that of E-158 Growth and fermentation abilities of engineered strains (28.64 ± 1.66 g/L) when YPD150 medium with 8.0% (v/v) using resistant strain E‑158 as host initial ethanol concentration was fermented (Fig.  6A, Since the overexpression of ENA5 or CRZ1 significantly Table  2). However, the ethanol concentration of strain improved multiple stress-tolerance of the original strain E-158-CRZ1 was lower than that of E-158. KF-7, the effects of overexpression of these two genes on Under fermentation at 44  °C, the ethanol concentra- resistant strain E-158 were further explored. Overexpres- tions of E-158-CRZ1 and E-158-ENA5 were increased sion of ENA5 and CRZ1 using E-158 as host resulted in by 11.86% and 14.17%, respectively, compared with that strains KF-7-CRZ1 and E-158-ENA5, respectively. The of E-158 (Fig.  6B, Table  2). Meanwhile, the ethanol pro- growth of E-158-ENA5 was significantly better than duction and glucose consumption rates of E-158-CRZ1 W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 9 of 19 Fig. 5 Growth abilities of engineered strains using resistant strain E‑158 as the host under different stress conditions and E-158-ENA5 were significant higher (P < 0.05) than 63.35 ± 2.50  g/L, 65.50 ± 3.71  g/L, and 68.40 ± 1.59  g/L, those of E-158 under the multiple stress of ethanol and respectively, which were increased by 13.35%, 17.19%, heat, and the final ethanol concentrations produced by and 22.38% individually, compared with that of the origi- them were increased by about 30% compared with that of nal strain KF-7 (55.89 ± 2.68  g/L) (Fig.  7A, Additional E-158 (Fig. 6C, Table 2). file  1: Fig. S1A, B). The engineered strains also showed When VHG fermentation was conducted under much higher ethanol yields (Additional file  1: Table  S5). 280.72  g/L glucose concentration, significant (P < 0.05) These results indicated that the overexpression of ENA5 difference in the fermentation performance among the improved the fermentation capacity of the strains under strains was not observed (Fig.  6D). However, under the high temperatures. fermentation condition of 1.25 mol/L NaCl, E-158-CRZ1 When the molasses with 270.91 g/L total sugar was fer- and E-158-ENA5 consumed all the glucose at 72 h, which mented, the final ethanol concentrations of KF-7-ENA5, was 24  h earlier than E-158 (Fig.  6E). When the con- E-158, and E-158-ENA5 were 22.32%-27.31% higher than centration of NaCl was increased to 1.5  mol/L, the final that of KF-7, and the strain E-158-ENA5 had the highest ethanol concentrations of E-158-CRZ1 and E-158-ENA5 ethanol concentration of 98.28  g/L (Fig.  7B, Additional were 46.90 ± 2.10  g/L and 56.73 ± 1.05  g/L, respectively, file  1: Fig. S1C). When cassavas with a solid content of which were 66.73% and 101.67% higher than that of 35% were used for SSF at 33  °C, the ethanol concentra- E-158 (28.13 ± 1.58  g/L) (Fig.  6F, Table  2). In conclusion, tions of strains KF-7-ENA5, E-158, and E-158-ENA5 overexpression of ENA5 improved all kinds of stress tol- were 6.50%, 11.01%, 14.08% respectively after 96-h fer- erance of resistant strain E-158. mentation, higher than that of KF-7, and the ethanol concentration produced by strain E-158-ENA5 was 138.43  g/L (Fig.  7C, Additional file  1: Fig. S1D). These Fermentation abilities of engineered strains results suggested that the overexpression of ENA5 simul- when fermenting pretreated straw, molasses and cassava taneously enhanced tolerance of the strains to the heat, under stress conditions ethanol, and osmosis when different industrial feedstocks To evaluate the potential of the strains engineered in this were fermented. study for industrial applications, the fermentation abili- ties of strains KF-7, KF-7-ENA5, E-158, and E-158-ENA5 were assessed using pretreated straw, molasses, and cas- Discussion sava, which are feedstocks commonly used in industrial To find target genes that can increase the multiple ethanol production (Additional file  1: Tables S2, S3, S4). stress-tolerant ability of S. cerevisiae suitable for vari- By SSF of pretreated straw at 42 °C, the ethanol concen- ous industrial feedstocks is still challenging because trations of KF-7-ENA5, E-158, and E-158-ENA5 were of the molecular regulation complexity of multiple Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 10 of 19 Fig. 6 Fermentation abilities of engineered strains using resistant strain E‑158 as the host under five stress conditions. A 8.0% initial ethanol; B 44 °C; C 43 °C with 2.6% initial ethanol; D 280 g/L glucose; E 1.25 mol/L NaCl; F 1.5 mol/L NaCl. Data are averages of three independent experiments (error bars represent SD) stress-tolerant phenotypes. Presently, researchers have In the present study, by comparing the transcriptomes of reported that single tolerance to ethanol or high tempera- E-158 and KF-7, 28 DEGs were found shared under five ture of S. cerevisiae can be significantly improved by over stress conditions (Fig. 2). Six of them were mined and all expressing or knocking out some genes or TFs [23, 24], of them were found to be associated with multiple stress- however, researches on screening key genes responsible tolerant phenotypes of S. cerevisiae. for enhancing the multiple stress-tolerance of industrial Among the six DEGs, ENA5 was the most prominent S. cerevisiae are absent. In our previous study, a multiple in the multiple stress-tolerance improvement. To date, stress-tolerant strain E-158 was obtained by mutagenesis no report has revealed the relationship between ENA5 and hybridization using KF-7 as the starting strain [18]. and the stress tolerance phenotypes of S. cerevisiae. Our W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 11 of 19 Table 2 Comparisons of fermentation performance of engineered strains using resistant strain E‑158 as the host Indexes Strains 8.0% (v/v) 44 °C 43 °C + 2.6% (v/v) 28% Glucose 1.5 M NaCl Initial ethanol (YPD100) Initial ethanol (YPD280) (YPD150) (YPD150) (YPD100) Final generated ethanol concentration (g/L) E‑158 28.64 ± 1.66bc 38.12 ± 1.90b 18.66 ± 1.62b 128.40 ± 1.17b 28.13 ± 1.58c E‑158‑ CRZ1 25.24 ± 1.99c 42.64 ± 1.71a 24.34 ± 1.76a 131.77 ± 0.79a 46.90 ± 2.10b E‑158‑ENA5 32.39 ± 1.02a 43.52 ± 1.17a 23.43 ± 0.95a 132.90 ± 1.80a 56.73 ± 1.05a E‑158 78.00 ± 3.40a 17.91 ± 1.72a 56.25 ± 3.00a 25.75 ± 2.22a 72.47 ± 4.53a Residual glucose (g/L) E‑158‑ CRZ1 82.34 ± 2.35a 9.70 ± 2.66b 43.99 ± 3.30b 19.21 ± 1.95b 34.24 ± 4.36b E‑158‑ENA5 70.44 ± 1.74b 7.21 ± 2.03b 44.13 ± 1.40b 17.79 ± 2.79b 8.75 ± 2.54c Ethanol yield E‑158 0.45 ± 0.01ab 0.46 ± 0.00a 0.44 ± 0.00a 0.50 ± 0.00a 0.40 ± 0.01b (g ethanol/g consumed glucose) E‑158‑ CRZ1 0.43 ± 0.01b 0.47 ± 0.01a 0.44 ± 0.01a 0.50 ± 0.01a 0.43 ± 0.00a E‑158‑ENA5 0.46 ± 0.01a 0.47 ± 0.01a 0.43 ± 0.01a 0.50 ± 0.01a 0.42 ± 0.01a The data in the table are those at the end of fermentation. Values indicate mean ± standard deviation of three biological replications. Values followed by different lowercase letters in the same column indicate significant differences at the level of P < 0.05 (Tukey-test) among strains. Same lowercase letters, no difference. E-158- CRZ1: Overexpression of TF Crz1p in E-158; E-158-ENA5: Overexpression of ENA5 in E-158 Fig. 7 Fermentation results of engineered strains when pretreated straw, molasses, and cassava were fermented under stress conditions. A High‑temperature SSF of pretreated straw; B VHG fermentation of molasses; C SSF of cassava with high solid content study revealed for the first time that the overexpression Fig. 6F). ENA5 is previously reported as encoding P-type of ENA5 could significantly improve the tolerance of ATPase that may assist the efflux of sodium ions [26, S. cerevisiae to all kinds of stresses studied. Especially, 29]. Therefore, the overexpression of ENA5 may reduce after overexpression of ENA5, the ethanol concentra- cytotoxicity and enhance the salt tolerance of S. cerevi- tions of engineered strains were increased to about two- siae through assisting in the efflux of sodium ions. Genes fold under the conditions of 1.5  mol/L NaCl (Figs.  4F, ENA1、ENA2、ENA5 are the members of a gene cluster Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 12 of 19 encoding proteins with very similar function [30]. These improvement of multiple stress-tolerance needs further genes highly expressed under high sucrose tolerance [31], investigations. The overexpression of CRZ1 significantly which indicating ion transport is possibly important for improved the high temperature tolerance as well as the S. cerevisiae to resist high osmotic stress. Nevertheless, high osmosis tolerance of the strains (Figs.  4, 6). Crz1p the specific regulatory mechanism of gene ENA5 on the is a zinc finger TF, which regulates 14.6% of the genes multiple stress-tolerant phenotypes of S. cerevisiae needs in the genome of S. cerevisiae based on YEASTRACT to be investigated in detail in the future study. database. The genes regulated by Crz1p are significantly In addition to gene ENA5, for the first time, gene ASP3 enriched in pathways of carbohydrate metabolic process was found having an important effect on high ethanol (GO: 0005975), cell wall organization or biogenesis (GO: and high temperature stress tolerance phenotypes of S. 0071554), and transmembrane transport (GO: 0055085). cerevisiae. ASP3 is a gene cluster composed of four iden- CRZ1 has been reported able to enhance the resistance of tical genes, i.e., ASP3-1, ASP3-2, ASP3-3, and ASP3-4, S. cerevisiae to high concentrations of cations including 2+ 2+ + + which encode L-asparaginase II [32]. Asparaginase II is Ca, Mn, Na , and Li by regulating the genes of cal- a periplasmic enzyme in yeast, hydrolyzing both D- and cium signaling pathway [39]. Interestingly, in the present L-asparagine to aspartate and ammonium cation [32]. study, overexpression of CRZ1 increased not only high ASP3 was upregulated during nitrogen starvation to facil- salt tolerance, but also high temperature and high glu- itate the utilization of extracellular asparagine as a source cose tolerance of the strains (Tables  1, 2). Though there of nitrogen [33]. Nitrogen starvation could promote the are reports that regulation the genes involved in carbo- synthesis of lipid and/or polyhydroxybutyrate (PHB) [34, hydrate metabolic and cell wall synthesis could effectively 35]. However, the molecular regulation mechanism of improve the high temperature, high ethanol, or high the deletion of ASP3 on stress tolerance and the possible osmosis stress tolerance of S. cerevisiae [23, 24, 40], the relationship between the nitrogen starvation response specific molecular regulation mechanism of Crz1p on and the stress tolerance are still unknown, which need multiple stress-tolerance should be clarified in the future. further investigations. Those strains over-expressing ENA5 showed much bet- Genes of unknown function were often found ter ethanol production than the original strains when expressed [36], however, no studies showed the relation- fermenting different raw materials. When high-temper - ship between genes of unknown function and stress- ature SSF and VHG fermentation were carried out with tolerant phenotypes of S. cerevisiae. Knocking out gene pretreated straw, molasses and cassava, the concentra- YOR012W of unknown function had a limited effect on tions of ethanol produced by the engineered strains were the multiple stress-tolerant phenotypes of KF-7. How- significantly higher than those produced by the original ever, knocking out YOL162W significantly improved the strains and strains reported by most researchers (Fig.  7, high salt tolerance while significantly reduced the high Table 3) [13, 14, 41–47]. Considering the costs of materi- temperature resistance of the strain KF-7. Although the als, equipment, energy consumption and labor, the costs function of the protein encoded by YOL162W is unclear, of ethanol production with straw, molasses and cassava YOL162W had a vital relationship with the high tempera- are calculated to be about 0.60 US$, 0.62 US$, and 0.98 ture and high salt tolerance phenotypes (Table  1), the US$ per liter (average price of ethanol in the market is underly mechanism is worthy for further investigation. about 0.75 US$ per liter) [48–51]. Though the system - Several studies reported that TFs are important to atic assessments of changes of parameters including regulate the tolerance phenotype of S. cerevisiae [24, fermentation temperature, mash concentration, and 37]. However, the relationship of the two TFs, Tos8p ethanol concentration on the ethanol production cost and Crz1p, with the multiple stress tolerances was not when different feedstocks are used is needed. Several reported to date. Tos8p was reported to be associated studies reported that if the fermentation temperature is with chromatin and highly expressed under meiosis and increased by 1 °C and if the ethanol yield is increased by cell damage [38]. In the present study, knocking out TOS8 10%, the cost of ethanol can be reduced by about 0.04 in original strain KF-7 increased the osmosis and high US$ per liter and 0.03 US$ per liter, respectively [51, 52]. temperature tolerance phenotypes of the strain (Table 1). This suggested that the strains engineered in the present YEASTRACT database shows that the TF Tos8p regu- study have good prospects for reducing ethanol produc- lates 8.0% of the genes in the genome of S. cerevisiae. tion cost and hence have wide industrial applications. The genes regulated by Tos8p are significantly enriched In the previous study, we obtained strain E-158 in pathways of fungal-type cell wall organization or bio- using KF-7 as the original strain by combined tech- genesis (GO: 0071852), cation transport (GO: 0006812), niques including ARTP mutagenesis, genome shuf- and siderophore transport (GO: 0015891). However, the fling and hybridization, which took a lot of time and molecular mechanism of the deletion of TOS8 on the labor [18]. However, in the present study, the key gene W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 13 of 19 Table 3 Comparisons of ethanol concentrations of strains when different raw materials were fermented under stress conditions Strains Process (Solid content) Temperature (℃) Substrates Ethanol References concentration (g/L) Cellulose materials S. cerevisiae Angel Yeast P‑SSF (20%) 39.0 Corn stover 59.80 [41] S. cerevisiae TJ14 P‑SSF (/) 39.0 Microcrystalline cellulose 45.00 [42] K. marxianus NRRL Y‑6860 SSF (24%) 41.5 Rice straw 52.30 [43] KF‑7 P‑SSF (20%) 42.0 Rice straw 55.89 This study KF‑7‑ENA5 P‑SSF (20%) 42.0 Rice straw 63.35 This study E‑158 P‑SSF (20%) 42.0 Rice straw 65.50 This study E‑158‑ENA5 P‑SSF (20%) 42.0 Rice straw 68.40 This study Molasses S. cerevisiae NCYC3233‑27c VHG (/) 35.0 Unpretreated molasses 78.90 [14] S. cerevisiae UAF‑1 VHG (270.0 g/L) 32.0 Acid pretreated molasses 96.00 [44] S. cerevisiae SFO6 VHG (250.0 g/L) 30.0 Unpretreated molasses 55.20 [13] KF‑7 VHG (270.9 g/L) 33.0 Unpretreated molasses 77.20 This study KF‑7‑ENA5 VHG (270.9 g/L) 33.0 Unpretreated molasses 94.43 This study E‑158 VHG (270.9 g/L) 33.0 Unpretreated molasses 95.71 This study E‑158‑ENA5 VHG (270.9 g/L) 33.0 Unpretreated molasses 98.28 This study Cassava S. cerevisiae CHY1011 SSF (18%) 32.0 Cassava 89.10 [45] S. cerevisiae dry yeast SSF (20%) 30.0 Cassava 71.84 [46] S. cerevisiae G2‑3‑2 SSF (23%) 30.0 Cassava 115.77 [47] KF‑7 SSF (35%) 33.0 Cassava 121.34 This study KF‑7‑ENA5 SSF (35%) 33.0 Cassava 129.23 This study E‑158 SSF (35%) 33.0 Cassava 134.70 This study E‑158‑ENA5 SSF (35%) 33.0 Cassava 138.43 This study ENA5 mined by a comprehensive strategy was identi- Conclusion fied to successfully enhance multiple stresses. The engi - In this study, six novel genes including functional genes, neered strain obtained by overexpression of ENA5 in genes of unknown function and genes encoding TFs, KF-7 had similar fermentation results to E-158 under were found for the first time to be related to the multi - all five stress conditions (Tables  1, 2), suggesting the ple stress-tolerant phenotypes of industrial S. cerevisiae. very high effectiveness of reverse metabolic engineer - Overexpression of gene ENA5 significantly improved the ing employed in the present study. Directly engineering high ethanol, high temperature, high sugar, and high salt the identified key target genes significantly reduced the tolerance phenotypes of the original strain KF-7 and the time and labor. Therefore, such strategy is powerful to resistant strain E-158. The fermentation performance of accumulate target gene information, which can be fur- the engineered strains under stress conditions was much ther adopted to support the construction of excellent better than strains reported by most researchers. These industrial strains. findings provide new insights guiding the engineering of In addition to ENA5, other genes investigated in the S. cerevisiae strains towards higher ethanol production in present study that contributed to stress tolerance pheno- the presence of diverse environmental stresses. type can be applied to obtain strains with specific stress tolerance or multiple stress-tolerant strains by simultane- Materials and methods ously regulating the expression of more than one of them. Strains, plasmids, primers, and media The effect of ENA5 and other genes on the stress toler - All the strains and plasmids used and constructed in ance phenotypes can also be explored using S. cerevisiae this study were listed in Table  4 [53, 54]. A flocculat- strains with different genetic backgrounds, including ing industrial S. cerevisiae strain KF-7, which has good xylose-fermenting S. cerevisiae strains, and even other ethanol fermentation capacity and stress tolerance, microorganisms having industrial application potentials. was used as the original strain [55, 56]. The multiple Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 14 of 19 Table 4 Plasmids and strains Plasmids and strains Description References Plasmids Cas9‑NAT Ampr; Cas9; NAT1 [53] pMEL13 Ampr; 2 μm origin, KanMX, gRNA‑ CAN1.Y [54] pMEL13‑CRZ1 Ampr; 2 μm origin, KanMX, gRNA‑ CRZ1 This study pMEL13‑ENA5 Ampr; 2 μm origin, KanMX, gRNA‑ENA5 This study pMEL13‑ASP3 Ampr; 2 μm origin, KanMX, gRNA‑ASP3 This study pMEL13‑TOS8 Ampr; 2 μm origin, KanMX, gRNA‑TOS8 This study pMEL13‑YOL162W Ampr; 2 μm origin, KanMX, gRNA‑YOL162W This study pMEL13‑YOR012W Ampr; 2 μm origin, KanMX, gRNA‑YOR012W This study Strains KF‑7 Flocculating diploid industrial Saccharomyces cerevisiae strain [55] E‑158 KF‑7; Random mutagenesis and hybridization [18] KF‑7‑ CRZ1 KF‑7; Replacement of promoter P to P This study CRZ1 TEF1 KF‑7‑ENA5 KF‑7; Replacement of promoter P to P This study ENA5 TEF1 KF‑7ΔASP3 KF‑7; Knockout ASP3 This study KF‑7ΔTOS8 KF‑7; Knockout TOS8 This study KF‑7ΔYOL162W KF‑7; Knockout YOL162W This study KF‑7ΔYOR012W KF‑7; Knockout YOR012W This study E‑158‑ CRZ1 E‑158; Replacement of promoter P to P This study CRZ1 TEF1 E‑158‑ENA5 E‑158; Replacement of promoter P to P This study ENA5 TEF1 stress-tolerant strain E-158 was obtained by mutagen- Batch fermentations and RNA extraction esis and hybridization using KF-7 as the starting strain The media and methods of batch fermentations under in our previous study [18]. Escherichia coli DH5α was five stress conditions: (1) 8.0% initial ethanol; (2) 44  °C; used for gene cloning and manipulation. Primers and (3) 43 °C with 2.6% initial ethanol; (4) YPD270; (5) 1.25 M other DNA fragments used in this study were pre- NaCl were described in our previous study [18]. Strains sented in Table 5 and Additional file 1: Table S6. were pre-cultivated in 100  mL YPD50 for 16  h (500  mL YP medium (10  g/L yeast extract, 20  g/L peptone) flasks). The cells were then collected, washed, and inocu - containing 20  g/L glucose (YPD20) was used for lated into fermentation media (100 mL in 300 mL flasks) cell growth. YP medium containing 150  g/L glucose with an initial cell density of OD 1.45–1.50. The flasks (YPD150) and 8.0% (v/v) ethanol was used for ethanol- were incubated in thermostatic water bath, and the stress fermentation. YP medium containing 100  g/L media was stirred (200  rpm/min) using magnetic stir- glucose (YPD100) was used for heat-stress fermenta- rers. Broth samples were collected during fermentation tion. YP medium containing 100 g/L glucose (YPD100) and used for the analysis of the concentrations of glucose and 2.6% (v/v) ethanol was used for multiple-stress and ethanol. For each group, three replicated fermenta- (ethanol and heat) fermentation. YP medium con- tion experiments were independently performed for the taining 270/280  g/L glucose (YPD270/280) was used measurements. for VHG-stress fermentation. YP medium containing To prepare RNA samples for transcriptomic sequenc- 150  g/L glucose (YPD150) and 1.25/1.5  mol/L NaCl ing, cells of E-158 and KF-7 were allowed to grow till was used for salt-stress fermentation. YP medium con- logarithmic growth under five stress conditions: (1) 8.0% taining 20  g/L glucose (YPD20), 20  g/L agar, 50  ng/ initial ethanol (48 h), (2) 44 °C (16 h), (3) 43 °C with 2.6% mL nourseothricin (NAT), and 100  ng/mL geneticin initial ethanol (12 h), (4) YPD270 (30 h), (5) 1.25 M NaCl (G418) was used for yeast transformation. LB medium (48 h). Then the cells were collected by centrifugation at (5  g/L yeast extract, 10  g/L peptone, and 10  g/L 8000×g for 2  min. Total RNA was extracted from using NaCl) supplemented with ampicillin (100  ng/mL) or Yeast RNA Kit (Omega Bio-Tek, USA). For each group, kanamycin (100  ng/mL) was used for E. coli DH5α three replicated fermentation experiments were indepen- transformation. dently performed. W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 15 of 19 Table 5 Target sequences used in yeast transformation Target Sequence gRNA insert tgR‑FTGC GCA TGT TTC GGC GTT CGA AAC TTC TCC GCA GTG AAAGA TAA ATG ATC tgR‑RGTT GAT AAC GGA CTA GCC TTA TTT TAA CTT GCT ATT TCT AGC TCT AAA AC ENA5 CSGAT AAC GTA TGT ACT CAC TGAGG CRZ1 CSGCA GAA TGT CTA CTA CGT CGAGG ASP3 CSGCT ACG GCA TGG ATC AGA TTAGG TOS8 CSAGA AAT TAC ATA ATA ACT GTAGG YOL162W CSAAG GTA CAA TGT TTA ATA AATGG YOR012W CSTTG AAA CTT TTT CAG TGA TTGGG Repair fragment TEF1 FCAC ACA CCA TAG CTT CAA AATG RTTT GTA ATT AAA ACT ENA5 RF FCCT TCA TCC TTT ACA TCG AGA ATA CGT TAA CCA AAT CAAC CAC ACA CCA TAG CTT CAA AATG RF RATT CTT CAT TAT TGT TTT CTT TGA CAG TTC CCT CGC TCAT TTT GTA ATT AAA ACT V FTTG TGA GGC TGA TGT TTT CTTC V RGCT TCT TCT GTA GTC AAT GTG TGA T CRZ1 RF FGGG CTG AAA AGT ACA TCC GCG CAT TTA ACA ATT GCT AAGC CAC ACA CCA TAG CTT CAA AATG RF RTAG TCA TGT AGG AAG CCA TAT TTC CGT TGC TGA ATG ACAT TTT GTA ATT AAA ACT V FGCT TTG ACT GCA CTT TAG CTTAG V RTTT CCG TTG CTG AAT GAC AT ASP3 RF FAGA GCA AAT GTT GGC TCG CTA TTC TTT TGT AAG CAA TCT GGT ACT CAC CAA CCT CCA ACT AGC CTG ATC AGT GAC TTT TCA TCA CAC TGT GTT TTT ATA TAG TTC TTA GTA GTA AAT ATA RF RTAT ATT TAC TAC TAA GAA CTA TAT AAA AAC ACA GTG TGA TGA AAA GTC ACT GAT CAG GCT AGT TGG AGG TTG GTG AGT ACC AGA TTG CTT ACA AAA GAA TAG CGA GCC AAC ATT TGC TCT V FTAT CAG ACC CTT CAG CAC GT V RTGA CAC TGC TCA AGG GAT AA TOS8 RF FTTT TTC AGT ATA GGA AGT AAT CAC TGT AGA AAT AAG TCA ACA ATA ATT GCA TAG AAA AAA TTT TAC TTT TTT CGG AAT TAC CTA AAA TGG GTT TAC GGC ATA GAA GAT AGA TAG ATT AAG RF RCTT AAT CTA TCT ATC TTC TAT GCC GTA AAC CCA TTT TAG GTA ATT CCG AAA AAA GTA AAA TTT TTT CTA TGC AAT TAT TGT TGA CTT ATT TCT ACA GTG ATT ACT TCC TAT ACT GAA AAA V FGTT CCC TTG TTT TGA AGC AC V RCGA AGA TTC TCA CCA AAG TT YOL162W RF FATG TCA CTT AAA ATG TTA TGG CAG GGG ATA ACA GAT TAC TAT ATA TAG CCT ATC TAC TTG ACT ATG TAG AAA TAT GGA TAC AAT CTC CAT GTT ATG TAT TTT TTA AGT TTG TGA ATC ATT RF RAAT GAT TCA CAA ACT TAA AAA ATA CAT AAC ATG GAG ATT GTA TCC ATA TTT CTA CAT AGT CAA GTA GAT AGG CTA TAT ATA GTA ATC TGT TAT CCC CTG CCA TAA CAT TTT AAG TGA CAT V FCTA AGC AAT CAC CTA AAC AT V RGAT GTC GTA CTT CTA CAG CT YOR012W RF FGAA AAA GGC AGT GAC AAA AAT ACT AAT CAG AAC GTT GAA AAC AAA TCA ATA GTT TTG ATA CCA TCC CGA AAT TAG AGG TTC AGT CAG AAA AAT ACT CGA AAA ATA TAA AAC CAA AGC AGA RF RTCT GCT TTG GTT TTA TAT TTT TCG AGT ATT TTT CTG ACT GAA CCT CTA ATT TCG GGA TGG TAT CAA AAC TAT TGA TTT GTT TTC AAC GTT CTG ATT AGT ATT TTT GTC ACT GCC TTT TTC V FTGC CTC ATA ACG TCT TGG GG V RGTA GGC CGT GAA TCC CTT CC tgR-F: upstream homologous of gRNA; tgR-R: downstream homologous of gRNA; CS: complementary sequence; RF: repair fragment; Vp: verification primer; F: forward primer; R: reverse primer, “double underline” represent the PAM (NGG) site, “underline” represent homologous arm Transcriptomic data analysis sequenced using an Illumina Novaseq 6000 platform A total of 30 mRNA samples (KF-7 and E-158 each had (Shanghai Majorbio Biopharm Technology Co. Ltd. three parallel samples under each stress condition) were (Shanghai, China)). Library construction was conducted Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 16 of 19 using the Illumina Truseq RNA sample prep kit. The region for overexpression of gene CRZ1 or ENA5 (Addi- mRNA was separated from total RNA by A-T base pair- tional file  1: Fig. S2A), and the complementary sequences ing, and then was broken into small fragments of about of gRNA were located in the coding sequence (CDS) 300  bp by the addition of fragmentation buffer. The region for knocking out genes ASP3, TOS8, YOL162W, cDNA was synthesized using mRNA as the template. The or YOR012W (Additional file  1: Fig. S2B). The gRNA sticky ends of the double-stranded cDNA were blunt- sequences were designed using the E-CRISP tool at ended with End Repair Mix, then an A-base was added http:// www.e- crisp. org/E- CRISP/ (Table  5). The gRNA to the 3′ end for the linker to the Y-line. The resulting was integrated into the linearized backbone using Gib- fragments were subjected to Illumina Novaseq sequenc- son assembly according to the manufacture’s manual ing. The Clean Data of each sample reached more than of Gibson Assembly Master Mix (New England Bio- 6.32 Gb. labs, Beverly, MA, USA). Each plasmid was transformed Difference in gene expression levels of one gene into E. coli DH5α. After sequencing, the plasmids con- between KF-7 and E-158 was quantified by an index, taining correct inserts were subsequently used for log FC, representing the logarithm to base 2 of the ratio transformation. of the RNA reads number of the gene in E158 to that in The strength of the promoter TEF1 (P , 420 bp) was TEF1 KF7. If∣log FC∣ ≥ 1 and P < 0.05, the expression of the high and relatively stable under five stress conditions related gene was defined to significantly change. These (Additional file  1: Table S7). P was used to replace the TEF1 analyses were performed on the online platform called promoters of CRZ1 and ENA5. The repair fragment was Majorbio Cloud Platform (www. major bio. com). The amplified using KF-7 genome as template, and it con - shared DEGs under five stress conditions were visual - tained upstream homologous arm, downstream homol- ized by Venn-diagram (http:// jvenn. toulo use. inra. fr/ app/ ogous arm, and TEF1 sequence (Additional file  1: Fig. examp le. html). Gene Ontology (GO) enrichment of the S2A). The repair fragments of ASP3, TOS8, YOL162W, shared DEGs was carried out with online tools developed and YOR012W were composed of upstream arm (60 bp) by Princeton University (http:// go. princ eton. edu/ cgi- bin/ and downstream arm (60  bp) of the target gene CDS, GOTer mMapp er), in which P ≤ 0.001 and enrichment which were synthesized in GENEWIZ (Suzhou, China) ratio ≥ 0.1 was set as the threshold. Kyoto Encyclopedia (Table 5, Additional file 1: Fig. S2B). of Genes and Genomes (KEGG) enrichment analysis of For yeast transformation, the lithium acetate method the shared DEGs was performed using the KEGG data- was used according to the protocol proposed by Finlay- base (http:// www. genome. jp/ kegg/). The threshold was son et  al. [57]. Cas9 plasmid was first transformed into set to P ≤ 0.05 and enrichment ratio ≥ 0.1. The shared KF-7 and E-158. The gRNA plasmid and repair fragment DEGs were searched in the YEASTRACT database (P ) were then transformed into the strains harboring TEF1 (http:// www. yeast ract. com/ form findre gulat ors. php) to Cas9 plasmid. Transformants grown on 2% YPD plate find the potential TFs. The protein–protein interaction containing 0.005% NAT and 0.01% G418 were confirmed network of shared DEGs was analyzed and constructed by PCR and Sanger sequencing. The removement of using Cytoscape 3.7.2 software. The original sequencing Cas9 and gRNA plasmids from the transformants were data are accessed in the National Center for Biotech- conducted according to Mans’ method [54]. The trans - nology Information platform under accession number formants were subjected to the following fermentation PRJNA642097. evaluation. Strains construction Evaluation of growth and fermentation performance CRISPR/Case9 gene-editing technology was used to over of engineered strains express or knock out the genes, and the experiments The growth of engineered strains under different stress were performed according to Li et  al. [37]. For gRNA conditions was evaluated using YPD20 agar medium. plasmid construction, the linearized plasmid backbone The engineered strains were pre-cultivated in YPD50 and gRNA insertion fragments were assembled to form medium for 16  h to logarithmic growth phase, and the the guideRNA (gRNA) plasmid. The linearized plasmid cells were harvested by centrifugation at 8000×g for backbone was PCR amplified from pMEL13 plasmid 2  min at 4  °C. The cells were washed twice using steri - using primer 6005/6006 [54]. The gRNA insert (120  bp) lized water and re-suspended in sterilized 0.5  mol/L was composed of upstream homologous arm (tgR-F, ethylenediaminetetraacetic acid disodium salt (EDTA- 50 bp), downstream homologous arm (tgR-R, 50 bp), and 2Na) solution with a final OD of 1.0. The solution complementary sequence (20  bp). The sequences were was then serially tenfold diluted. Aliquots of 2 μL were synthesized in GENEWIZ (Suzhou, China). The comple - spotted on YPD20 agar medium containing 13% (v/v) mentary sequence of gRNA was located in the promoter ethanol, 400 g/L glucose, 3 mol/L sorbitol, and 2 mol/L W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 17 of 19 NaCl. The plates were incubated at 30 °C for 72–120 h. Supplementary Information To examine the growth at high temperature, the plates The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s13068‑ 022‑ 02109‑x. were incubated at 44 °C for 72 h. The fermentation capacity under different stress con - Additional file 1. Additional Figures and Tables. ditions was evaluated using both YPD medium and three different raw materials. The method of fermenta - tion using YPD medium was the same as described in Acknowledgements Not applicable. Batch fermentation and RNA extraction. The compo - sitions of the pretreated straw, molasses, and cassava Authors’ contributions used in fermentation were shown in Additional file  1: LW: conceptualization, methodology, investigation, validation, and writing‑ original draft. BL: formal analysis and methodology. RS: formal analysis. SW: Tables S2, S3 and S4. The fermentation using the pre - investigation and methodology. ZX: writing–review and editing. CX: supervi‑ treated straw was performed by pre-saccharification sion and software. Y T: conceptualization, writing–review & editing, data and SSF at 42 °C. The solid content of pretreated straw curation, supervision and funding acquisition. All authors read and approved the final manuscript. was adjusted to 20% with PBS buffer solution (pH 5). CTec3 was added at a dosage of 20 FPU/g cellulose. The Funding slurry was pre-saccharified for 8  h at 50  °C. The pre- This work was supported by National Key R&D Program of China (2018YFA0902100 and 2018YFA0902102). saccharified slurry was inoculated with pre-cultivated fresh cells (0.5 g dry weight/kg slurry), and the SSF was Availability of data and materials conducted in a thermostat water bath for 96 h at 42 °C. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. The original RNA The VHG fermentation using molasses was conducted sequencing data can be accessed through the National Center for Biotechnol‑ at 33  °C. Diluted molasses (total sugar concentration ogy Information (https:// www. ncbi. nlm. nih. gov/) under project accession no. of 270.91 g/L) was inoculated with pre-cultivated fresh PRJNA642097. cells (0.5  g dry weight/L), and the VHG fermentation was conducted in a thermostat water bath for 96  h Declarations at 33  °C. High solid SSF of cassava was performed at Ethics approval and consent to participate 33 °C. Cassava slurry with 35% solid content was gelat- Not applicable. inized at 105  °C for 15  min. The resultant gelatinized Consent for publication slurry was liquefied at 95  °C for 2  h by α-amylase (10 All the authors agreed for publication. U/g starch). After cooling to room temperature, glucoa- mylase (160 U/g starch), pectinase (20 U/g raw mate- Competing interests The authors declare that they have no competing interests. rials), cellulase (10 U/g raw materials), 1  g/L K H PO , 2 4 0.5 g/L CaCl H O, 0.5  g/L MgSO .7H O, and 1  g/L 2 2 4 2 Author details (NH ) CO were added. Pre-cultivated fresh cells (0.5  g College of Architecture and Environment, Sichuan University, No. 24 South 2 2 Section 1 First Ring Road, Chengdu 610065, Sichuan, China. Institute of New dry weight/kg slurry) were inoculated. SSF was con- Energy and Low‑Carbon Technology, Sichuan University, No. 24 South ducted in a thermostat water bath for 96 h at 33 °C. All 3 Section 1 First Ring Road, Chengdu 610065, Sichuan, China. Engineering fermentation experiments were performed three times Research Center of Alternative Energy Materials & Devices, Ministry of Educa‑ tion, China, No. 24 South Section 1 First Ring Road, Chengdu 610065, Sichuan, independently. China. Sichuan Environmental Protection Key Laboratory of Organic Wastes Valorization, No. 24 South Section 1 First Ring Road, Chengdu 610065, Sichuan, China. Analytical methods Received: 13 November 2021 Accepted: 9 January 2022 Broth samples were diluted and filtered through 0.22  μm filters before analysis. The concentration of glucose was determined by HPLC (LC-10 ADVP, Shi- madzu, Kyoto, Japan) at 25  °C, with a mobile phase of References 5  mmol/L sulfuric acid at a flow rate of 0.6  mL/min. 1. Favaro L, Jansen T, van Zyl WH. Exploring industrial and natural Saccha- romyces cerevisiae strains for the bio‑based economy from biomass: the Ethanol concentration was determined using gas chro- case of bioethanol. Crit Rev Biotechnol. 2019;39(6):800–16. https:// doi. matography (GC 353B, GL Sciences, Kyoto, Japan) with org/ 10. 1080/ 07388 551. 2019. 16191 57. an FID detector, and isopropanol was used as the inter- 2. Mat Aron NS, Khoo KS, Chew KW, Show PL, Chen WH, Nguyen THP. 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Screening novel genes by a comprehensive strategy to construct multiple stress-tolerant industrial Saccharomyces cerevisiae with prominent bioethanol production

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Abstract

ENA5 Functional KF-7-ENA5 vs KF-7 genes E-158-ENA5 vs E-158 ASP3 KF-7 Mutagenesis Crz1p Transcription and factors Tos8p hybridization YOL162W Genes of unknow function YOR012W Transcriptome under five stress E-158 conditions Fermentation Expression regulation Background of S. cerevisiae [13, 14]. Such environmental stresses Bioethanol, an eco-friendly renewable biofuel, is one of possibly cause lipid peroxidation, protein denaturation, the alternatives of fossil gasoline [1]. Bioethanol produc- DNA damage, cell apoptosis, etc., of S. cerevisiae [15, tion is based on the fermentation of starchy (cassava, 16]. Extensive improvements of the multiple stress-toler- corn, microalgae, etc.), sugary (molasses, sweet sorghum/ ance and robustness of S. cerevisiae are of paramount to sugarcane juice, etc.), or lignocellulosic (straw, corn achieve high bioethanol production. cob, etc.) biomass [1, 2]. Species including Saccharomy- However, breeding multiple stress-tolerant industrial ces cerevisiae, Kluyveromyces marxianus, Zymomonas S. cerevisiae strains that perform well when using which- mobilis, and Pichia stipites are bioethanol producers ever feedstocks is still challenging [17]. Presently, some [3–5]. S. cerevisiae is the main species used for indus- studies have reported that stress-tolerance of strains can trial ethanol production due to its good fermentation be improved by random mutagenesis [18], genome shuf- performance and stress resistance [6–8]. However, S. cer- fling [19], and genetic engineering [17]. Compared with evisiae is commonly exposed to different kinds of envi - random mutagenesis and genome shuffling, genetic engi - ronmental stresses in the industrial fermentation process neering is of great significance because of short breeding with different feedstocks. For example, in simultaneous time, clear gene targeting and clear relationship between saccharification and fermentation (SSF) with lignocel - gene and phenotype. Over the past decades, studies have lulosic or starchy biomass as feedstock, S. cerevisiae is reported that a number of genes were closely related to expected to resist high temperatures (since the optimal ethanol, heat, or osmosis stress tolerance of S. cerevisiae enzymatic saccharification temperature is 45–50  °C) [9, 20–22], which can be used as the potential targets to and high ethanol concentration [9–11]. Similarly, during improve stress tolerance of the strains. Based on these very high gravity (VHG) fermentation using sugar-based findings, a number of trials have been performed. For raw materials (molasses, concentrated sweet sorghum example, overexpression of ISU1 and JAC1 increased the juice, and sugarcane juice), strains should withstand the ethanol tolerance [23] and overexpression of HSF1 and high concentration of sugar at the early stage and high MSN2 promoted cell growth and high temperature fer- ethanol concentration at the later stage [12]. Moreover, mentation [24]. Salt tolerance can be enhanced by over molasses without acid pretreatment has high salt con- expressing CDS1 and CHO1 [25]. However, these stud- tent, which notably impedes the fermentation efficiency ies mainly focused on the improvement of resistance to 9% Ethanol 44°C 43°C+3% (v/v) ethanol 28% Glucose 1.5 M NaCl Increased percentage of ethanol concentration (%) W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 3 of 19 single stress (high ethanol or high temperature). To our of RNA-seq data, hundreds of DEGs were found under knowledge, none of the genes linking to multiple stress- each kind of stress condition (Fig. 2A). tolerance has been reported to date. Since S. cerevisiae Twenty-eight DEGs were found shared under all five strains are forced to face diverse environmental stresses stress conditions via Venn diagram (Fig.  2B, Addi- during the industrial fermentation, it is vital to identify tional file  1: Table  S1), suggesting their potential con- gene targets that could be engineered to improve multi- tributions to multiple stress-tolerant phenotypes. GO ple stress-tolerance of S. cerevisiae. and KEGG analyses revealed that these DEGs were In our previous study, a S. cerevisiae strain E-158 was involved in multiple biological processes. The func - obtained by random mutagenesis and hybridization, tional gene ASP3, whose expression largely decreased which shows higher capability of multiple stress-toler- (log FC: − 10 ~ − 12), was involved in both processes ance than its original strain KF-7 [18]. To identify poten- of response to stress (GO: 0006950) and cellular nitro- tial target genes related to multiple stress-tolerance, in gen compound metabolism (GO: 0034641) (Fig.  2C). the present study, the comparative transcriptome analy- ASP3 was also involved in cyanoamino acid metabo- sis was performed between strain E-158 and its original lism (KEGG Pathway: sce00460), the only pathway strain KF-7 under five stress conditions. Six target genes significantly enriched by the KEGG analysis, suggest - which possibly contribute to the multiple stress-tolerant ing ASP3 may be one of the key genes regulating mul- phenotypes of S. cerevisiae were mined by a comprehen- tiple-tolerant phenotypes of S. cerevisiae (Fig.  2D). To sive strategy. CRISPR/Cas9 technology was used to reg- reveal the relationship among DEGs and to find the ulate the expression of these six target genes to explore core regulatory target genes, protein–protein interac- their impacts on the multiple stress-tolerance pheno- tion network analysis was performed for the 28 shared types of S. cerevisiae. Moreover, the stress tolerance of DEGs. As shown in Fig. 2E, gene ENA5 (log FC: 2 ~ 16) the engineered strains was assessed using three kinds of was located at the core of the network and had strong typical industrial feedstocks. relationships with other DEGs. ENA5 encodes a P-type + + ATPase (extrudes Na probably in exchange for H ), which may assist the efflux of sodium ions, thus reduc - ing cytotoxicity [26]. It could be one key functional Results gene responsible for regulating multiple-tolerant phe- Fermentation performance of original strain KF‑7 notypes of S. cerevisiae. and resistant strain E‑158 Six DEGs with unknown function (putative pro- In our previous study, an excellent multiple stress-tol- tein with unknown function in Saccharomyces erant strain E-158 was obtained by using a strategy of Genome Database) in 28 shared DEGs were all sig- random mutagenesis and hybridization [18]. The strain nificantly down-regulated (Fig.  2F). Among these E-158 showed higher ethanol production and glucose six DEGs, the expression of DEGs named YOL162W consumption rates than the original strain KF-7 under (log FC: − 8 ~ − 11), YOL163W (log FC: − 8 ~ − 10) 2 2 five stress conditions. The final concentrations of etha - and YOR012W (log FC: − 8 ~ − 10) decreased more nol produced by E-158 during batch fermentations were than other three DEGs, suggesting they may have a 66.89%, 33.37%, 81.02%, 10.14%, and 35.98%, respectively, greater impact on the tolerance phenotype [27]. Genes higher than those of KF-7 under five stress conditions: YOL162W and YOL163W have high sequence similar- (1) 8.0% (v/v) initial ethanol, (2) 44 °C, (3) 43 °C and 2.6% ity and were proposed to have similar function [28]. (v/v) initial ethanol, (4) 27% glucose, (5) 1.25  M NaCl Hence, YOL162W and YOR012W were selected as can- (Fig. 1). didate genes to explore their effects on multiple-toler - ant phenotypes of S. cerevisiae. Crz1p (log FC: 1 ~ 2) and Tos8p (lo g FC: − 9 ~ − 13) 2 2 Comprehensive strategy of mining key genes regulating were two transcriptional factors (TFs) found in the stress‑tolerant phenotypes of S. cerevisiae 28 shared DEGs (Fig.  2G). The regulatory relation - To mine the potential key genes governing the multiple ship between these two TFs and the 28 shared DEGs stress-tolerant phenotypes of S. cerevisiae, transcrip- was explored through YEASTRACT database. The tional profiles of strains KF-7 and E-158 under five stress results showed that the DEGs including SPO24, ENA5, conditions were investigated based on RNA-seq with WSC2, HSP150, YOL162W, and YOL163W among the three biological replicates (the RNA extraction times 28 shared DEGs were potentially regulated by Crz1p. were shown in Fig.  1, and the gene expression levels of DEGs of GEX2 and YDR222W were potentially regu- KF-7 under same stress conditions were taken as the con- lated by Tos8p. Therefore, Crz1p and Tos8p may be trol group). According to differential expression analysis Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 4 of 19 60 120 140 160 44°C 8.0% Ethanol 130 140 50 100 120 120 RNA: 16 h 40 80 110 100 30 60 100 80 90 60 20 40 80 40 10 20 70 20 RNA: 48 h 0 0 60 0 Time (h) Time (h) 160 320 70 120 270 g/L Glucose 43°C + 2.6% Ethanol 140 280 60 100 120 240 50 80 100 200 RNA: 30 h 40 60 80 160 60 120 30 40 40 80 20 20 20 40 RNA: 12 h 10 0 0 0 01020304050607080 0102030405060708090 100 Time (h) Time (h) 70 210 1.25 mol/L NaCl 60 180 50 150 RNA: 48 h 40 120 30 90 20 60 10 30 0 0 Time (h) Fig. 1 Fermentation characteristics under five stress conditions. Fermentation kinetics (A–E) of KF‑7 (open squares: glucose; closed squares: ethanol) and E‑158 (open circles: glucose; closed circles: ethanol) were shown. Data are averages of three independent experiments (error bars represent SD) (See figure on next page.) Fig. 2 A comprehensive selection of key genes potentially related to the multiple stress‑tolerant phenotypes. A DEGs under five stress conditions; B Venn diagram of DEGs under the five stress conditions, including 28 shared DEGs; C GO enrichment analyses of 28 shared DEGs; D the pathway of cyanoamino acid metabolism; E protein–protein interaction network of 28 shared DEGs. In the plot, the bluer the circle, the greater the contribution of the gene, the thicker the line, the stronger the interaction between the two genes; F Relative expression level of the DEGs of unknown function in 28 shared DEGs; G DEGs regulated by the two identified TFs in 28 shared DEGs Ethanol concentration (g/L) Ethanol concentration (g/L) Ethanol concentration (g/L) Glucose concentration (g/L) Glucose concentration (g/L) Ethanol concentration (g/L) Ethanol concentration (g/L) Glucose concentration (g/L) Glucose concentration (g/L) Glucose concentration (g/L) W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 5 of 19 A A Down-regulated genes B Up-regulated genes 28 shared DEGs 300 404 200 133 122 112 C D Transport L-isoleucine Response to stress N-Hydroxy-L-isoleucine Cellular nitrogen compound metabolic process L-Aspartate APS3 Functional gene L-Asparagine Reproduction Cell wall organization or biogenesis Log2FC E F SPO24 YOL163W MF(ALPHA)2 GEX2 AAD15 ASP3-3 YOL162W AGA1 HSP150 PHO12 ASP3-2 ASP3-4 BDS1 Log2FC ASP3-1 ENA5 FLO9 VTH2 VTH1 CRZ1 Functional gene Node color (degree): TOS8 LowHigh CRZ1 Transcriptional factor TOS8 Transcriptional factor Positive Negative Unspecified SPO24 HSP150 YOL162W WSC2 GEX2 ENA5 YOL163W YDR222W Fig. 2 (See legend on previous page.) EE vs KE ET vs KT ETE vs KTE EG vs KG ES vs KS Differentially expressed genes (DEGs) Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 6 of 19 key TFs regulating multiple-tolerant phenotypes of S. not grow when the temperature was 44 °C. However, the cerevisiae. growth of other strains was significantly better than that of KF-7. When the spot assay was respectively performed Growth and fermentation abilities of engineered strains under the osmotic stress conditions, i.e., 400 g/L glucose using original strain KF‑7 as host and 3  mol/L sorbitol, strains KF-7-CRZ1, KF-7-ENA5, To experimentally verified whether the identified key KF-7ΔASP3, KF-7ΔTOS8, and KF-7ΔYOR012W grew DEGs are responsible for the multiple-tolerant pheno- better than KF-7, but there was no significant difference types in strain E-158, using its original strain KF-7 as a between KF-7ΔYOL162W and KF-7. host, genes CRZ1 and ENA5 were over expressed, and To evaluate the ability of ethanol tolerance of the genes ASP3, TOS8, YOL162W, and YOR012W were engineered strains, batch fermentations were per- knocked out to result in strains KF-7-CRZ1, KF-7-ENA5, formed using YPD150 media with 8.0% (v/v) initial KF-7ΔASP3, KF-7ΔTOS8, KF-7ΔYOL162W, and ethanol concentration (Fig.  4A). Except for KF-7-CRZ1 KF-7ΔYOR012W, respectively. The growth of these engi - and KF-7ΔYOL162W, the other strains produced sig- neered strains under different stress conditions was com - nificantly (P < 0.05) more ethanol than KF-7 (Table  1). pared with that of KF-7 through the spot assay (Fig.  3). After 96-h fermentation, the order of the final ethanol Under the condition without stress, strains showed simi- concentrations produced by these strains was as fol- lar growth capacities. When exposed to 13% (v/v) etha-lows: K F-7 -EN A 5 > KF- 7 Δ ASP 3 > KF- 7 ΔYO R01 2 W > nol, all strains, except strain KF-7-CRZ1, grew better than KF- 7ΔTO S8 > K F -7Δ YOL 162W > KF-7 > KF- 7-C RZ1 . Th KF-7. Under the heat stress, strain KF-7ΔYOL162W did e e tha nol concentration of KF- 7-ENA5 was the highest Fig. 3 Growth abilities of engineered strains using original strain KF‑7 as the host under different stress conditions W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 7 of 19 Fig. 4 Fermentation abilities of engineered strains using original strain KF‑7 as the host under five stress conditions. A 8.0% initial ethanol; B 44 °C; C 43 °C with 2.6% initial ethanol; D 270 g/L glucose; E 1.25 mol/L NaCl; F 1.5 mol/L NaCl. Data are averages of three independent experiments (error bars represent SD) Meanwhile, the ethanol concentration of KF-7ΔASP3 (23.96 ± 0.73 g/L), which was 27.57% higher than that of (25.91 ± 2.24  g/L) was 99.31% higher than that of KF-7 KF-7 (18.79 ± 2.11 g/L) (Table 1). (13.00 ± 1.84 g/L) under two stresses of ethanol and heat During the batch fermentations at 44  °C, the etha- (Fig. 4C, Table 1). nol concentration of KF-7ΔYOL162W was only 56.39% VHG fermentations were conducted using YP of that of KF-7, but the ethanol concentrations of other medium with 271.09  g/L glucose concentration. strains were significantly (P < 0.05) higher than that Except for strain KF-7ΔYOL162W, the ethanol con- of KF-7 (Fig.  4B, Table  1). Among them, KF-7ΔASP3 centrations of other strains were increased by 2.45% (44.37 ± 1.86  g/L) had the highest ethanol production, (KF-7ΔYOR012W ) ~ 6.24% (KF-7-ENA5) compared which was 41.35% higher than KF-7 (31.39 ± 2.54  g/L). Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 8 of 19 Table 1 Comparisons of fermentation performance of engineered strains using original strain KF‑7 as the host Indexes Strains 8.0% (v/v) 44 °C 43 °C + 2.6% (v/v) 27% Glucose 1.25 M NaCl Initial ethanol (YPD100) Initial ethanol (YPD270) (YPD150) (YPD150) (YPD100) KF‑7 18.79 ± 2.11c 31.39 ± 2.54c 13.00 ± 1.84b 123.92 ± 0.79c 43.78 ± 1.37d Final generated ethanol concentration KF‑7‑ CRZ1 14.82 ± 1.48d 40.11 ± 2.42ab 21.93 ± 1.49a 128.99 ± 1.05b 63.66 ± 1.50a (g/L) KF‑7‑ENA5 23.96 ± 0.73a 41.69 ± 0.66ab 22.50 ± 1.70a 131.65 ± 0.99a 64.26 ± 1.12a KF‑7ΔASP3 22.76 ± 1.12ab 44.37 ± 1.86a 25.91 ± 2.24a 128.19 ± 0.69b 45.16 ± 1.17d KF‑7ΔTOS8 20.26 ± 1.57ab 36.58 ± 2.19bc 14.63 ± 1.79b 129.40 ± 0.96ab 54.78 ± 0.81bc KF‑7ΔYOL162W 19.49 ± 0.94bc 17.70 ± 3.60d 4.24 ± 1.26c 122.80 ± 1.19c 57.77 ± 1.62b KF‑7ΔYOR012W 22.45 ± 1.11ab 37.63 ± 1.54bc 16.94 ± 1.43b 126.95 ± 1.99bc 51.16 ± 1.33c KF‑7 100.12 ± 4.07ab 29.51 ± 3.57b 71.80 ± 3.41b 25.09 ± 1.49a 40.18 ± 4.81a Residual glucose (g/L) KF‑7‑ CRZ1 105.01 ± 3.12a 13.75 ± 3.78 cd 50.59 ± 2.80d 13.48 ± 2.58c 0.00 ± 0.00c KF‑7‑ENA5 86.88 ± 1.55d 12.62 ± 4.69 cd 50.10 ± 3.37d 10.90 ± 1.88c 0.00 ± 0.00c KF‑7ΔASP3 89.53 ± 1.29 cd 5.89 ± 2.90d 41.76 ± 4.16d 15.05 ± 1.31bc 34.11 ± 2.72a KF‑7ΔTOS8 95.74 ± 2.71bc 19.88 ± 3.72bc 67.85 ± 3.33bc 13.74 ± 1.91c 9.76 ± 1.88b KF‑7ΔYOL162W 98.98 ± 1.86ab 57.75 ± 5.06a 85.36 ± 2.35a 29.66 ± 2.92a 1.36 ± 0.53c KF‑7ΔYOR012W 90.97 ± 1.13 cd 18.56 ± 2.63c 61.66 ± 2.84c 19.48 ± 1.17b 14.66 ± 3.09b Ethanol yield (g ethanol/g consumed KF‑7 0.45 ± 0.01a 0.45 ± 0.01bc 0.47 ± 0.01a 0.50 ± 0.01a 0.42 ± 0.02ab glucose) KF‑7‑ CRZ1 0.41 ± 0.01b 0.46 ± 0.00ab 0.46 ± 0.01a 0.50 ± 0.00a 0.44 ± 0.02ab KF‑7‑ENA5 0.44 ± 0.00a 0.48 ± 0.02a 0.46 ± 0.01a 0.50 ± 0.01a 0.45 ± 0.01a KF‑7ΔASP3 0.44 ± 0.00a 0.47 ± 0.00ab 0.46 ± 0.01a 0.50 ± 0.00a 0.41 ± 0.00bc KF‑7ΔTOS8 0.44 ± 0.02a 0.46 ± 0.01ab 0.47 ± 0.01a 0.49 ± 0.01a 0.41 ± 0.00bc KF‑7ΔYOL162W 0.46 ± 0.01a 0.42 ± 0.01c 0.32 ± 0.02b 0.49 ± 0.01a 0.41 ± 0.01bc KF‑7ΔYOR012W 0.45 ± 0.01a 0.46 ± 0.01ab 0.45 ± 0.02a 0.50 ± 0.01a 0.39 ± 0.01c The data in the table are those at the end of fermentation. Values indicate mean ± standard deviation of three biological replications. Values followed by different lowercase letters in the same column indicate significant differences at the level of P < 0.05 (Tukey-test) among strains. Same lowercase letters, no difference. KF-7-CRZ1: overexpression of TF Crz1p in KF-7; KF-7-ENA5: overexpression of ENA5 in KF-7; KF-7ΔASP3: Knockout ASP3 in KF-7; KF-7ΔTOS8: Knockout TOS8 in KF-7; KF-7ΔYOL162W: Knockout YOL162W in KF-7; KF-7ΔYOR012W: Knockout YOR012W in KF-7 with that of KF-7 (Fig.  4D, Table  1). All strains had that of E-158 in the presence of 13% (v/v) ethanol, while improved fermentation performance when ferment- the growth of E-158-CRZ1 was poor (Fig.  5). E-158- ing YPD150 medium supplemented with 1.25  mol/L CRZ1 and E-158-ENA5 grew better than E-158 under (7.31%) NaCl (Fig.  4E). Especially, after 96-h fermenta- heat stress at 44  °C. Under the high osmotic conditions tion, strains KF-7-CRZ1 and KF-7-ENA5 utilized all of 400  g/L glucose, 3  mol/L sorbitol, or 2  mol/L NaCl, glucose, but the residual glucose was 43.78 ± 1.37  g/L the growths of E-158-CRZ1 and E-158-ENA5 were bet- for KF-7 (Table  1). When the concentration of NaCl ter than that of E-158. Particularly, under 2  mol/L NaCl was increased to 1.5  mol/L, strains KF-7-CRZ1 and KF- stress, both the engineered strains showed excellent 7-ENA5 showed high ethanol production and glucose growth capacities. consumption rates (Fig. 4F). The final ethanol concentra - Batch fermentations of E-158-CRZ1 and E-158-ENA5 tions were 52.48 ± 0.97  g/L and 44.93 ± 1.58  g/L, which were conducted under five stress conditions. Overex - were 121.42% and 89.56% higher than those of KF-7, pression of ENA5 further increased the ethanol toler- respectively. ance of E-158. The ethanol produced by E-158-ENA5 (32.39 ± 1.02  g/L) was 13.09% higher than that of E-158 Growth and fermentation abilities of engineered strains (28.64 ± 1.66 g/L) when YPD150 medium with 8.0% (v/v) using resistant strain E‑158 as host initial ethanol concentration was fermented (Fig.  6A, Since the overexpression of ENA5 or CRZ1 significantly Table  2). However, the ethanol concentration of strain improved multiple stress-tolerance of the original strain E-158-CRZ1 was lower than that of E-158. KF-7, the effects of overexpression of these two genes on Under fermentation at 44  °C, the ethanol concentra- resistant strain E-158 were further explored. Overexpres- tions of E-158-CRZ1 and E-158-ENA5 were increased sion of ENA5 and CRZ1 using E-158 as host resulted in by 11.86% and 14.17%, respectively, compared with that strains KF-7-CRZ1 and E-158-ENA5, respectively. The of E-158 (Fig.  6B, Table  2). Meanwhile, the ethanol pro- growth of E-158-ENA5 was significantly better than duction and glucose consumption rates of E-158-CRZ1 W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 9 of 19 Fig. 5 Growth abilities of engineered strains using resistant strain E‑158 as the host under different stress conditions and E-158-ENA5 were significant higher (P < 0.05) than 63.35 ± 2.50  g/L, 65.50 ± 3.71  g/L, and 68.40 ± 1.59  g/L, those of E-158 under the multiple stress of ethanol and respectively, which were increased by 13.35%, 17.19%, heat, and the final ethanol concentrations produced by and 22.38% individually, compared with that of the origi- them were increased by about 30% compared with that of nal strain KF-7 (55.89 ± 2.68  g/L) (Fig.  7A, Additional E-158 (Fig. 6C, Table 2). file  1: Fig. S1A, B). The engineered strains also showed When VHG fermentation was conducted under much higher ethanol yields (Additional file  1: Table  S5). 280.72  g/L glucose concentration, significant (P < 0.05) These results indicated that the overexpression of ENA5 difference in the fermentation performance among the improved the fermentation capacity of the strains under strains was not observed (Fig.  6D). However, under the high temperatures. fermentation condition of 1.25 mol/L NaCl, E-158-CRZ1 When the molasses with 270.91 g/L total sugar was fer- and E-158-ENA5 consumed all the glucose at 72 h, which mented, the final ethanol concentrations of KF-7-ENA5, was 24  h earlier than E-158 (Fig.  6E). When the con- E-158, and E-158-ENA5 were 22.32%-27.31% higher than centration of NaCl was increased to 1.5  mol/L, the final that of KF-7, and the strain E-158-ENA5 had the highest ethanol concentrations of E-158-CRZ1 and E-158-ENA5 ethanol concentration of 98.28  g/L (Fig.  7B, Additional were 46.90 ± 2.10  g/L and 56.73 ± 1.05  g/L, respectively, file  1: Fig. S1C). When cassavas with a solid content of which were 66.73% and 101.67% higher than that of 35% were used for SSF at 33  °C, the ethanol concentra- E-158 (28.13 ± 1.58  g/L) (Fig.  6F, Table  2). In conclusion, tions of strains KF-7-ENA5, E-158, and E-158-ENA5 overexpression of ENA5 improved all kinds of stress tol- were 6.50%, 11.01%, 14.08% respectively after 96-h fer- erance of resistant strain E-158. mentation, higher than that of KF-7, and the ethanol concentration produced by strain E-158-ENA5 was 138.43  g/L (Fig.  7C, Additional file  1: Fig. S1D). These Fermentation abilities of engineered strains results suggested that the overexpression of ENA5 simul- when fermenting pretreated straw, molasses and cassava taneously enhanced tolerance of the strains to the heat, under stress conditions ethanol, and osmosis when different industrial feedstocks To evaluate the potential of the strains engineered in this were fermented. study for industrial applications, the fermentation abili- ties of strains KF-7, KF-7-ENA5, E-158, and E-158-ENA5 were assessed using pretreated straw, molasses, and cas- Discussion sava, which are feedstocks commonly used in industrial To find target genes that can increase the multiple ethanol production (Additional file  1: Tables S2, S3, S4). stress-tolerant ability of S. cerevisiae suitable for vari- By SSF of pretreated straw at 42 °C, the ethanol concen- ous industrial feedstocks is still challenging because trations of KF-7-ENA5, E-158, and E-158-ENA5 were of the molecular regulation complexity of multiple Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 10 of 19 Fig. 6 Fermentation abilities of engineered strains using resistant strain E‑158 as the host under five stress conditions. A 8.0% initial ethanol; B 44 °C; C 43 °C with 2.6% initial ethanol; D 280 g/L glucose; E 1.25 mol/L NaCl; F 1.5 mol/L NaCl. Data are averages of three independent experiments (error bars represent SD) stress-tolerant phenotypes. Presently, researchers have In the present study, by comparing the transcriptomes of reported that single tolerance to ethanol or high tempera- E-158 and KF-7, 28 DEGs were found shared under five ture of S. cerevisiae can be significantly improved by over stress conditions (Fig. 2). Six of them were mined and all expressing or knocking out some genes or TFs [23, 24], of them were found to be associated with multiple stress- however, researches on screening key genes responsible tolerant phenotypes of S. cerevisiae. for enhancing the multiple stress-tolerance of industrial Among the six DEGs, ENA5 was the most prominent S. cerevisiae are absent. In our previous study, a multiple in the multiple stress-tolerance improvement. To date, stress-tolerant strain E-158 was obtained by mutagenesis no report has revealed the relationship between ENA5 and hybridization using KF-7 as the starting strain [18]. and the stress tolerance phenotypes of S. cerevisiae. Our W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 11 of 19 Table 2 Comparisons of fermentation performance of engineered strains using resistant strain E‑158 as the host Indexes Strains 8.0% (v/v) 44 °C 43 °C + 2.6% (v/v) 28% Glucose 1.5 M NaCl Initial ethanol (YPD100) Initial ethanol (YPD280) (YPD150) (YPD150) (YPD100) Final generated ethanol concentration (g/L) E‑158 28.64 ± 1.66bc 38.12 ± 1.90b 18.66 ± 1.62b 128.40 ± 1.17b 28.13 ± 1.58c E‑158‑ CRZ1 25.24 ± 1.99c 42.64 ± 1.71a 24.34 ± 1.76a 131.77 ± 0.79a 46.90 ± 2.10b E‑158‑ENA5 32.39 ± 1.02a 43.52 ± 1.17a 23.43 ± 0.95a 132.90 ± 1.80a 56.73 ± 1.05a E‑158 78.00 ± 3.40a 17.91 ± 1.72a 56.25 ± 3.00a 25.75 ± 2.22a 72.47 ± 4.53a Residual glucose (g/L) E‑158‑ CRZ1 82.34 ± 2.35a 9.70 ± 2.66b 43.99 ± 3.30b 19.21 ± 1.95b 34.24 ± 4.36b E‑158‑ENA5 70.44 ± 1.74b 7.21 ± 2.03b 44.13 ± 1.40b 17.79 ± 2.79b 8.75 ± 2.54c Ethanol yield E‑158 0.45 ± 0.01ab 0.46 ± 0.00a 0.44 ± 0.00a 0.50 ± 0.00a 0.40 ± 0.01b (g ethanol/g consumed glucose) E‑158‑ CRZ1 0.43 ± 0.01b 0.47 ± 0.01a 0.44 ± 0.01a 0.50 ± 0.01a 0.43 ± 0.00a E‑158‑ENA5 0.46 ± 0.01a 0.47 ± 0.01a 0.43 ± 0.01a 0.50 ± 0.01a 0.42 ± 0.01a The data in the table are those at the end of fermentation. Values indicate mean ± standard deviation of three biological replications. Values followed by different lowercase letters in the same column indicate significant differences at the level of P < 0.05 (Tukey-test) among strains. Same lowercase letters, no difference. E-158- CRZ1: Overexpression of TF Crz1p in E-158; E-158-ENA5: Overexpression of ENA5 in E-158 Fig. 7 Fermentation results of engineered strains when pretreated straw, molasses, and cassava were fermented under stress conditions. A High‑temperature SSF of pretreated straw; B VHG fermentation of molasses; C SSF of cassava with high solid content study revealed for the first time that the overexpression Fig. 6F). ENA5 is previously reported as encoding P-type of ENA5 could significantly improve the tolerance of ATPase that may assist the efflux of sodium ions [26, S. cerevisiae to all kinds of stresses studied. Especially, 29]. Therefore, the overexpression of ENA5 may reduce after overexpression of ENA5, the ethanol concentra- cytotoxicity and enhance the salt tolerance of S. cerevi- tions of engineered strains were increased to about two- siae through assisting in the efflux of sodium ions. Genes fold under the conditions of 1.5  mol/L NaCl (Figs.  4F, ENA1、ENA2、ENA5 are the members of a gene cluster Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 12 of 19 encoding proteins with very similar function [30]. These improvement of multiple stress-tolerance needs further genes highly expressed under high sucrose tolerance [31], investigations. The overexpression of CRZ1 significantly which indicating ion transport is possibly important for improved the high temperature tolerance as well as the S. cerevisiae to resist high osmotic stress. Nevertheless, high osmosis tolerance of the strains (Figs.  4, 6). Crz1p the specific regulatory mechanism of gene ENA5 on the is a zinc finger TF, which regulates 14.6% of the genes multiple stress-tolerant phenotypes of S. cerevisiae needs in the genome of S. cerevisiae based on YEASTRACT to be investigated in detail in the future study. database. The genes regulated by Crz1p are significantly In addition to gene ENA5, for the first time, gene ASP3 enriched in pathways of carbohydrate metabolic process was found having an important effect on high ethanol (GO: 0005975), cell wall organization or biogenesis (GO: and high temperature stress tolerance phenotypes of S. 0071554), and transmembrane transport (GO: 0055085). cerevisiae. ASP3 is a gene cluster composed of four iden- CRZ1 has been reported able to enhance the resistance of tical genes, i.e., ASP3-1, ASP3-2, ASP3-3, and ASP3-4, S. cerevisiae to high concentrations of cations including 2+ 2+ + + which encode L-asparaginase II [32]. Asparaginase II is Ca, Mn, Na , and Li by regulating the genes of cal- a periplasmic enzyme in yeast, hydrolyzing both D- and cium signaling pathway [39]. Interestingly, in the present L-asparagine to aspartate and ammonium cation [32]. study, overexpression of CRZ1 increased not only high ASP3 was upregulated during nitrogen starvation to facil- salt tolerance, but also high temperature and high glu- itate the utilization of extracellular asparagine as a source cose tolerance of the strains (Tables  1, 2). Though there of nitrogen [33]. Nitrogen starvation could promote the are reports that regulation the genes involved in carbo- synthesis of lipid and/or polyhydroxybutyrate (PHB) [34, hydrate metabolic and cell wall synthesis could effectively 35]. However, the molecular regulation mechanism of improve the high temperature, high ethanol, or high the deletion of ASP3 on stress tolerance and the possible osmosis stress tolerance of S. cerevisiae [23, 24, 40], the relationship between the nitrogen starvation response specific molecular regulation mechanism of Crz1p on and the stress tolerance are still unknown, which need multiple stress-tolerance should be clarified in the future. further investigations. Those strains over-expressing ENA5 showed much bet- Genes of unknown function were often found ter ethanol production than the original strains when expressed [36], however, no studies showed the relation- fermenting different raw materials. When high-temper - ship between genes of unknown function and stress- ature SSF and VHG fermentation were carried out with tolerant phenotypes of S. cerevisiae. Knocking out gene pretreated straw, molasses and cassava, the concentra- YOR012W of unknown function had a limited effect on tions of ethanol produced by the engineered strains were the multiple stress-tolerant phenotypes of KF-7. How- significantly higher than those produced by the original ever, knocking out YOL162W significantly improved the strains and strains reported by most researchers (Fig.  7, high salt tolerance while significantly reduced the high Table 3) [13, 14, 41–47]. Considering the costs of materi- temperature resistance of the strain KF-7. Although the als, equipment, energy consumption and labor, the costs function of the protein encoded by YOL162W is unclear, of ethanol production with straw, molasses and cassava YOL162W had a vital relationship with the high tempera- are calculated to be about 0.60 US$, 0.62 US$, and 0.98 ture and high salt tolerance phenotypes (Table  1), the US$ per liter (average price of ethanol in the market is underly mechanism is worthy for further investigation. about 0.75 US$ per liter) [48–51]. Though the system - Several studies reported that TFs are important to atic assessments of changes of parameters including regulate the tolerance phenotype of S. cerevisiae [24, fermentation temperature, mash concentration, and 37]. However, the relationship of the two TFs, Tos8p ethanol concentration on the ethanol production cost and Crz1p, with the multiple stress tolerances was not when different feedstocks are used is needed. Several reported to date. Tos8p was reported to be associated studies reported that if the fermentation temperature is with chromatin and highly expressed under meiosis and increased by 1 °C and if the ethanol yield is increased by cell damage [38]. In the present study, knocking out TOS8 10%, the cost of ethanol can be reduced by about 0.04 in original strain KF-7 increased the osmosis and high US$ per liter and 0.03 US$ per liter, respectively [51, 52]. temperature tolerance phenotypes of the strain (Table 1). This suggested that the strains engineered in the present YEASTRACT database shows that the TF Tos8p regu- study have good prospects for reducing ethanol produc- lates 8.0% of the genes in the genome of S. cerevisiae. tion cost and hence have wide industrial applications. The genes regulated by Tos8p are significantly enriched In the previous study, we obtained strain E-158 in pathways of fungal-type cell wall organization or bio- using KF-7 as the original strain by combined tech- genesis (GO: 0071852), cation transport (GO: 0006812), niques including ARTP mutagenesis, genome shuf- and siderophore transport (GO: 0015891). However, the fling and hybridization, which took a lot of time and molecular mechanism of the deletion of TOS8 on the labor [18]. However, in the present study, the key gene W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 13 of 19 Table 3 Comparisons of ethanol concentrations of strains when different raw materials were fermented under stress conditions Strains Process (Solid content) Temperature (℃) Substrates Ethanol References concentration (g/L) Cellulose materials S. cerevisiae Angel Yeast P‑SSF (20%) 39.0 Corn stover 59.80 [41] S. cerevisiae TJ14 P‑SSF (/) 39.0 Microcrystalline cellulose 45.00 [42] K. marxianus NRRL Y‑6860 SSF (24%) 41.5 Rice straw 52.30 [43] KF‑7 P‑SSF (20%) 42.0 Rice straw 55.89 This study KF‑7‑ENA5 P‑SSF (20%) 42.0 Rice straw 63.35 This study E‑158 P‑SSF (20%) 42.0 Rice straw 65.50 This study E‑158‑ENA5 P‑SSF (20%) 42.0 Rice straw 68.40 This study Molasses S. cerevisiae NCYC3233‑27c VHG (/) 35.0 Unpretreated molasses 78.90 [14] S. cerevisiae UAF‑1 VHG (270.0 g/L) 32.0 Acid pretreated molasses 96.00 [44] S. cerevisiae SFO6 VHG (250.0 g/L) 30.0 Unpretreated molasses 55.20 [13] KF‑7 VHG (270.9 g/L) 33.0 Unpretreated molasses 77.20 This study KF‑7‑ENA5 VHG (270.9 g/L) 33.0 Unpretreated molasses 94.43 This study E‑158 VHG (270.9 g/L) 33.0 Unpretreated molasses 95.71 This study E‑158‑ENA5 VHG (270.9 g/L) 33.0 Unpretreated molasses 98.28 This study Cassava S. cerevisiae CHY1011 SSF (18%) 32.0 Cassava 89.10 [45] S. cerevisiae dry yeast SSF (20%) 30.0 Cassava 71.84 [46] S. cerevisiae G2‑3‑2 SSF (23%) 30.0 Cassava 115.77 [47] KF‑7 SSF (35%) 33.0 Cassava 121.34 This study KF‑7‑ENA5 SSF (35%) 33.0 Cassava 129.23 This study E‑158 SSF (35%) 33.0 Cassava 134.70 This study E‑158‑ENA5 SSF (35%) 33.0 Cassava 138.43 This study ENA5 mined by a comprehensive strategy was identi- Conclusion fied to successfully enhance multiple stresses. The engi - In this study, six novel genes including functional genes, neered strain obtained by overexpression of ENA5 in genes of unknown function and genes encoding TFs, KF-7 had similar fermentation results to E-158 under were found for the first time to be related to the multi - all five stress conditions (Tables  1, 2), suggesting the ple stress-tolerant phenotypes of industrial S. cerevisiae. very high effectiveness of reverse metabolic engineer - Overexpression of gene ENA5 significantly improved the ing employed in the present study. Directly engineering high ethanol, high temperature, high sugar, and high salt the identified key target genes significantly reduced the tolerance phenotypes of the original strain KF-7 and the time and labor. Therefore, such strategy is powerful to resistant strain E-158. The fermentation performance of accumulate target gene information, which can be fur- the engineered strains under stress conditions was much ther adopted to support the construction of excellent better than strains reported by most researchers. These industrial strains. findings provide new insights guiding the engineering of In addition to ENA5, other genes investigated in the S. cerevisiae strains towards higher ethanol production in present study that contributed to stress tolerance pheno- the presence of diverse environmental stresses. type can be applied to obtain strains with specific stress tolerance or multiple stress-tolerant strains by simultane- Materials and methods ously regulating the expression of more than one of them. Strains, plasmids, primers, and media The effect of ENA5 and other genes on the stress toler - All the strains and plasmids used and constructed in ance phenotypes can also be explored using S. cerevisiae this study were listed in Table  4 [53, 54]. A flocculat- strains with different genetic backgrounds, including ing industrial S. cerevisiae strain KF-7, which has good xylose-fermenting S. cerevisiae strains, and even other ethanol fermentation capacity and stress tolerance, microorganisms having industrial application potentials. was used as the original strain [55, 56]. The multiple Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 14 of 19 Table 4 Plasmids and strains Plasmids and strains Description References Plasmids Cas9‑NAT Ampr; Cas9; NAT1 [53] pMEL13 Ampr; 2 μm origin, KanMX, gRNA‑ CAN1.Y [54] pMEL13‑CRZ1 Ampr; 2 μm origin, KanMX, gRNA‑ CRZ1 This study pMEL13‑ENA5 Ampr; 2 μm origin, KanMX, gRNA‑ENA5 This study pMEL13‑ASP3 Ampr; 2 μm origin, KanMX, gRNA‑ASP3 This study pMEL13‑TOS8 Ampr; 2 μm origin, KanMX, gRNA‑TOS8 This study pMEL13‑YOL162W Ampr; 2 μm origin, KanMX, gRNA‑YOL162W This study pMEL13‑YOR012W Ampr; 2 μm origin, KanMX, gRNA‑YOR012W This study Strains KF‑7 Flocculating diploid industrial Saccharomyces cerevisiae strain [55] E‑158 KF‑7; Random mutagenesis and hybridization [18] KF‑7‑ CRZ1 KF‑7; Replacement of promoter P to P This study CRZ1 TEF1 KF‑7‑ENA5 KF‑7; Replacement of promoter P to P This study ENA5 TEF1 KF‑7ΔASP3 KF‑7; Knockout ASP3 This study KF‑7ΔTOS8 KF‑7; Knockout TOS8 This study KF‑7ΔYOL162W KF‑7; Knockout YOL162W This study KF‑7ΔYOR012W KF‑7; Knockout YOR012W This study E‑158‑ CRZ1 E‑158; Replacement of promoter P to P This study CRZ1 TEF1 E‑158‑ENA5 E‑158; Replacement of promoter P to P This study ENA5 TEF1 stress-tolerant strain E-158 was obtained by mutagen- Batch fermentations and RNA extraction esis and hybridization using KF-7 as the starting strain The media and methods of batch fermentations under in our previous study [18]. Escherichia coli DH5α was five stress conditions: (1) 8.0% initial ethanol; (2) 44  °C; used for gene cloning and manipulation. Primers and (3) 43 °C with 2.6% initial ethanol; (4) YPD270; (5) 1.25 M other DNA fragments used in this study were pre- NaCl were described in our previous study [18]. Strains sented in Table 5 and Additional file 1: Table S6. were pre-cultivated in 100  mL YPD50 for 16  h (500  mL YP medium (10  g/L yeast extract, 20  g/L peptone) flasks). The cells were then collected, washed, and inocu - containing 20  g/L glucose (YPD20) was used for lated into fermentation media (100 mL in 300 mL flasks) cell growth. YP medium containing 150  g/L glucose with an initial cell density of OD 1.45–1.50. The flasks (YPD150) and 8.0% (v/v) ethanol was used for ethanol- were incubated in thermostatic water bath, and the stress fermentation. YP medium containing 100  g/L media was stirred (200  rpm/min) using magnetic stir- glucose (YPD100) was used for heat-stress fermenta- rers. Broth samples were collected during fermentation tion. YP medium containing 100 g/L glucose (YPD100) and used for the analysis of the concentrations of glucose and 2.6% (v/v) ethanol was used for multiple-stress and ethanol. For each group, three replicated fermenta- (ethanol and heat) fermentation. YP medium con- tion experiments were independently performed for the taining 270/280  g/L glucose (YPD270/280) was used measurements. for VHG-stress fermentation. YP medium containing To prepare RNA samples for transcriptomic sequenc- 150  g/L glucose (YPD150) and 1.25/1.5  mol/L NaCl ing, cells of E-158 and KF-7 were allowed to grow till was used for salt-stress fermentation. YP medium con- logarithmic growth under five stress conditions: (1) 8.0% taining 20  g/L glucose (YPD20), 20  g/L agar, 50  ng/ initial ethanol (48 h), (2) 44 °C (16 h), (3) 43 °C with 2.6% mL nourseothricin (NAT), and 100  ng/mL geneticin initial ethanol (12 h), (4) YPD270 (30 h), (5) 1.25 M NaCl (G418) was used for yeast transformation. LB medium (48 h). Then the cells were collected by centrifugation at (5  g/L yeast extract, 10  g/L peptone, and 10  g/L 8000×g for 2  min. Total RNA was extracted from using NaCl) supplemented with ampicillin (100  ng/mL) or Yeast RNA Kit (Omega Bio-Tek, USA). For each group, kanamycin (100  ng/mL) was used for E. coli DH5α three replicated fermentation experiments were indepen- transformation. dently performed. W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 15 of 19 Table 5 Target sequences used in yeast transformation Target Sequence gRNA insert tgR‑FTGC GCA TGT TTC GGC GTT CGA AAC TTC TCC GCA GTG AAAGA TAA ATG ATC tgR‑RGTT GAT AAC GGA CTA GCC TTA TTT TAA CTT GCT ATT TCT AGC TCT AAA AC ENA5 CSGAT AAC GTA TGT ACT CAC TGAGG CRZ1 CSGCA GAA TGT CTA CTA CGT CGAGG ASP3 CSGCT ACG GCA TGG ATC AGA TTAGG TOS8 CSAGA AAT TAC ATA ATA ACT GTAGG YOL162W CSAAG GTA CAA TGT TTA ATA AATGG YOR012W CSTTG AAA CTT TTT CAG TGA TTGGG Repair fragment TEF1 FCAC ACA CCA TAG CTT CAA AATG RTTT GTA ATT AAA ACT ENA5 RF FCCT TCA TCC TTT ACA TCG AGA ATA CGT TAA CCA AAT CAAC CAC ACA CCA TAG CTT CAA AATG RF RATT CTT CAT TAT TGT TTT CTT TGA CAG TTC CCT CGC TCAT TTT GTA ATT AAA ACT V FTTG TGA GGC TGA TGT TTT CTTC V RGCT TCT TCT GTA GTC AAT GTG TGA T CRZ1 RF FGGG CTG AAA AGT ACA TCC GCG CAT TTA ACA ATT GCT AAGC CAC ACA CCA TAG CTT CAA AATG RF RTAG TCA TGT AGG AAG CCA TAT TTC CGT TGC TGA ATG ACAT TTT GTA ATT AAA ACT V FGCT TTG ACT GCA CTT TAG CTTAG V RTTT CCG TTG CTG AAT GAC AT ASP3 RF FAGA GCA AAT GTT GGC TCG CTA TTC TTT TGT AAG CAA TCT GGT ACT CAC CAA CCT CCA ACT AGC CTG ATC AGT GAC TTT TCA TCA CAC TGT GTT TTT ATA TAG TTC TTA GTA GTA AAT ATA RF RTAT ATT TAC TAC TAA GAA CTA TAT AAA AAC ACA GTG TGA TGA AAA GTC ACT GAT CAG GCT AGT TGG AGG TTG GTG AGT ACC AGA TTG CTT ACA AAA GAA TAG CGA GCC AAC ATT TGC TCT V FTAT CAG ACC CTT CAG CAC GT V RTGA CAC TGC TCA AGG GAT AA TOS8 RF FTTT TTC AGT ATA GGA AGT AAT CAC TGT AGA AAT AAG TCA ACA ATA ATT GCA TAG AAA AAA TTT TAC TTT TTT CGG AAT TAC CTA AAA TGG GTT TAC GGC ATA GAA GAT AGA TAG ATT AAG RF RCTT AAT CTA TCT ATC TTC TAT GCC GTA AAC CCA TTT TAG GTA ATT CCG AAA AAA GTA AAA TTT TTT CTA TGC AAT TAT TGT TGA CTT ATT TCT ACA GTG ATT ACT TCC TAT ACT GAA AAA V FGTT CCC TTG TTT TGA AGC AC V RCGA AGA TTC TCA CCA AAG TT YOL162W RF FATG TCA CTT AAA ATG TTA TGG CAG GGG ATA ACA GAT TAC TAT ATA TAG CCT ATC TAC TTG ACT ATG TAG AAA TAT GGA TAC AAT CTC CAT GTT ATG TAT TTT TTA AGT TTG TGA ATC ATT RF RAAT GAT TCA CAA ACT TAA AAA ATA CAT AAC ATG GAG ATT GTA TCC ATA TTT CTA CAT AGT CAA GTA GAT AGG CTA TAT ATA GTA ATC TGT TAT CCC CTG CCA TAA CAT TTT AAG TGA CAT V FCTA AGC AAT CAC CTA AAC AT V RGAT GTC GTA CTT CTA CAG CT YOR012W RF FGAA AAA GGC AGT GAC AAA AAT ACT AAT CAG AAC GTT GAA AAC AAA TCA ATA GTT TTG ATA CCA TCC CGA AAT TAG AGG TTC AGT CAG AAA AAT ACT CGA AAA ATA TAA AAC CAA AGC AGA RF RTCT GCT TTG GTT TTA TAT TTT TCG AGT ATT TTT CTG ACT GAA CCT CTA ATT TCG GGA TGG TAT CAA AAC TAT TGA TTT GTT TTC AAC GTT CTG ATT AGT ATT TTT GTC ACT GCC TTT TTC V FTGC CTC ATA ACG TCT TGG GG V RGTA GGC CGT GAA TCC CTT CC tgR-F: upstream homologous of gRNA; tgR-R: downstream homologous of gRNA; CS: complementary sequence; RF: repair fragment; Vp: verification primer; F: forward primer; R: reverse primer, “double underline” represent the PAM (NGG) site, “underline” represent homologous arm Transcriptomic data analysis sequenced using an Illumina Novaseq 6000 platform A total of 30 mRNA samples (KF-7 and E-158 each had (Shanghai Majorbio Biopharm Technology Co. Ltd. three parallel samples under each stress condition) were (Shanghai, China)). Library construction was conducted Wang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 16 of 19 using the Illumina Truseq RNA sample prep kit. The region for overexpression of gene CRZ1 or ENA5 (Addi- mRNA was separated from total RNA by A-T base pair- tional file  1: Fig. S2A), and the complementary sequences ing, and then was broken into small fragments of about of gRNA were located in the coding sequence (CDS) 300  bp by the addition of fragmentation buffer. The region for knocking out genes ASP3, TOS8, YOL162W, cDNA was synthesized using mRNA as the template. The or YOR012W (Additional file  1: Fig. S2B). The gRNA sticky ends of the double-stranded cDNA were blunt- sequences were designed using the E-CRISP tool at ended with End Repair Mix, then an A-base was added http:// www.e- crisp. org/E- CRISP/ (Table  5). The gRNA to the 3′ end for the linker to the Y-line. The resulting was integrated into the linearized backbone using Gib- fragments were subjected to Illumina Novaseq sequenc- son assembly according to the manufacture’s manual ing. The Clean Data of each sample reached more than of Gibson Assembly Master Mix (New England Bio- 6.32 Gb. labs, Beverly, MA, USA). Each plasmid was transformed Difference in gene expression levels of one gene into E. coli DH5α. After sequencing, the plasmids con- between KF-7 and E-158 was quantified by an index, taining correct inserts were subsequently used for log FC, representing the logarithm to base 2 of the ratio transformation. of the RNA reads number of the gene in E158 to that in The strength of the promoter TEF1 (P , 420 bp) was TEF1 KF7. If∣log FC∣ ≥ 1 and P < 0.05, the expression of the high and relatively stable under five stress conditions related gene was defined to significantly change. These (Additional file  1: Table S7). P was used to replace the TEF1 analyses were performed on the online platform called promoters of CRZ1 and ENA5. The repair fragment was Majorbio Cloud Platform (www. major bio. com). The amplified using KF-7 genome as template, and it con - shared DEGs under five stress conditions were visual - tained upstream homologous arm, downstream homol- ized by Venn-diagram (http:// jvenn. toulo use. inra. fr/ app/ ogous arm, and TEF1 sequence (Additional file  1: Fig. examp le. html). Gene Ontology (GO) enrichment of the S2A). The repair fragments of ASP3, TOS8, YOL162W, shared DEGs was carried out with online tools developed and YOR012W were composed of upstream arm (60 bp) by Princeton University (http:// go. princ eton. edu/ cgi- bin/ and downstream arm (60  bp) of the target gene CDS, GOTer mMapp er), in which P ≤ 0.001 and enrichment which were synthesized in GENEWIZ (Suzhou, China) ratio ≥ 0.1 was set as the threshold. Kyoto Encyclopedia (Table 5, Additional file 1: Fig. S2B). of Genes and Genomes (KEGG) enrichment analysis of For yeast transformation, the lithium acetate method the shared DEGs was performed using the KEGG data- was used according to the protocol proposed by Finlay- base (http:// www. genome. jp/ kegg/). The threshold was son et  al. [57]. Cas9 plasmid was first transformed into set to P ≤ 0.05 and enrichment ratio ≥ 0.1. The shared KF-7 and E-158. The gRNA plasmid and repair fragment DEGs were searched in the YEASTRACT database (P ) were then transformed into the strains harboring TEF1 (http:// www. yeast ract. com/ form findre gulat ors. php) to Cas9 plasmid. Transformants grown on 2% YPD plate find the potential TFs. The protein–protein interaction containing 0.005% NAT and 0.01% G418 were confirmed network of shared DEGs was analyzed and constructed by PCR and Sanger sequencing. The removement of using Cytoscape 3.7.2 software. The original sequencing Cas9 and gRNA plasmids from the transformants were data are accessed in the National Center for Biotech- conducted according to Mans’ method [54]. The trans - nology Information platform under accession number formants were subjected to the following fermentation PRJNA642097. evaluation. Strains construction Evaluation of growth and fermentation performance CRISPR/Case9 gene-editing technology was used to over of engineered strains express or knock out the genes, and the experiments The growth of engineered strains under different stress were performed according to Li et  al. [37]. For gRNA conditions was evaluated using YPD20 agar medium. plasmid construction, the linearized plasmid backbone The engineered strains were pre-cultivated in YPD50 and gRNA insertion fragments were assembled to form medium for 16  h to logarithmic growth phase, and the the guideRNA (gRNA) plasmid. The linearized plasmid cells were harvested by centrifugation at 8000×g for backbone was PCR amplified from pMEL13 plasmid 2  min at 4  °C. The cells were washed twice using steri - using primer 6005/6006 [54]. The gRNA insert (120  bp) lized water and re-suspended in sterilized 0.5  mol/L was composed of upstream homologous arm (tgR-F, ethylenediaminetetraacetic acid disodium salt (EDTA- 50 bp), downstream homologous arm (tgR-R, 50 bp), and 2Na) solution with a final OD of 1.0. The solution complementary sequence (20  bp). The sequences were was then serially tenfold diluted. Aliquots of 2 μL were synthesized in GENEWIZ (Suzhou, China). The comple - spotted on YPD20 agar medium containing 13% (v/v) mentary sequence of gRNA was located in the promoter ethanol, 400 g/L glucose, 3 mol/L sorbitol, and 2 mol/L W ang et al. Biotechnology for Biofuels and Bioproducts (2022) 15:11 Page 17 of 19 NaCl. The plates were incubated at 30 °C for 72–120 h. Supplementary Information To examine the growth at high temperature, the plates The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s13068‑ 022‑ 02109‑x. were incubated at 44 °C for 72 h. The fermentation capacity under different stress con - Additional file 1. Additional Figures and Tables. ditions was evaluated using both YPD medium and three different raw materials. The method of fermenta - tion using YPD medium was the same as described in Acknowledgements Not applicable. Batch fermentation and RNA extraction. The compo - sitions of the pretreated straw, molasses, and cassava Authors’ contributions used in fermentation were shown in Additional file  1: LW: conceptualization, methodology, investigation, validation, and writing‑ original draft. BL: formal analysis and methodology. RS: formal analysis. SW: Tables S2, S3 and S4. The fermentation using the pre - investigation and methodology. ZX: writing–review and editing. CX: supervi‑ treated straw was performed by pre-saccharification sion and software. Y T: conceptualization, writing–review & editing, data and SSF at 42 °C. The solid content of pretreated straw curation, supervision and funding acquisition. All authors read and approved the final manuscript. was adjusted to 20% with PBS buffer solution (pH 5). CTec3 was added at a dosage of 20 FPU/g cellulose. The Funding slurry was pre-saccharified for 8  h at 50  °C. The pre- This work was supported by National Key R&D Program of China (2018YFA0902100 and 2018YFA0902102). saccharified slurry was inoculated with pre-cultivated fresh cells (0.5 g dry weight/kg slurry), and the SSF was Availability of data and materials conducted in a thermostat water bath for 96 h at 42 °C. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. The original RNA The VHG fermentation using molasses was conducted sequencing data can be accessed through the National Center for Biotechnol‑ at 33  °C. Diluted molasses (total sugar concentration ogy Information (https:// www. ncbi. nlm. nih. gov/) under project accession no. of 270.91 g/L) was inoculated with pre-cultivated fresh PRJNA642097. cells (0.5  g dry weight/L), and the VHG fermentation was conducted in a thermostat water bath for 96  h Declarations at 33  °C. High solid SSF of cassava was performed at Ethics approval and consent to participate 33 °C. Cassava slurry with 35% solid content was gelat- Not applicable. inized at 105  °C for 15  min. The resultant gelatinized Consent for publication slurry was liquefied at 95  °C for 2  h by α-amylase (10 All the authors agreed for publication. U/g starch). After cooling to room temperature, glucoa- mylase (160 U/g starch), pectinase (20 U/g raw mate- Competing interests The authors declare that they have no competing interests. rials), cellulase (10 U/g raw materials), 1  g/L K H PO , 2 4 0.5 g/L CaCl H O, 0.5  g/L MgSO .7H O, and 1  g/L 2 2 4 2 Author details (NH ) CO were added. Pre-cultivated fresh cells (0.5  g College of Architecture and Environment, Sichuan University, No. 24 South 2 2 Section 1 First Ring Road, Chengdu 610065, Sichuan, China. Institute of New dry weight/kg slurry) were inoculated. SSF was con- Energy and Low‑Carbon Technology, Sichuan University, No. 24 South ducted in a thermostat water bath for 96 h at 33 °C. All 3 Section 1 First Ring Road, Chengdu 610065, Sichuan, China. Engineering fermentation experiments were performed three times Research Center of Alternative Energy Materials & Devices, Ministry of Educa‑ tion, China, No. 24 South Section 1 First Ring Road, Chengdu 610065, Sichuan, independently. China. Sichuan Environmental Protection Key Laboratory of Organic Wastes Valorization, No. 24 South Section 1 First Ring Road, Chengdu 610065, Sichuan, China. Analytical methods Received: 13 November 2021 Accepted: 9 January 2022 Broth samples were diluted and filtered through 0.22  μm filters before analysis. The concentration of glucose was determined by HPLC (LC-10 ADVP, Shi- madzu, Kyoto, Japan) at 25  °C, with a mobile phase of References 5  mmol/L sulfuric acid at a flow rate of 0.6  mL/min. 1. Favaro L, Jansen T, van Zyl WH. Exploring industrial and natural Saccha- romyces cerevisiae strains for the bio‑based economy from biomass: the Ethanol concentration was determined using gas chro- case of bioethanol. Crit Rev Biotechnol. 2019;39(6):800–16. https:// doi. matography (GC 353B, GL Sciences, Kyoto, Japan) with org/ 10. 1080/ 07388 551. 2019. 16191 57. an FID detector, and isopropanol was used as the inter- 2. Mat Aron NS, Khoo KS, Chew KW, Show PL, Chen WH, Nguyen THP. 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Journal

Biotechnology for Biofuels and Bioproducts – Springer Journals

Published: Jan 21, 2022

Keywords: Saccharomyces cerevisiae; Multiple stress-tolerance; Comparative transcriptome; ENA5; ASP3; Crz1p

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