中文  |  English

菌物学报, 2022, 41(4): 546-560 doi: 10.13346/j.mycosystema.210397

研究论文

木屑处理迷宫栓孔菌Zn(II)-Cys(6)转录因子差异表达分析

李姝璇,, 池玉杰,,*

东北林业大学林学院,黑龙江 哈尔滨 150040

Analysis of the differentially expressed Zn(II)-Cys(6) transcription factors in Trametes gibbosa treated with sawdust

LI Shuxuan,, CHI Yujie,,*

School of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, China

收稿日期: 2021-10-5   接受日期: 2021-11-10  

基金资助: 中央高校基本科研业务费专项资金(2572017AA17)
2018外国文教专家聘请计划高校重点项目(T2018013)

Corresponding authors: * 623005873@qq.com ORCID: CHI Yujie (0000-0003-4676-0374)

Received: 2021-10-5   Accepted: 2021-11-10  

Fund supported: Fundamental Research Funds for the Central Universities(2572017AA17)
2018 Project of Hiring Foreign Cultural and Educational Experts(T2018013)

作者简介 About authors

ORCID:LIShuxuan(0000-0001-7855-3260) 。

摘要

Zn(II)-Cys(6)蛋白是一类仅存在于真菌中的锌指转录因子,其在迷宫栓孔菌(曾用名“偏肿革裥菌”) Trametes gibbosa中的相关研究较少。本研究对木屑处理后的迷宫栓孔菌进行转录组测序分析,以期挖掘到差异表达的Zn(II)-Cys(6)转录因子,为后续进一步对其功能的分析提供支持。首先,对在木屑处理下的T. gibbosa木质素降解酶进行了酶活检测,确认迷宫栓孔菌能有效降解木质素。之后,用木屑分别处理迷宫栓孔菌0、3、5、7和11 d,提取菌丝总RNA,利用高通量测序技术对这5个菌丝样本进行了转录组测序分析。通过COG、GO、Pfam和Swiss等数据库进行功能注释分析,鉴定出迷宫栓孔菌中全部的Zn(II)-Cys(6)家族转录因子基因,并进一步筛选出7个差异表达基因。进一步又对这7个差异基因的表达及蛋白结构进行了分析,绘制表达趋势热图,同时也对其理化性质,二、三级结构,疏水性等生物学特性进行了预测。通过构建系统发育树、预测Motif序列等初步分析了它们的进化关系及特性。最后,对这7个基因又利用RT-qPCR技术,进一步验证了转录组测序的结果。本研究从转录水平分析并鉴定出在木屑处理条件下迷宫栓孔菌中7个差异表达的Zn(II)-Cys(6)转录因子,研究结果将对后续研究迷宫栓孔菌中Zn(II)-Cys(6)转录因子的功能和表达调控机制有重要的参考价值。

关键词: 迷宫栓孔菌; 转录组; Zn(II)-Cys(6)转录因子; 生物信息学

Abstract

Zn(II)-Cys(6) proteins are zinc-finger type transcription factor that exist only in fungi, which play important roles in biological processes. Their precise function is still unclear in Trametes gibbosa. In this study, the transcriptome of T. gibbosa treated with sawdust was constructed to discover Zn(II)-Cys(6) transcription factor differentially expressed genes for exploring the function and role of the transcription factor of the fungus in a woody environment. The lignin degrading enzyme activity of T. gibbosa was tested under sawdust treatment, then the RNA of hyphae aged 0, 3, 5, 7, and 11 d was extracted, and the transcriptome of the hyphal samples was sequenced using HiSeq high-throughput sequencing technology. COG, GO, Pfam, and Swiss databases were used for functional annotation analysis. All Zn(II)-Cys(6) protein genes were screened out and seven differentially expressed genes were further screened out for analysis. Differentially expressed gene structures were analysed, and a heat map of the expression trends was constructed. A variety of biological characteristics, physical and chemical properties, secondary and tertiary structures, and hydrophobicity was predicted. Phylogenetic trees were constructed and the motif sequences were predicted to analyze the evolutionary relationship among the seven differentially expressed genes, and RT-qPCR was performed on these genes to further verify the results of the transcriptome sequencing. Seven Zn(II)-Cys(6) transcription factor differentially expressed genes in T. gibbosa were analyzed and identified and these results provide a reference for subsequent studies examining the function and expression of Zn(II)-Cys(6) transcription factors.

Keywords: Trametes gibbosa; transcriptome; Zn(II)-Cys(6) transcription factor; bioinformatics

PDF (975KB) 元数据 多维度评价 相关文章 导出 EndNote| Ris| Bibtex  收藏本文

本文引用格式

李姝璇, 池玉杰. 木屑处理迷宫栓孔菌Zn(II)-Cys(6)转录因子差异表达分析[J]. 菌物学报, 2022, 41(4): 546-560 doi:10.13346/j.mycosystema.210397

LI Shuxuan, CHI Yujie. Analysis of the differentially expressed Zn(II)-Cys(6) transcription factors in Trametes gibbosa treated with sawdust[J]. Mycosystema, 2022, 41(4): 546-560 doi:10.13346/j.mycosystema.210397

木质素是植物细胞壁的重要组成部分(Grabber et al. 2004),占植物干重的比率为15%-20%;它与纤维素、半纤维素一起构成了植物骨架的主要成分(吴坤等 2000;路瑶等 2013)。因木质素自然降解过程极其缓慢,导致目前相关资源无法得到高效利用,造成严重的资源浪费及环境污染(Vanholme et al. 2010;黄曹兴等 2019)。

研究表明,利用微生物法能有效降解木质素(顾晓利等 2010),其中真菌发挥主要作用。降解木质素的真菌主要包括白腐菌、褐腐菌和软腐菌(Temp et al. 1998),其中白腐菌能够分泌胞外氧化酶降解木质素(张力等 2009),被认为是最主要的木质素降解微生物,在自然界的碳素循环中发挥关键作用(Ohkuma et al. 2001;张力等 2009)。迷宫栓孔菌Trametes gibbosa (Pers.) Fr.是一种生长速度较快、对木材和木质素分解能力较强的多孔菌科Polyporaceae白腐菌,生长在多种阔叶树的活立木、倒木及枯立木上,可引起木材海绵状白色腐朽(Cui et al. 2019)。

大多数含锌(Zn)蛋白最早在非洲爪蟾卵母细胞中被发现(Miller et al. 1985),是一类能够结合DNA的具有手指状结构域的转录因子,因此被命名为锌指蛋白(Nieto 2003;黄骥等 2004;Macpherson et al. 2006)。根据与锌的结合方式,锌指蛋白被划分为不同的家族,如Cys2His2 (C2H2)蛋白(Zhang et al. 2019)、Cys4 (C4)蛋白和Zn(II)-Cys(6)锌簇蛋白等(Chang & Ehrlich 2013;Zhang et al. 2019)。Zn(II)-Cys(6)家族蛋白最早在酿酒酵母中被发现(Foster et al. 2013),之后发现也存在于如乳酸克鲁维酵母、粟酒裂殖酵母、白色念珠菌和黑曲霉等真菌中(Sohnle et al. 2000;Schillig & Morschh 2013)。研究显示该家族成员均来自于真菌(Schjerling 1996);该家族成员的半胱氨酸残基能与两个锌原子结合,具有保守的基序CysX2CysX6CysX5-12CysX2CysX6-8Cys (Schjerling 1996;Macpherson et al. 2006)。Zn(II)-Cys(6)蛋白在生物学过程中发挥广泛的作用,包括氨基酸和维生素合成、碳和氮代谢、减数分裂和形态发生(Macpherson et al. 2006)。

目前对迷宫栓孔菌T. gibbosa中锌指蛋白的研究较少,该菌中大部分锌簇蛋白的表达及功能均未知,因此探究木屑诱导条件下迷宫栓孔菌中锌簇蛋白转录因子的基因表达和调控过程及变化,对锌指蛋白在木质素及纤维素降解调控过程中的作用机制研究具有重要理论指导意义。真菌降解木质素是个漫长的过程,为分析木屑短时间和长时间处理下迷宫栓孔菌的变化,本研究选择0、3、5、7和11 d 共5个时间点来处理和收集菌丝,对木质素降解酶系统进行检测,并利用HiSeq高通量测序技术对菌丝样本进行转录组测序,拟从转录水平上分析迷宫栓孔菌中Zn(II)-Cys(6)转录因子基因的表达调控变化,筛选与木质素降解相关的基因,为探索迷宫栓孔菌Zn(II)-Cys(6)转录因子基因在木质环境下参与的代谢过程提供分子层面的数据支持与理论基础。

1 材料与方法

1.1 实验材料

供试菌株Trametes gibbosa采样于中国东北长白山国家级自然保护区,菌株保存在马铃薯葡萄糖琼脂(potato dextrose agar,PDA)斜面培养基上,冷藏于4 ℃。

供试木材为光皮小黑杨(小叶杨×欧洲黑杨Populus simonii Carr. × Populus nigra Linnaeus),实验前对木段进行去皮处理并剪成小块,经高温高压灭菌后备用。

1.2 样品处理及酶活测定

T. gibbosa菌株复温后转移到新的PDA平板培养基上,26 ℃避光培养至菌丝长满整个平板。用5 mm孔径的打孔器在平板上均匀打孔,接种到含有70 mL LNAS液体培养基和5 mL过滤除菌的15%葡萄糖的锥形瓶中。每个锥形瓶中加5个菌饼,26 ℃避光预培养10 d。设置一组不加任何木质基质的空白对照组,并向剩余锥形瓶中各加入2 g无菌木屑,作为处理组。分别在0、3、5、7和11 d提取酶液,利用紫外分光光度计法检测MnP酶及漆酶酶活(赵清泉 2019)。

1.3 菌丝收集和转录组cDNA文库测序

在0 d时随机选取5瓶菌丝混合为1个样本,3个生物学重复共计15瓶,提取菌丝作为对照组,分别记为CK1、CK2、CK3;并在处理组3、5、7和11 d时分别提取菌丝,每5瓶作为一个样本,3个生物重复共计15瓶。处理组共得到12组样本,其按时间顺序记为MX11、MX12、MX13、MX21、MX22、MX23、MX31、MX32、MX33、MX41、MX42和MX43。将收集的菌丝样品送至北京百迈客生物技术有限公司,提取菌丝的总RNA,质量评估合格后在Illumina HiSeq X Ten 高通量测序平台上对文库进行双端测序(Zhang et al. 2019)。对得到的转录组数据进行多种生物信息学分析以获得相应基因的生物信息。

1.4 Zn(II)-Cys(6)转录因子差异表达基因的筛选及基因结构

根据转录组数据中COG、eggNOG、GO、KEGG、NR和SwissProt数据库中的功能注释,筛选出72个Zn(II)-Cys(6)转录因子基因,并根据表达量的变化确定了7个差异表达基因,分别命名为MW788071、MW788078、MW788081、MW788086、MW788089、MW788102和MW788113。利用Gene Structure Display Server (Guo et al. 2007) 对7个差异基因的外显子和内含子进行分析,并通过TBtools (Chen et al. 2018) 进行可视化。

1.5 Zn(II)-Cys(6)转录因子差异表达基因表达模式热图

根据7个差异基因在木屑处理不同时间点后的表达情况及趋势变化,计算出差异表达倍数,并通过TBtools (Chen et al. 2018) 绘制表达趋势热图。

1.6 Zn(II)-Cys(6)转录因子差异表达基因进化关系及理化特性

将7个差异表达基因氨基酸序列放入ProtParam (http://web.expasy.org/protparam/) (Wilkins et al. 1999)在线软件进行理化性质预测,得到蛋白分子量和等电点等理化属性。使用SOPMA (https://npsa-prabi.ibcp.fr/) (Geourjon & Deléage 1995)在线网站对7个差异表达基因氨基酸序列的二级结构进行预测。使用Swiss-Model (https:// swissmodel.expasy.org/) (Torsten et al. 2003)在线网站进行蛋白序列三级结构同源建模在线预测。

1.7 转录因子家族的进化关系及蛋白Motif序列分析

为研究转录因子家族进化关系,在NCBI (http://www.ncbi.nlm.nih.gov/) (Edgar et al. 2002)通过BLAST软件比对出15个与差异基因相似的基因,使用MEGA 5.1 (Tamura et al. 2011)对全部22个基因的氨基酸序列进行多序列比对,并在此基础上使用邻接法(neighbor-joining),样本自检举1 000次,构建系统发育进化树,为进一步揭示NJ模型的可靠性,同时使用最大似然法(maximum likelihood)构建系统发育进化树。通过MEME (http://meme-suite.org/) (Bailey et al. 2006)在线软件对蛋白质motif序列进行分析。

1.8 蛋白质的亲疏水性分析

利用网站ExPASy ProtScale (https://web.expasy.org/protscale/)对7个Zn(II)-Cys(6)差异基因的氨基酸序列进行分析,默认值为Hphob./Kyte & Doolittle,选择线性模型,判断蛋白质的疏水性。

1.9 亚细胞定位预测

使用WoLFPSORT (https://wolfpsort.hgc.jp/) (Horton et al. 2007)在线网站预测7个差异基因潜在的分布位置,帮助了解这些基因的功能。

1.10 Zn(II)-Cys(6)转录因子差异表达基因的荧光定量分析

为了对转录组分析结果进行分子验证,对7个差异表达基因进行了实时定量PCR。按照荧光定量PCR引物设计原则,使用BioXM 2.6软件设计引物。使用三磷酸甘油醛脱氢酶基因(Gpd)作为内参基因,引物序列见表1。以CK组对应基因的表达情况为对照,计算实验组中每个基因的表达水平。

表1   RT-qPCR引物序列

Table 1  RT-qPCR primer sequence

基因名称
Gene name
上游引物
5ʹ primers (5ʹ→3ʹ)
下游引物
3ʹ primers (5ʹ→3ʹ)
片段长度
Fragment length (bp)
GpdAACGGTTTCGGTCGTATCGGCTTGCCCTCGACCCAGAGCT152
MW788071CGATGCTCAACTCCGACTATGGATCCCTCTATGAACTCTGCAG290
MW788078AGACAAGCGAAACCTCCAAGCATCTGATACTGCTCCCTGAAC211
MW788081GGGTAAAGTCGGGTCTTGTATCGCATCAGCTCACACGTTTTC261
MW788086CAGAAGGTGAAGTGCGAGTACGGTGACTGGGAGAAGTTTC289
MW788089CAGCCAGTCAGAGATCAATCCTGTGGATGACGGGAAAGAAC152
MW788102TCCACTTTCTAATGCCGGTGATCAATAGGAAGCACTGGACG289
MW788113TGGTGATGGACAAGTACGTGGCATATCTCGCTCAGGATCAC257

新窗口打开| 下载CSV


2 结果与分析

2.1 迷宫栓孔菌在木质基质下的酶活测定

本研究分别测定了对照组和处理组MnP酶及漆酶的酶活,并将数据绘制成折线图(图1A、1B)。在木屑处理下,T. gibbosa的MnP酶和漆酶活性均得到提高且呈上升趋势,而在非木屑处理下,两种酶的活性均无明显变化。

图1

图1   木屑组与对照组的酶活性比较

A:锰过氧化物酶活性;B:漆酶活性

Fig. 1   Comparison of enzyme activity between sawdust group and control group.

A: Manganese peroxidase (MnP) enzyme activity; B: Laccase (LA) enzyme activity.


2.2 Zn(II)-Cys(6)转录因子差异表达基因的筛选

根据COG、eggNOG、GO、KEGG、NR和SwissProt等基因功能注释数据库的注释结果,对转录组全部基因中与Zn(II)-Cys(6)相关的基因进行搜索,共搜索到72个Zn(II)-Cys(6)转录因子基因,并根据转录组数据中Log2FC值,进一步确认出7个差异表达基因(表2)。其中MW788071、MW788086、MW788089和MW788113这4个基因上调,MW788081、MW788078、MW788102这3个基因下调。

表2   差异表达基因Log2FC值

Table 2  Log2FC values of differentially expressed genes

基因名称
Gene name
0 d vs 3 d0 d vs 5 d0 d vs 7 d0 d vs 11 d表达趋势
Trend of expression
MW7880711.9972.0481.6911.538上调Upregulate
MW788086-1.1761.0111.7721.356上调Upregulate
MW7880890.4371.1941.7721.836上调Upregulate
MW788113-1.0951.0821.1611.479上调Upregulate
MW788081-1.642-1.532-1.722-1.871下调Downregulate
MW788078-1.131-1.107-1.189-1.307下调Downregulate
MW788102-2.344-2.625-1.562-2.612下调Downregulate

新窗口打开| 下载CSV


2.3 差异基因的基因结构分析

本研究通过对7个差异基因的基因结构进行预测分析,确定了基因外显子和内含子的位置(图2)。黄色区域表示UTR (上游为5ʹ UTR,下游为3ʹ UTR),绿色区域代表编码区,线为内含子。其中MW788078、MW788081、MW788086、MW788102含有非编码区,MW788071、MW788089和MW788113这3个基因不含UTR。7个差异基因均具有多个内含子和外显子。

图2

图2   差异基因的基因结构分析

上游黄色区域为5ʹ UTR;下游黄色区域为3ʹ UTR;绿色区域为编码区,线为内含子

Fig. 2   Gene structure analysis of differential genes.

The upstream yellow boxes represent 5ʹ UTR; The downstream yellow boxes represent 3ʹ UTR; The green boxes represent coding regions, and the lines represent introns.


2.4 差异基因的表达模式热图

以7个差异基因在0 d的表达水平作为对照,分析各基因在不同时间处理下相对于0 d的差异表达倍数,制作表达趋势并绘制热图(图3)。通过热图我们更直观地看出MW788071、MW788089、MW788086和MW788113这4个基因与对照组相比表达量显著上调,其中MW788086和MW788113为先下调后上调,MW788081、MW788078、MW788102这3个基因与对照组相比表达量显著下调。

图3

图3   差异基因表达模式热图

Fig. 3   Heat map of differential gene expression patterns.


2.5 差异基因的理化特性分析

本研究对7个Zn(II)-Cys(6)转录因子差异基因进行了理化性质分析,7个差异基因相应蛋白质的参数显著不同(表3)。氨基酸数的范围在225-1 114,氨基酸数平均值为821.28。分子量的范围是24.223-122.033 kDa,平均分子量为90.024 kDa。理论等电点的范围在6.26-9.09,等电点的平均值为7.43。脂肪系数在50.40-75.14,平均脂肪系数为66.35。蛋白质亲水性系数的平均值为-0.538,亲水系数均为负数表明72个蛋白质均为疏水蛋白。这些蛋白质均由C、H、N、O和S这5种元素组成。原子总数范围在3 360- 16 922,原子总数的平均值为12 491。

表3   蛋白质理化性质分析

Table 3  Analysis of protein physical and chemical properties

基因名称
Gene name
氨基酸数
Number of
amino acids
分子量
Molecular
weight (kDa)
理论等电点
Theoretical
pI
脂肪系数
Aliphatic
index
亲水系数
Grand average of
hydropathicity
分子式
Formula
原子总数
Total number
of atoms
MW78807140343.0178.2956.33-0.666C1 851H2 899N567O586S175 920
MW7880781 016111.3707.6072.73-0.418C4 962H7 692N1 404O1 448S3715 543
MW788081948103.5217.5675.14-0.436C4 532H7 124N1 316O1 381S4314 396
MW78808622524.2239.0950.40-0.736C1 031H1 673N317O321S183 360
MW788089962108.0526.2970.21-0.560C4 765H7 354N1 358O1 436S4414 957
MW7881021 114122.0336.2669.52-0.448C5 348H8 349N1 531O1 642S5216 922
MW7881131 081117.9546.9270.14-0.503C5 128H8 051N1 539O1 574S4716 339

新窗口打开| 下载CSV


本研究对7个差异基因蛋白质的二、三级结构进行了预测(表4)。以MW788071为例,在其氨基酸序列中,Alpha螺旋占氨基酸总数的22.08%;延伸链占氨基酸总数的3.23%;无规则链占氨基酸总数的74.19%,属于调节蛋白GAL4,并预测出该蛋白质的三级结构模型。

表4   蛋白质的二、三级结构预测

Table 4  Prediction of protein secondary and tertiary structure

基因名称
Gene name
Alpha螺旋
Alpha helix (%)
延伸链
Extended
strand (%)
无规则链
Random
coil (%)
描述
Description
同源性建模
Homology-modelling
MW78807122.083.2374.19调节蛋白GAL4;Gal4在DNA识别中二聚化的结构基础
Regulatory protein GAL4; Structural basis for dimerization in DNA recognition by Gal4
MW78807832.286.7958.07着丝粒DNA结合蛋白复合物CBF3亚基B;
出芽酵母动粒的CBF3-CEN3复合物的冷冻电镜结构
Centromere DNA-binding protein complex CBF3 subunit B; Cryo-EM structure of the CBF3-CEN3 complex of the budding yeast kinetochore
MW78808138.197.0751.48着丝粒DNA结合蛋白复合物CBF3亚基B;
出芽酵母动粒的CBF3-msk复合物的冷冻电镜结构
Centromere DNA-binding protein complex CBF3 subunit B; Cryo-EM structure of the CBF3-msk complex of the budding yeast kinetochore
MW78808621.338.0067.11着丝粒DNA结合蛋白复合物CBF3亚基B;
出芽酵母动粒的CBF3-CEN3复合物的冷冻电镜结构
Centromere DNA-binding protein complex CBF3 subunit B; Cryo-EM structure of the CBF3-CEN3 complex of the budding yeast kinetochore
MW78808932.125.6159.88着丝粒DNA结合蛋白复合物CBF3亚基B;
出芽酵母动粒的CBF3-CEN3复合物的冷冻电镜结构
Centromere DNA-binding protein complex CBF3 subunit B; Cryo-EM structure of the CBF3-CEN3 complex of the budding yeast kinetochore
MW78810230.434.8562.39着丝粒DNA结合蛋白复合物CBF3亚基B
Centromere DNA-binding protein complex CBF3 subunit B
MW78811334.69.0753.19着丝粒DNA结合蛋白复合物CBF3亚基B
Centromere DNA-binding protein complex CBF3 subunit B

新窗口打开| 下载CSV


2.6 差异基因的系统发育进化树及Motif序列分析

通过BLAST软件,比对出包括云芝Trametes versicolor、灵芝Ganoderma lucidum、毛栓菌Trametes hirsuta、污叉丝孔菌Dichomitus squalens等在内的多种真菌共15个同源基因,并通过对7个差异基因及15个同源基因进行多序列比对,构建了NJ系统发育树(图4A),同时利用JTT+G+F的模型构建了ML系统发育进化树(图4B),两种发育进化树的结果具有较好的一致性,揭示了Zn(II)-Cys(6)转录因子家族差异基因间的进化关系。

图4

图4   差异基因系统发育进化树

A:NJ模型;B:ML模型

Fig. 4   Evolutionary tree of differential gene phylogeny.

A: NJ model; B: ML model.


通过对7个差异基因蛋白质进行的保守结构域Motif分析,发现这些基因蛋白质均含有相同或相似的蛋白质保守结构域。通过MEME软件对7个蛋白质进行分析,最终选择了10个motif序列,并确定了它们在基因中的分布(图5)。通过Pfam和InterProScan两个数据库对这些Motif序列进行注释分析发现,Motif2、Motif4和Motif7包含真菌转录因子结构域。Motif3包含Zn(II)- Cys(6)真菌型DNA结合域超家族(表5)。

图5

图5   保守结构域分析及分布

Fig. 5   Analysis and distribution of conserved domains.


表5   Motif序列分析

Table 5  Motif sequence analysis

名字
Name
序列
Sequence
Pfam注释
Description of Pfam
分布
Distribution
Motif1RRSTRACDRCRKSKSKCE-MW788071; MW788078;
MW788081; MW788086;
MW788089; MW788102;
MW788113
Motif2JLDTTYQTSRPSTVQALLLL
ALREFGIGALEQGWLYVGM
ALRMAQDLGLN
真菌转录因子结构域
Fungal transcription
factor domain
MW788078; MW788081;
MW788089; MW788102;
MW788113
Motif3CKNCALAGTQCTFLGPSFKR
GPPKGYIQAJEARLHQVE
Zn(II)-Cys(6)真菌型DNA结合域超家族
Zn(II)-Cys(6) fungal DNA
binding domain superfamily
MW788078; MW788081;
MW788089; MW788102;
MW788113
Motif4EKZIRKRIWWGCYILDKLSAL
YLGRPVAIREGDFDTEJP
真菌转录因子结构域
Fungal transcription
factor domain
MW788078; MW788081;
MW788089; MW788102;
MW788113
Motif5PHILMLHIQYWAAVLLLHRPF-MW788078; MW788081;
MW788089; MW788102;
MW788113
Motif6HYDICNRAANHISLLAGJYNE
KYSLRRAPPFLANYIFSAGITHVIT
-MW788078; MW788081;
MW788089; MW788113
Motif7QDRLLDLYFAYVHPALPIVDKQ
DFLDQYRNLND
真菌转录因子结构域
Fungal transcription factor domain
MW788078; MW788081;
MW788089; MW788102;
MW788113
Motif8EDDVADAFGQLSIDENKZVRYH
GKASGLQLLAQSERKDGRN
-MW788078; MW788089;
MW788102; MW788113
Motif9CFRELCELYVILGDILDKIY-MW788078; MW788081;
MW788089; MW788102;
MW788113
Motif10RARSVIDDLAGDPLAKEILDRV
DTGPYGAKGR
-MW788078; MW788089;
MW788113

Note: -, not detected.

新窗口打开| 下载CSV


2.7 差异基因的亲疏水性分析

7个差异基因蛋白质的亲疏水性分析结果见图6。以MW788071的结果(表6)为例进行说明。MW788071蛋白中的第28位赖氨酸(K)具有-4.067的低疏水性评分,第63位的甘氨酸(G)具有1.700的高疏水性得分,表明其更具有亲水性。表6中列出了7个差异基因氨基酸序列的疏水性分析结果,可知7个差异基因蛋白质均为亲水性蛋白。

图6

图6   差异基因疏水性分析

Fig. 6   Hydrophobicity analysis of differential genes.


表6   Zn(II)-Cys(6)转录因子蛋白质疏水性分析

Table 6  Zn(II)-Cys(6) transcription factor protein hydrophobicity analysis

基因名称
Gene name
低分值处位置
Position of
low score
低分值处氨基酸
Amino acid of
low score
低分值
Low score
高分值处位置
Position of high
score
高分值处氨基酸
Amino acid of high
score
高分值
High score
MW78807128Lys (K)-4.06763Gly (G)1.700
MW788078312Thr (T)-3.144472Val (V)2.389
MW788081847Gln (Q)-3.611320Leu (L)2.511
MW788086115Pro (P)-2.83337Ala (A)1.222
MW788089164Arg (R)-3.756404Ala (A)3.111
MW788102765, 766Arg (R), Asp (D)-3.544652Leu (L)2.778
MW788113332, 333Gln (Q), Asp (D)-3.422445Ala (A)2.744

新窗口打开| 下载CSV


2.8 差异基因亚细胞定位分析

7个差异基因的亚细胞定位预测结果见表7,7个基因的蛋白均定位于细胞核中,概率为76.7%-94.1%,且大部分含有多个明显的核定位信号。

表7   差异基因的亚细胞定位及核信号定位预测

Table 7  Subcellular localization of differential genes and prediction of nuclear signal localization

基因名称
Gene name
位置
Position
可靠性
Reliability (%)
核定位信号
Nuclear localization signal
MW788071细胞核Nucleus94.1H(25)RRK; R(26)RKR; R(27)KRR
MW788078细胞核Nucleus89.0P(238)PRSRRR; P(239)RSRRRL; P(828)SDRRQK
MW788081细胞核Nucleus94.1R(31)KRK; P(399)PRKDRQ; P(400)RKDRQI; P(520)FYRRKS
MW788086细胞核Nucleus94.1R(215)PKR; P(216)KRK; P(120)CERCKR; P(214)RPKRKW;
P(216)KRKWIE; R(42)RWLLKPLNMLCRGRRT
MW788089细胞核Nucleus89.0-
MW788102细胞核Nucleus89.0P(33)KKK; K(34)KKR; R(68)RKK; R(762)PRR; R(837)KRP;
P(30)HPPKKK; P(32)PKKKRV; P(33)KKKRVD; P(358)RLKKFD;
P(686)GARKCK; P(763)RRDRSR; R(57)RRVWRACESCRRKKIK;
R(58)RVWRACESCRRKKIKC
MW788113细胞核Nucleus76.7P(433)RKR; R(434)KRR; R(849)HKR; P(67)SRKRGP;
P(353)NGQRRR; P(430)IGPRKR; P(433)RKRRVP; P(848)RHKRVA;
R(26)RRSSKACDQCRKSKCK

Note: -, not detected.

新窗口打开| 下载CSV


2.9 Zn(II)-Cys(6)转录因子差异表达基因的实时荧光定量分析

为了验证7个差异表达基因在不同时间点木屑处理条件下的差异表达情况,进行了RT-qPCR操作,将得到的数据换算为Log2FC值,并与转录组中的Log2FC值进行对照。各基因在木屑处理不同时间点后的表达情况及趋势变化见图7。RT-qPCR结果表明,在木屑处理不同时间点条件下,7个差异表达基因的表达水平表现出不同趋势,其中MW788071、MW788086、MW788089和MW788113这4个基因整体呈现上调趋势,MW788078、MW788081和MW788102这3个基因整体呈现下调趋势。基于以上分析结果可知,7个差异表达基因在木屑处理条件下均做出相应的响应,并显示出了不同的表达量差异,且与转录组中的差异表达趋势整体一致。

图7

图7   不同天数处理条件下的差异基因表达水平

Fig. 7   Differential gene expression levels under different days of treatment.


3 结论与讨论

木材的降解是一个十分漫长的过程,因为木质素是一种非多糖高分子物质,可为植物细胞提供足够的强度和硬度,在木质素的包裹下,木质纤维集合体拥有了更强的硬度与强度(路瑶等 2013)。作为木材中木质素的主要降解者,白腐菌在全球碳循环中起着重要的作用(赵清泉 2019)。

转录因子能与真核生物启动子特定DNA结合,在转录和调控中严格控制生物表达过程(Miller et al.1985),而微量元素锌(Zn)是许多蛋白质包括各种酶的功能及表达调控所必需的(Macpherson et al. 2006;Chang & Ehrlich 2013),因此我们选择了锌指转录因子蛋白进行进一步的研究。真核生物中的锌指蛋白参与了细胞的生长分化和凋亡等,同时在生物逆境胁迫中发挥调控作用(Keene et al. 1997)。锌指蛋白主要分为C2H2型、C4型和C6型。其中C6型Zn(II)-Cys(6)转录因子家族基因只存在于真菌中,半胱氨酸残基与两个锌原子结合,这两个锌原子参与DNA结合的结构域的折叠并进行协调。在真菌中,对Zn(II)-Cys(6)转录因子家族基因的研究较少,所以仅有少量基因被注释和富集,仍有大量关键基因有待于挖掘,需要通过寻找代谢通路和序列比对等方式挖掘锌簇转录因子家族中更多的关键基因及功能注释。

在前期研究中,通过用木屑、秸秆及稻草处理迷宫栓孔菌发现,木质素降解酶活性均有提高,其中木屑处理下的木质素降解酶活性提升最为明显(赵清泉 2019)。本研究通过对木屑处理迷宫栓孔菌后MnP酶和漆酶的测定,再次验证了迷宫栓孔菌在木质环境中可以通过分泌木质素降解酶对木质素做出反应。本研究首次分析了木屑处理条件下迷宫栓孔菌的转录组数据,并结合多种基因功能注释数据库,鉴定出72个Zn(II)-Cys(6)转录因子家族成员,并根据不同时间处理下的Log2FC值,最终筛选得到了7个差异表达基因,命名为MW788071、MW788078、MW788081、MW788086、MW788089、MW788102和MW788113。其中4个基因表达量呈上调趋势,3个基因表达量呈下调趋势,并具备一定的规律。基因结构分析表明,7个差异基因均含有多个内含子及外显子,其中MW788078、MW788081、MW788086、MW788102含有UTR。根据转录组数据中的表达量变化,绘制了表达模式热图,更直观地看出7个差异基因的表达趋势。理化性质分析结果表明,7个Zn(II)-Cys(6)转录因子基因相应蛋白质的参数差别显著。蛋白质二、三级结构的预测分析表明,大部分蛋白质的结构类似,描述为着丝粒DNA结合蛋白复合物CBF3亚基B,仅MW788071的结构相对特殊,描述为调节蛋白GAL4。在NCBI中找到15个同源基因进行多序列比对,用两种方法构建系统发育树,得到了7个Zn(II)-Cys(6)家族成员的进化关系。保守结构域分析结果表明,这些基因均含有多个保守结构域,其中Motif2、Motif4、Motif7为真菌转录因子结构域,Motif3为Zn(II)-Cys(6)真菌DNA 结合域,其他结构域的功能未知。蛋白质疏水性分析表明,7个差异基因蛋白质均为亲水蛋白。基因的亚细胞定位分析表明,7个差异基因均被预测在细胞核中起作用,且具有多个核定位信号,具体定位情况还需要分子生物学实验进一步验证。通过RT-qPCR的实验结果表明,MW788071、MW788086、MW788089和MW788113为上调表达基因,MW788102、MW788078和MW788081为下调表达基因,在不同的时间点显示出了不同的表达量差异,但整体趋势与转录组测序结果一致,说明7个Zn(II)-Cys(6)差异转录因子基因在木屑处理条件下做出相应的响应,也验证了这7个基因很可能在迷宫栓孔菌降解木质素的过程中起调控作用。

本研究对在木屑处理条件下迷宫栓孔菌中7个差异表达的Zn(II)-Cys(6)转录因子进行了多种生物信息学分析,并对转录组分析得到的结果进行了RT-qPCR验证。初步判断这些差异表达基因与迷宫栓孔菌对木质素的降解相关,该结果为进一步分析Zn(II)-Cys(6)转录因子基因的功能提供了全面的数据,为后续Zn(II)-Cys(6)转录因子家族关键基因的挖掘和功能调控及其对木质素的降解机制提供重要的参考价值。

参考文献

Ohkuma M, Maeda Y, Johjima T, Kudo T, 2001.

Lignin degradation and roles of white rot fungi: study on an efficient symbiotic system in fungus-growing termites and its application to bioremediation

Riken Review, 42: 39-42

[本文引用: 1]

Schillig R, Morschhäuser J, 2013.

Analysis of a fungus-specific transcription factor family, the Candida albicans zinc cluster proteins, by artificial activation

Molecular Microbiology, 89(5): 1003-1017

DOI:10.1111/mmi.12327      PMID:23844834      [本文引用: 1]

The zinc cluster proteins are a family of transcription factors that are unique to the fungal kingdom. In the pathogenic yeast Candida albicans, zinc cluster transcription factors control the expression of virulence-associated traits and play key roles in the development of antifungal drug resistance. Gain-of-function mutations in several zinc cluster transcription factors, which result in constitutive overexpression of their target genes, are a frequent cause of azole resistance in clinical C. albicans isolates. We found that zinc cluster proteins can also be artificially activated by C-terminal fusion with the heterologous Gal4 activation domain. We used this strategy to create a comprehensive library of C. albicans strains expressing all 82 zinc cluster transcription factors of this fungus in a potentially hyperactive form. Screening of this library identified regulators of invasive filamentous growth and other phenotypes that are important during an infection. In addition, the approach uncovered several novel mediators of fluconazole resistance, including the multidrug resistance regulator Mrr2, which controls the expression of the major C. albicans multidrug efflux pump CDR1. Artificial activation therefore is a highly useful method to study the role of zinc cluster transcription factors in C. albicans and other fungi of medical, agricultural and biotechnological importance. © 2013 John Wiley & Sons Ltd.

Schjerling P, Holmberg S, 1996.

Comparative amino acid sequence analysis of the C 6 zinc cluster family of transcriptional regulators

Nucleic Acids Research, 24(23): 4599-4607

PMID:8967907      [本文引用: 2]

The C6 zinc cluster family of fungal regulatory proteins shares as DNA-binding motif the C6 zinc cluster, also known as the Zn(II)2Cys6 binuclear cluster. This family includes transcriptional activators like Gal4p, Leu3p, Hap1p, Put3p and Cha4p from Saccharomyces cerevisiae, qutA and amdR from Aspergillus, nit4 from Neurospora and Ntf1 from Schizosaccharomyces pombe. Seventy-nine proteins were retrieved from databases by homology to the C6 zinc cluster. All were fungal and 56 were found in the entire genome sequence of S.cerevisiae. Sequence analysis suggests that 60 of the 79 proteins possess one or more coiled-coil dimerization regions succeeding the C6 zinc cluster. Previous comparisons of Gal4p and seven other C6 zinc cluster proteins identified an additional region with weak homology. This region, designated the middle homology region (MHR), was shown to be present in 50 of the 79 proteins. Although reported mutation and deletion analyses suggest a role of MHR in regulation of protein activity, no function has yet been assigned specifically to this region. We find that the family of MHR sequences is confined to C6 zinc cluster proteins and hypothesize that one MHR function is to assist the C6 zinc cluster in DNA target discrimination.

Sohnle PG, Hunter MJ, Beth H, Chazin WJ, 2000.

Zinc-reversible antimicrobial activity of recombinant calprotectin (migration inhibitory factor-related proteins 8 and 14)

Journal of Infectious Diseases, 2000(4): 1272-1275

[本文引用: 1]

Schwede T, Kopp J, Guex N, Peitsch MC, 2003.

SWISS-MODEL: an automated protein homology- modeling server

Nucleic Acids Research, 31(13): 3381-3385

DOI:10.1093/nar/gkg520      URL    

Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S, 2011.

MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods

Molecular Biology and Evolution, 28(10): 2731

DOI:10.1093/molbev/msr121      URL     [本文引用: 1]

Temp U, Eggert C, Eriksson KEL, 1998.

A small-scale method for screening of lignin-degrading microorganisms

Applied and Environmental Microbiology, 64(4): 1548-1549

PMID:16349553      [本文引用: 1]

A new method to facilitate rapid screening of lignin-degrading microorganisms was developed. Fungal strains are cultivated in tissue culture plates containing C-ring-labeled dehydrogenation polymerizate (DHP) (synthetic lignin). Evolved CO(2) is trapped in barium-saturated filter paper and is detected by exposing the paper to X-ray film. Analysis of the autoradiograms, carried out by density measurement with an image analysis program, allows for a semiquantitative estimation of the amount of CO(2) evolved. The method is especially useful for screening for new, powerful lignin-degrading strains in both man-made and natural environments. It eliminates the need for special equipment for their cultivation and trapping of CO(2) as well as laborious sample analysis. The method has in this study been used to test three novel fungal isolates and a laccaseless mutant of the basidiomycete Pycnoporus cinnabarinus. Their ligninolytic capacities were compared with those of the potent lignin degrader Ceriporiopsis subvermispora.

Vanholme R, Demedts B, Morreel K, Ralph J, Boerjan W, 2010.

Lignin biosynthesis and structure

Plant Physiology, 153(3): 895-905

DOI:10.1104/pp.110.155119      PMID:20472751      [本文引用: 1]

Wilkins MR, Gasteiger E, Bairoch A, Sanchez JC, Williams KL, Appel RD, Hochstrasser DF, 1999.

Protein identification and analysis tools in the ExPASy server

Methods in Molecular Biology, 112: 531-552

PMID:10027275      [本文引用: 1]

Wu K, Zhang SM, Zhu XF, 2000.

Recent research advances on the lignin biodegradation

Journal of Henan Agricultural University, 2000(4): 349-354 (in Chinese)

Yu MG, Yang HQ, Zhai H, 2003.

Lignin and physiological function in plant

Journal of Shandong Agricultural University (Natural Science Edition), 2003(1): 124-128 (in Chinese)

Zhang CH, Huang H, Deng WQ, Li TH, 2019.

Genome-wide analysis of the Zn(II)2Cys6 zinc cluster-encoding gene family in Tolypocladium guangdongense and its light-induced expression

Genes, 10(3): 179

DOI:10.3390/genes10030179      URL     [本文引用: 3]

Bailey TL, Williams N, Misleh C, Li WW, 2006.

MEME: discovering and analyzing DNA and protein sequence motifs

Nucleic Acids Research, 34: W369-W373

[本文引用: 1]

Chang PK, Ehrlich KC, 2013.

Genome-wide analysis of the Zn(II)2Cys6 zinc cluster-encoding gene family in Aspergillus flavus

Applied Microbiology & Biotechnology, 97(10): 4289-4300

[本文引用: 2]

Chen CJ, Chen H, He YH, Xia R, 2018.

TBtools, a toolkit for biologists integrating various biological data handling tools with a user-friendly interface bioRxiv

Doi.org/10. 1101/289660

[本文引用: 2]

Cui BK, Li HJ, Ji X, Zhou JL, Song J, Si J, Yang ZL, Dai YC 2019.

Species diversity, taxonomy and phylogeny of Polyporaceae (Basidiomycota) in China

Fungal Diversity 97: 137-392

DOI:10.1007/s13225-019-00427-4      URL     [本文引用: 1]

Edgar R, Domrachev M, Lash AE, 2002.

Gene expression omnibus: NCBI gene expression and hybridization array data repository

Nucleic Acids Research, 30(1): 207-210

DOI:10.1093/nar/30.1.207      PMID:11752295      [本文引用: 1]

The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Foster HA, Cui MF, Naveenathayalan A, Unden H, Schwanbeck R, Höfken T, 2013.

The zinc cluster protein Sut 1 contributes to filamentation in Saccharomyces cerevisiae

Eukaryotic Cell, 12(2): 244-253

DOI:10.1128/EC.00214-12      PMID:23223039      [本文引用: 1]

Sut1 is a transcriptional regulator of the Zn(II)(2)Cys(6) family in the budding yeast Saccharomyces cerevisiae. The only function that has been attributed to Sut1 is sterol uptake under anaerobic conditions. Here, we show that Sut1 is also expressed in the presence of oxygen, and we identify a novel function for Sut1. SUT1 overexpression blocks filamentous growth, a response to nutrient limitation, in both haploid and diploid cells. This inhibition by Sut1 is independent of its function in sterol uptake. Sut1 downregulates the expression of GAT2, HAP4, MGA1, MSN4, NCE102, PRR2, RHO3, and RHO5. Several of these Sut1 targets (GAT2, HAP4, MGA1, RHO3, and RHO5) are essential for filamentation in haploids and/or diploids. Furthermore, the expression of the Sut1 target genes, with the exception of MGA1, is induced during filamentous growth. We also show that SUT1 expression is autoregulated and inhibited by Ste12, a key transcriptional regulator of filamentation. We propose that Sut1 partially represses the expression of GAT2, HAP4, MGA1, MSN4, NCE102, PRR2, RHO3, and RHO5 when nutrients are plentiful. Filamentation-inducing conditions relieve this repression by Sut1, and the increased expression of Sut1 targets triggers filamentous growth.

Geourjon C, Deléage G, 1995.

SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments

Bioinformatics, 11(6): 681-684

DOI:10.1093/bioinformatics/11.6.681      URL     [本文引用: 1]

Gu XL, He M, Shi YJ, Li ZZ, 2010.

Present development in the effective degradability of renewable lignin resource

Forestry Science & Technology, 35(4): 37-40 (in Chinese)

Guo AY, Zhu QH, Chen X, Luo JC, 2007.

GSDS: a gene structure display server

Hereditas, 29(8): 1023-1026

[本文引用: 1]

Grabber JH, Ralph J, Lapierre C, Barrière Y, 2004.

Genetic and molecular basis of grass cell-wall degradability.Ⅰ. Lignin-cell wall matrix interactions

Comptes Rendus Biologies, 327(5): 455-465

PMID:15255476      [本文引用: 1]

Lignification limits grass cell-wall digestion by herbivores. Lignification is spatially and temporally regulated, and lignin characteristics differ between cell walls, plant tissues, and plant parts. Grass lignins are anchored within walls by ferulate and diferulate cross-links, p-coumarate cyclodimers, and possibly benzyl ester and ether cross-links. Cell-wall degradability is regulated by lignin concentration, cross-linking, and hydrophobicity but not directly by most variations in lignin composition or structure. Genetic manipulation of lignification can improve grass cell-wall degradability, but the degree of success will depend on genetic background, plant modification techniques employed, and analytical methods used to characterize cell walls.

Horton P, Park KJ, Obayashi T, Fujita N, Harada H, Adams-Collier CJ, Nakai K, 2007.

WoLF PSORT: protein localization predictor

Nucleic Acids Research, 35: W585-W587

[本文引用: 1]

Huang CX, He J, Liang C, Tang S, Yong Q, 2019.

Progress in applications of high value-added lignin materials

Journal of Forestry Engineering, 19(1): 24-33 (in Chinese)

Huang J, Wang JF, Zhang HS, 2004.

Structure and function of plant C2H 2 zinc finger protein

Hereditas, 26(3): 414-418 (in Chinese)

Keene JD, King PH, Levine T, 1997. Methods and compositions involved in cell growth, neoplasia and immunoregulation: America, US5698427. 1997-12-16

[本文引用: 1]

Lu Y, Wei XY, Zong ZM, Lu YC, Zhao W, Cao JP, 2013.

Structural investigation and application of lignins

Progress in Chemistry, 25(5): 838-858 (in Chinese)

Macpherson S, Larochelle M, Turcotte B, 2006.

A fungal family of transcriptional regulators: the zinc cluster proteins

Microbiology and Molecular Biology Reviews, 70(3): 583-604

DOI:10.1128/MMBR.00015-06      URL     [本文引用: 4]

Miller J, Mclachlan AD, Klug A, 1985.

Repetitive zinc-binding domains in the protein transcription factor IIIA from Xenopus oocytes

The EMBO Journal, 4(6): 1609

DOI:10.1002/j.1460-2075.1985.tb03825.x      URL     [本文引用: 2]

Nieto MA, 2003.

The snail superfamily of zinc-finger transcription factors

Nature Reviews Molecular Cell Biology, 3(3): 155-166

DOI:10.1038/nrm757      URL     [本文引用: 1]

Zhang J, Chi YJ, Li SX, Zhang J, Chen J, 2019.

Expression and analysis of zinc finger family gene in Lenzites gibbosa

Journal of Forestry Research, 31: 1889-1898

DOI:10.1007/s11676-019-01044-2      URL    

Zhang L, Shao XX, Han DY, 2009.

Research progress of white-rot fungus lignin-degrading enzymes

Jilin Animal Husbandry and Veterinary Medicine, 251(30): 9-12 (in Chinese)

顾晓利, 何明, 史以俊, 李忠正, 2010.

有效降解可再生资源木质素的研究进展

林业科技, 35(4): 37-40

[本文引用: 1]

黄曹兴, 何娟, 梁辰, 唐硕, 勇强, 2019.

木质素的高附加值应用研究进展

林业工程学报, 19(1): 24-33

[本文引用: 1]

黄骥, 王建飞, 张红生, 2004.

植物C2H2型锌指蛋白的结构与功能

遗传, 26(3): 414-418

[本文引用: 1]

路瑶, 魏贤勇, 宗志敏, 陆永超, 赵炜, 曹景沛, 2013.

木质素的结构研究与应用

化学进展, 25(5): 838-858

[本文引用: 2]

吴坤, 张世敏, 朱显峰, 2000.

木质素生物降解研究进展

河南农业大学学报, 2000(4): 349-354

[本文引用: 1]

于明革, 杨洪强, 翟衡, 2003.

植物木质素及其生理学功能

山东农业大学学报(自然科学版), 2003(1): 124-128

张力, 邵喜霞, 韩大勇, 2009.

白腐真菌木质素降解酶系研究进展

吉林畜牧兽医, 251(30): 9-12

[本文引用: 2]

/