Literature DB >> 32529805

Insights into the mechanism of cyanobacteria removal by the algicidal fungi Bjerkandera adusta and Trametes versicolor.

Guomin Han1,2, Hui Ma3, Shenrong Ren1, Xueyan Gao1, Xiaolong He4, Suwen Zhu1,2, Ruining Deng1, Shihua Zhang4.   

Abstract

Fungal mycelia can eliminate almost all cocultured cyanobacterial cells within a short time. However, molecular mechanisms of algicidal fungi are poorly understood. In this study, a time-course transcriptomic analysis of algicidal fungus Bjerkandera adusta T1 was applied to investigate gene expression and regulation. A total of 132, 300, 422, and 823 differentially expressed genes (DEGs) were identified at 6, 12, 24, and 48 hr, respectively. Most DEGs exhibited high endopeptidase activity, cellulose catabolic process, and transmembrane transporter activity by using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Many decomposition genes encoding endopeptidases were induced a little later in B. adusta T1 when compared with previously investigated algicidal fungus Trametes versicolor F21a. Besides, the accumulated expression of Polysaccharide lyases8 (PL8) gene with peptidoglycan and alginate decomposition abilities was greatly delayed in B. adusta T1 relative to T. versicolor F21a. It was implied that endopeptidases and enzymes of PL8 might be responsible for the strong algicidal ability of B. adusta T1 as well as T. versicolor F21a.
© 2020 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Entities:  

Keywords:  Algicidal fungi; Algicidal mechanism; Decomposition; Endopeptidase; Polysaccharide lyases8; Transcriptomic analysis

Mesh:

Substances:

Year:  2020        PMID: 32529805      PMCID: PMC7424253          DOI: 10.1002/mbo3.1042

Source DB:  PubMed          Journal:  Microbiologyopen        ISSN: 2045-8827            Impact factor:   3.139


INTRODUCTION

The occurrence of algal blooms or cyanobacterial blooms not only leads to the asphyxiation of aquatic fauna, but also releases highly toxic compounds, including microcystins, threatening the health of human beings and other organisms (Dai et al., 2018; Sun, Sun, Zhang, Esquivel‐Elizondo, & Wu, 2018). Biological methods are known to be simple and efficient to control algal blooms, with less pollution compared with the physical and chemical methods (Hou et al., 2019; Yu et al., 2019; Zhang et al., 2018). In addition to the inhibition of cyanobacterial growth, algicidal bacteria and viruses can affect the water clarity and aquatic ecosystem (Wang et al., 2010). Recently, a new method for the removal of cyanobacteria by fungi was reported (Jia et al., 2010). Further, it has been reported that the mycelia of fungus Trichaptumabietinum 1302BG could enclose and eliminate almost all cocultivated cyanobacterial cells within a short time (Jia et al., 2010), and the color of cyanobacterial medium turned transparent (Han et al., 2011). Other fungi, such as Trametes versicolor F21a, Bjerkandera adusta T1, Lophariaspadicea, Phanerochaete chrysosporium, Trichoderma citrinoviride, and Irpexlacteus T2b have been reported to exhibit algicidal ability (Han et al., 2011; Shu et al., 2016; Wang et al., 2010; Zeng, Wang, & Wang, 2015; Zeng et al., 2019). Among these, T. versicolor F21a and B. adusta T1 were considered as the two best algicidal fungi (Dai et al., 2018; Han et al., 2011; Zeng et al., 2015, 2019). Previous studies have reported that both living and dead cyanobacterial cells first adhere to fungal mycelia before being eliminated by surrounding mycelia (Dai et al., 2018; Jia et al., 2010). It has been further demonstrated that the membranes of cyanobacterial cells and the pyrrole ring of chlorophyll a were extensively disrupted by mycelia of P. chrysosporium (Zeng et al., 2015). Transcriptomic and proteomic analyses of the algicidal mechanism of T. versicolor F21a showed that several biological processes, such as glucan 1,4‐α‐glucosidase activity, hydrolase activity, lipase activity, and endopeptidase activity, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including glycolysis/gluconeogenesis, pyruvate metabolism, starch and sucrose metabolism, and amino acids biosynthesis, are involved in the elimination cyanobacterial cells (Dai et al., 2018; Gao et al., 2017). The expression of all Carbohydrate‐Active enZYmes (CAZyme) genes significantly increased during the algicidal process in T. versicolor F21a (Dai et al., 2018; Gao et al., 2017). Several members of CAZyme, such as AA5, GH18, GH5, GH79, GH128, and PL8, might play key roles in the decomposition of cyanobacterial cells at different eliminating stages (Dai et al., 2018). Although the underlying molecular mechanism of algicidal fungus T. versicolor F21a was elucidated, there are no reports on the mechanism of other efficient algicidal fungi. B. adusta is a widely distributed “white rot” fungus, which has been often associated with the decomposition of hardwoods (Moody, Dudley, Hiscox, Boddy, & Eastwood, 2018). The components of wood cell walls, such as cellulose, hemicellulose, and recalcitrant lignin, can be degraded by this fungus (Moody et al., 2018). Besides, this fungus has been reported to decompose a wide range of environmental pollutants (Bouacem et al., 2018; Han et al., 2011; Sugawara, Igeta, Amano, Hyuga, & Sugano, 2019). In our previous study, B. adusta T1 was found to be one of the best algicidal fungi (Han et al., 2011). In this study, gene expression in the mycelia of B. adusta T1, cocultivated with and without cyanobacterial cells during the algicidal process, was compared by a time‐serial transcriptomic analysis. Differentially expressed genes (DEGs) were used to identify key decomposition gene(s) and pathway(s) in B. adusta T1, and the results were compared with that of T. versicolor F21a reported in a previous study (Dai et al., 2018).

MATERIALS AND METHODS

Fungal and algal strains

The previously isolated fungus B. adusta T1 from Zijinshan Mountain was used in this study (Han et al., 2011). Cyanobacterial strain (Microcystis aeruginosa PCC7806) was provided by the Institute of Hydrobiology of the Chinese Academy of Sciences (Wuhan, China).

Cocultivation of fungal mycelia and cyanobacterial cells

The cyanobacterial strain was cultivated at 25°C under 12‐hr light and 12‐hr dark cycles with ~90 μmol/m2 s‐1 of photons in BG‐11 medium (Jia et al., 2010). Round fungal mycelium (seven mm in diameter) was inoculated onto a nine‐cm plate, containing 15 ml of potato liquid medium, and incubated under static conditions for five days. Then, fungal mycelia were taken and transferred into 250‐mL Erlenmeyer flasks containing 100 ml of algal solution or medium. The cocultures were incubated at 25°C, 90 μmol photons/m2 s‐1, and 120 rpm to investigate differentially expressed fungal genes. Total chlorophyll a was measured according to the Standard Methods for the Examination of Water and Wastewater (Standard Methods for the Examination of Water & Wastewater, 1998).

RNA isolation and sequencing

Mycelia of B. adusta T1 were collected from cocultures after 6, 12, 24, and 48 hr of incubation. Two biological replicates of each treatment were used for RNA sequencing. Total RNA was extracted from each sample with TRIzol reagent following the manufacturer's instructions (Takara, Dalian, China). Then, crude RNA was digested via 10 U DNase I (TaKaRa, Japan) at 37°C for 30 min, and then, mRNA was isolated using Dynabeads® Oligo (dT) 25 (Life, America) following the manufacturer's instructions. One hundred ng mRNA of each sample was used to construct a sequencing library using NEBNext® UltraTM RNA Library Prep Kit (NEB, America). Paired‐end sequencing of cDNA fragments (~300 bp) was performed using Illumina HiSeq 4,000 platform at BGI‐Shenzhen, China.

Transcriptomic analysis

In this study, RNA‐Seq data of B. adusta T1 at 6, 12, 24, and 48 hr were analyzed. The quality of 150‐bp reads was assessed using the FASTQC program (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The paired‐end raw reads from RNA sequencing were trimmed using the pipeline Trimmomatic (v0.33) with parameters (LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 HEADCROP:12 MINLEN:36) (Bolger, Lohse, & Usadel, 2014). The clean reads were mapped to the B. adusta genome (v1.0) using STAR software (v2.5.3a) (Binder et al., 2013; Dobin et al., 2013). Expression value in FPKM (fragments per kilobase of exon model per million reads mapped) and DEGs were calculated via Cuffdiff (v2.2.1) using default parameters (p < .05, a fold change ≥ 2) (Si et al., 2019; Trapnell et al., 2012). Gene function was annotated using BLAST against reference protein‐encoding sequences from the Nr database of GenBank, Gene Ontology (GO), and KEGG (Ashburner et al., 2000; Kanehisa, Furumichi, Tanabe, Sato, & Morishima, 2017; Kanehisa & Goto, 2000; Kanehisa, Sato, Kawashima, Furumichi, & Tanabe, 2016). Fisher's exact test was used to obtain enriched functional terms at p < .05.

CAZyme and Secretome Annotation

All putative protein sequences of B. adusta were annotated with hmmscan against dbCAN database (Cantarel et al., 2009; Johnson, Eddy, & Portugaly, 2010; Yin et al., 2012) and further classified according to mycoCLAP database (Strasser et al., 2015). Signal information of the proteins was predicted by Target P 1.1 Server (Emanuelsson, Brunak, von Heijne, & Nielsen, 2007).

Quantitative PCR (qPCR) validation

qPCR was used to validate the gene expression calculated from RNA‐Seq data. A few randomly selected lignocellulose‐active enzyme genes were used in this study, and the β‐actin gene of B. adusta T1 was used as the endogenous control. The 20 μl reaction mixture consisted of 10 μl SYBR® Fast qPCR Mix (2x), 0.5 μl of each primer (10 μmolL−1), and 120–150 ng cDNA (Table A1). The qRT‐PCR program was set as follows: 95°C for 10 min, followed by 40 cycles of 95°C for 15 s, 60°C for 20 s, and 72°C for 30 s. Relative expression levels were calculated using 2−ΔΔCT method (Livak & Schmittgen, 2001). Three biological replicates were used for qRT‐PCR.
TABLE A1

Primers used in this study

Protein IDAnnotationPrimer
jgi|Bjead1_1|459664|MIX10988_17319_14Radical oxidaseGTCGAAGCGGGTGGTCTTAA
CCTCTCCTCGTTGCCGTTT
jgi|Bjead1_1|34143|fgenesh1_kg.1_#_945_#_Locus732v1_medCvg1115.6sEsterase family 1 proteinCCTCCCTGCAAACATCTCACA
GGAGACGTGTCGGGAAAGAG
jgi|Bjead1_1|172436|gm1.8875_gHydrolase family 5 proteinTACGAGGGCGACGATTGG
CTCACCGGACACGTAAACCA
jgi|Bjead1_1|35099|fgenesh1_kg.2_#_711_#_Locus118v3_medCvg9284.2sHydrolase family 5 proteinCTCGTTGACCCGCACAACTT
GGGAATATCGTGAGGCTCGTT
jgi|Bjead1_1|355947|CE167616_517Hydrolase family 128 proteinAGCGCGGTGTGTCATACAAC
TGTGTCCGGCATCGGTATT
jgi|Bjead1_1|38229|fgenesh1_kg.7_#_551_#_Locus8080v1_medCvg1578.8sHydrolase family 13 proteinCACGCCCGACTATTCGAAGT
GTCGGGTTTTCCGTGTCAAG

RESULTS

Elimination rate during the algicidal process

The algicidal process of B. adusta T1 was monitored via spectrophotometer. As shown in Figure 1, the chlorophyll a content gradually decreased with the increase in incubation time. Approximately 86% of cyanobacterial cells were eliminated within 48 hr. The cyanobacterial cells were almost disappeared in the flask cocultivated with living fungal mycelia while the cyanobacterial cells were almost not affected by dead fungal mycelia compared with the blank control (Figure 1).
FIGURE 1

Changes in the algicidal process of B. adusta T1. Note: (a) Images of cocultivation after 48 hr; CK, the cyanobacterial cells as control;T1, the cocultivation of cyanobacterial cells and B. adusta T1 mycelia; S‐T1, the cocultivation of cyanobacterial cells and died fungal mycelia. (b) Changes in chlorophyll a content during the algicidal process

Changes in the algicidal process of B. adusta T1. Note: (a) Images of cocultivation after 48 hr; CK, the cyanobacterial cells as control;T1, the cocultivation of cyanobacterial cells and B. adusta T1 mycelia; S‐T1, the cocultivation of cyanobacterial cells and died fungal mycelia. (b) Changes in chlorophyll a content during the algicidal process

RNA‐Seq data generation and mapping

Mycelia of B. adusta T1 that was cocultivated with cyanobacterial cells at 6, 12, 24, and 48 hr were used for RNA sequencing. Fungal mycelia without cyanobacterial cells at the same time point were used as a control. Good quality RNA was isolated and used for RNA sequencing (Figure A1). A total of 63,437,015 pairs of raw reads (SRA accession: PRJNA543936) were generated (Table A2). Approximately 96% of reads were retained after the removal of adaptor and low‐quality bases (Table A2). More than 64% of reads were uniquely mapped to the reference genome by pipeline STAR (Table A2), suggesting that the results of mapping can be used for the identification of fungal DEGs.
TABLE A2

Statistics of RNA‐Seq reads mapping results

SampleRaw readsNumber of input readsCleaned lengthUniquely mapped reads numberUniquely mapped reads (%)
6h_ck13,713,9103,531,468129.692,491,98170.57
6h_ck23,618,2913,416,852129.0552,205,29064.54
6h_T13,644,3903,577,152128.7452,802,46678.34
6h_T24,379,8584,280,639128.8353,282,56976.68
12h_ck13,832,6203,691,873129.5052,706,11173.30
12h_ck23,806,8013,651,869129.092,603,46171.29
12h_T13,493,7773,325,461125.8652,458,20173.92
12h_T24,020,5713,899,676128.92,967,51676.10
24h_ck13,609,6353,388,118128.8752,326,95568.68
24h_ck23,684,9733,497,767129.6552,466,21270.51
24h_T14,831,6274,684,474128.623,554,34275.87
24h_T24,567,2954,436,833128.93,395,50876.53
48h_ck13,638,7763,456,573129.2552,500,09572.33
48h_ck23,594,5923,405,731128.512,473,90972.64
48h_T14,499,7184,347,471128.2753,264,95775.10
48h_T24,500,1814,353,762128.583,277,08475.27

The number of reads were expressed in pairs.

Identification of fungal DEGs involved in the algicidal process

Boxplot of FPKM values across all samples showed the consistency of biological replicates of each treatment (Figure A2). Multi‐dimensional scaling (MDS) showed that the gene expression in mycelia cocultured with cyanobacterial cells was distinctly separated from that of mycelia without cyanobacterial cells (Figure 2). The difference became highly apparent with the increase in cocultivation time (Figure 2). A total of 132, 300, 422, and 823 fungal DEGs were identified at 6, 12, 24, and 48 hr in the mycelia cocultivated with cyanobacterial cells compared with the control, respectively (Figure 3). The expression of six randomly selected lignocellulose‐active enzyme genes, that is, a gene of esterase family, two genes of hydrolase family, a gene of hydrolase family 5, a radical oxidase encoding gene, a gene of hydrolase family 128, and a gene of hydrolase family 13, were further investigated via qRT‐PCR (Table A1). Similar expression patterns were observed between qRT‐PCR and transcriptomic analysis (Figure A3), indicating that DEGs identified by the transcriptomic analysis were suitable for further analyses.
FIGURE 2

Multi‐dimensional scaling of gene expression data. Note: 6h_ck, control sample at 6h; 6h_T, treatment sample at 6 hr; 12h_ck, control sample at 12 hr; 12h_T, treatment sample at 12 hr; 24h_ck, control sample at 24 hr; 24h_T, treatment sample at 24 hr; 48h_ck, control sample at 48 hr; 48h_T, treatment sample at 48 hr

FIGURE 3

Number of fungal DEGs during the algicidal process of B. adusta T1

Multi‐dimensional scaling of gene expression data. Note: 6h_ck, control sample at 6h; 6h_T, treatment sample at 6 hr; 12h_ck, control sample at 12 hr; 12h_T, treatment sample at 12 hr; 24h_ck, control sample at 24 hr; 24h_T, treatment sample at 24 hr; 48h_ck, control sample at 48 hr; 48h_T, treatment sample at 48 hr Number of fungal DEGs during the algicidal process of B. adusta T1

Annotation and enrichment analyses of fungal DEGs

After the comparison of candidate genes with Nr from NCBI, GO, and KEGG databases, DEGs were used to obtain enriched terms by Fisher's exact test (p < .05). The GO terms of DEGs were enriched in the extracellular region, cell wall, signal recognition particle, proteasome core complex, prefold in complex, ribosome, and other cellular components categories (Figure 4). Similarly, DEGs were found to be enriched on transport and catabolic processes in the biological process category, particularly cellulose catabolism and carbohydrate transport (Figure 5). Further, DEGs were enriched on decomposition and transporter activities in the molecular function category that included the activities of triglyceride lipase, serine‐type peptidase, manganese peroxidase, carboxypeptidase, cellulose 1,4‐β‐cellobiosidase, β‐glucosidase, aspartic‐type endopeptidase, α‐amylase, glycolipid transporter, amino acid transmembrane transporter, and other (Figure 6). The KEGG analysis showed that DEGs were enriched on glycerolipid metabolism, starch and sucrose metabolism, metabolism of xenobiotics by cytochrome P450, galactose metabolism, and ascorbate and aldarate metabolism in different stages of the algicidal process (Figure 7).
FIGURE 4

GO term enrichment of fungal DEGs in the cellular component category

FIGURE 5

GO term enrichments of fungal DEGs in the biological process category

FIGURE 6

GO term enrichments of fungal DEGs in the molecular function category

FIGURE 7

KEGG term enrichments of fungal DEGs during the algicidal process

GO term enrichment of fungal DEGs in the cellular component category GO term enrichments of fungal DEGs in the biological process category GO term enrichments of fungal DEGs in the molecular function category KEGG term enrichments of fungal DEGs during the algicidal process

Composition and expression of CAZyme genes of B. adusta T1 and its comparison with that of T. versicolor F21a

A total of401 CAZyme genes were identified in the genome of B. adusta by hmmscan against the dbCAN database (Table 1). The lignocellulose‐active genes can be divided into 77 CAZyme modules (Table 1). Most of the genes belonged to Glycoside Hydrolases (GH) family and Auxiliary Activities (AA) family. About 312 CAZyme genes were identified in the genome of T. versicolor F21a (Dai et al., 2018). The number of CAZyme genes in B. adusta T1 genome (401 CAZyme genes) was higher than that of T. versicolor F21a (312 CAZyme genes). Seventy CAZyme modules were detected in B. adusta T1, compared to 43 CAZyme modules in T. versicolor F21a in the previous study (Dai et al., 2018). However, the algicidal effects of T. versicolor F21a were slightly more efficient than that of B. adusta T1 (Han et al., 2011).
TABLE 1

The number of decomposition enzymes detected by RNA‐Seq

Enzyme classesCAZyme moduleNo. of decomposition enzymes in the genomeNo. of decomposition enzymes detected by RNA‐SeqNo. of decomposition enzymes in DEGs by RNA‐Seq
Auxiliary activitiesAA111 
AA2211910
AA3383012
AA41  
AA5786
AA6543
AA71063
AA822 
AA927207
Carbohydrate esterasesCE118113
CE1042316
CE1232 
CE1411 
CE1522 
CE161463
CE211 
CE311 
CE4533
CE8221
CE91  
GH1221
Glycoside hydrolasesGH10454
GH105331
GH109885
GH115221
GH1221 
GH12511 
GH12711 
GH128532
GH13996
GH1313  
GH1522 
GH1619175
GH1711 
GH1813103
GH2322
GH2042 
GH231  
GH2411 
GH2511 
GH27331
GH2864 
GH3884
GH30111
GH31453
GH3544 
GH37211
GH381  
GH43664
GH4763 
GH520168
GH51221
GH5311 
GH55331
GH6111
GH6321 
GH7541
GH71331
GH7211 
GH7433 
GH7621 
GH7822 
GH79796
GH8511 
GH8811 
GH8911 
GH911 
GH92331
GH9511 
GH991  
Polysaccharide lyasesPL111 
PL1211 
PL14565
PL322 
PL41  
PL5122
PL811 
 Total401324128
The number of decomposition enzymes detected by RNA‐Seq The identified 128 differentially expressed CAZyme genes in B. adusta T1 were found to belong to 37 modules (Table 1). The genes within the same module exhibited diverse expression profiles during the algicidal process of B. adusta T1 (Figure 8). It was observed that module GH128, AA7, AA6, and GH109 had the highest accumulated expression during the algicidal process. The sublocation analysis showed that ~ 61% (245/401) of lignocellulose‐active proteins contained secretory pathway signal peptides that can be secreted outside of fungal mycelia (Table A3). Genes within GH128 that encoded endo‐1,3‐β‐glucanase (EC3.2.1.39) could decompose xyloglucans and β‐1,3‐glucans into xylose and glucose, respectively. The enzymes of GH128, AA7, AA6, and GH109 were less efficient in cyanobacterial cell disruption. It is noteworthy that the accumulated expression of Polysaccharide lyases genes, particularly the PL8 module was highly up‐regulated during the later stage of the algicidal process of B. adusta T1, which was much delayed when compared to T. versicolor F21a (Dai et al., 2018).
FIGURE 8

Total expression levels of each CAZyme module during the algicidal process

TABLE A3

Sublocation of CAZyme proteins of B. adusta

Protein IDLenmTPSPOtherLocRC
399481,0410.0950.0930.844_2
1702036460.0830.1050.872_2
2294833190.0490.9170.053S1
1133592950.0450.950.032S1
400213200.0810.9080.028S1
400404650.0530.9420.029S1
2302531,0240.0140.9660.07S1
2303541,0050.3420.7050.024S4
1832393850.6710.0270.355M4
625853050.1470.1040.761_2
1139616040.5340.0550.439M5
4528493100.0770.0370.944_1
1704553220.0910.0680.894_1
2373783160.0420.9490.058S1
404612440.0540.9540.043S1
1835096120.5580.0240.588_5
2401223010.0920.8730.031S2
406155870.0370.1590.919_2
2419756050.0680.0730.901_1
528115370.0630.9130.03S1
407433770.1030.8920.017S2
1709297040.0880.0480.937_1
1709345510.0630.8970.086S1
2442006740.0270.930.065S1
2442466690.0180.9710.054S1
629864990.0580.9060.041S1
714316170.4910.6580.014S5
2450496040.4420.6550.01S4
408126110.0870.0440.906_1
2452975980.0610.810.11S2
1710026060.1960.680.028S3
845033730.1010.050.922_1
1710595930.140.8720.019S2
1560545960.0440.8870.074S1
1149545740.0840.1150.897_2
408866140.0790.0520.904_1
1366316140.1230.0450.86_2
1149025930.4230.5560.029S5
529836130.0520.0440.95_1
529915970.0440.9140.052S1
1838965990.0140.930.089S1
530871,0110.0360.9690.05S1
411086960.1590.0810.841_2
411135730.0930.2070.634_3
1713684780.0690.0790.9_1
412413960.2740.840.018S3
4547034020.630.0210.452M5
412513370.0750.7360.21S3
413053710.110.0940.754_2
413065380.0940.0990.816_2
2565094230.4680.8910.004S3
1842246000.1030.1010.838_2
414903030.0520.1470.93_2
2608931990.0860.0890.914_1
1843945820.8030.0530.115M2
1571497680.0290.9560.036S1
415962660.0690.9290.046S1
1717697740.0210.960.057S1
2618598080.0850.060.922_1
1161112810.0690.1430.873_2
2632364000.0540.9580.066S1
297584000.0430.9950.011S1
2632523980.0530.980.022S1
416864270.3070.3690.337S5
417086490.180.8620.014S2
417546470.0530.1820.858_2
417634040.0940.7680.13S2
536826930.2550.7590.029S3
418545170.0210.9680.058S1
418634910.110.9130.016S1
418693360.2220.9080.016S2
418964470.7130.0250.412M4
1382037740.050.1270.857_2
1846973720.0850.8740.045S2
1168163620.0780.8630.061S2
1721023770.0680.8870.051S1
419613290.0440.920.064S1
4560423280.0380.9420.045S1
2689703860.0250.9530.056S1
299572830.0190.9580.067S1
1169452030.1430.0620.889_2
1577714010.0370.9440.045S1
1577753040.0390.9330.056S1
638383430.0150.9740.051S1
419823730.1560.8070.026S2
1721523620.0460.9270.051S1
2694813670.1240.7870.049S2
2695243730.130.8230.028S2
419976180.090.9580.02S1
1722463720.1170.8540.028S2
1579243740.1550.8570.027S2
1171493960.0130.4960.863_4
1849353090.0340.9440.061S1
1387044750.0960.0710.887_2
1724364860.0830.0490.928_1
422913470.0560.9380.021S1
813411410.0590.2740.852_3
1583344140.2370.0540.674_3
424344210.050.9140.051S1
541723630.0170.9770.039S1
1851794520.090.8050.059S2
1176662590.0560.9130.05S1
425343270.0840.8830.031S2
425392700.190.0440.855_2
2961518480.1780.1120.76_3
1853113970.0370.7060.59S5
426175040.0240.2390.872_2
426319750.1410.860.023S2
1177723300.4540.0180.718_4
543993130.0270.9480.043S1
1729253480.0680.9790.031S1
1729263550.0310.9680.045S1
1588173380.0370.9360.087S1
1588421,1020.1310.0590.88_2
1854852870.0990.1490.826_2
1183196480.1180.8320.057S2
1395643870.9470.0410.047M1
428892850.0550.1920.895_2
3025523440.1910.0440.811_2
3052922530.0840.8890.033S1
430953660.1290.8160.031S2
3064043660.1130.8490.032S2
431143480.0990.8180.057S2
3068633660.0410.9010.056S1
1187183630.0520.8840.049S1
1190373140.050.910.069S1
433293640.1430.8430.03S2
1734953640.3370.7820.013S3
3118504370.0820.9040.031S1
548934160.1490.8350.047S2
1859215680.190.8470.046S2
4596647770.0520.7770.257S3
434463860.0990.8820.061S2
3136828590.0470.950.031S1
1736732600.0150.9680.041S1
1193503990.0330.9410.062S1
1195225750.9050.0420.13M2
1195931,0000.120.8640.027S2
438121,0340.0270.8340.427S3
438926150.0190.9710.047S1
3232803690.2390.7630.019S3
439292580.0260.9650.084S1
1863443200.1220.8490.039S2
1200023620.080.870.048S2
553342490.0340.9070.075S1
439667420.0240.9460.05S1
3244208190.0320.9340.049S1
1863884340.1360.8790.039S2
440474950.0250.9660.045S1
440725570.4120.5950.018S5
3266594700.380.6170.062S4
1412904600.0620.1470.889_2
1203992980.1170.3620.535_5
3448676630.0920.9270.021S1
1415396630.1010.9040.022S1
3459148040.2940.8420.009S3
443705710.2360.7770.041S3
443765320.0370.9640.029S1
443913850.0220.9640.048S1
1416484660.3690.6860.046S4
556964660.590.6890.03S5
4626287300.2230.0870.657_3
1209681,0200.0180.9660.057S1
1613634520.0520.9120.047S1
1747345310.0540.8570.206S2
1615003260.050.9270.032S1
3534902840.8070.0440.166M2
3534892540.4220.0510.632_4
448031,1340.1050.0280.928_1
3559472640.0210.9460.08S1
738112870.4890.7450.016S4
1216643690.0790.8740.033S2
319363320.2110.7830.03S3
738693570.1230.120.842_2
4637449310.0290.9720.025S1
450299580.0160.9690.057S1
1872706150.0440.9570.029S1
562259600.1660.2020.582_4
320514060.1860.0730.732_3
3613677130.080.0630.949_1
739724810.1590.6980.092S3
1752835210.2080.9450.004S2
451357780.1660.8950.011S2
1219365370.0430.9180.053S1
451535880.0430.8450.111S2
1221055000.0970.1280.838_2
563072080.3230.1150.412_5
452813400.3410.590.036S4
453146010.0820.120.844_2
4657116110.0710.2790.729_3
1755137000.0520.3670.644_4
1430006040.1010.1280.746_2
564494030.040.960.034S1
1755363790.1270.8720.031S2
741645870.1440.1450.649_3
1625055870.0810.1650.796_2
564997980.3680.8080.011S3
565253300.4490.6530.023S4
455168500.0670.8910.081S1
1626022150.090.0860.866_2
3846586980.1420.8790.033S2
455701,4680.0180.9650.042S1
1877286050.1160.1570.718_3
456474040.10.6920.179S3
663776260.1580.640.062S3
664008900.1440.0230.921_2
1229373610.080.9190.03S1
664932040.0460.3040.687_4
1435853740.0450.0940.947_1
1233236500.1140.2950.801_3
459053130.1270.9250.028S2
4035543390.2620.0750.74_3
568593200.0810.8630.059S2
1764204580.0190.9720.037S1
462608470.0350.1890.908_2
1882418620.0380.1610.94_2
332158010.0670.7770.182S3
1012675130.0220.9460.089S1
332634490.0210.90.099S1
1029853380.0670.9740.027S1
4488995400.4130.0420.616_4
1774507480.0430.9390.031S1
1963305440.050.9610.019S1
336367170.1680.1750.701_3
1253622390.3580.0420.545_5
1009353960.0910.3520.583_4
1641808360.3030.8450.012S3
1024797500.2430.060.721_3
1995633880.6780.270.052M3
1453175570.0440.7990.201S3
95645990.090.1930.743_3
339063120.190.0870.732_3
2019586070.8260.0180.328M3
339595940.7080.0320.35M4
339633400.0250.9210.133S2
2032964220.120.9230.024S1
341432920.0610.0790.934_1
474023900.0280.9420.071S1
1645506820.5060.4340.072M5
1263637850.2260.140.716_3
341755060.9370.0260.099M1
1264404190.0580.1370.91_2
2073385230.0420.9260.053S1
342264790.0710.0860.922_1
2078902080.0420.9260.053S1
247539920.2570.0360.723_3
1012423660.1650.0490.851_2
2094262550.0730.2260.761_3
475583670.0350.9160.062S1
1647403370.0480.7980.118S2
476477440.0340.9460.075S1
1038824130.1530.0520.854_2
249407810.1040.0770.907_1
345774740.2230.030.844_2
249503740.0490.9780.015S1
2753306500.4650.6290.023S5
346226070.1470.120.719_3
346515260.1270.0390.875_2
347056530.0610.0670.905_1
1651475770.0630.0860.896_1
348053910.9140.0350.118M2
2808565450.2040.0730.755_3
1046755050.0970.8690.039S2
2827064660.0890.9520.038S1
349454660.2610.7220.022S3
350993970.0340.9570.044S1
351236030.730.0550.209M3
352553350.090.8690.039S2
1281742790.1240.950.01S1
3313562510.0660.790.195S3
353272330.0370.8870.112S2
353302350.040.8810.096S2
1049834350.3650.0840.512_5
1658792800.0630.0950.909_1
1659935460.0720.7070.106S2
3385806780.0480.9470.019S1
357115280.0890.1770.79_2
1051453620.3610.720.031S4
487235460.070.9640.021S1
357425160.0530.4570.796_4
3400633770.1930.1760.709_3
1054693460.2040.0510.772_3
1057232030.1240.0970.841_2
487654610.5820.0760.307M4
1055604320.0530.9040.049S1
684085640.030.9560.04S1
257723210.0250.9660.043S1
1069984040.0520.1720.887_2
358763250.0460.9210.085S1
358804880.0540.1820.909_2
1060463210.1030.9370.018S1
1063512750.1180.0590.875_2
593608630.0790.830.127S2
258433210.3030.8820.013S3
1662333230.1810.8570.033S2
359053250.0610.9370.04S1
1291503250.1670.9090.032S2
3649633400.0550.8990.036S1
3654478260.0770.8930.039S1
3658225090.0360.9210.071S1
1062305420.3450.0680.679_4
4647183270.10.8560.041S2
490964740.0510.9610.044S1
1296553890.2740.1870.411_5
492057790.0280.9540.046S1
1666293010.3510.1340.447_5
1800532920.40.10.395M5
1070811,0180.0210.9620.059S1
1068593960.040.4840.631_5
3876731920.1270.1150.864_2
1072292190.140.060.876_2
1071885030.0530.8680.154S2
1084478820.0210.9470.069S1
365728670.0820.0870.879_2
3892565830.0570.9580.017S1
494732380.0190.9640.071S1
1802797010.4330.7470.012S4
1077027420.1890.0420.841_2
1501512570.4130.0590.588_5
497483860.0150.9060.209S2
1503995880.1230.8170.031S2
369854530.0510.2940.694_4
369945890.0450.9170.036S1
1309485900.0380.9420.053S1
369965880.0660.9250.036S1
370052030.0440.2610.726_3
370237530.0680.4770.496_5
3968254100.0220.9660.049S1
370516810.0560.1010.905_1
1673397230.0810.0470.918_1
1080318400.0390.2980.854_3
603065100.960.0180.089M1
949001990.3490.0540.575_4
1507879290.1740.4910.328S5
1086312540.70.0290.417M4
1510045870.0560.6450.36S4
4089881,1190.130.8870.023S2
374674670.030.9840.031S1
1317603700.030.7050.316S4
4128785100.0490.8880.057S1
1092223370.0860.9290.02S1
4208412960.430.1090.29M5
1679842730.2560.0650.614_4
378323140.2940.7360.057S3
1812554020.0210.960.068S1
378824580.0340.9450.064S1
1681227720.030.9490.05S1
1324355970.1380.3640.28S5
4249414460.0250.9650.038S1
697482,3500.1140.9070.026S2
381695650.0210.9580.058S1
381897960.1150.1470.695_3
1097575660.9080.0330.094M1
382088060.0570.9660.015S1
508238920.0530.0660.95_1
382295280.1230.9230.014S2
699313750.0440.990.027S1
612324000.2650.2560.365_5
383975580.0190.9470.08S1
1331715630.1940.780.019S3
384062530.170.8630.026S2
384072530.120.8220.058S2
1107583220.1720.3830.274S5
1527283840.0620.7980.143S2
1109787400.2790.1410.526_4
1686565470.0410.970.032S1
1111625280.0410.3160.851_3
4349435230.1460.9210.011S2
613663440.0680.9510.018S1
385625790.0480.9610.032S1
614375600.0530.9510.021S1
1111961500.1180.1180.85_2
386327520.110.7140.134S3
386735890.0450.90.09S1
387968900.0510.8890.068S1
1117614080.0650.9590.023S1
4418003390.3620.2120.32M5
1690267140.0620.9870.015S1
1533313070.0410.530.552_5
1533508690.2930.0630.66_4
1119544630.020.9810.054S1
617582540.030.3370.811_3
515142570.0430.2880.734_3
1113485340.030.9780.038S1
1692835310.0710.9440.017S1
391204600.0390.1390.91_2
1537984670.0610.1580.896_2
1823934680.0380.1330.935_1
1123045450.1540.1130.64_3
392906050.0790.1290.844_2
2146185030.0810.0560.926_1
392962690.0610.9150.031S1
393758900.0550.8650.069S2
518425880.1120.1220.793_2
518884750.3140.6630.039S4
1827055110.0530.8830.083S1
2198173690.3170.3280.142S5
2198433360.450.8660.004S3
1828726680.0340.9560.057S1
398164710.0210.960.064S1
2277346170.1180.0490.865_2

Abbreviation: cTP, chloroplast transit peptide; Len, Sequence length; Loc, prediction of localization; M, Mitochondrion; RC, Reliability class; S, secretory pathway; SP, signal peptide.

Total expression levels of each CAZyme module during the algicidal process

Expression of other decomposition genes in B. adusta T1 and their comparison with that of T. versicolor F21a

Only a few serine‐type peptidase, carboxypeptidase, and aspartic‐type endopeptidase, with strong ability in cyanobacterial cells disruption, were enriched in the DEGs list during the early stage of the algicidal process (6 hr) (Figure 6). However, no strong decomposition enzyme was enriched during the later stage of the algicidal process until 24 hr (Figure 6). During the later stage (24 hr), proteins with aspartic‐type endopeptidase activity and manganese peroxidase activity were the main decomposition enzymes (Figure 6). Various types of decomposition enzymes, such as threonine‐type endopeptidase and serine‐type endopeptidase, were induced after 48 hr of cocultivation. In this study, proteases with Protein ID jgi|Bjead1_1|36244|fgenesh1_kg.4_#_443_#_Locus8459v1_medCvg1568.9s and jgi|Bjead1_1|342083|CE153752_10262, and jgi|Bjead1_1|110676|e_gw1.8.836.1 were observed to be the main degradation genes that might be involved in cyanobacterial cells disruption (Figure 9). Thus, these proteases can play significant roles in the algicidal process. The decomposition genes showed delayed expression compared with that of T. versicolor F21a.
FIGURE 9

Time‐course change of protease genes expression level of T1 cocultivation with cyanobacteria. Note: 6h_ck, control sample at 6h; 6h_T, treatment sample at 6 hr; 12h_ck, control sample at 12 hr; 12h_T, treatment sample at 12 hr; 24h_ck, control sample at 24 hr; 24h_T, treatment sample at 24 hr; 48h_ck, control sample at 48 hr; 48h_T, treatment sample at 48 hr

Time‐course change of protease genes expression level of T1 cocultivation with cyanobacteria. Note: 6h_ck, control sample at 6h; 6h_T, treatment sample at 6 hr; 12h_ck, control sample at 12 hr; 12h_T, treatment sample at 12 hr; 24h_ck, control sample at 24 hr; 24h_T, treatment sample at 24 hr; 48h_ck, control sample at 48 hr; 48h_T, treatment sample at 48 hr

DISCUSSION

Although several fungi showed a strong algicidal activity (Han et al., 2011), the underlying molecular mechanisms for algicidal capacities are largely less investigated. Interestingly, a few fungi from the Polyporales order of Basidiomycota exhibited a strong algicidal activity (Han et al., 2011). Comparative genome analyses found that the genomes of white rot fungi contain more genes encoding plant cell wall degrading enzymes than that of brown rot and mycorrhizal fungi (Kohler et al., 2015; Tisserant et al., 2013). White rot fungi including the order Polyporales can degrade lignin as well as cellulose (Kohler et al., 2015). In the present study, we observed that the number of CAZyme genes and expressed CAZyme genes of B. adusta T1 was great than that of T. versicolor F21a. However, the algicidal effects of B. adusta T1 were slightly less efficient than that of T. versicolor F21a (Han et al., 2011). More genome sequences of fungi with diverse algicidal abilities are available now, and we also compared the number of CAZyme genes in the genome of different algicidal fungi. No direct correlation was found between algicidal efficiency and several CAZyme genes (Data not shown). A similar result was observed in the study of Pilgaard et al., 2019. This suggested that the high efficiencies of algicidal fungi are not attributed to the number of genes encoding CAZyme in the fungal genome. High lignocellulose degradation ability of white rot fungi, in comparison with that of brown rot fungi and mycorrhizal fungi, can be attributed to the number of genes encoding plant cell wall degrading enzymes in fungal genomes as a result of long term natural selection (Kohler et al., 2015). The numbers of CAZyme genes were not directly correlated with algicidal abilities, which might be due to the fact that most algicidal fungi were isolated from terrestrial environments and lacked evolution selection pressure in the water system (Han et al., 2011). Direct contact between fungal mycelia and cyanobacterial cells was required for eliminating cyanobacterial cells by fungi (Han et al., 2011; Jia et al., 2010). Previous studies showed that a few decomposition enzymes might play important roles in eliminating cyanobacterial cells by T. versicolor F21a. In particular, cellulase, β‐glucanase, and protease were supposed to efficiently disrupt cyanobacterial cells by T. versicolor F21a (Dai et al., 2018; Gao et al., 2017). In the present study, a large number of decomposition enzymes belonging to 37 modules were observed during the algicidal process of B. adusta T1. Among them, GH128, AA7, AA6, and GH109 were the highest accumulated expression module. However, the enzymes of GH128, AA7, AA6, and GH109 were not able to efficiently disrupt the macromolecules (Ekstrom, Taujale, McGinn, & Yin, 2014; Yin et al., 2012), such as cellulose in the cell wall of cyanobacterial cells. This suggested that lignocellulose‐active proteins of B. adusta T1 might not be the key enzymes for the breakdown of cyanobacterial cells. Previous studies showed that chondroitin ABC lyase (EC4.2.2.1) of PL8 and alginate lyase (EC4.2.2.3) of PL14 were able to decompose peptidoglycan and alginate (Lombard, Golaconda Ramulu, Drula, Coutinho, & Henrissat, 2014), and the expression level was also significantly up‐regulated during the algicidal process of T. versicolor F21a (Dai et al., 2018; Gao et al., 2017). Chondroitin AC lyase (chondroitin sulfate) and alginate lyase were unique to a known saprophytic marine fungus Paradendryphiella salina in the breakdown of dried brown algae in the medium compared with its terrestrial counterparts (Pilgaard et al., 2019). Recombinant expression of Chondroitin AC lyase of the marine fungus P.salina reveals that alginate lyase can degrade several types of brown algae polysaccharides (Pilgaard et al., 2019). A putative PL8 of P.salina with a similar sequence should also decompose brown macroalgae (Pilgaard et al., 2019). Proteomic analysis of the secretome of P. salina grown on three species of brown algae and under carbon limitation implied that the basic CAZyme repertoire of saprobic fungi belongs to ascomycetes, with the addition of PL7 alginate lyases, provide P. salina with sufficient enzymatic capabilities to degrade several types of brown algae polysaccharides (Pilgaard et al., 2019). In the present study, the total expression level of PL14 was down‐regulated during the algicidal process of B. adusta T1, while no gene, belonging to PL7, was detected in the genome of B. adusta. The accumulated expression level of PL8 was highly up‐regulated in the later stage of the algicidal process of B. adusta T1, which was much delayed when compared with T. versicolor F21a (Dai et al., 2018). All the evidence indicated that enzymes of PL8 with strong peptidoglycan and alginate decomposition abilities might be a vital genetic factor for the determination of the algicidal ability of T. versicolor F21a as well as B. adusta T1. Analysis of the enriched GO terms and KEGG pathways showed that several types of peptidases were enriched during the algicidal process of B. adusta T1. In particular, proteases (protein ID jgi|Bjead1_1|36244|fgenesh1_kg.4_#_443_#_Locus8459v1_medCvg1568.9s, jgi|Bjead1_1|342083|CE153752_10262, and jgi|Bjead1_1|110676|e_gw1.8.836.1) were highly up‐regulated during the later stages of cocultivation. Proteomic analysis of P. salina also implied that the PL7 and PL8 enzymes, abundantly secreted together with enzymes of P.salina, were necessary for degradation of laminarin, cellulose, lipids, and peptides of brown algae (Pilgaard et al., 2019). Different types of peptides were detected in P. salina grown on three species of brown algae (Pilgaard et al., 2019). Additionally, several fungal proteins belonging to peptidase were also up‐regulated during the algicidal process of T. versicolor F21a (Gao et al., 2017). Besides, four homologous decomposition enzymes of other species with endo‐glycosidase and endopeptidase activities were selected to investigate their effects on cyanobacterial cells, and one type of protease was found to effectively disrupt cyanobacterial cells (Dai et al., 2018). Comparison of the gene expression during the algicidal process of B. adusta T1 and T. versicolor F21a demonstrated that majority of decomposition genes with endopeptidase and endo‐glycosidase activities in B. adusta T1 were expressed in the later stage of cocultivation, while the similar genes in T. versicolor F21a were induced in the early stage (Dai et al., 2018). Thus, protease together with enzymes of PL8 might play a key role in the elimination of cyanobacterial cells both by B. adusta T1 and T. versicolor F21a. The expression of enzymes of PL8 and peptidases in B. adusta T1 was little delayed compared with that of T. versicolor F21a, which should be the reason why the algicidal efficiency of T. versicolor F21a is better than that of B. adusta T1. The production of microcystins (MC) by cyanobacterial blooms often severely threatens human and ecosystems health (Li, Li, & Li, 2017). Biodegradation is an efficient and sustainable biological strategy for MC removal (Li et al., 2017). A large number of bacteria and several fungi were reported with MC removal or degrading capabilities (Dziga, Wasylewski, Wladyka, Nybom, & Meriluoto, 2013; Jia, Du, Song, Zhao, & Tian, 2012; Li et al., 2017; Mohamed, Hashem, & Alamri, 2014; Qin et al., 2019). Four mlr genes (i.e., mlrC, A, D, and B) located sequentially in a gene cluster in the genome of Sphingomonas sp. ACM‐3962 strain were identified for MC biodegradation (Bourne et al., 1996; Bourne, Riddles, Jones, Smith, & Blakeley, 2001). The enzymatic pathway involves at least three intracellular enzymes and two intermediate products (Li et al., 2017). Heterologous expression of the mlrA gene originated from Novosphingobium sp. THN1 showed that the recombinant MlrA hydrolyzed microcystin‐RR into a linear intermediate product by cleaving the peptide bond between Adda and arginine residue, which is also the first step involved in MC degradation pathway (Wang et al., 2017). Site‐directed mutants of MlrA suggested that MlrA is likely not a metalloprotease but a glutamate protease belonging to type II CAAX prenyl endopeptidases (Xu et al., 2019). A few fungi, for example, T. abietinum 1302BG, T.citrinoviride, and Mucor hiemalis were reported with MC removal or degrading capability (Esterhuizen‐Londt, Hertel, & Pflugmacher, 2017; Jia et al., 2012; Mohamed et al., 2014; Stephan, 2015); however, the enzymatic pathway was poorly understood compared with that of bacteria. In our study, many genes with endopeptidase activities were enriched during the algicidal process, and a gene encoding aflatoxin‐detoxifizyme with peptidase activity (Protein ID: jgi|Bjead1_1|37717|fgenesh1_kg.7_#_39_#_Locus4370v1_medCvg2101.1s) was up‐regulated during the algicidal process of B. adusta T1. Further mining the gene expression during the algicidal process of T. versicolor F21a identified a homolog gene (Protein ID: jgi|Trave1|56726|estExt_fgenesh1_pm.C_3_t10209) that was slightly up‐regulated in the later stage. In consideration bacterial MlrA encoding a protease, fungal aflatoxin‐detoxifizyme could be a possible candidate enzyme involving in MC degradation. In order to investigate the mechanism for MC degradation in fungi, there is more work need to be done.

CONCLUSIONS

In this study, the algicidal process of B. adusta T1 was investigated by a time‐serial transcriptomic analysis, and the results were compared with these from T. versicolor F21a, reported in our previous study. The identified DEGs were enriched in endopeptidase activity, cellulose catabolic process, and transmembrane transporter activity. Endopeptidases together with enzymes of PL8 might play a key role in the elimination of cyanobacterial cells by both algicidal fungi, B. adusta T1 and T. versicolor F21a.

CONFLICTS OF INTEREST

None declared.

AUTHOR CONTRIBUTION

Guomin Han: Conceptualization (equal); Software (lead); Writing‐original draft (equal). Hui Ma: Investigation (equal). Shenrong Ren: Investigation (supporting). Xueyan Gao: Investigation (supporting). Xiaolong He: Investigation (supporting). Suwen Zhu: Resources (equal); Validation (supporting). Ruining Deng: Validation (supporting). Shihua Zhang: Conceptualization (equal); Writing‐review & editing (equal).

ETHICS STATEMENT

None required.
  44 in total

1.  Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

Authors:  M Ashburner; C A Ball; J A Blake; D Botstein; H Butler; J M Cherry; A P Davis; K Dolinski; S S Dwight; J T Eppig; M A Harris; D P Hill; L Issel-Tarver; A Kasarskis; S Lewis; J C Matese; J E Richardson; M Ringwald; G M Rubin; G Sherlock
Journal:  Nat Genet       Date:  2000-05       Impact factor: 38.330

2.  A fungus capable of degrading microcystin-lr in the algal culture of Microcystis aeruginosa PCC7806.

Authors:  Yong Jia; Jingjing Du; Fuqiang Song; Guiying Zhao; Xingjun Tian
Journal:  Appl Biochem Biotechnol       Date:  2011-12-15       Impact factor: 2.926

3.  Phylogenetic and phylogenomic overview of the Polyporales.

Authors:  Manfred Binder; Alfredo Justo; Robert Riley; Asaf Salamov; Francesc Lopez-Giraldez; Elisabet Sjökvist; Alex Copeland; Brian Foster; Hui Sun; Ellen Larsson; Karl-Henrik Larsson; Jeffrey Townsend; Igor V Grigoriev; David S Hibbett
Journal:  Mycologia       Date:  2013-08-11       Impact factor: 2.696

Review 4.  Microorganisms-based methods for harmful algal blooms control: A review.

Authors:  Rui Sun; Pengfei Sun; Jianhong Zhang; Sofia Esquivel-Elizondo; Yonghong Wu
Journal:  Bioresour Technol       Date:  2017-08-01       Impact factor: 9.642

5.  Uptake and biotransformation of pure commercial microcystin-LR versus microcystin-LR from a natural cyanobacterial bloom extract in the aquatic fungus Mucor hiemalis.

Authors:  Maranda Esterhuizen-Londt; Stefanie Hertel; Stephan Pflugmacher
Journal:  Biotechnol Lett       Date:  2017-06-08       Impact factor: 2.461

6.  KEGG: new perspectives on genomes, pathways, diseases and drugs.

Authors:  Minoru Kanehisa; Miho Furumichi; Mao Tanabe; Yoko Sato; Kanae Morishima
Journal:  Nucleic Acids Res       Date:  2016-11-28       Impact factor: 16.971

7.  Proteomic enzyme analysis of the marine fungus Paradendryphiella salina reveals alginate lyase as a minimal adaptation strategy for brown algae degradation.

Authors:  Bo Pilgaard; Casper Wilkens; Florian-Alexander Herbst; Marlene Vuillemin; Nanna Rhein-Knudsen; Anne S Meyer; Lene Lange
Journal:  Sci Rep       Date:  2019-08-26       Impact factor: 4.379

8.  Whole-Genome and Transposed Duplication Contributes to the Expansion and Diversification of TLC Genes in Maize.

Authors:  Weina Si; Tianlu Hang; Mingyue Guo; Zhen Chen; Qizhi Liang; Longjiang Gu; Ting Ding
Journal:  Int J Mol Sci       Date:  2019-11-04       Impact factor: 5.923

9.  Insights into the mechanism of cyanobacteria removal by the algicidal fungi Bjerkandera adusta and Trametes versicolor.

Authors:  Guomin Han; Hui Ma; Shenrong Ren; Xueyan Gao; Xiaolong He; Suwen Zhu; Ruining Deng; Shihua Zhang
Journal:  Microbiologyopen       Date:  2020-06-11       Impact factor: 3.139

10.  mycoCLAP, the database for characterized lignocellulose-active proteins of fungal origin: resource and text mining curation support.

Authors:  Kimchi Strasser; Erin McDonnell; Carol Nyaga; Min Wu; Sherry Wu; Hayda Almeida; Marie-Jean Meurs; Leila Kosseim; Justin Powlowski; Greg Butler; Adrian Tsang
Journal:  Database (Oxford)       Date:  2015-03-08       Impact factor: 3.451

View more
  3 in total

Review 1.  Recent Advances in the Research on the Anticyanobacterial Effects and Biodegradation Mechanisms of Microcystis aeruginosa with Microorganisms.

Authors:  Yun Kong; Yue Wang; Lihong Miao; Shuhong Mo; Jiake Li; Xing Zheng
Journal:  Microorganisms       Date:  2022-05-31

2.  Insights into the mechanism of cyanobacteria removal by the algicidal fungi Bjerkandera adusta and Trametes versicolor.

Authors:  Guomin Han; Hui Ma; Shenrong Ren; Xueyan Gao; Xiaolong He; Suwen Zhu; Ruining Deng; Shihua Zhang
Journal:  Microbiologyopen       Date:  2020-06-11       Impact factor: 3.139

3.  Transcriptome Analysis Reveals the Algicidal Mechanism of Brevibacillus laterosporus against Microcystis aeruginosa through Multiple Metabolic Pathways.

Authors:  Yulei Zhang; Jieyi Li; Zhangxi Hu; Dong Chen; Feng Li; Xianghu Huang; Changling Li
Journal:  Toxins (Basel)       Date:  2022-07-15       Impact factor: 5.075

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.