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Article

# Characterization of the *XTH* Gene Family: New Insight to the Roles in Soybean Flooding Tolerance

Li Song<sup>1,2,*</sup>, Babu Valliyodan<sup>2</sup>, Silvas Prince<sup>2,3</sup>, Jinrong Wan<sup>2</sup> and Henry T. Nguyen<sup>2,*</sup>

¹ Institutes of Agricultural Science and Technology Development, Joint International Research Laboratory of Agriculture and Agri-Product Safety, Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China

² National Center for Soybean Biotechnology and Division of Plant Sciences, University of Missouri, Columbia, MO 65211, USA; valliyodanb@missouri.edu (B.V.); sjprince@noble.org (S.P.); wanj@missouri.edu (J.W.)

³ Noble Research Institute, 2510 Sam noble Pkwy, Ardmore, OK 73401, USA

* Correspondence: songli@yzu.edu.cn (L.S.); nguyenhenry@missouri.edu (H.T.N.)

Received: 26 June 2018; Accepted: 6 September 2018; Published: 11 September 2018

**Abstract:** Xyloglucan endotransglycosylases/hydrolases (XTHs) are a class of enzymes involved in the construction and remodeling of cellulose/xyloglucan crosslinks and play an important role in regulating cell wall extensibility. However, little is known about this class of enzymes in soybean. Here, 61 soybean *XTH* genes (*GmXTHs*) were identified and classified into three subgroups through comparative phylogenetic analysis. Genome duplication greatly contributed to the expansion of *GmXTH* genes in soybean. A conserved amino acid motif responsible for the catalytic activity was identified in all GmXTHs. Further expression analysis revealed that most *GmXTHs* exhibited a distinct organ-specific expression pattern, and the expression level of many *GmXTH* genes was significantly associated with ethylene and flooding stress. To illustrate a possible role of *XTH* genes in regulating stress responses, the *Arabidopsis* *AtXTH31* gene was overexpressed in soybean. The generated transgenic plants exhibited improved tolerance to flooding stress, with a higher germination rate and longer roots/hypocotyls during the seedling stage and vegetative growth stages. In summary, our combined bioinformatics and gene expression pattern analyses suggest that *GmXTH* genes play a role in regulating soybean stress responses. The enhanced soybean flooding tolerance resulting from the expression of an *Arabidopsis* *XTH* also supports the role of *XTH* genes in regulating plant flooding stress responses.

**Keywords:** Glycine max; *XTH* gene family; transgenic soybean; plant genome; plant hormone; flooding; root plasticity

## 1. Introduction

Xyloglucan endotransglycosylases/hydrolases (XET/XTHs also named XTHs) are classified as glycoside hydrolase family 16 (available online: http://www.cazy.org/fam/GH16.html) and play an important role in organ elongation by modifying xyloglucan chains or catalyzing the hydrolysis of xyloglucan [1-4]. Several studies have emphasized the significant role of this gene family in the regulation of cell wall extensibility. Overexpression of the *BcXTH1* gene from *Brassica campestris* enhanced stem elongation in *Arabidopsis* by promoting cell expansion and elongation [5]. Increased *SIXET1* activity affects the xyloglucan structure during the fruit ripening and softening process in transgenic tomato fruit [6]. Overexpression of *GhXTH1* in cotton loosens and elongates cell wall fibers due to cleavage down the xyloglucan-cellulose chains [7,8]. *PtxtXET16-34* is strongly expressed in primary-walled xylem. Transgenic hybrid Aspen analysis indicated that wood cell expansion and xyloglucan content were affected when the *PtxtXET16-34* gene was overexpressed [9]. *AtXTH31*
regulates cell wall xyloglucan content, and *AtXTH21* influences the development of primary roots by regulating the deposition of cellulose and the thickness of the cell wall in *Arabidopsis* [10,11].

It was reported that the XTH enzyme activity may vary with changes in environmental conditions (i.e., abiotic stresses), and that hormones play important roles in tuning XTH activity during plant development. XET activity in the maize primary root elongation zone contributes to cell wall loosening at low water potential, which is partly regulated by abscisic acid (ABA) [12,13]. Low water potential decreased the XET activity in the hypocotyl elongation zone of dark-grown soybean [14]. A decrease in XET activity was also reported in the basal 5–10 mm of maize primary roots treated with polyethylene glycol solution, which reduced the cell wall extensibility and cell elongation in that region [15]. *CaXTH3* overexpressing transgenic *Arabidopsis* showed improved tolerance to water deficit and less tolerance to high salinity compared to wild type [16]. *OsXTH8*, which is highly expressed in the vascular bundles of leaf sheath and young nodal roots in rice, was upregulated by gibberellic acid. Repressed growth in transgenic rice was associated with knocking down the expression of *OsXTH8* [17]. Loss of function of *AtXTH31* reduces sensitivity to ABA and faster germination in *Arabidopsis* [18]. Downregulation of *XTH8* and *XTH31* is also responsible for the reduced leaf cell expansion of the *Arabidopsis siz1* mutant in an SA-dependent manner [19]. The homologue of *GmXTH16* in maize is induced by flooding and ethylene and is associated with aerenchyma development [20].

As the third most cultivated crop worldwide, soybean provides protein, oil, and plant natural products for human and animal consumption, but its production is limited by environmental constraints [21–23]. Among the major abiotic stresses, soybean is particularly sensitive to flooding stress, as plant growth and grain yields are markedly reduced in flooded soil [24]. The downregulation of gene expression related to cell wall metabolism, cellulose synthesis, and cell wall degradation caused by flooding indicates that cell wall biosynthesis is inhibited by flooding [25]. Therefore, functional characterisation of the *XTH* gene family in soybean will be very useful for revealing the mechanism of soybean flooding resistance. However, little is known about soybean *XTHs*, except for the report showing that *pBRU1* (*GmXTH16*) is involved in brassinosteroid-regulated soybean epicotyls elongation [26]. The availability of soybean genome sequences and comparative analysis of the XTH gene family across plant species provide an excellent opportunity to explore the XTH diversity in soybean. In this study, genome-wide analyses of soybean *XTHs* were performed, including phylogenetic analysis, chromosomal distribution, structural, and conserved motif (DExDxEFLG) analysis. Then, a comparative analysis of the XTH gene family transcriptome in soybean tissues was performed. Further functional validation of the roles of *AtXTH31* was executed in transgenic soybean during the early seedling stage under flooding stress.

## 2. Results

### 2.1. Genome-Wide Identification of Soybean XTH Family and Phylogenetic Relationship

A total of 61 *GmXTHs* were identified with a blasting core value over 100 by using the AtXTH31 amino acid sequence as query. They were designated *GmXTH1* through *GmXTH61* according to their positions on chromosomes 1 to 20 (Supplemental Table S1). The putative proteins encoded by these *GmXTHs* document the conserved structural features of the XTHs.

An unrooted phylogenetic analysis was constructed using a total of 123 full-length XTH protein sequences from *Arabidopsis* (AtXTH), rice (OsXTH), and soybean (GmXTH). According to the NJ phylogenetic tree, 46 *GmXTH* genes were clustered in group I/II, and 15 members were classified in group III (Figure 1). Two major groups have been previously classified based on the sequence similarity as group I/II and group III in *Arabidopsis* and rice [27,28]. Phylogenetic analysis revealed that the soybean *GmXTH* gene family was expanded widely in contrast to *Arabidopsis* and rice, which may correspond to the larger genome of soybean. Group III is further divided into two subgroups: group IIIA (red) and group IIIB (pink), which contains eight and seven *GmXTH* genes, respectively.
<figure><img src="image_58.png" /><figcaption>**Figure 1.** An unrooted phylogenetic tree for *AIXTH*, *OsXTH*, and *GmXTH* genes. A phylogenetic tree was constructed using the neighbor-joining method implemented in MEGA7. The number beside the branches represents bootstrap values based on 1000 replications. The XTH members are classified into three subfamilies. Genes from groups I/II and III are shown in the black and red/pink lines, respectively. Group III was designated group IIIA (red) and group IIIB (pink).</figcaption></figure>

## 2.2. Chromosomal Location and Duplication Process of GmXTHs

Genome localization analysis revealed that *GmXTHs* were widely dispersed across 19 of the 20 chromosomes (Figure 2). Most *GmXTH* genes were distributed on the chromosome arms, except for two genes (*GmXTH40* and *GmXTH53*) which are located in the heterochromatin regions around the centromeric repeats. Chromosome 13 contained the largest number (eight *XTH* genes), followed by seven on chromosome 17 and five on chromosome 8. No *XTH* genes were found on chromosome 4, and the remaining chromosomes each contained one to four *XTH* genes.

Here, we found that tandem duplication or segmental duplication was involved in the expansion of the *GmXTH* gene family (Supplementary Table S3). Mapping the *XTH* genes to their chromosome physical positions (Figure 3) revealed that many *XTH* genes were clustered together, suggesting that they might be the result of tandem duplication events. For example, *GmXTH31*, *32*, *33*, *34*, and *35* on chromosome 13 and *GmXTH44*, *45*, *46*, *47*, *48*, and *49* on chromosome 17 come from tandem duplication. *GmXTH41/42* pair and *GmXTH55/56* pair come from tandem duplication. In addition, most of the segmental duplications of *GmXTH* genes occurred approximately 13 Million
years ago when Glycine-specific duplication occurred in the soybean genome (Schmutz et al., 2010, [29] Supplementary Table S3). The Ka/Ks ratio for each segmentally duplicated gene pair varied from 0.06 to 0.46. This analysis suggests that all mutations in paralogous *GmXTH* genes are neutral or disadvantageous, as their Ka/Ks ratios were less than 1. In general, tandem and segmental duplication contributed to *XTH* gene expansion in soybean. Only seven genes (*GmXTH11*, *GmXTH13*, *GmXTH17*, *GmXTH28*, *GmXTH53*, *GmXTH54*, and *GmXTH58*) were not involved in duplication events.

<figure><img src="image_59.png" /><figcaption>**Figure 2.** Chromosomal location of 61 *GmXTH* genes along soybean's 20 chromosomes. Physical map showed the distribution of the *Glycine max* XTH genes along the 20 chromosomes with colors indicating duplicated gene pairs. The chromosome number is indicated at the bottom.</figcaption></figure>

## 2.3. Gene Structure and Conserved Protein Motif Analysis

To gain further insights into the evolutionary relationships among *GmXTH* genes, the exon/intron structures were predicted based on the alignment of coding sequence (CDS) sequences with corresponding genomic DNA sequences. As illustrated in Supplementary Figure S1, all members of the *GmXTH* family contain three or four exons. Several genes showed a different structure; for example, *GmXTH44* has an extremely long 5' untranslated region (UTR), and *GmXTH39*, *GmXTH5*, and *GmXTH58* have no 5' and 3' UTRs.

All *GmXTH* proteins contained the conserved amino acid motif DExDxEFLG (Figure 3A), which is predicted to be responsible for the catalytic activity [30,31]. Therefore, *GmXTHs* reported here may cut/rejoin xyloglucan chains or catalyze the hydrolysis of xyloglucan. Compared with the genes of
group III, this conserved motif could be extended upstream and downstream with a more conserved motif among *Arabidopsis*, rice, and soybean (Figure 3B).

<figure><img src="image_60.png" /><figcaption>**Figure 3.** Conserved protein motifs in soybean XTHs. (A) Motifs in XTH protein sequences of 61 GmXTH identified with the MEME tool. (B) Alignment of the putative-site amino acid residues in group III XTH proteins from *Arabidopsis*, rice, and soybean constructed with the CLUSTALW2 program. Amino acid residues that are identical within this motif are indicated by gray shading. "*" means that the residues or nucleotides in that column are identical in all sequences in the alignment. ":" means that conserved substitutions have been observed.</figcaption></figure>

## 2.4. GmXTHs Show an Organ-Specific Expression Pattern

To determine the expression patterns of *GmXTH* genes, we used publicly available genome-wide transcriptome data of soybean organs as a resource [32]. As shown in Figure 4, *GmXTH* genes are broadly expressed in various soybean organs. However, most of the *GmXTHs* exhibit distinct tissue-specific expression patterns. For example, fourteen *GmXTHs* (XTH4, 41, 53, 10, 27, 17, 48, 45, 47,
33, 2, 19, 16, and 61) were highly expressed in roots, eighteen *GmXTHs* (XTH9, 38, 34, 44, 8, 35, 20, 42, 40, 52, 5, 39, 1, 18, 29, 31, 43, and 56) were highly expressed in flowers, thirteen *GmXTHs* (XTH60, 12, 14, 23, 6, 46, 49, 57, 3, 51, 26, 59, and 25) were highly expressed in stems, and three *GmXTHs* (XTH 36, 13, and 22) highly expressed in seeds, whereas expression levels were relatively low in other organs. In contrast, several organs only contained one or a few genes that showed specific expression patterns. For example, *GmXTH54* was the only gene highly expressed in leaves compared with other organs, and *GmXTH55* was the only gene highly expressed in root hair compared with other organs.

<figure><img src="image_61.png" /><figcaption>**Figure 4.** Heatmap of the expression profiles of the *GmXTH* gene family in nine organs. Relative organ expression levels of *GmXTHs* based on RNA-seq data were used to construct the heatmap. The expression values (Reads Per Kilobase Million) were median-centered and normalized for each gene in different tissues before transforming to color scale. The color bar at the bottom shows the range of expression values from highest expression level (red) to lowest expression level (green), and 0 is the median expression level (Black). SAM (Shoot Apical Meristem).</figcaption></figure>
No sequence reads were found for *GmXTH58* in any of the soybean organs included in the study, indicating that *GmXTH58* is probably a pseudogene or expressed under special conditions or at specific developmental stages. No *GmXTH* gene showed specifically higher expression level in nodules. Similar expression patterns were found for some phylogenetically paired genes. For example, *GmXTH25* and *GmXTH27* from group IIIA were highly expressed in roots, and *GmXTH29* and *GmXTH38* from group IIIA were highly expressed in flowers. *GmXTH14*, *GmXTH12*, and *GmXTH59* from group IIIB were highly expressed in stems.

## 2.5. *Expression Patterns of GmXTHs Correlated with Flooding Stress*

Identification of the regulatory elements indicated that one 4-bp oxygen-deficiency response element (S000493 GTAC) was significantly enriched in most *GmXTH* promoter regions, except *GmXTH23* and *GmXTH55* (Supplementary Table S4). Most *GmXTH* genes contain more than 3 response elements. The main effect of flooding is hypoxia, which reduces submerged plant normal growth and nutrient/water uptake [33]. These results suggest that the *GmXTH* gene family may play important roles during soybean sustained flooding stress.

To further assess whether the expression profiles of *GmXTH* genes are changed under flooding stress, soybean seedlings (Williams 82 genotype) were exposed to flooding conditions for 7 days [34], and their leaves were collected for gene expression analysis by RNA-seq method. Ten out of sixty-one genes were significantly regulated under flooding stress (Figure 5A), and all genes were located in group I/II. Then, the gene expression levels of twenty genes from group I/II were assessed in soybean hypocotyl and root organs under 2 days of flooding stress by quantitative Real-Time PCR (qRT-PCR) method. The results indicated that *GmXTH32* and *GmXTH34*, together with the marker genes *GmADH2* and *GmPDC1* [35,36], were predominantly upregulated by flooding stress, and all others showed higher expression levels than the untreated control, except four genes that were slightly downregulated (Figure 5B).

Ethylene will quickly accumulate under flooding conditions, and many regulators of submergence respond to ethylene [33,37]. To further investigate the relationship between the expression level of *GmXTH* genes and ethylene, we monitored the abundance of 61 *GmXTH* transcripts in soybean root tissue exposed to 50 µM 1-Aminocyclopropane-1-carboxylic acid (ACC) for 5 h by RNA-seq method (Wang and Nguyen et al., University of Missouri, Columbia, MO. Williams 82, 2015). We found that twenty-three *GmXTH* genes were significantly regulated under ACC treatment (Figure 5). Among them, *GmXTH18* was highly induced, and *GmXTH29* was highly down-regulated. Interestingly, *GmXTH25*, 27, 28, and 29 (group IIIA) were downregulated. We also found the *GmXTH40* was oppositely adjusted by flooding in leaf and root tissues. *GmXTH32* and *GmXTH34* were significantly induced by flooding in roots but not in leaves. Interestingly, a similar expression pattern was found for the tandem or segmental duplicated gene pairs located on chr13 and chr17. For example, *GmXTH31* and *GmXTH49* are both upregulated, and *GmXTH18* and *GmXTH40* are both downregulated by flooding stress in the root (Figure 5).

## 2.6. *Stable Transgenic Soybean with Overexpression of AtXTH31*

To further characterize how *XTH* genes affect root morphology and maintain physiological response under flooding conditions during soybean seedling development, *AtXTH31* (under the control of the AtMyb2 promoter) was transformed into soybean (cultivar Maverick). Over twenty independent transgenic events were generated, and six events were first identified through the general PCR method. Subsequently, the copy number variation of the transgene in those events (T0 generation) was inferred using the Q3D PCR method. Three events (Code: ND-30-2, ND-30-9 and ND-30-11) contained one copy number of the transgene, and one event (Code: ND-30-12) showed two copies of inserts (Figure 6A). However, the other two events showed a very low copy number (less than 0.5), which indicates that those events are chimeras (transgenic plant or plant part that is a mixture of two or more genetically different types of cells). Homozygous T3 transgenic soybean lines from the above
events were obtained and confirmed using herbicide-resistance segregation analysis. An ND-30-12 single copy insert line was chosen from segregated T1 generation by the Q3D PCR method.

<figure><img src="image_62.png" /><figcaption>**Figure 5.** Expression patterns of individual *XTH* genes in response to flooding and ACC treatment studied by qRT-PCR or RNA-seq. (A) Expression pattern of individual *XTH* genes in response to 24 h flooding treatment in root and hypocotyl organs of two-day-old soybean seedlings. (B,C) Organ-specific expression analysis showed that most *XTH* genes were unregulated by the ACC in the root tissue, but there was no significant difference in the aerial parts of the three-week-old soybean. Three flooding-related homologous marker genes in soybean were studied as positive controls. Fold change (Log2) of relative gene expression (Actin (Glyma.18G290800)) of soybean was used as the normalization control.</figcaption></figure>
<figure><img src="image_63.png" /><figcaption>**Figure 6.** Calculation of transgene AtXTH31 copy numbers and relative expression levels in four transgenic events. (A) Ratios of copy number between AtXTH31 and lectin gene (Glyma.02G009600) were determined by digital PCR in soybean T0 transgenic generation. Soybean transgenic plants contained a single insert copy when the ratio value was equal to 0.5 and two insert copies when the ratio value was equal to 1. (B) The relative expression of AtXTH31 in T3 homozygous transgenic soybean roots determined by qRT-PCR. The relative levels of transcripts were normalized to the soybean actin gene (Glyma.18G290800). Bars represent mean values of three biological replicates (standard error). \* indicates significantly different at *p* < 0.05 as tested by Fisher's least significant difference. Non-transgenic Maverick soybean as a control and MYB2:AtXTH31 transgenic soybean lines ND-30-2, ND-30-9, ND-30-11, and ND-30-12 with overexpression of AtXTH31 were studied.</figcaption></figure>

The transcript abundance of *AtXTH31* in different T3 homozygous transgenic soybean lines was investigated using qRT-PCR. Lines ND-30-2 and ND-30-12 had approximately 28-fold increases compared to the non-transgenic control, whereas lines ND-30-9 and ND-30-11 had moderately high (between 43-fold to 48-fold) increases (Figure 6B).

## 2.7. Transgenic Soybean Exhibits Tolerance to Flooding during the Germination Stage

In a comparison of the flooding tolerance between the control and transgenic lines, the germination rate of each line was counted first. As shown in Figure 7, all transgenic soybean lines had longer roots and hypocotyls (range from 45 mm to 51 mm) than the control (38 mm) after 5 days of flooding (Figure 7A). Four transgenic homozygous T3 transgenic lines with varied transgene expression conferred a range of tolerance with an increase in germination rate after 7 days of flooding, which ranged from 40% to 58% and two lines (ND-30-2 and ND-30-9) showed significant increase (Figure 7B). The length of roots and hypocotyls in the two lines (ND-30-9 and ND-30-11) was significantly greater than that in the control (Figure 7C). These results indicated that overexpressed AtXTH31 in soybean induced higher germination rate, and enhanced root/hypocotyl elongation compared with susceptible parent Maverick.
<figure><img src="image_64.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_65.png" /><figcaption>C</figcaption></figure>

<figure><img src="image_66.png" /><figcaption>**Figure 7.** Soybean *AtXTH31* transgenic plants show an enhanced germination ratio and elongated root and hypocotyl under flooding conditions. (A) Two-day-old seedlings were flooded with water for 5 days. Bar indicates 1 cm. (B) The germination rate of transgenic and wild-type plants under 7 days of flooding. (C) Length of roots and hypocotyls of flooded Maverick soybean and transgenic seedlings. (n ≥ 3). \* indicates differences between the maverick and transgenic soybean (p < 0.05).</figcaption></figure>

## 2.8. Transgenic Soybean Exhibits Tolerance to Flooding during the Vegetative Stage

Similarly, the ability of transgenic seedlings (V1 stage) to withstand flooding was then investigated. Seedlings were grown up to the V1 stage and flooded for 14 days (Figure 8A). We found that the primary root of transgenic plants was longer than that of non-transgenic controls under flooding conditions. Except for ND-30-2, the roots of all other three transgenic plants showed a significant increase in length (Figure 8B). In addition, two transgenic events (ND-30-2 and ND-30-9) showed great number of lateral roots and tertiary root tips as a response to flooding. Meanwhile, we observed that aerial root formation significantly increased in other two lines than the wild type (Figure 8E). Thus, ectopic expression of AtXTH31 in soybean could promote root development under flooding conditions and provide enhanced tolerance to flooding stress.
<figure><img src="image_67.png" /><figcaption>**Figure 8.** Soybean AtXTH31 transgenic plants show an enhanced flooding tolerance phenotype by promoting adventitious roots, lateral roots, tertiary root tips, and elongated primary roots. (A) Flooding effects on soybean seedlings. The V1 stage seedlings were flooded with water for 7 days. Bar indicates 5 cm. (B) Length of primary root compared between transgenic and control soybean plants under 7 days of flooding conditions. (C–E) The effects of flooding on number of lateral roots, tertiary root tips and adventitious roots per transgenic plant. (n ≥ 20). * indicates differences between the maverick and transgenic soybean (*p* < 0.05).</figcaption></figure>

**3. Discussion**

The *XTH* gene family has been identified in several plant species, including *Arabidopsis* [27], rice [28], barley [38], poplar [39], tomato [40], and bryophyte [41]. In this study, we report the identification and characterization of the soybean *XTH* gene family and make a comparison to
*Arabidopsis* and rice. Expression pattern analysis suggested that *GmXTHs* may play an important role under flooding stress. Transgenic soybean plants overexpressing *AtXTH31* showed an increase in tolerance to flooding, along with the increased aerial root number and elongated primary root length.

### 3.1. Characterization of GmXTHs Gene Family

Although the role of plant XTHs in regulating cell wall extensibility is well known, there is limited information on the XTH gene family size and the evolutionary relationships between XTH genes in soybean. Previous phylogenetic studies showed that XTHs form three groups in *Arabidopsis* and rice [27,28]. The number of *GmXTH* genes identified was substantially higher than in *Arabidopsis* and rice, and clustered into three groups. Further, the evolutionary mechanism analysis suggested that GmXTHs family expanded partly due to segmental and tandem duplication events. These duplication events further contributed to the conserved protein motif and gene structure. These *GmXTHs* genes displayed differential expression patterns either between different organs or under flooding stress. For example, *GmXTH22* showed the highest expression level in root hair and seeds, but *GmXTH23* exhibited the highest expression level in stems. *GmXTH29* and *GmXTH30* showed the highest and lower expression levels in flower tissue, respectively. The expression patterns of these paralogous pairs suggest that *GmXTH* gene family might have undergone sub-functionalization or neofunctionalization during the subsequent evolution process. Considering these facts, the characterization of *GmXTH* gene family provides valuable information on the evolution of the *XTH* soybean gene family and underlines basis for future research.

### 3.2. The Expression Patterns of GmXTHs Were Regulated by Flooding and Ethylene

Flooding causes severe production losses in soybean [42,43] through inhibition of stem and root growth, decreased photosynthesis, and induced leaf abscission and premature fruit drop [20,44,45]. Therefore, investigating gene expression patterns of the *GmXTH* gene family can help us advance the fundamental understanding of how soybean adjusts to flooding stress during growth and development.

In this study, we found that the expression pattern of *GmXTHs* may confer precise regulation with temporal, spatial, and environmental conditions. One of the main effects of flooding is the deprivation of oxygen from plant roots, and low oxygen will increase the synthesis of ethylene [46]. Ethylene production was higher in soybean waterlogging-tolerant lines than in susceptible lines [47]. It has been reported that the expression of *XTH* genes is associated with shoot elongation, which is promoted by ethylene in arrowhead tubers [48]. Several *AtXTH* genes were differentially regulated during ACC-induced inhibition of *Arabidopsis* root cell elongation [49]. Ethylene increases *XTH* and *EXPANSIN7* (*EXP7*) expression in *Arabidopsis* roots [50]. Accordingly, investigation of *GmXTH* expression levels under ACC treatment will provide more hints to further gene functional analysis. In this study, we found that 23 *GmXTH* genes were significantly regulated by ethylene in soybean roots, indicating that the hormone ethylene plays important roles in GmXTH-mediated cell wall remodeling during flooding stress. However, further analysis is needed to reveal the relationship between hormone ACC and cell wall remodeling by regulating *XTH* transcription level in soybean.

### 3.3. The Biological Function of AtXTH31 in Soybean Root Development Under Flooding Stress

It was reported that the elongation of soybean roots was suppressed in the first 24 h and then significantly retarded after 48 h under flooding stress, which indicated that the flooding responses in the initial stages are critical for soybean growth and survival [51]. The XTH activity in the hypocotyl elongation zone of dark-grown soybean decreases when the root is exposed to low water potential [14], which directly indicates that XTH may be involved in the abiotic stress response. In this paper, the phenotypes of transgenic soybean plants carrying *AtXTH31* gene on seedling growth under flooding conditions were studied. *AtXTH31* belongs to subgroup IIIA, which was predicted to exhibit hydrolase activity with higher activity in vitro than XET activity [10,52]. *AtXTH31* exhibits a root-specific expression pattern and is involved in *Arabidopsis* cell wall modification and
cell elongation [27]. The *xth31* mutant shows slower root elongation [10]. Therefore, the *AtXTH31* gene was selected for heterologous overexpression in soybean. Here we found that transgenic soybean's ability to produce more adventitious roots and longer primary roots corresponded to an increase in tolerance under flooding stress during early seedling development. It was reported that soybean root length was positively correlated with waterlogging tolerance in soybean germplasm lines [53,54]. Waterlogging-tolerant soybean lines normally developed more adventitious roots than waterlogging-susceptible lines [47,55]. Clearly, our results indicate that XTH-mediated cell wall adjustment may play a critical role in the adaptation of plants to flooding stress, and *AtXTH31* could be a useful candidate gene to develop flooding tolerance lines through molecular transgenic breeding methods. However, the corresponding tolerance mechanisms demand further investigation.

### 3.4. Digital PCR Provides a Simple and Accurate Method for Soybean Transgene Copy Number Analysis

Detection and quantification of transgene copy numbers are very important in characterizing transgenic plants. Recently, the application of digital PCR for the precise analysis of transgene copy numbers in crops has been reported in an array of crops [56–58]. This technology accelerates molecular breeding workflow in transgenic plants, enhances data quality in characterizing transgenes, and finally benefits the environment. However, no reports have been available on soybean for detecting copy number variations by the application of digital PCR until now.

In our study, digital PCR technology was applied to validate the transgenic *AtXTH31* copy numbers using T0 plants. Here, the digital PCR method provided more accurate results than those provided by Southern blotting and classical PCR. For example, chimeric plants (a plant or plant part that is a mixture of two or more genetically different types of cells) can be easily identified through the ratio of copy numbers. Furthermore, the dPCR method was continuously used to identify homozygous plants in the T1 generation, which saved the experiment time and no need to evaluate the homozygous lines through calculating the segregation rate of T2. In particular, the dPCR method was successfully applied to choose single-copy insert transgenic lines through analysis of copy number variation in the T1 generation. In summary, the dPCR method provides a very useful technical support for the transgenic soybean research community.

## 4. Materials & Methods

### 4.1. Identification, Chromosomal Location, and Structural Organization of GmXTH Family Members in Glycine Max

All sequence information for genes and proteins was retrieved by searching Phytozome v10.3 database (available online: http://www.phytozome.net) with a BLASTP algorithm using the *AtXTH31* amino acid sequence. The chromosome location of each *GmXTH* was obtained from Phytozome. The exon/intron organizations of *GmXTHs* were visualized with the Gene Structure Display Server program ([59] GSDS: available online: http://gsds.cbi.pku.edu.cn/).

### 4.2. Protein Sequence Alignment, Phylogenetic Analysis, and Gene Duplications of GmXTH Genes

Multiple sequence alignments were constructed using ClustalW2 (available online: http://www.ebi.ac.uk/Tools/clustalw2/index.html). Subsequently, a phylogenetic tree was constructed using the neighbor-joining method and implemented using the MEGA7 software tool [60]. The reliability of an inferred tree was confirmed with bootstrap analysis performed with 1000 replications. The evolutionary distances were computed using the Poisson correction method [61] and are in the units of the number of amino acid substitutions per site. A total of 123 coding sequences from *Arabidopsis*, rice, and soybean were collected for phylogenetic analysis. All positions containing gaps and missing data were eliminated. The Ks (synonymous substitutions per synonymous site) and Ka (non-synonymous substitutions per non-synonymous site) values were extracted from the Plant Genome Duplication Database (PGDD: available online: http://chibba.agtec.uga.edu/duplication/), and these were used
for calculating the approximate dates of duplication events. The date of duplication events was subsequently estimated according to the equation $T = Ks/2\lambda$, in which the mean synonymous substitution rate ($\lambda$) for soybean is $6.1 \times 10^{-9}$ [62].

### 4.3. Plant Growth, Hormonal/Flooding Treatments, and Tissue Collection

Soybean cultivar Williams 82 was used for gene expression pattern analysis. For ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) treatment, plants were grown in 4-gallon pots (Greenhouse megastore, USA) containing a 3:1 mixture of surface and sand in a growth chamber under the conditions of 28/20 °C day/night temperature, 14/10 h light/dark photoperiod, 800 µmol m⁻² s⁻¹ light intensity and 60% humidity. Two-week-old plants were sprayed with 50 µM ACC (or a mock solution without ACC) on the leaf, irrigated with 2 l of hormone solution in a plastic case and then incubated for 5 h before root tissue collection.

For flooding stress treatment, two-day-old seedlings cultivated on quartz sand were completely submerged in 700 ml of water for 5 days at 25 °C with a light/dark cycle (600 µmol m⁻² s⁻¹, 16 h light/8 h dark). The water level was kept at 2 cm above the quartz sand surface, and control seedlings were grown with a water level below the quartz sand surface. Roots and hypocotyls were collected from soybean seedlings. The collected tissues were frozen immediately in liquid nitrogen and stored at -80 °C. All samples were collected in biological triplicate.

For waterlogging treatment, transgenic and control seeds were sown in cones filled with surface and sand in the ratio of 2:1. The cones with plants at the V1 stage were kept inside a tub and flooded above the soil level (>2 cm high) for 14 days. The greenhouse temperatures (24~26 °C) were exactly the same during day and night. The heating system turned on when temperatures were below 23.8 °C. A passive cooling ridge vent opened when temperatures were above 26.6 °C. Active cooling fans turned on when temperatures were above 29.4 °C. The shade was set to stay open all the time, and the HID lights were set to be on at all levels between 5 am and 7 pm.

### 4.4. Promoter Analysis

The DNA sequences 2000 bp upstream of the translation start site (ATG) were extracted from the soybean genome, and the presence and abundance of the known cis-elements were analyzed with the help of the program SOGO (available online: https://sogo.dna.affrc.go.jp/cgi-bin/sogo.cgi?lang=en&pj=640&action=page&page=newplace).

### 4.5. Expression Profiling Using RNA-seq Datasets

The RNA-seq data generated by Libault et al. [32] from nine different soybean tissues (William 82 genotype) including flowers, leaves, nodules, pods, roots, root hairs, seeds, shoot apical meristems, and stems were used to analyze expression patterns of *GmXTHs* members. Chen et al. [34] generated RNA-seq data using soybean (Williams 82 genotype) leaf tissue under flooding stress. Briefly, flooding stress was imposed at the soybean V4 stage (four unfolded trifoliate leaves) by placing the pots into a larger pot filled up to a water level of 4 cm above the soil surface for 7 days.

### 4.6. RNA Extraction for Expression Pattern Analysis

The frozen samples were ground to powder in liquid nitrogen with a mortar and pestle. Approximately 100 mg tissue samples were used for RNA extraction using a RNeasy Plant mini kit (Cat# 74904, Qiagen, Valencia, CA, USA) according to the manufacturer's protocol. On-Column DNA digestion performed by following the RNase-Free DNase kit (Cat#79254, Qiagen) manufacturer's protocol. The quantity and quantity of RNA were assessed using a Nanodrop®1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA).
## 4.7. *Quantitative RT-PCR Analysis*

A total of 2 µg RNA from each sample was reverse-transcribed to cDNA in 20 µL reaction volume using RNA to cDNA Ecopy™ Premix (Double primed) cDNA Synthesis Kit (Cat# 639549, Clontech, Foster City, CA, USA) according to the manufacturer's protocol. PCR was performed in a 10 µL reaction volume using the Maxima SYBR Green/ROX qPCR Master Mix (Cat# K0223, Thermo, USA) on the ABI7900HT detection system machine (ABI PRISM® 7900HT, Foster City, CA, USA). The results from three biological replicates and two technical replicates were used for data analysis. The PCR conditions were as follows: 50 °C for 2 min, 95 °C for 10 min, and 40 cycles of 95 °C for 15 s, and 60 °C for 1 min. To normalize the gene expression levels, the actin (Glyma.18G290800) gene was used as an internal control. All novel primers were designed using the Primer3 web interface (available online: http://frodo.wi.mit.edu/primer3/ [63,64]). The primer sequences are listed in Supplementary Table S2.

## 4.8. *Construction of the pZY101-AtXTH31 Vector, Agrobacterium-mediated Soybean (Glycine max) Transformation and Progeny Segregation Analysis*

The gene-specific primer pair 5'-CATGCCATGGATGGCTTTGTCTCTTATCTTTC-3' and 5'-CATGCCATGGCTAACATTCTGGTGTTTGGG-3' was designed to isolate the full-length CDS of *AtXTH31* from *Arabidopsis*. The PCR product (902 bp) was cloned into the pCR4-TOPO vector, and the positive plasmid was fully sequenced with M13 sequencing primers. The *AtXTH31* gene sequence was inserted into the pCNSH.131. AtMyb2p-Gus vector, which contained the Myb2 promoter. Finally, the whole cassette contained a promoter, and the gene sequence was moved into the pZY101-Asc binary vector. An improved *Agrobacterium*-mediated transformation of the soybean cotyledonary node system [65] was performed using the elite genotype "Maverick". To determine the segregation of gene of interest and selectable marker gene, at least 30 plants from each T0 event were screened using leaf paint (100 mg/L glufosinate, Sigma, St. Louis, MO, USA) analysis carried out for the T0 generation. T2 progeny from the T1 generation was similarly analyzed to identify homozygous T1 lines for subsequent study.

## 4.9. *DNA Extraction and Quantification and PCR Confirmation of Transgenes*

DNA was extracted from the transgenic plant leaves (mixed leaf tissue) using CTAB methods [66]. DNA concentrations and quality were initially estimated using a Nanodrop spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) and then estimated using a QuantiT dsDNA HS Kit (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA). The concentrations from the Qubit assays were used to quantify the DNA input in each PCR reaction. Primers were designed to detect the *AtXTH31* gene of interest and the bar gene as the selectable marker gene (Supplementary Table S2). PCR conditions were as follows: 95 °C hot start 30 s, followed by 36 cycles of 95 °C denaturing 10 s, 55 °C annealing 10 s, and 72 °C extension 1 min, followed by 72 °C final extension 10 min. PCR products were analyzed on an agarose gel, and events were considered transgenic if they displayed an approximately 800 bp band for the gene of interest and a 500 bp band for the bar gene. Four positive transgenic events were obtained and used for further phenotype analysis.

## 4.10. *TaqMan Assays and QuantStudio 3D Digital PCR Analysis for Soybean AtXTH31 Transgenic Copy Number Variation*

The following equipment and chemicals were used from Applied Biosystems (Waltham, MA, USA), Thermo Fisher Scientific, USA: QuantStudio™ 3D Imager (Cat#: PN4489084), QuantStudio™ 3D Loader (Cat#: PN4482592), Dual Flat Block GeneAmpR PCR System 9700 (Cat#: PN4428235), Tilt Base & chip adapters (Cat#: PN4486414 and 4485513), QuantStudio™ 3D Digital PCR 20K Chips (Cat#: PN4485507), and QuantStudio™ 3D Digital PCR Master Mix (Cat#: PN4485718). The probe was designed and synthesized by Life Technology Company. The dPCR reaction volume was 20 µL and contained 10 µL 2× TaqMan 3D mix, 1 µL 20× FAM labeled primers and probe, 1 µL 20× VIC labeled primers and probe, 1 µL DNA samples (40 ng/ µL), and 7 µL nuclease-free water. In total, 14.5 µL
each reaction product was loaded on the chips. Data analysis was conducted using QuantStudio™
3D Analysis Suite™ Cloud Software as described previously [55]. The designed probes could only
amplify transgene *AtXTH31* to ensure that no soybean homologous genes were detected. The ratio
of the copy number of *AtXTH31* with lectin in the same soybean material was calculated as follows:
(copies/µL of the *AtXTH31* transgene)/(copies/µL of the lectin gene Glyma.02G009600) in the same
PCR reaction product. Soybean transgenic plants contained a single insert copy when the ratio value
was equal to 0.5 and two insert copies when the ratio value was equal to 1. The ratio value was less
than 0.5 when chimeric transgenic plants were found. The primers and probe sequences are shown in
Supplementary Table S2.

**5. Conclusions**

In conclusion, our results showed that the soybean genome contains 61 *XTH* genes, the largest family of XTH proteins characterized in any organism to date. The results of phylogenetic analysis and chromosome location/structure provide an overview of the soybean *GmXTH* gene family. The results of the segmental and tandem duplication during expansion of the *GmXTH* gene family provide a genome-wide evolutionary overview. The results of conserved amino acid motif analysis and expression pattern analysis further provide insight into their putative function. Additionally, functional analysis of *AtXTH31* in a heterologous system suggests that the higher germination rate and longer roots/hypocotyls induced by the increased XTH activity may be responsible for the flooding tolerance of transgenic plants. Further comprehensive experiments may be required to elucidate the cellular locations and functions to understand the biological role of XTHs in soybean.

**Supplementary Materials:** Supplementary materials can be found at http://www.mdpi.com/1422-0067/19/9/2705/s1. Supplementary Table S1: Information related to the 61 genes homologous to XTH genes in the soybean genome; Supplementary Table S2: Oligonucleotide primer sequences used in this work; Supplementary Table S3: Estimate of the dates of the segmental duplication events of the soybean XTH gene pairs; Supplementary Figure S1: Exon-intron structure of soybean *XTHs*; Supplementary Table S4: Search for cis-elements in the GmXTH gene promoters.

**Author Contributions:** L.S. designed the experiments, analyzed the data, and prepared the manuscript. B.V. worked on the gene clone and vector construction. S.P. worked on the transgenic soybean phenotype analysis. J.W. analyzed the digital PCR data. H.T.N. conceived and supervised the project. All authors have read, revised, and approved the manuscript.

**Acknowledgments:** We acknowledge Missouri Soybean Merchandising Council, USA and Yang Zhou Science and Technology Bureau (YZ2018156), China for financial support and Plant Transformation Core Facility at the University of Missouri for soybean transformation. We thank Thermo Scientific (Life Technology) for supporting the Q3D PCR equipment. We thank Caifu Chen, Yalei Wu, Pius Brzoska, and David Keys for digital PCR technical support. We thank Yongqin Wang and Chenglin Chai for helping with plant hormone treatment. We thank Mackensie Murphy and Raymond Mutava for their help on the transgenic plant flooding assay.

**Conflicts of Interest:** The authors declare no conflict of interest.

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Review

# Cell Wall Proteins Play Critical Roles in Plant Adaptation to Phosphorus Deficiency

Weiwei Wu, Shengnan Zhu, Qianqian Chen, Yan Lin, Jiang Tian and Cuiyue Liang*

Root Biology Center, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China; weiweiwu2016@163.com (W.W.); shnzhu@163.com (S.Z.); qian2016200202@163.com (Q.C.); anlynlin@126.com (Y.L.); jtian@scau.edu.cn (J.T.)

* Correspondence: liangcy@scau.edu.cn; Tel.: +86-20-8528-0156; Fax: +86-20-8528-1829

Received: 2 August 2019; Accepted: 14 October 2019; Published: 23 October 2019

**Abstract:** Phosphorus is one of the mineral nutrient elements essential for plant growth and development. Low phosphate (Pi) availability in soils adversely affects crop production. To cope with low P stress, remodeling of root morphology and architecture is generally observed in plants, which must be accompanied by root cell wall modifications. It has been documented that cell wall proteins (CWPs) play critical roles in shaping cell walls, transmitting signals, and protecting cells against environmental stresses. However, understanding of the functions of CWPs involved in plant adaptation to P deficiency remains fragmentary. The aim of this review was to summarize advances in identification and functional characterization of CWPs in responses to P deficiency, and to highlight the critical roles of CWPs in mediating root growth, P reutilization, and mobilization in plants.

**Keywords:** cell wall protein; phosphate starvation; Pi mobilization; roots

## 1. Introduction

Phosphorus (P) is one of the mineral nutrients essential for plant development and growth, and serves as a major structural component and functions directly/indirectly in a set of biological and metabolic processes such as energy transmission, membrane and nucleotide synthesis, photosynthesis, and signal transduction [1]. However, due to its strong fixation and binding ability with organic matter and other minerals in soils, phosphate (Pi) bioavailability is often limiting, particularly in the highly-weathered acid soils in tropical and subtropical areas [2]. Therefore, low Pi availability becomes a major factor inhibiting crop production on arable lands, especially on acid soils [2,3]. To cope with low P stress on soils, plants have evolved a series of adaptive strategies to increase their Pi acquisition and utilization efficiency [4,5]. In plant roots, these multiple adaptive strategies to P deficiency mainly include: (i) using alternative metabolism pathways to reduce ATP consumption, (ii) stimulating root proliferation and enhancing symbiotic association with arbuscular mycorrhiza fungi to explore a more extensive volume of soil for Pi, (iii) enhancing root-mediated organic acid and purple acid phosphatase (PAP) exudation to remobilize sparingly-soluble P sources, and (iv) up-regulation of Pi transporters to enhance Pi uptake and translocation [1,4–7].

As part of the apoplast, which constitutes the extracellular space outside the plasma membrane, the cell wall is generally believed to play essential roles in cell division, enlargement, and differentiation. Meanwhile, the plant cell wall could also function as an important P pool for Pi reutilization when plants encounter P deficiency [8]. Therefore, many physiological and developmental changes of plant responses to Pi starvation are functionally related to cell wall modifications, and these modifications mainly determined by cell wall proteins (CWPs) [8–12]. For example, pectin content and the activities of pectin methylesterase (PMEs) in rice cell wall were found to be increased under low P conditions [11,12]. It was suggested that the carboxylate group (–COO–) in homogalacturonans can trap PO₄³⁻ by forming a –COO–Fe–PO₄³⁻–likage. The increasing amount of pectins in low P conditions might be able to
provide more –COO–, which will bind Fe more tightly and subsequently release the trapped PO₄³⁻ [8]. Therefore, the coordinated increase of PME activities under low P conditions has been suggested to provide more negative charges for the cell wall, which facilitates the release of cell-wall-bound Pi for reutilization [11–13].

With the aid of genetic, molecular, and proteomic analysis, numerous CWPs have been identified and functionally characterized [14–20]. In particular, great progress has been achieved in clarifying the function of CWPs in plant responses to various abiotic stresses [19,21–24]. Moreover, complex regulatory networks underlying CWP responses to stresses have been documented [19,25–27]. This review focuses on the characterization of Pi-starvation-responsive CWPs mediating plant adaptation to P deficiency. We briefly summarize the current methods for purification and identification of CWPs in plants. Subsequently, the role of CWPs in controlling plant adaptation to P deficiency has been discussed, especially for expansins, proline-rich proteins (PRPs), oxidoreductases, and purple acid phosphatases.

## 2. Extraction and Identification of CWPs in Responses to Pi Starvation

Proteins localized in cell walls are ubiquitous in plants. Early studies characterized CWPs as proteins unusually rich in one or two amino acids, containing highly repetitive sequence domains, and glycosylated to varying degrees [14]. The most common types of CWPs include hydroxyproline-rich glycoproteins (HRGPs) or extensins, the arabinogalactan proteins (AGPs), the glycine-rich proteins (GRPs), the proline-rich proteins (PRPs), and chimeric proteins that contain extensin-like domains [14,28]. With assistances of the development of molecular, genetic, and proteomic technologies, a large number of other CWPs have been identified and the classical CWPs are understood to harbor several properties, including containing an N-terminal cleavage signal peptide, but lacking the ER-retention C-terminal motif KDEL/HDEL and transmembrane domains [18,20,29–32].

According to their binding ability to cell walls, plant CWPs can be classified into three categories: labile proteins, weakly bound proteins, and strongly bound proteins [18,30]. Due to these properties, different extraction approaches have been separately developed and widely applied to isolate diverse CWPs from plants [18,24,30,33–36]. Feiz et al. (2006) developed an efficient method for extracting weakly bound CWPs, in which several sequential steps are conducted, including plant sample homogenization in low ionic strength acid buffer, purification of cell walls through increasing density cushions, extensive washing of cell walls with a low ionic strength acid buffer to remove cytosolic protein contamination, and using CaCl₂ and high concentration of LiCl to extract CWPs instead of detergents. Compared to other available methods of CWP extraction, this method increases the proportion of the potential CWPs while decreasing the intracellular protein contamination [33]. This method has been successfully and widely used to extract CPWs from a broad range of plants, such as potato (Solanum tuberosum), flax (Linum usitatissimum), and soybean [37–39]. However, it could not be avoided losing about 15% CWPs during cell wall purification and protein extraction because of the complexity of cell wall components and the diversity of CWP properties in plants [37]. Therefore, more efficient methods for CWP purification and isolation are yet to be designed.

Compared to CWP extraction, the approaches for separation, identification, and quantification of CWPs are better developed [40–42]. With the aid of various proteomics techniques, CWPs have been widely identified in different organs of many plant species, including Medicago (Medicago truncatula) [17,18,30,36,43–46], maize (Zea mays) [47], chickpea (Cicer arietinum) [48], rice (Oryza sativa) [34,49–52], potato [53], flax [54], and sugarcane (Saccharum officinarum) cell suspension cultures [55]. These identified CWPs can be functionally classified as proteases, structural proteins, proteins functioning in carbohydrate metabolism, proteins acting as oxidoreductases, proteins associated with lipid metabolism, proteins related to signaling transduction, proteins with predicted interaction domains, miscellaneous proteins, and unknown function proteins [18]. The diverse biological functions of CWPs indicate sophisticated modulations of the cell wall during plant development.
In addition, proteomics techniques have been widely used to identify CWPs differentially accumulated in responses to abiotic stresses in plants. For instance, Zhu et al (2007) [56] used 2D electrophoresis to separate the CWP from water-deficit maize primary roots, and subsequently applied time-of-flight mass spectrometry to identify the differentially accumulated proteins. The results showed that a total of 152 water-deficit-responsive CWP were identified, which were functionally categorized into proteins related to reactive oxygen species (ROS) metabolism, proteins involved in defense reponse, hydrolases, proteins associated with carbohydrate metabolism, and other/unknown proteins [56]. Similar proteomic studies were also conducted to quantify and characterize CWP in plant responses to a set of stresses, such as dehydration stress in maize [56], chickpea [57], and rice [58], flooding stress in both wheat (Triticum aestivum) [22] and soybean (Glycine max) [59], and hydrogen peroxide stress in rice [60]. The results indicate that stress-responsive CWP mediate multiple processes, and thus regulate the responses of cell elongation and expansion under abiotic stress conditions.

Despite the cumulative studies on the identification of differentially accumulated CWP in response to abiotic stresses, few studies have been conducted to globally identify CWP in responses to nutrient deficiencies using proteomic approaches, particularly for P deficiency. Recently, a pioneer study was conducted to identify Pi-starvation-responsive and weakly bound CWP in soybean roots through proteomic analysis [39]. The CWP were extracted from soybean roots following the methods developed by Feiz et al. [33] and were subsequently analyzed by isobaric tag in relative and absolute quantitation (iTRAQ) proteomics techniques. A total of 71 differentially accumulated proteins were identified, among which, 53 proteins (74.6%) were predicted to be secreted and were considered cell-wall-associated proteins by bioinformatic analysis. These proteins were predicted to be involved in carbohydrate metabolism, oxido-reduction, protein modification and turnover, signal transduction, miscellaneous functions, and unknown functions [39]. The results strongly suggest that CWP may regulate the complex responses in soybean roots under low P conditions. However, except for the purple acid phosphatase1 like (PAP1-like) protein, which was subsequently characterized, the functions of all other CWP in soybean adaptation to low P stress remain unclear [39].

### 3. CWP Related to Root Growth in Responses to Pi Starvation

Changes of root morphology and architecture have been widely observed in plants in response to Pi starvation, which extensively increases root proliferation for soil exploration [4,61]. The modulation of root morphology and architecture is highly related to root cell wall synthesis and remodeling, which mainly relies on coordinated regulation of CWP's enzymatic activities. However, differences of root growth in response to Pi starvation among various plant species could lead to more complex regulatory networks. For example, in P-deficient Arabidopsis, growth of primary root is arrested, while growth of lateral roots and root hairs is promoted [62]. For other plant species, such as rice and soybean, both the primary root and lateral (adventitious) root length are increased by short-term Pi starvation [39,63]. Moreover, white lupine (Lupinus albus) develops large numbers of cluster roots under Pi starvation conditions [64]. Thus, different responses of root morphology in various plant species should be also taken into consideration when functions of CWP are characterized in plant acclimatization to low P stress.

So far, the functions of most CWP in mediating plant root growth in responses to Pi starvation remain largely unknown, except for a small set of CWP including expansins, PRPs, and some oxidoreductases [65–69].

#### 3.1. Expansin

Expansins have been widely identified in plant cell walls, and are believed to loosen the cell wall by breaking the hydrogen bonds between hemicellulose and cellulose microfibrils in a pH-dependent manner, thus enabling turgor-driven cell expansion [70,71]. Since increases in cell size are considered to be essential for plant root growth, it is generally assumed that expansins play a critical role in mediating root growth and development. In plants, expansins are classified into four sub-families,
including α-expansin or expansin A (EXPA), β-expansin or expansin B (EXPB), expansin-like A (EXPLA), and expansin-like B (EXPLB) [71,72].

Since the first expansin protein was identified in cucumber (*Cucumis sativus*) hypocotyls [73], diverse biological functions of expansin members have been widely found to be associated with environmental stresses in plants [71]. However, the roles of expansins in plant adaptation to P deficiency has attracted little attention. A β-expansin gene from soybean, *GmEXPB2*, was the first one found to regulate root growth in responses to Pi starvation [65]. It was reported that *GmEXPB2* was highly induced by Pi starvation. Transgenic Arabidopsis with *GmEXPB2* overexpression exhibited increased root cell division and elongation, which subsequently enhanced plant growth and Pi uptake [65]. A follow-up report provided supporting evidence that transgenic soybean with *GmEXPB2* overexpression also had higher plant dry weight and P content compared to wild-type plants when grown in calcareous soils [66]. Similar results were reported in wheat coleoptiles: that multiple expansins (five α- and nine β-expansin genes) were up- or down-regulated in responses to Pi application [74]. Overexpression of one expansin member, *TaEXPB23*, significantly increased the number of lateral roots in transgenic tobacco (*Nicotiana tabacum*) under both high and low P conditions [74]. These results strongly suggest the involvement of expansins in mediating root growth in responses to P deficiency.

Besides enhancing tap or lateral root elongation, root hair growth is also regulated by expansins. In soybean, *GmEXPB2* was suggested to play roles in the process of soybean root hair development basing on the observation that overexpression of *GmEXPB2* dramatically increased root hair density and size of the root hair zone [75]. Similar functions were also reported for a group of expansins in other plants [71]. For example, AtEXPA7 in Arabidopsis and OsEXPA17 in rice have been documented to be required for root hair elongation [76,77], while HvEXPB1 in barley has been demonstrated to be root-hair-specific and to play roles in root hair formation [78,79]. Since increased root hair density and length is considered to improve Pi uptake efficiency in plants [80,81], root hair growth and development regulated by expansins presents a good example in which CWPs play a critical role in mediating root growth in responses to low P stress.

### 3.2. Proline-Rich Proteins

PRPs is a protein family with Pro- and Hyp-rich amino acid sequences. Following the identification of the first PRP in carrot (*Daucus carota*) storage roots [82,83], a number of PRPs have been characterized in many plant species such as soybean [84–89], bean (*Phaseolus vulgaris*) [90], Medicago [91], pea (*Pisum sativum*) [86,92], maize [93], tomato (*Lycopersicon esculentum*) [94–96], and Arabidopsis [97–99]. PRPs have multiple functions, and are assumed to participate in plant development and growth, nodule formation, pathogen infection, and abiotic stress and wounding responses [83,86,90–92,100–103].

Although the roles of PRPs in response to biotic and abiotic stresses have been well documented, little information is available on their functions in plant adaptation to P deficiency. Recently, a SRPP protein, which is partially homologous to PRPs but lacks the proline-rich domain in its N-terminal region, was reported to function in Arabidopsis responses to Pi starvation [69]. It was found that SRPP is localized in cell walls, and its transcripts are specifically accumulated in both root hairs and fruits. Furthermore, loss function of SRPP results in shorter root hair length and reduced root hair viability under Pi starvation conditions, strongly suggesting that SRPP is involved in the regulation of root hair growth and development under low P conditions [69]. Although functions of other PRPs in plant adaptation to Pi starvation remain largely unknown, it could be hypothesized that they might play a role in plants’ adaptation to Pi starvation, because transcripts of other PRP or PRP-like genes were found to be up-regulated by Pi starvation through transcriptomic analysis in plants such as Arabidopsis [104].
### 3.3. Oxidoreductases

A number of CWPs associated with oxido-reduction have been identified and functionally characterized in plant responses to Pi starvation [39,67]. A typical example is the cell-wall-localized ferroxidase LPR1 (Low Phosphate Root1), which has been well documented to play a critical role in cell-wall-mediated primary root responses to Pi starvation in Arabidopsis [67]. During Pi limitation, LPR1 modulates Fe deposition in cell walls of the root apical meristem and elongation zone, and thus leads to an oxidative environment for enhancing reactive oxygen species (ROS) generation. Meanwhile, increased accumulation of ROS in the apoplast subsequently induces callose deposition in cell walls and finally impairs SHORT ROOT protein movement and the maintenance of stem cell niche in root apical meristem [67]. On the other hand, ROS may also enhance the activity of class III peroxidases in the cell wall during Pi starvation, which could use H₂O₂ as a co-substrate and stiffen cell walls by catalyzing the cross-link between cell wall components [68,105]. However, since lateral root responses to Pi starvation are quite different from those of the primary roots, it still remains unclear whether cell wall modifications mediated by the LPR1-modulated ROS pathway are applicable to lateral root development under low P conditions.

Meanwhile, with the aid of transcriptomic and proteomics analysis, Pi-starvation-responsive peroxidases have been observed in plants [39, 106, 107]. For example, proteomics analysis of CWPs in soybean roots revealed that abundance of five peroxidase isoforms was either increased or decreased by Pi starvation, indicating a possible role of these peroxidases in soybean cell wall modification in response to low P stress [39]. Similar results were also obtained in cotton (Gossypium hirsutum): that 180 peroxidases were predicted to be secreted into the apoplast [107]. Among them, the expression patterns of 18 peroxidase genes were significantly influenced by P deficiency [107]. The results indicate complex regulation and diverse functions of peroxidases in responses to Pi starvation, suggesting that it is worth to investigating their functions in plant cell wall modification under low P conditions.

In addition, a cell-wall-targeted berberine bridge enzyme (BBE)-like protein was demonstrated to be regulated by Pi starvation in soybean roots [39]. It was revealed that protein abundance of the BBE-like protein was increased by about 6-fold under low P conditions, strongly suggesting that BBE-like protein might participate in root responses to Pi starvation [39]. The BBE protein in plants was first functionally characterized in poppy (Eschscholzia californica) in which it oxidates the N-methyl group of (S)-reticuline, yielding (S)-scoulerine [108]. In recent years, numbers of genes encoding BBE-like enzymes have been identified in plants, but functions of BBE-like proteins in plants are largely unexplored. In Arabidopsis, a total of 28 BBE-like genes have been identified [109]. The transcripts of AtBBE-like genes were found by microarray assay at different root developmental stages, such as lateral root initiation, root elongation and maturation [109, 110]. Moreover, four members of this group, including AT1G01980, AT4G20840, AT1G11770, and AT4G20830, exhibit the ability to oxidize oligogalacturonides, thus enhancing resistance to fungi [111]. Additionally, oligogalacturonides have been demonstrated to play a role in root elongation by inducing the oxidative burst in alfalfa (Medicago sativa), suggesting that BBE-like proteins might have the potential role of controlling root growth by mediated the dynamic equilibrium of oligogalacturonides in cell walls [112]. However, the functions of BBE-like proteins in plant root development in responses to Pi starvation remain enigmatic.

## 4. Purple Acid Phosphatase Functions in Cell Wall Synthesis and Pi Mobilization

Another plant adaptation strategy to low P stress is to increase the accumulation of extracellular acid phosphatase (APase), which facilitates the scavenging of Pi from organophosphate compounds in apoplasts [4,113].

PAPs belong to the APase family, which exhibits distinct biochemical properties, such as purple color in aqueous solution, activity insensitive to inhibition by L-tartrate, and a bimetallic active site [113]. The plant PAP family is composed of a large group of members and displays non-specific APase activities, which catalyze the hydrolysis of Pi from a wide range of organophosphates, with optimum reaction pH below 7.0. Although diverse functions of plant PAPs have been observed in plants, most
plant PAPs are suggested to play a critical role in P scavenging and recycling in plants, especially for extracellular PAPs [113,114].

A group of cell-wall-targeted PAPs has been well characterized in plants, including Arabidopsis, soybean, and tobacco [113]. In Arabidopsis, 14 PAPs have been identified in cell wall proteomes (WallProtDB, http://www.polebio.lrvs.ups-tlse.fr/WallProtDB/). Among them, four PAPs, including AtPAP10, AtPAP12, AtPAP25, and AtPAP26, have been functionally characterized in Arabidopsis responses to Pi starvation [115–119]; AtPAP12 and AtPAP26 contribute to over 70% of the total APase activity secreted by roots or targeted to shoot cell walls of Arabidopsis under low P conditions [115,117]. Furthermore, an *atpap12/atpap26* double mutant exhibited impaired growth when organic P (e.g., glycerol-3-phospahte and herring sperm DNA) was applied as the sole P source, strongly suggesting that cell-wall-associated AtPAP12 and/or AtPAP26 participates in recycling Pi from endogenous phosphomonoesters that leak into cell walls [118,120]. Similarly, AtPAP10 is predominantly localized to the surface of root epidermal cells and functions in the acclimation of Arabidopsis to Pi deprivation through activating organic P in solid MS medium [116,117].

Recently, an iTRAQ proteomics analysis was conducted to identify CWPs with differential accumulations in soybean roots in response to Pi starvation [39]. Among differential CWPs, a cell wall-localized PAP, GmPAP1-like, was identified to be up-regulated by Pi starvation. Furthermore, *GmPAP1-like* overexpression resulted in significant increases of both relative growth and P content in soybean hairy roots when deoxy-ribonucleotide triphosphate (dNTP) was supplied as the sole external P source, strongly suggesting that cell-wall-targeted GmPAP1-like participates in extracellular organic-P utilization in plants [39].

However, unlike GmPAP1-like, AtPAP12, and AtPAP26, a cell-wall-targeted PAP, AtPAP25, exhibited high phosphatase activity against several phosphoproteins and phosphoamino acids in vitro. Moreover, mutation of *AtPAP25* led to a reduced level of transcripts encoding *At4*, *AtPPCK1*, *AtRNS1*, *AtPAP12*, and *AtPAP17*, which were involved in Pi starvation responses. Therefore, it was suggested that AtPAP25 might function as a phosphoprotein phosphatase and play important signaling roles during Pi deprivation [119]. Similarly, a cell wall localized PAP, NtPAP12, was purified in tobacco [121]. Furthermore, it was found that NtPAP12 could dephosphorylate several cell-wall-bound enzymes, such as α-xylosidase and β-glucosidase, in vitro, suggesting that NtPAP12 might be involved in the regulation of cell wall biosynthesis [122].

Therefore, it seems that functional dissection of cell-wall-targeted PAPs will be a complex task because functions vary among PAPs owing to their respective protein structures, accumulation patterns, and a wide variety of potential substrates. Furthermore, considering that several substrates of plant PAPs have been suggested to be signaling molecules, such as ATP, it is reasonable to hypothesize that PAP could influence signaling molecule metabolism, and thus participate in the complex signaling network in plants. Therefore, identification and characterization of cell-wall-targeted PAPs will be helpful in elucidating the functions of PAP in plant acclimation to P deficiency [113].

## 5. Conclusions and Perspectives

Great progress has been made in revealing the important roles of CWPs in the modification of cell wall properties, which is crucial for the meticulous modulation of plant roots in response to P deficiency. For example, LPR1-mediated callose deposition results in the inhibition of primary root growth under Pi-starvation conditions in Arabidopsis [67]. However, the primary root growth responses of other plant species are quite different from those of Arabidopsis [39,63]; whether the same regulatory pathway also exists in other plant species remains for further studies to determine. Moreover, the plant cell wall is a complex matrix, mainly consisting of cellulose microfibrils and other wall components, such as pectins, hemicelluloses, callose, and lignin, depending on the cell wall type [14,27,123]. When plants were subjected to Pi starvation, the cell wall components were changed, thus changing the cell wall's physical properties, and subsequently influencing cell expansion [8,68]. Therefore, to understand the roles of CWPs in root modulation under low P conditions, future studies
are expected to investigate how CWPs concomitantly modulate the biochemistry and physiological
properties of the cell wall components.

In order to elucidate the functions of CWPs in cell wall adaptation to Pi starvation, identification of CWPs with differential accumulation is critical. However, few proteomic studies have been conducted to identify CWPs in response to Pi starvation, thus limiting the understanding of the functions of CWPs in plant adaptation to Pi starvation. Meanwhile, since covalently bound proteins are poorly extracted, the full coverage of plant cell wall proteomes remains challenging [37]. A better extraction protocol remains to be developed to increase this coverage.

Taken together, the studies referenced here have demonstrated that CWPs play important roles
in plant responses to Pi starvation. It can be anticipated that increased knowledge in this field will
provide important theoretical bases for engineering crops with increased P efficiency.

**Funding:** This research was funded by the National Natural Science Foundation of China (31672220 and 31872164), Nature Science Foundation of Guangdong Province (2015A030306034), Integrated Demonstration of Key Techniques for the Industrial Development of Featured Crops in Rocky Desertification Areas of Yunnan-Guangxi-Guizhou Provinces, National Key Research and Development Program of China (2016YFD0100700), the High Level Talents Special Support Plan of Guangdong Province (2015TX01N042 and 2015TQ01N078), Key R&D Program of Guangdong Province (2019B020219003) and the Research Team Project of the Natural Science Foundation of Guangdong Province (2016A030312009).

**Conflicts of Interest:** The authors declare no conflict of interest.

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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Article

Novel Insights from Comparative In Silico Analysis
of Green Microalgal Cellulases

Gea Guerriero 1,*, Kjell Sergeant 1, Sylvain Legay 1, Jean-Francois Hausman 1,
Henry-Michel Cauchie 1, Irshad Ahmad 2 and Khawar Sohail Siddiqui 2,*

Received: 10 May 2018; Accepted: 8 June 2018; Published: 15 June 2018

**Abstract:** The assumption that cellulose degradation and assimilation can only be carried out by heterotrophic organisms was shattered in 2012 when it was discovered that the unicellular green alga, *Chlamydomonas reinhardtii* (Cr), can utilize cellulose for growth under CO₂-limiting conditions. Publications of genomes/transcriptomes of the colonial microalgae, *Gonium pectorale* (Gp) and *Volvox carteri* (Vc), between 2010–2016 prompted us to look for cellulase genes in these algae and to compare them to cellulases from bacteria, fungi, lower/higher plants, and invertebrate metazoans. Interestingly, algal catalytic domains (CDs), belonging to the family GH9, clustered separately and showed the highest (33–42%) and lowest (17–36%) sequence identity with respect to cellulases from invertebrate metazoans and bacteria, respectively, whereas the identity with cellulases from plants was only 27–33%. Based on comparative multiple alignments and homology models, the domain arrangement and active-site architecture of algal cellulases are described in detail. It was found that all algal cellulases are modular, consisting of putative novel cysteine-rich carbohydrate-binding modules (CBMs) and proline/serine-(PS) rich linkers. Two genes were found to encode a protein with a putative Ig-like domain and a cellulase with an unknown domain, respectively. A feature observed in one cellulase homolog from Gp and shared by a spinach cellulase is the existence of two CDs separated by linkers and with a C-terminal CBM. Dockerin and Fn-3-like domains, typically found in bacterial cellulases, are absent in algal enzymes. The targeted gene expression analysis shows that two Gp cellulases consisting, respectively, of a single and two CDs were upregulated upon filter paper addition to the medium.

**Keywords:** cellulase; glycosyl hydrolase family 9; carbohydrate binding module (CBM); bioinformatics; RT-qPCR

# 1. Introduction

Cellulose, a linear polysaccharide of glucose linked by β-1,4-glycosidic linkages, is the most abundant biopolymer on Earth and is found in the cell walls of plants. Cellulose consists of long chains of glucose tightly packed together due to H-bonds and constitutes the chief load-bearing polysaccharide. It is embedded in a matrix of pectins and hemicelluloses, and is additionally impregnated by lignin in some instances [1]. Cellulases are grouped into endoglucanases (EC: 3.2.1.4), that randomly hydrolyse internal β-1,4-glycosidic bonds and exoglucanases (cellobiohydrolase, EC: 3.2.1.91) that processively release mainly cellobiose from the reducing or non-reducing chain

<footnote n="1">¹ Environmental Research and Innovation (ERIN) Department, Luxembourg Institute of Science and Technology (LIST), 5 Avenue des Hauts-Fourneaux, L-4362 Esch/Alzette, Luxembourg; kjell.sergeant@list.lu (K.S.); sylvain.legay@list.lu (S.L.); jean-francois.hausman@list.lu (J.-F.H.); henry-michel.cauchie@list.lu (H.-M.C.)</footnote>

<footnote n="2">² Life Sciences Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia; irshad@kfupm.edu.sa</footnote>

<footnote>* Correspondence: gea.guerriero@list.lu (G.G.); ksiddiqui@kfupm.edu.sa (K.S.S.); Tel.: +352-275-888-5023 (G.G.); +966-13-860-8397 (K.S.S.)</footnote>
extremity [2]. Processive endoglucanases that possess the properties of both endo- and exocellulases have also been described [3,4].

Based on amino acid sequence similarity, cellulases are classified into different glycosyl hydrolase (GH) families [5,6]. For example, endocellulases span the GH-families, 5–10, 12, 26, 44, 45, 48, 51, 61, 74, and 124, whereas exocellulase members are found in the GH families, 5, 6, and 9 (CAZy database, available online: http://www.cazy.org/Glycoside-Hydrolases.html). Most cellulases involved in the degradation of cellulose deriving from plant lignocellulosic biomass are produced by bacteria, archaea, fungi, and protozoa [7]. Some bacteria, oomycetes, protozoa, sea squirts, the fungus *Microdochium nivale* [8] and especially plants synthesize cellulose for growth and development, and, hence, require cellulases to degrade, modify, and remodel cellulose [9]. Some microorganisms (bacteria, fungi, protozoa) that live in a symbiotic relationship within the guts of phytophagous organisms also produce cellulases [10]. Later it was discovered that, apart from cellulolytic enzymes from symbionts, invertebrates also possess endogenous cellulases secreted by salivary glands and the gut [11]. Until recently, it was considered that cellulose catabolism was limited to heterotrophic organisms and higher plants (for remodeling cellulose). However, in 2012, it was experimentally established that the photosynthetic microalga *Chlamydomonas reinhardtii* (Cr) can utilize cellulose for growth in the absence/limitation of other C-sources by secreting endocellulases [12]. The alga combines features of both plants and animals (it is considered a "planimal" [12]), and has a genome characterized by an expansion of transporter gene families, indicative of an adaptation to life in soil environments [13].

In view of the biotechnological applications of novel cellulases in the degradation of lignocellulosic biomass to produce biofuel, here, we bioinformatically analyze, for the first time, cellulases from three microalgal species whose complete genomes have been published and compared [14,15]. We choose cellulase homologs from microalgae with increasing multicellularity (unicellular alga *C. reinhardtii*; colonial algae *Gonium pectorale*, Gp, with 16 and *Volvox carteri*, Vc, with 2000–6000 cells) and compare their sequences with different cellulases from diverse taxonomic groups. We model all the microalgal cellulase homologs and analyze in detail conserved motifs and their phylogenetic relationship, arrangement of different domains, and active-site architecture in addition to examining carbohydrate-binding modules (CBMs) and linker regions. We conclude this study by determining the expression levels of three cellulases in Gp in a control condition and after the addition of crystalline cellulose substrate (filter paper) to the growth medium.

## 2. Results and Discussion

The present work is based on the discovery that the photosynthetic microalga, *C. reinhardtii*, can secrete cellulases into the medium under CO₂-limiting conditions, although cellulase secretion was not detected in the closely related Chlorella kessleri [12]. Interestingly, Chlorella has cellulose, whereas Cr, Gp, and Vc do not have cellulose in their cell walls [16]. In the present paper, we discuss the sequence and structural analysis of cellulases from three members of Chlorophyceae (Cr, Gp, and Vc) with increasing cellular complexity (from single cells to colonies).

### 2.1. Algal Cellulases Belong to Glycosyl Hydrolase Family 9

The structurally and functionally important conserved residues show that all algal sequences of catalytic domains (CDs) belong to the inverting GH9 family of CAZymes (Carbohydrate-Active Enzymes) with (α/α)₆-barrel topology. Glucanases, belonging to the GH family 9, are considered the most conserved cellulases and are widely distributed among bacteria, fungi, amoebozoa, invertebrate metazoans, mosses, ferns, gymnosperms, and angiosperms [17]. Three conserved regions are identified in the CDs of algal cellulases (Figure 1 lower panels, Supplementary Figure S1a), consistent with the motifs/patterns of GH9 cellulases reported from across diverse taxonomic groups [17]. The variation of amino acids at each position within each region is compared between microalgal (Figure 1, lower panels) and all other GH9 cellulases described (Figure 1, upper panels) [17]. Region I of microalgal cellulases contains the characteristic DAGD motif where, in addition to
H-bonding of acidic residues with water (Figure 1, lower panel and asterisks), the C-terminal D acts as the catalytic base that extracts a proton from the nucleophilic water and the N-terminal D acts as an essential supporting residue [3,18–20]. The pattern corresponding to Region I, ([LVS]-x-[GK]-G-[WFYLM]-[YHF]-D-[ACGS]-G-[DSN]-X(2)-[KMR]-[FAILY]-X-[FWYLQTV]-[APTN S]-[MLGAQS]) has now been included in the PROSITE database (PS60032) [21]. Interestingly, in Region I of GH9 from all other organisms, D (catalytic base) is replaced by an N in the Angiosperm *Medicago* and G in few sea-squirt isoenzymes [17]; however, the activities of these enzymes have not been determined. In Region I of GH9 from all other organisms, two G and a K residues are also conserved, however, their role in catalysis has not yet been elucidated (Figure 1, upper panel).

The comparison of Region II (PROSITE pattern, PS00592) reveals that, although H and R residues (Figure 1, upper panels) are involved in substrate-binding via H-bonding [18,19], both residues are not conserved. The H is replaced by V in Vc and by S in *Panesthia cribrata* (Metazoa), whereas R is replaced by K and S in microalgae and by A or G in many GH9 cellulases [17]. An interesting finding about Region II of algal cellulases is the presence of an extra four residue sequence (PT[PTA][YSG]) (Figure 1, lower middle panel), which is missing in non-algal GH9 enzymes, with the exception being two cellulase homologs (CrCel9D and Gp KXZ44756) (Supplementary Figure S1a). The PROSITE pattern, PS00592, has now been revised to [HLY]-[AILMV]-[FIL]-G-x-[NSTW]-x(2,4)-[SCTV]-[FY]-[LIVMFY]-[SITV]-G-x(1,5)-[GSY]-x(2)-[AFPSTY]-[FLPSV]-x(2)-[AILPQVM]-[HV]-[DHLS]-[KRS] [21].

Residues in Region III are involved in substrate-binding and catalysis (Figure 1, asterisks), with fully conserved E acting as an acid that protonates the leaving group [19,22] and stabilizes the positively-charged oxocarbonium transition-state [18,23]. The fully conserved nucleophilic D forms H-bonds with the residues of the active-site loop, comprising of regions I and II, to bring it in proper alignment [18].

<figure><img src="image_73.png" /><figcaption>**Figure 1.** Variation in amino acids at each position within three conserved motifs of microalgal cellulases compared to other consensus sequences of GH9 cellulases from across the taxonomic groups. The sequences from different taxonomic groups were chosen, as mentioned in Figure 2. Upper panels, sequences from [17]; lower panels, microalgal sequences (this study). The gaps are denoted by dashes. *, catalytic, and binding residues. Blue residues, variations in algal sequences. The extra four residues in Region II is found in all algal cellulases, except CrCel9D and Gp KXZ44756. “X” refers to extra residues in Region II not shown by [17]. The pattern corresponding to Region I updates the PROSITE Database.</figcaption></figure>

## 2.2. Algal Cellulases Are Closest to Invertebrate Metazoan GH9 Enzymes

The percentage identity matrix (Supplementary Figure S1b) and the phylogenetic analysis (Figure 2) of CD regions (such as blue highlighted regions, Supplementary Figure S1a) from GH9 cellulases reveal that algal cellulases are closer to invertebrate metazoan enzymes than to plants.
The identity matrix of GH9 family cellulases from selected groups show that algal enzymes have the highest (33–42%) and lowest (17–36%) sequence identity, with proteins from invertebrates and bacteria, respectively, whereas the identity with cellulases from plants is 27–33% (Supplementary Figure S1b).

Full length sequences of GH9 cellulases have other domains, such as CBM, immunoglobulin (Ig-like), fibronectin type III (Fn3-like), and dockerin, which can produce a bias during phylogenetic analysis [17]. To accurately determine the similarity, all cellulases were truncated to comprise only CDs (Supplementary Figure S2) and the phylogenetic tree was then constructed. The phylogenetic analysis revealed that truncated GH9 cellulases cluster together within a taxonomic group and that algal cellulases are closer to invertebrate metazoan enzymes (Figure 2), as suggested by the identity matrix (Supplementary Figure S1b). Notably, the GH9 belonging to the representatives of a specific (Sub)Kingdom (notably, Eubacteria, Fungi, Metazoa, Plantae) cluster together, except for *Ciona savignyi*, which does not form a cluster with the other representatives of Chordata *Branchiostoma floridae* and *Ciona intestinalis*, but clusters, instead, with arthropods. *C. intestinalis* forms a separate branch where the two cellulases analyzed are found together. The only representative of the Kingdom Protista (Phylum Amoebozoa), *Dictyostelium discoideum*, clusters in a sister clade to the one formed by bacteria. Interestingly, the cellulases from the green microalgae, *G. pectorale*, *C. reinhardtii*, *V. carteri*, and *Chlorella zofingiensis*, do not cluster with GH9 from Plantae, but instead form separate groups. This is consistent with the hypothesis that GH9 genes are related by vertical descent and not by horizontal gene transfer [17]. Particularly, the *G. pectoral*, GH9 KXZ44756, is sister to *C. reinhardtii* CrCel9D, which is the gene described as being strictly induced by crystalline cellulose [12].

<figure><img src="image_74.png" /></figure>

**Figure 2.** Maximum likelihood phylogenetic tree of GH9 cellulases (built using catalytic domains, CD in the protein sequences; see Supplementary Figure S2) from different species (100 bootstraps). The circles refer to the bootstraps (range 0.6–1; the size of the circles is proportional to the bootstrap values). The name of the species analyzed and their accession numbers are indicated in the tree. The *V. carteri* cellulases are indicated VC2958622 and VC2952174. The different colors represent the different taxonomic groups, i.e., either (Sub) Kingdoms, Phyla, Divisions, or Orders.

## 2.3. Algal Cellulases Are Multimodular

Sequence alignment (Supplementary Figure S1a) and homology models (Figure 3) reveal that algal GH9 cellulases consist of catalytic and non-catalytic modules. Multidomain cellulases are widespread among many taxonomic groups, however, cellulases from anaerobic bacteria, found in cellulosomes,
have the most complex architecture consisting of different types of modules (Supplementary Figure S3). For example, *Clostridium cellulolyticum* produces 13 GH9 modular cellulases containing a different number and arrangement of CD (single), CBM (0–2), dockerin (0–1), and Ig-like domain (0–1) [24]. However, among templates, only the full sequences of 1JS4/4TF4 and 1KFG/1GA2, comprising CD, linker, and CBM, have been crystallized (Supplementary Figure S3) [18,25]. Multimodular cellulases are more efficient than free enzyme (with only CD) due to synergism because of the close proximity between the enzyme and the cellulosic substrate [1,2,26]. Glycosylated linkers provide flexibility to the CD for higher activity [27] and protease protection, as well as increased binding to the cellulose surface [28] (see also Section 2.6). The statistics regarding homology-based modelling are given in Supplementary Table S1, showing the top templates employed by I-TASSER, such as 1KS8 (an endocellulase from a termite), 1JS4, 1TF4 (mixed endo-/exocellulase from *Thermobifida fusca*), and 1UT9 (exocellulase from *Clostridium thermocellum*).

<figure><img src="image_75.png" /><figcaption>**Figure 3.** Homology models of selected family GH9 cellulases. Blue, CD (catalytic domain); pink, CBM (carbohydrate binding module); grey, linker; yellow, Ig-like domain; red/?, unknown. Organism names, accession/PDB codes, and cellulase types are given alongside the structures. (a) Cr, *Chlamydomonas reinhardtii*; (b) and (c) Gp, *Gonium pectoral* and *Vc, Volvox carteri*. The X-ray structures of templates (PDB: 1JS4/4TF4, 1KFG/1GA2, 1UT9, 1KS8, 1CLC and 2YIK) used by I-TASSER for generating homology models are given in Supplementary Figure S3. The domain arrangement is given below the structure, with a dot showing separation between two adjacent domains. CD, catalytic domain; CBM, carbohydrate-binding module; arrow, linker. The I-TASSER statistics are given in Supplementary Table S1 and the X-ray structures of templates are given in Supplementary Figure S3.</figcaption></figure>
Some physicochemical properties (Supplementary Table S2) and arrangement of various domains in algal (Figure 3) and some other non-algal cellulases (Supplementary Figure S3) are given. In addition to GH9 CDs, all algal cellulases were found to have putative CBMs linked to CD by linkers, except CrCel9C (hereafter, indicated, for simplicity, as Cr9C; Figure 3a). Only Cr9C was found to have an Ig-like domain and no CBM, whereas Cr9D had an unknown sequence at the N-terminus (Figure 3a). Interestingly, Gp KXZ51468 (hereafter, referred to as Gp51468) had two consecutive CD, separated by two linkers with a single CBM (CD1-linker-CD2-linker-CBM), whereas Vc2952174 has two putative CBMs and a single CD. Spinach cellulase (Supplementary Figure S3b,c) was found to have a similar domain arrangement to Gp51468, whereas the bacterial cellulase from *Caldocellum saccharolyticum* has one family GH9 CD and another family GH48 CD, along with three CBMs [29]. In contrast to bacterial cellulases [30], dockerin and Fn3-like domains were found to be absent in algal, plant, and invertebrate metazoan cellulases (Figure 3). Multimodular microalgal cellulases were found to be closest to invertebrate metazoan homologs (Figure 2, Supplementary Figure S1b); however, in contrast to the modular cellulase from abalone, many invertebrate cellulases (such as termite) were found to be non-modular (Supplementary Figure S3).

### 2.4. Active-Site Architecture Shows Different Types of Cellulolytic Activities in Algal GH9 Cellulases

Cellulolytic organisms secrete different types of cellulases, in addition to β-glucosidases, xylanases and lignin-degrading enzymes [1,7]. In this work, we focus on microalgal cellulases. Various residues (white) involved in substrate binding (S-labelled), Ca⁺⁺-binding (M-labelled), catalytic residues (C-labelled), and loops (pink boxed) within the CD (blue highlighted region) are shown in the multiple alignment (Supplementary Figure S1a). All the catalytic acidic residues are strictly conserved in all GH9 cellulases, including microalgae (Figure 1 upper panel, Supplementary Figure S1a and Figure 4a). However, there is variation in Ca⁺⁺-binding residues among algal and other GH9 cellulases, probably reflecting different metal-binding affinities. For example, a D residue is substituted by an A and G in Vc2952174 and 1UT9, respectively (M-labelled, blue highlighted, Supplementary Figure S1a), that are unable to bind calcium. In glucanases, the active-site is mostly lined by aromatic residues in order to bind sugar moieties, although polar amino acids are also present (Figure 4b). These amino acids bind to cellulose via H-bonding and hydrophobic interaction, whereas aromatic amino acids interact via CH-π interaction with the sugar rings [18,31]. The substrate-binding residues around the active-site pocket are mostly conserved among GH9 sequences (Figure 4b), however, there are exceptions (red residues, Supplementary Figure S1a). In Region II (Figure 1, lower panel), highly conserved H and R are replaced by V465 and K467, respectively, in Vc2952174 (Supplementary Figure S1a).

Cellulases can be classified into endo-, exo-, and exo/endo- (also called processive endoglucanases) [3,4] (Figure 5). It has been shown that cellulases with similar sequences have different specificities, implying that exo- versus endo-versus exo/endo activities are a consequence of subtle differences in and around the active-site cleft [32]. However, in spite of this limitation, modelling of algal CDs may give valuable insight into their likely mode of action, although determination of X-ray structures and experimental data obtained via enzyme assays using various substrates (soluble, amorphous, and crystalline), as well as product analysis (cellobiose versus oligosaccharides), are more reliable options [4].
<figure><img src="image_76.png" /><figcaption>**Figure 4.** Active-site pocket of selected GH9 cellulases showing conserved residues around the substrate superimposed on each other. (a) Catalytic-residues (above, E412; below left to right, D54, D57) and (b) binding-residues (above from left to right: W253, F205, H124, R361, W127; below from left to right: H306, Y417, W301, Y408, H359). The residue number refers to that of termite (PDB, 1KS8). Red, substrate (C4 + C2); blue, termite; green, algae; pink, spinach; black, *T. fusca* (4TF4); orange, fungus (*Neocallimastix patriciarum*).</figcaption></figure>

<figure><img src="image_77.png" /><figcaption>**Figure 5.** Various mechanisms of GH9 family cellulases found in algal enzymes. (a) Random cleavage of cellulose by endoglucanases to form oligosaccharides; (b) sequential cleavage of cellulose by GH9 exoglucanase-like enzyme due to partial blockage of the active site similar to that found in CbhA from Ruminiclostridium, 1UT9; (c) sequential cleavage of cellulose by processive endoglucanases (also called exo/endo cellulases) into oligosaccharides not longer than cellotetraoses due to blockage after the –4 binding site. Numbers (–4 to +2) show binding subsites (non-reducing to reducing) in the cellulase catalytic domain (blue). Arrows show the cleavage site; hexagon, glucose units.</figcaption></figure>

Space-filled active-sites of algal and selected GH9 cellulases derived from homology models of CD were compared with the X-ray structures of endocellulases, an exoglucanase (both from GH6 and GH9 families), and mixed exo/endo processive endoglucanases (Figure 6). Binding and catalytic residues are shown as space-filled atoms, along with cellotetraose + cellobiose substrates (Figure 6b, top and lower panels). The X-ray structures of 4TF4 from *T. fusca* and 1KFG from *C. cellulolyticum*, with their respective oligosaccharides, were found to superimpose perfectly on each other, implying that the substrate can be modelled on algal cellulases, with the aim to locate the position of the substrate and orientation of subsites within the active-site [3,25]. To show the accessibility of the substrate, the degree of indentations and obstructions in the form of blockages and cavities around the active-site
are depicted in different shades of color ranging from orange/red (humps) to dark blue (depressions) (Figure 6, middle panels).

Cellulose is a very recalcitrant crystalline polymer due to intensive H-bonding between tightly packed glucose chains [1] and the cleavage of β-glycosidic bonds is much more energy-demanding than α-linked glycosidic bonds [33]. Glucanases that act on cellulose are broadly divided into endocellulases and exocellulases [34]. Endocellulases have an open cleft or groove structure that allows the binding of many sugar units to randomly cleave internal bonds, with concomitant release of cellulose chain after every cleavage and, finally, producing oligosaccharides (Figure 5a). In contrast, exocellulases (cellobiohydrolases) from the families, GH5 and GH6, such as from *Humicola insolens* (Figure 6f), have a tunnel structure due to loops that partially cover the active-site, enabling the cellulose chain to thread through [5]. This geometry allows exoglucanase to hold on to the cellulose chain during product release without losing the chain to the surroundings. During such a processive movement, every alternate glucose unit is presented to the active site, resulting in the liberation of the cellobiose product [35].

In nature, however, the differentiation between an exo- and endo-acting cellulase is, at best, blurred, since many cellulases show characteristics of both endo- and exocellulase, depending on the active-site architecture and/or the presence of CBM close to the reducing end of the active-site [3,18,35,36]. True exocellulase with unique tunnel-like active-sites, such as in GH6 cellobiohydrolase [35] (Figure 6f, *H. insolens*), have not yet been found in GH9 family cellulases. However, one GH9 member (CbhA from *Ruminiclostridium*, 1UT9) was shown to have exocellulase activity (despite the absence of a tunnel-like active site), which was explained by the abrupt blockage of the active-site after the –2 subsite by a GEDNGLW loop, which is absent in other GH9 cellulases (Figures 5b and 6e). However, a transient tunnel formation by extended loops (DIYA-NDDY, Supplementary Figure S1a; Figure 6p–r) upon substrate binding has also been proposed [23].

The mixed exo/endo type cellulases show some type of blockage of the active-site [3,18]. A classic example showing this type of active-site architecture is a processive cellulase (E4) from Thermobifida fusca in which the non-reducing end is blocked (Figure 6c grey "tower block"). This block acts as a "measuring stick", resulting in cleavage products that are not any longer than cellotetraose that exit towards the bottom, whereas the remaining chain is held in place by the C-terminal CBM and is fed to the active-site in a processive manner (Figure 5c) [3,18]. With time, the enzyme cleaves cellulose and celooligosaccharides (G5-G6) into cellotetraose and smaller oligosaccharides (G1-G3). Further incubation of G3-G6 celooligosaccharides with the E4 results in the formation of a mixture of cellotetraose, cellotriose, cellobiose, and glucose products, as determined by thin-layer chromatography using purified enzymes [37]. The formation of cellotriose and cellobiose from amorphous and crystalline cellulose by cloned and purified *Clostridium thermocellum* and *Saccharophagus degradans* processive endoglucanases has also been demonstrated [4]. Other mechanisms have also been described to account for processive endoglucanases, including the presence of a CBM that binds cellulose, disrupts its crystalline structure, and feeds substrate to the active-site. Additionally, an increase in the substrate affinity for the active-site to prevent instant dissociation of the cellulose chain after initial attack has also been proposed [36]. Interestingly, a change discovered in a single amino acid around the active-site can convert a non-processive into a processive pectinase [38]. Later work extended this to *C. cellulolyticum* cellulases and proposed that the presence of a single critical aromatic residue around the active-site can influence the processive behaviour [22].

The active-site architecture of all algal enzymes, except Vc2952174, illustrates a fully open cleft (Figure 6a–n upper panels) with tower blocks towards the non-reducing end, suggesting that these may either be GH9 exo (as 1UT9) [23] or exo/endo processive enzymes [5,19,39]. The active-site architecture and the accessibility analysis of algal enzymes, such as Cr9D and Gp44756, is indicative of an open cleft and the absence of any "tower blocks" on the non-reducing end of the active-site (Figure 5a; Figure 6i,l, upper and lower panels), implying that these may simply be pure endocellulases [22].
The cavity analysis gives additional support for the presence of humps (greenish to yellowish shades) near the non-reducing end (—4 subsite) in the exo/endo-type of cellulases, whereas the active-site cleft is depicted in shades of blue depending on the depth (Figure 6j,k,m,n, middle panels). The lower panels (Figure 6) show the view from the reducing end looking down to the active-site cleft. This view confirms that, whereas pure endoglucanases (1KS8, a; 1CLC, b, Cr9D, i; Gp44756, l; Figure 6, lower panels) show low-height obstructions, GH9 exo/endo and exo-type of cellulases are characterized by tower blocks (Figure 6, lower panels; 4TF4/1JS4, c; 1KFG, d; 1UT9, e; Cr9B, g; Cr9C, h; Gp51468, j and k; Gp51466, m and both Vc cellulases, n and o). As both GH9 exo- and exo/endo processive cellulases are characterized by tower blocks (Figure 6), to unambiguously distinguish between these two types, loops responsible for purely exocellulase activity in CbhA from *Ruminoclostridium* (1UT9) were modelled for all algal enzymes (Figure 6p–r). Modeling of CbhA (1UT9) shows that these extra loops (QGY-WGS and NSPH-GCFT, Supplementary Figure S1a, pink boxed) are responsible for exo-activity by either partially covering the active-site near the non-reducing end (—4 subsite) or by running parallel along the active-site (IYAE-NDDY, Supplementary Figure S1a). This specific conformation means that they are modeled to cover the active-site upon substrate binding (Figure 6p–r, red loops) [23].

Among all algal cellulases (Figure 6g–o), only Vc2952174 has the necessary loop (CVSR-GSAR, Supplementary Figure S1a) that can block the active-site (Figure 6o,r; light pink) similar to that of CbhA exo-cellulase (red loops). In purely endo (1KS8) and exo/endo (4TF4) cellulases, these loops point away from the active-site, as seen in all algal cellulases except Vc2952174 (Figure 6p–r). The loops in all microalgal cellulases (Figure 6p–r), equivalent to the CbhA long loop (Figure 6p–r, red), running parallel to the active-site are much shorter. In the absence of X-ray structures and experimental data, it is not clear whether these shorter loops in microalgal cellulases will occlude the active-site upon substrate binding, such as in CbhA [23]. It is noteworthy that, in Vc2952174 (CVSR-GSAR) and Cr9B (THTD-GSSS), there is an extra loop that is absent in all cellulases described here (Supplementary Figure S1a). This loop covers the active-site in Vc2952174 (Figure 5b; Figure 6r, light pink loop), but is farther away from the active-site in Cr9B (Figure 6p, yellow loop).

Currently available experimental data on Chlamydomonas (Cr) cellulases can be exploited in support of our assignment of different algal cellulases as GH9 exo-, endo-, and exo/endo types. These cellulase types can be differentiated on the basis of substrates utilized and products released [12]. Cellulases with open clefts, such as exo-acting GH9, endo, and exo/endo, can hydrolyze filter paper, as well as carboxymethyl cellulose (CMC). However, whereas endo-acting enzymes form oligosaccharides preferably from amorphous cellulose, exo and exo/endo-acting enzymes can also produce cellobiose [18,34,37]. The published results showed that a mixture of all three Cr cellulases can utilize both CMC, crystalline Avicel, and filter paper, with the release of C5, C4, and C3, as well as C2 (cellobiose) as products, suggesting the presence of either an exo- or an endo- and at least one processive mixed exo/endo types of cellulase [12].

Collectively, based on the experimental data of Cr cellulases [12] and active-site and loop analysis described here (Figure 6), it can be deduced that all algal cellulases are likely to be exo/endo processive enzymes (presence of tower blocks with exo-loops shortened and pointing away from the active-site), except for Cr9D (Figure 6i) and Gp44756 (Figure 6l), which seem to be endoglucanases (absence of tower blocks with exo-loops shortened and pointing away from the active-site). The corresponding tower block (Figure 6e, 1UT9), due to extra loops [23] responsible for exocellulase activity in CbhA, seems to be pointing away from the active-site or is shortened in all microalgal cellulases, except in Vc2952174 (Figure 6o) where the loop (light pink) covers the active-site (Figures 5b and 6r). However, it is possible that these shortened loops in microalgal enzymes (Figure 6p–r) may close the active-site upon substrate binding. It is interesting that both the C- and N-terminal CDs in Gp51468 seem to have similar activities (processive exo/endo). It is noteworthy that Gp51468 is composed of two CDs separated by a linker, which is also found for spinach cellulase (Figure 3).
<figure><img src="image_78.png" /><figcaption>**Figure 6.** *Cont.*</figcaption></figure>
<figure><img src="image_79.png" /><figcaption>**Figure 6.** Active-site architecture of selected family GH9 cellulases determined from X-ray structures and homology models. Upper panels (**a-o**): Top view of the active-site. Critical residues surrounding the active-site. Blue, H; pink, W; turquoise, R/K; yellow, S; in lieu of substrate-binding, W; green, Y; orange, F; red, catalytic residues (E/D); grey, blocking residues/loops; Middle panels (**a-o**): Cavity analysis of the active-site pocket highlighting clefts, tunnels, and blocks in various shades. Dark blue, completely buried; orange/red, at least 75% surface accessible. Upper and middle panels showing substrate (C4 + C2) from -4 non-reducing (left) to +2 reducing end (right); Lower panels (**a-o**): View of the active-site from +2 to -4 subsite looking down the cleft/barrel highlighting the absence or presence of “tower blocks” (grey) at the non-reducing end. The extra loop in Vc2952174 (**o**) is shown as ball and stick (pink); (**p-r**): Analysis of the blocking loops/secondary structure elements in microalgal CDs compared with 1KS8, (endo-type, white), 4TF4 (exo/endo-type, brown) and 1UT9 (exo-type, red);</figcaption></figure>
(p) Cr9B (XP_001701544), yellow; Cr9C (XP_001701546), light green, Cr9D (XP_001696497), dark green; (q) N-Gp (KXZ51468), turquoise; C-Gp (KXZ51468), blue; Gp (KXZ51466), magenta, Gp (KXZ44756), orange; (r) Vc (XP_002952174), light pink; Vc (XP_002958622), dark blue. Black, cleaved hexose substrate. The text description is as in Figure 3.

## 2.5. Novel Cysteine-Rich CBM in Algal Cellulases

The non-catalytic CBMs recognize polysaccharides and promote the association of the enzyme with its substrate, although standalone CBMs that are not linked to CDs have also been described [40]. Based on sequence similarity, CBMs are currently divided into 83 families (CAZy database available online: http://www.cazy.org/Carbohydrate-Binding-Modules.html). Three main functions of CBMs have been described [40] that include concentrating CDs of enzymes on the surface of polysaccharides for enhanced degradation, targeting distinct regions of a polysaccharide, such as crystalline cellulose [41,42], and, possibly, disrupting polysaccharide structure via replacement of H-bonds in crystalline cellulose by H-bonds from polar residues in CBM [3,43]. In addition, CBMs were proposed to help feed cellulose chain into the catalytic site, especially in the case of processive endocellulases [18].

Among the microalgal cellulases that have been described here, only Cr9C does not have a CBM, whereas all other enzymes have CBMs located on the C-terminal side, with Vc2952174 having two CBMs (Figure 3). Multiple alignment (Supplementary Figure S1a, pink highlighted), phylogenetic analysis (Supplementary Figure S4 built using the sequences in Supplementary Figure S5), and identity matrix of putative microalgal CBMs compared to CBMs across different families (1–6, 10, 11, 12, 14, 17/28, 18, 20, 41, 43–45, 47–50, 53, 81) and taxonomic groups (bacteria, fungi, microalgae, invertebrates, plants) shows low similarity between them. The identity matrix of top hits (Supplementary Figure S6) shows that, although Cr, Gp, and Vc putative CBMs have high identity (15–75%) with each other, microalgal CBMs show lower identity (19–27%) across members of known families, implying that Cr, Gp, and Vc CBMs do not belong to any of the previously described families in the CAZy database (available online: http://www.cazy.org/Carbohydrate-Binding-Modules.html). Like CBM14 and 18 family members, Cr, Gp, and Vc putative CBMs have a high percentage of cysteine residues.

To identify motifs in Cr, Gp, and Vc, CBM sequences from members belonging to different families and taxonomic groups were subjected to MEME analysis (Table 1). In addition to 2-C motifs that were found in all algal CBMs, 6-C and 4-C residue motifs were only found in Cr9B, Gp51466, Gp51468, and Vc2958622 (Table 1, motifs 1–2). It is noteworthy that none of the microalgal CBMs (Cr, Gp and Vc) have a Hevein motif characteristic of cysteine-rich CBM18 members. None of the motifs 1–3 are found in any other algal, bacterial, fungal, or plant CBMs, including Cys-rich CBM1, CBM14, and CBM18, nor in CBMs that are commonly associated with endo- (EC:3.2.1.4) and exoglucanases (EC: 3.2.1.91). Based on our results (Supplementary Figures S3 and S4, Table 1), we propose that Cys-rich algal GH9-appended CBMs are classified into a new CBM family or two separate families. One family may include Cr9B, Gp51466, Gp51468, and Vc2958622, whereas another family may include Cr9D, Gp44756, and Vc2952174.

It has been proposed that a lack of aromatic residues in the CBM binding region, along with flexible linkers, results in a decreased cellulose-CMB affinity that can promote movement and feeding of the cellulose chain to the catalytic site of processive endoglucanes [18]. In the context of microalgal GH9-appended exo/endo processive glucanase (Section 2.4, Figure 6), described here, this feature may be crucial, however, the absence of structural data precludes drawing any further conclusions. The presence of multiple C residues (10–16) in algal cellulases is also intriguing. For example, a CBM-like region on the C-terminal side of a CD/linker containing an eight cysteine-box with 4-disulfide bridges has been proposed to promote substrate binding, help in the folding of secretory proteins, maintain conformational stability, and induce a conformational change required for activity [44]. In the present study, the identification of novel CBMs in Cr, Gp, and Vc is solely based on the evidence
that modular cellulases require CBM modules, along with CD and linkers (Supplementary Figure S1a). In view of the novelty of algal CBMs described here, binding data between CBMs and cellulose is vital for unequivocal confirmation.

<table><caption>**Table 1.** Motif analysis of GH9-appended microalgal CBMs (carbohydrate binding modules) by MEME.</caption><thead><tr><th>E-Value/Cys</th><th>Motifs</th><th>Proteins</th></tr></thead><tbody><tr><td>Motif 1<br>6-C 5.4e-30</td><td></td><td>Cr9B, Gp51466, Gp51468, Vc2958622</td></tr><tr><td>Motif 2<br>4-C 7.8e-10</td><td></td><td>Cr9B, Gp51466, Gp51468, Vc2958622</td></tr><tr><td>Motif 3<br>2-C 4.1e-7</td><td></td><td>Cr9B, Cr9D, all three Gp, Vc2958622</td></tr><tr><td>Hevein Motif:<br>7 C</td><td></td><td>General CBM18 motif</td></tr><tr><td>6 C</td><td>[CG]X<sub>5-7</sub>[C]X<sub>4</sub>[CCS]X<sub>4</sub>[C]X<sub>6</sub>[C]X<sub>3</sub> [C]<br>[CG]X<sub>6</sub>[C]X<sub>5</sub>[CCS]X<sub>4</sub>[C]X<sub>7</sub>[C]</td><td>Plants (MS), Fungus (BD)<br>Diatom (Fc)</td></tr></tbody></table>

None of the CBM1 and CBM14 motifs were found in any Cr, Gp, and Vc sequences. For a comparison, the consensus sequence of the Hevein motif is provided in the table.

## 2.6. Algal Cellulases Have PS-Rich Linkers

The linkers were, generally, thought of simply as a connecting “rope” between CD and CBMs, which, due to their flexibility, allow cellulases to nudge forward on the surface of cellulose with a caterpillar-like movement [45]. However, recent data point to many crucial functions, such as binding of glycosylated linkers to cellulose substrate [28] and the modulation of endoglucanase activity [42]. Putative linkers have been found in all algal cellulases (Figure 7). All these linkers are located between CD and CBMs, except in Cr9C, which is lacking a CBM (Figure 3). Collectively, algal linkers can be roughly classified into P/S-rich (N-Gp51468, C-Vc2952174 and Vc2958622), P/S/T-rich (Cr9D) and non-P/S/T linkers (Cr9B, Cr9C, Gp51466, C-Gp51468 and N-Vc2952174). Although it is straightforward to identify PS/PT linkers [29,46], it is not possible to confidently assign linker functions to non-P/S/T regions because of high sequence variability [27,30,46] (Figure 7). In cellulases, the average length of linkers is 20–50 residues [47]. However, linkers as small as 6–14 residues long and lacking S and/or T residues and as long as >100 residues have been reported in addition to the substitution of Ig-like or Fn3-like domains in lieu of linkers between CD and CBD modules (Figure 3) [27,30,32,46]. Interestingly, Vc2952174 has two linkers (N-Vc2952174 lacking P/S/T residues and C-Vc2952174 rich in P/S residues), one for each CBM (Figures 3 and 7). On the other hand, Gp51468 has two linkers on the C-terminal side of a single CBM (Figure 3), where N-Gp51468 is PS-rich and C-Gp51468 is lacking P, S, and T residues (Figure 7). It is intriguing to note that GH9-appended microalgal linkers have a preponderance of PS residues (Figure 7), which contrasts with PT residues found in the invertebrate metazoan abalone [48] and *Caldocellum saccharolyticum* cellulase linkers [29]). While many cellulase-appended linkers from *Pseudomonas fluorescence* are S-rich, these have very low P content [32,47], unlike microalgal linkers, which are found to be P/S-rich (Figure 7).

Glycosylation shows great diversity that depends on the sugars (type, sequence, chain length, branching point, anomeric nature) attached to various amino acid side chains that, generally, include N for N-linked modification; S, T, and Y for O-linked modification via the OH-group, and W for C-mannosylation. Whereas N-linked glycosylation requires a N-X-S/T consensus sequence (X can be any amino acid, except P), no consensus motif has been described for O-glycosylation. As glycans are secondary gene products, glycosylation is also cell/tissue and species specific [49]. Although N-glycosylation of the secreted proteins in microalgae is well documented [50], no information is available regarding O-glycosylation in modular algal glucanases. However, glycosylation in fungal glucanases, including *Trichoderma reesei*, has been described that displays extensive modification of
linkers with di- and tri-saccharides at OH-groups of T and S residues [51]. S and T residues confer different properties to glycosylated peptides. In contrast to S, the steric repulsion between the side chain methyl group in T and the carbohydrate moiety can drastically alter the sugar to peptide backbone orientation with the possibility of altered water structure and/or H-bond formation [52]. These modifications likely lead to changes in the binding affinity of S versus T O-glycosylated peptides to the polysaccharide substrate, however, further experimental verification is required in the case of cellulase linker-cellulose interaction.

The presence of linkers with different amino acid sequences implies different functions. Linkers are highly divergent in lengths and sequences, but typically contain G, P, S, and T residues. P imparts extended conformation [53] and does not form H-bonds, while G provides flexibility, and S/T are often involved in O-glycosylation, which confers rigidity, stability, and protease-resistance [27,47]. Recent studies have found that the length (distance between the CD and CBM) and rigidity/flexibility of linkers play a critical role in the efficient functioning of cellulases; however, the precise role of a linker in the structure-function of modular cellulase is not yet fully understood [54]. For example, an increase in the number of PS/T boxes enhanced the cellulolytic activity on crystalline cellulose due to desorption of the enzyme from the substrate [55], whereas progressive shortening of linkers were shown to cause a decrease in flexibility, with concomitant reduction in activity and enhancement in stability [56].

<figure><img src="image_80.png" /><figcaption>**Figure 7.** Linkers in microalgal cellulases (between the arrows). Black, PS, or PST linkers; red, putative linker sequence (or may be part of C-terminal CD or N-terminal CBM).</figcaption></figure>

## 2.7. Expression of Cellulases in *Gonium Pectorale* (Gp)

RT-qPCR revealed an increased expression when *Gonium* was cultivated in the presence of cellulose for two of the three cellulases analyzed in this study (Figure 8). The genes, *Gp51466* and *Gp51468*, showed a statistically-significant increase in expression in the presence of filter paper. The cellulase encoded by *Gp44756* shows a trend, which is, however, not statistically-significant. Nevertheless, if we consider the phylogenetic position of *Gp44756*, the modelling results shown in Figure 6 and the gene expression analysis, it is reasonable to assume *Gp44756* is the *G. pectorale* ortholog of *CrCel9D*.
<figure><img src="image_81.png" /><figcaption>**Figure 8.** Gene expression analysis of the three *G. pectorale* cellulases after growth for 14 days under continuous light in the presence/absence of 0.1% (*w/v*) filter paper. Asterisks denote statistically-significant values after Student's *t*-test (*p*-value < 0.05).</figcaption></figure>

# 3. Materials and Methods

## 3.1. Computational Methods

The cellulase accession numbers are indicated in the phylogenetic tree. The sequences were taken from [17], manually truncated to CDs, and enriched by blasting in the Metazome database (Available online: https://metazome.jgi.doe.gov/pz/portal.html#!search?show=BLAST). The physico-chemical properties of algal cellulases were determined using the ProtParam tool (Available online: http://web.expasy.org/protparam/). Conserved domains and GH-family assignment were identified with the MotifScan (Available online: http://myhits.isb-sib.ch/cgi-bin/motif_scan) and ScanProsite [21] algorithms. The pair-wise multiple alignment of algal cellulases for identifying conserved residues and motifs were determined by using CLUSTAL-W (Available online: http://www.ebi.ac.uk/Tools/msa/clustalo/) [57]. The 3D homology models of the algal sequences comprising complete sequences, as well as only CD regions, were generated with I-TASSER Suite (Available online: http://zhanglab.ccmb.med.umich.edu/I-TASSER/) [58] utilizing LOMETS, SPICKER, and TM-align. The models were then refined using REMO by optimizing the backbone hydrogen-bonding networks and FG-MD by removing the steric clashes and improving the torsion angles. Separate homology models for Gp1468 and the spinach homolog were generated due to the presence of two CDs. The residues implicated in substrate binding and activity were manually annotated using the 3D structures of cellulase templates available in the PDBsum database (Available online: http://www.ebi.ac.uk/thornton-srv/databases/cgi-bin/pdbsum/GetPage.pl?pdbcode=index.html) [59], CLUSTAL-W, and COACH/COFACTOR tools within the I-TASSER Suite and published literature. The final structures showing various domains, conserved regions, motifs, and active-site architecture (including surface accessibility, blocks, clefts, and tunnels) were visualized by superimposing each model on the *T. fusca* template (4TF4) in the presence of cellotetraose substrate from -1 to -4 subsites and cellobiose from +1 to +2 subsites with DeepView Swiss-PdbViewer v4.1 (Available online: http://www.expasy.org/spdbv/) [60]. For the phylogenetic analysis, truncated CD and CBM sequences (the sequences are given in Supplementary Figures S2 and S5) were aligned with Clustal-W and the alignment submitted to PhyML [61] (available at http://phylogeny.lirmm.fr/phylo_cgi/one_task.cgi?task_type=phyml) to obtain a maximum likelihood phylogenetic tree (100 bootstraps). The tree
was visualized with iTOL-Interactive Tree of Life (Available online: http://itol.embl.de/). Putative CBMs in Cr, Gp, and Vc algae were analyzed using MotifScan and the CAZY database (Available online: http://www.cazy.org/Carbohydrate-Binding-Modules.html) by a manual search through all 83 families. For CBM analysis, the selected sequences from the CAZY database belonging to various families were truncated to only CBM parts by subjecting these sequences to MotifScan (Available online: https://myhits.isb-sib.ch/cgi-bin/motif_scan). Full sequences were used for standalone CBMs, especially from the algae and for those sequences where CBM motifs were not identified. The CBM sequences were aligned using CLUSTAL-W and subjected to the MEME tool (Available online: http://meme-suite.org/tools/meme) for the discovery of novel motifs [62].

### 3.2. Growth of G. pectorale, RNA Extraction, cDNA Synthesis and RT-qPCR

G. pectorale (strain K3-F3-4, mating type minus, NIES-2863 obtained from the Microbial Culture Collection at National Institute for Environmental Studies, Tsukuba, Japan; Available online: http://mcc.nies.go.jp/) was grown under continuous light (1300 lux) in 50 mL of modified Bold's 3N medium (UTEX, Austin, TX, USA) for 14 days in the presence/absence of autoclaved 0.1% *w/v* Whatman Grade 1 filter paper (Merck, Darmstadt, Germany). Algae were centrifuged for 10 min at 15,000× *g*, the pellet immediately frozen in liquid nitrogen, and cells disrupted using sterilized 5 mm stainless steel beads and a bead beater (Retsch MM400, Aartselaar, Belgium) set at 20 Hz for 2 min (the holders were previously cooled with liquid nitrogen to avoid heating of the samples during disruption). Total RNA was extracted using the Qiagen RNA extraction kit (Qiagen, Leusden, The Netherlands) coupled to the on-column DNase I digestion. The RNA purity and quality were measured with a Nanodrop ND-1000 (Thermo Scientific, Villebon-sur-Yvette, France) and a 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA), respectively. Two hundred nanograms of RNA were retrotranscribed into cDNA with the ProtoScript II RTase (New England Biolabs, Leiden, The Netherlands) and random primers, according to the manufacturer's instructions.

The cDNA was diluted to 2 ng/µL and 2 µL were used for the RT-qPCR analysis (final volume of the reaction: 10 µL) in 384-wells plates. An automated liquid handling robot (epMotion 5073, Eppendorf, Hamburg, Germany) was used to prepare the plates, which were run on a Viia™ 7 System (Thermo Scientific, Villebon-sur-Yvette, France). The TaqMan Low ROX 2x Mix was used (Takyon, Eurogentec, Seraing, Belgium). To ensure robust results, the TaqMan chemistry was used to evaluate *Gonium* cellulase relative expression (fluorescent dye and quencher used are FAM-TAMRA, target-specific primers and probes are given in Supplementary Table S3). The expression of the *Gonium* cellulases was calculated with qbase⁺ version 3.1 (Biogazelle, Zwijnaarde, Belgium; Available online: www.qbaseplus.com) after normalization using the genes, *rpl23* and *eef1*, that the program, *geNorm™*, identified as the most stable. Normalized relative quantities were calculated according to [63], by considering specific target PCR efficiency and multiple reference gene normalization. Here, four candidate reference genes were validated for gene expression analysis, the eukaryotic translation elongation factor, 1α *eef1*, *rpl23*, encoding the 60S ribosomal protein, L23, *tbpA* coding for the TATA-box binding protein and *tubA1* coding for α tubulin. For statistical analysis, the normalized relative quantities exported from qbase⁺ were subjected to a Student's *t*-test, as implemented in Excel.

The primers used in this study are reported in Supplementary Table S3. Primers were designed using Primer3Plus (Available online: http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi/) and further checked with the OligoAnalyzer 3.1 tool from Integrated DNA technologies (Available online: http://eu.idtdna.com/calc/analyzer). Primer efficiencies were checked via qPCR using 6 points of a serial five-fold dilution of cDNA starting at 20 ng.

## 4. Conclusions and Future Direction

This is the first report on the bioinformatics of algal family GH9 cellulases. The GH9 catalytic domains of algal cellulases form a distinct group, which is phylogenetically closer to invertebrate metazoan than plant or bacterial homologs. All algal enzymes were found to be modular
and analysis of the active-site architecture of the considered CDs indicates endoglucanase and mixed
exo/endo (processive endoglucanase) types of activities. It has been suggested that the lack of
pure cellobiohydrolases (exo-acting) in algae are compensated by the presence of many processive
endoglucanases, along with endocellulases, to produce a simple and efficient enzyme system for
the degradation of cellulose [4]. Except for Cr9C, all cellulase homologs have at least one putative
C-terminal novel cysteine-rich CBM. The presence of novel CBMs and PS-rich linkers, in combination
with CDs, indicate that the studied cellulases may have enhanced catalytic properties suitable for
the efficient degradation of cellulosic biomass. In this context, Gp51468 is of special interest as it
is composed of two CDs with exo/endo activities, two different linkers, and a single CBM. Future
work will involve cloning, purification, and crystallization of Gp51468 to fully understand its mode
of action, as well as growing it in the presence of different cellulosic substrates for the production of
valuable biochemicals.

**Supplementary Materials:** Supplementary materials can be found at http://www.mdpi.com/1422-0067/19/6/
1782/s1.

**Author Contributions:** G.G. and K.S.S. conceived the idea of writing the paper and designed the experiments; G.G., K.S.S. performed the experiments; K.S., S.L. and I.A. contributed to the experimental work concerning bioinformatics and the Taqman-based RT-qPCR; G.G., I.A., K.S.S. analyzed the data; G.G. and K.S.S. wrote the paper draft; all authors discussed, contributed to and edited the paper.

**Acknowledgments:** The personal assistance of K.S.S. and I.A. by KFUPM is acknowledged.

**Conflicts of Interest:** The authors declare no conflict of interest.

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