Transcriptome analysis reveals the molecular mechanism of differences in growth between photoautotrophy and heterotrophy in Chlamydomonas reinhardtii

doi:10.21203/rs.3.rs-3636939/v1

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Research Article

Transcriptome analysis reveals the molecular mechanism of differences in growth between photoautotrophy and heterotrophy in Chlamydomonas reinhardtii

https://doi.org/10.21203/rs.3.rs-3636939/v1

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published 19 Jun, 2024

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Background

Chlamydomonas reinhardtii can grow photoautotrophically and heterotrophically, and is the typical model species for heterotrophy increasingly cultured in commercial cultivation. By observing their growth changes, transcriptomic analysis and molecular regulation, we investigated the molecular mechanism of differences in growth from photoautotrophy 12h (P12h) to heterotrophy 12h (H12h).

Results

We observed changes in the cell numbers, OD750, Fv/Fm, and total chlorophyll content of photoautotrophy and heterotrophy during 10 days and they were significantly different. These indicators were further analyzed between photoautotrophy 12h (P12h) and heterotrophy 12h (H12h), and the P12h group was significantly higher than the H12h group. The transcriptome data demonstrated that a total of 2,970 differentially expressed genes (DEGs) were identified between the P12h and H12h groups. There were 10 DEGs involved in the photosynthesis and carbon fixation metabolic pathway, 18 DEGs involved in the glycolysis and the TCA cycle metabolic pathway, 8 DEGs related to the pyruvate metabolic pathway, and 17 DEGs related to the oxidative phosphorylation. To explore the relationship between DEGs and the major metabolic pathways, the relative expression levels of marker genes and key enzyme activities were examined. The relative expression levels of MDH, SDH, ATPase and SSS were increased significantly from P12h and H12h. NAD-MDH and SDH activity of the H12h group was significantly higher than the P12h group.

Conclusions

Our study exhibited characteristics of early fermentation in Chlamydomonas reinhardtii. Based on analysis of transcriptome and biochemical, we speculated the nutrient and energy metabolism models and partly elucidated the molecular mechanism of both the heterotrophic and autotrophic Chlamydomonas reinhardtii. Our study provides preliminary evidence for the differences in the growth of photoautotrophy and heterotrophy in algae.

Chlamydomonas reinhardtii

photoautotrophy

heterotrophy

transcriptomics

metabolic pathways

As we all know, microalgae are found in oceans and lakes around the world. They are abundant in vitamins, fatty acids, proteins, and several nutrients, which are important food sources for fish, shellfish, and other animals [1, 2]. Microalgae are typically autotrophic organisms that depend on organic and inorganic carbon sources for cell growth [3]. Phototrophic microalgal species are capable of producing energy and carbon for growth using only inorganic compounds and light. Heterotrophic microalgal species are wholly dependent on preformed organic material for nutrition [4]. In addition, a small proportion of microalgae can be both photoautotrophic and heterotrophic [5]. Some microalgal species cannot utilize organic carbon to grow. A deficiency of glucose-concentrating capacity was demonstrated in three cases: Nostoc sp. (PCC7118) and two Synechocystis strains (PCC6308 and PCC7008) [6]. Spirulina sp. was able to grow photoautotrophically, heterotrophically, and mixotrophically [7]. Chlorella vulgaris was able to grow in both autotrophic and heterotrophic conditions. While autotrophic growth did provide higher cellular lipid content, the lipid productivity was much lower compared with that from heterotrophic growth [8]. The green alga Chlamydomonas reinhardtii can grow photoautotrophically utilizing CO₂, heterotrophically utilizing acetate, and mixotrophically utilizing both carbon sources [9]. Chlamydomonas reinhardtii is an excellent model organism with which to study photosynthesis, cell physiology, and photoprotective mechanisms [10]. Previous studies have shown that Chlamydomonas reinhardtii is mainly photoautotrophic through light-related metabolic pathways such as photosynthesis, chlorophyll metabolism, glycolysis, the TCA cycle, and pyruvate metabolism. Whereas, when the cultural environment was heterotrophic, Chlamydomonas reinhardtii mainly showed dark hypoxic metabolism and acetic acid metabolism [11].

With the rapid development of omics, physiological data and omics-based technologies such as transcriptomics, metabolomics, and proteomics have been increasingly used cooperatively to provide mechanistic insights into growth differences of microalgae in different culturing conditions [3, 12]. Transcriptome sequencing (RNA-seq) is a cost-effective and time-saving approach to survey the putative differentially expressed genes (DEGs) and contribute to understanding biological processes and metabolic pathways of microalgae from autotrophic to heterotrophic growth [12, 13]. Transcriptome analyses contributed to finding the target genes and pathways that could be the focus of further physiological and molecular research [14]. Recent studies have summarized recent advances in transcriptomic research on heterotrophic and autotrophic protists, including physiology and metabolism, development and life cycles, environmental and ecological studies [15]. However, there is little research focus on the transcriptome comparing the growth differences between Chlamydomonas rheinensis under autotrophic and heterotrophic conditions.

Therefore, this study attempted to identify molecular alterations during the transition from autotrophy to heterotrophy in Chlamydomonas reinhardtii by combining physiological, transcriptomic, and molecular biology methods. The ultimate goal was to elucidate the molecular basis for differences in growth between photoautotrophy and heterotrophy in Chlamydomonas reinhardtii and to provide a theoretical basis for the in-depth research on the photoautotrophy and heterotrophy in algae.

Cell strain and culture conditions

Chlamydomonas reinhardtii strain CC-125 was obtained from the Chlamydomonas Resource Center (CRC, University of Minnesota). For photoautotrophy, CC-125 cells were continuously cultured in a high-salt (HS) medium [16], and heterotrophy was cultured in tris–acetate–phosphate (TAP) medium [17] in 500 mL Erlenmeyer flasks (with 150 mL medium). The air was bubbled into the medium at 0.4 L/min using an LZB-3WB float-type flowmeter (Nanjing Shunlaida Measurement and Control Equipment Co., Ltd), which was required for photoautotrophy. The photoautotrophy was cultured under a temperature of 25 ℃ with a light intensity of 80 µmol m^− 2 s^− 1, a 24:0 h (light: dark) photoperiod, and constant shaking at 120 rpm. By contrast, the culture condition of heterotrophy was the same as above except for the light time, which was a 0:24 h (light: dark) photoperiod.

In the transcriptome analysis, the CC-125 strain was cultured in photoautotrophy for 12 hours, then collected 2×10^7 algal cells (for the P12h group). The remaining CC-125 cultures were rinsed three times with TAP medium and immediately transferred to a conical flask containing TAP medium for further heterotrophy cultivation (as mentioned above) for 12 hours. We again collected 2ⅹ10^7 algal cells (for the H12h group). These algal cells were rinsed with PBS three times, then transferred into liquid nitrogen for quick freezing, and transferred to a -80℃ refrigerator for storage.

Growth measurement and morphological observation

The cell density of Chlamydomonas rheinensis was measured by cell counting and optical density methods under autotrophic and heterotrophic culture modes. Chlorophyll was extracted using an 80% acetone solution and the concentration of chlorophyll a (Chl a), chlorophyll b (Chl b), and total chlorophyll were measured using spectrophotometry as described by Lichtenthaler et al [18]. The following equations [19] (Unit: µg/mL) were used:

Ch a = 12.21 × A₆₆₃ – 2.81 × A₆₄₆ (1)

Ch b = 20.13 × A₆₄₆ – 5.03 × A₆₆₃ (2)

Ch l = Ch a + Ch b (3)

Transcriptome analysis

Total RNA was extracted and sequenced by previous methods [20].The clustering of index-coded samples was performed on the cBot Cluster Generation System using the Tru Seq PE Cluster Kit v3-cBot-HS (Illumina). After cluster generation, libraries were prepared for sequencing on the Illumina Nova seq platform, generating 150 bp paired-end reads. FPKM was the expected number of fragments per kilobase of transcribed sequence per million base pairs sequenced, took into account the effect of sequencing depth and gene length on read counts and was the method most frequently used to calculate gene expression levels. Cluster Profiler R package was used to implement a gene ontology (GO) enrichment analysis of the differentially expressed genes (DEGs) that were adjusted for gene length bias. We used a corrected P-value of ≤ 0.05 and a |log2 (fold change) | ≥ 1 to evaluate significant gene expression differences. GO keywords were deemed to be significantly enriched by DEGs [21]. The KEGG [22] database was used to understand high-level biological system functions and utilities based on molecular data, particularly sizable molecular datasets produced by genome sequencing and other high-throughput experimental technologies (http://www.genome.jp/kegg/). The statistical enrichment of DEGs in KEGG pathways was further analyzed in some key metabolic pathways.

Determination of key enzyme activities

For enzyme activities, we used CC-125 cells that were stored at -80 ℃ in a refrigerator. After adding PBS (5 million cells/1 mL, 1 × PBS), the CC-125 cells were disrupted by sonication. After centrifugation at 10000 g at 4°C for 10 min, the supernatant was removed and kept on ice for testing. Then, we transferred the supernatant into a test tube containing 10 mL of distilled water and shook it before use. Key enzyme activities were then detected using the following kits: Rubisco-Bisphosphate Carboxylase/Oxygenase (Rubisco) Activity Assay Kit, NAD-Malate Dehydrogenase (NAD-MDH) Activity Assay Kit; Soluble Starch Synthase (SSS) Activity Assay Kit; Pyruvate Kinase (PK) Activity Assay Kit; Succinate Dehydrogenase (SDH) Activity Assay Kit; ATP Activity Assay Kit.

Real-time quantitative PCR

RNA was extracted for Novogene analyses. After determination the RNA quality using agarose gel electrophoresis, complementary cDNA synthesis was carried out using Rever Tra Ace q PCR RT Master Mix with gDNA Remover (TOYOBO). Quantitative real-time PCR (qRT-PCR) was performed using TB Green® Premix Ex Taq™ II to measure the relative transcript levels of the genes associated with metabolic changes. The gene encoding UBC8 was used as the endogenous control. The genes of interest and the primers are listed in Supplementary Table S6. The means of the individual biological samples (n = 3) were calculated and used to determine the ratio and the respective log2 value using Microsoft Excel (Microsoft) and SPSS 20.0 (SPSS).

Statistical analysis

The experiments were performed with three replicates for each treatment. The results of the biochemical and physiological parameter values obtained for all the variables were subjected to analysis of variance (one-way ANOVA, P < 0.05) followed by Tukey's test (P ≤ 0.05) using SPSS 20.0 software. The results of the qRT-PCR were calculated as described above. PowerPoint, GraphPad Prism 8, and Paint 3D (Windows 10) were used to draw and modify the figures.

Effects of photoautotrophy and heterotrophy on the growth of Chlamydomonas reinhardtii

As shown in Fig. 1, the growth characteristics of Chlamydomonas rhineae in autotrophic and heterotrophic conditions were quite different. We examined some indicators related to the growth of Chlamydomonas rhineae under autotrophic and heterotrophic cultures, including the cell numbers, OD₇₅₀, Fv/Fm, and total chlorophyll content. The number of cells increased significantly during these 10 days in photoautotrophy and heterotrophy (Fig. 1a). The changes in OD₇₅₀ of the Chlamydomonas reinhardtii were investigated (Fig. 1b). It increased significantly to a maximum of 0.66 in photoautotrophy from the 0 day to 4 day, and then it declined slightly over the next few days. By contrast, the heterotrophy increased to its highest point of 0.671 on the eighth day, and then it decreased slowly between the eighth day and the tenth day. The Fv/Fm of photoautotrophy and heterotrophy shared the same downward trend, but heterotrophy was falling faster (Fig. 1c). The total chlorophyll content of photoautotrophy rose considerably from the 0 day to the 4 day and then declined gradually in the following days. By contrast, the total chlorophyll content of photoautotrophy did not change abruptly, with variation from 2.4 µg/mL to 2.6 µg/mL (Fig. 1d). To observe the differences in above indicators between photoautotrophy 12h (P12h) to heterotrophy 12h (H12h), we showed bar graphs as in Fig. e-h. The P12h group was significantly higher than the H12h group in the cell numbers, OD750, Fv/Fm, and total chlorophyll content.

Analysis of transcriptome in P12h and H12h

For a better insight into the differences in growth, biochemical composition, and photosynthetic physiology of photoautotrophy and heterotrophy in the Chlamydomonas reinhardtii, transcriptome analysis was used in this study. We constructed total RNA libraries of P12h and H12h by RNA-sequencing (Fig. 2). According to Illumina sequencing, the transcriptome sequencing of Chlamydomonas reinhardtii produced 39.84–47.81 million raw reads (Illumina NovaSeq 6000). Fastp (version 0.19.7) was used to filter the raw data, obtaining over 37.57 million clean reads (Supplementary Table S1). The dependability and credibility of the data were shown by a strong correlation coefficient (R² > 0.909) of gene expression between biological replicates (Supplementary Fig. S1). To assess differences in the sequencing data between P12h and H12h, holistic principal component analysis (PCA) was performed. The first and second principal components explained 44.61% and 19.38% of the variation, respectively (Fig. 2a). The Venn diagram showed the number of uniquely expressed genes in P12h or H12h, and overlapping areas showed the number of co-expressed genes in both groups (Fig. 2b). The differential genes were screened with p-value ≤ 0.05 and the absolute value of log2 (FC) ≥ 1 as the screening condition. A total of 2970 differential genes (1317 upregulated, 1653 downregulated) were identified between P12h and H12h groups (Fig. 2c). The heat map indicated the expression levels of DEGs in P12h and H12h groups (Fig. 2d). The data columns from the two culture conditions P12h and H12h, per column represented the corresponding biological replicate. The color scale from red to blue indicated the normalized relative abundance of each transcript, the red colors represented up-regulated genes and blue represented down-regulated genes. Additionally, DEGs clustered with the R package Mclust demonstrated that the group had similar expression profiles.

Functional annotations and classification of DEGs

To explore the regulatory role of DEGs between P12h and H12h, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. In the comparison of the DEGs from H12h vs. P12h, the GO analysis showed enrichment of three categories Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). They were mainly enriched in ATP hydrolysis and energy transport, including sulfuric ester hydrolase activity, cofactor binding, energy-coupled proton transmembrane transport, and coenzyme binding (Supplementary Fig. S2). In P12h vs. H12h, the top 20 GO enrichments with DEGs were mainly enriched in membrane part, ATP hydrolysis, energy transport cofactor binding, transporter activity and cation binding (Fig. 3a). Additionally, the Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analysis for the DEGs revealed that the majority of the DEGs were involved in the manufacture of secondary metabolites (Supplementary Fig. S3). The top 20 KEGG pathway enrichment analysis demonstrated that the DEGs in P12h vs. H12h were mainly enriched in several metabolic pathways including biosynthesis of secondary metabolites, carbon metabolism, biosynthesis of amino acids, oxidative phosphorylation, citrate cycle, chlorophyll metabolism, and others (Fig. 3b).

To further understand how DEGs regulate metabolic pathways involved in the growth of C. rein-hardtii in P12h and H12h, the DEGs were mapped to four main metabolite-related pathways (the photosynthesis and carbon fixation metabolic pathway, the glycolysis and the TCA cycle metabolic pathway, the pyruvate metabolic pathway and the oxidative phosphorylation) and analyzed the expression levels (FPKM value) of DEGs.

Analyses of the DEGs related to the photosynthesis and carbon fixation metabolic pathway in P12h and H12h

According to KEGG enrichment analysis, the photosynthesis and carbon fixation metabolic pathway was one of the representative pathways in P12h and H12h. Based on previous studies and transcriptome data, the simplified photosynthetic carbon fixation metabolic pathway was constructed in Fig. 4a. The 10 DEGs were identified related to the photosynthetic carbon fixation pathway (Supplementary Table S2), four of these genes involved in C4-Dicarboxylic acid cycle including AST, MDN2, MME, and AAT. The expression levels of these genes increased from P12h to H12h according to the FPKM values of the transcriptome (Fig. 4b). MDN1 and MME involved in the crassulacean pathway (CAM), and their expression levels were elevated in P12h vs. H12h according to the FPKM values. Ribulose-1,5-bisphosphate carboxylase (Rubisco) was a key enzyme in the process of the Calvin cycle, and its expression pattern was decreased (Fig. 4b).

Analyses of the DEGs related to the glycolysis and the TCA cycle metabolic pathway in P12h and H12h

A total of 20 DEGs were screened and related to the glycolysis and the TCA cycle metabolic pathway (Supplementary Table S3). A proposed glycolysis and the TCA cycle metabolic pathway was built based on these identified DEGs (Fig. 5a). The expression levels of these DEGs were analyzed according to the FPKM values of the transcriptome (Fig. 5b). The expression levels of two key enzymes in glycolysis pathway phosphoglucomutase (GPM1) and glyceraldehyde 3-phosphate dehydrogenase (GAPN1) were up-regulated. The glyceraldehyde 3-phosphate dehydrogenase (GAP2) and pyruvate kinase (PYK6) were down-regulated in Chlamydomonas reinhardtii from P12h to H12h. The pyruvate, an intermediate of glycolysis, enters the tricarboxylic acid cycle (TCA). The expression levels of 11 key enzymes were significantly increased between P12h and H12h (Fig. 5). The expression of most DEGs significantly increased from P12h to H12h. However, there were three genes including ALD5, PYK6, and GAP2 whose expression levels were downregulated from P12h to H12h (Fig. 5b).

Analyses of the DEGs related to the pyruvate metabolic pathway in P12h and H12h

To understand the roles of DEGs in regulating the pyruvate metabolic pathway, correlation analysis between the pyruvate metabolic network and the expression profiles of the DEGs were performed (Fig. 6). In this study, a total of 8 shared DEGs were identified to be implicated in the pyruvate metabolic pathway, including ALD5, PYK6, MME1, PDC1, ACS, MDN1, MDN3 and FUM1 (Fig. 6a and Supplementary Table S4). According to the FPKM values of the transcriptome, the expression of ALD5 and PYK6 gradually decreased from P12h to H12h. By contrast, the expression levels of MME1, PDC1, ACS, MDN1, MDN3 and FUM1 were dramatically up-regulated (Fig. 6b).

Analyses of the DEGs related to the oxidative phosphorylation in P12h and H12h

According to the transcriptome results, the 17 DEGs involved in oxidative phosphorylation, were significantly up-regulated from P12h to H12h (Fig. 7 and Supplementary Table S5). Based on previous research we constructed a diagram of complex Ⅴ (ATP synthase) which was a key enzyme in oxidative phosphorylation (Fig. 7a). Moreover, the 12 genes were summarized together with ATPase to catalyze ATP synthesis (Fig. 7b). Transcriptome data revealed that the expression levels of these genes were significantly elevated in P12h vs. H12h by the FPKM values of the transcriptome (Fig. 7b).

The relative expressions of marker genes

To further explore the relationship between DEGs and the major metabolic pathways mentioned above, the relative expression levels of RBCL, MDH, SDH, Atpase, and SSS were detected by qRT-PCR (Fig. 8). Detailed analysis indicated that ribulose-1,5-bisphosphate carboxylase (RBCL) transcripts were improved from P12h to H12h, without significant difference between the two groups (Fig. 8a). The relative expression patterns of MDH, SDH, ATPase and SSS were increased significantly between P12h and H12h. As shown in Fig. 8b, relative expression levels of NAD-malate dehydrogenase (MDH) in the H12h group were significantly higher than in the P12h group. Figure 8c demonstrated that the expression of succinate dehydrogenase (SDH) in the P12h group was 1.0120 and dramatically increased to 12.2199 in the H12h group. In P12h vs. H12h comparison group, the expression of the ATP synthase (ATPase) increased significantly (P < 0.05) (Fig. 8d). The expression of starch synthase (SSS) improved from only 1.0319 in P12h group to 13.0615 in H12h group (Fig. 8e). These results were consistent with RNA-seq.

The change of key enzyme activities in P12h and H12h

To comprehend the roles of key DEGs in the regulation of main metabolic pathways, the change of key enzyme activities was examined. The enzyme activities were investigated including Rubisco, NAD-MDH, SSS, PK and SDH between the P12h group and the H12h group (Fig. 9). The activity of Rubisco showed a significant decline (p < 0.01) from the P12h group to the H12h group (Fig. 9a). In contrast, the NAD-MDH activity of H12h group was significantly higher than the P12h group (Fig. 9b). The change of SSS activity and Pyruvate kinase activity were no significant among two groups, presented in Fig. 9c and Fig. 9d. The activity of SDH was markedly increased (p < 0.01) from P12h group to H12h group (Fig. 9e).

Photoautotrophy and heterotrophy affect the growth of C. reinhardtii

The photoautotrophic growth is an attractive cultivation because it can be used for natural resources, for example, sunlight and carbon dioxide. Even though photosynthetic autotrophy has these advantages, the maximum biomass concentration can be negatively correlated with light penetration [24]. The heterotrophy of microalgae is cultivated in the dark where the cell growth and reproduction are supported by organic carbons [25]. It has been reported that heterotrophic growth of the diatom Nitschia laevis, the dinoflagellate Crypthecodinium cohnii, and the rhodophyte Galdieria sulphuraria accumulated much higher cell densities and biomass productivities than autotrophic growth cells [26–29]. The Chlorella protothecoides had been described, in which lipid content was much higher than in photoautotrophic cultures [25]. The previous results indicated that cultivation conditions had significant effects on C. reinhardtii biomass productivity and bioproduct accumulation [30]. It demonstrated that the biomass, carbohydrates, and chlorophyll b production were higher in photoautotrophic growth. In contrast, lipids and chlorophyll concentrations were higher in heterotrophic growth [31]. Our results represented Fv/Fm and total chlorophyll content of photoautotrophy were significantly higher than heterotrophy (Fig. 1). The previous study reported that the chlorophyll content of Nannochloropsis and Chlorella were reduced in heterotrophic condition, compared with autotrophic condition [32]. Chlorophyll is a green pigment that has a strong ability to absorb light energy and transmit, therefore, reduced content of chlorophyll illustrates that the growth of cells may be less dependent on solar energy in heterotrophic conditions.

Transcriptomics reveals the expression of DEGs from autotrophs to heterotrophs

In previous studies, the transcriptome was widely used in heterotrophic and autotrophic microalgae including physiology and metabolism, development and life cycles, environmental and ecological studies [33]. In this study, the transcriptomics analysis was estimated for samples from photoautotrophy (P12h) and heterotrophy (H12h). As shown in Fig. 1, the P12h group and H12h group, each group had three samples. The PCA and correlation coefficients for parallel samples displayed differences between groups and sample duplication within groups. The results suggested that RNA-seq was accurate and reliable (Fig. 2 and Supplementary Fig. S1). In total, 12742 and 12328 genes were obtained in P12h and H12h of C. reinhardtii, respectively, as shown in Fig. 2b. Differentially expressed genes (DEGs) were analyzed by pairwise statistical comparisons between P12h and H12h. A total of 498 up-regulated genes and 893 down-regulated genes were screened by p-value < 0.05 and the absolute value of log2 (FC) > 2 in Fig. 2d. Heatmap showed the FPKM expression patterns that were normalized, mean-centered, and scaled by Z-score method.

The GO analysis showed enrichment of ATP hydrolysis and energy transport (Supplementary Fig. S2). These DEGs were particularly abundant in the proton-transporting two-sector ATPase complex. The majority of the DEGs had enhanced sulfuric ester hydrolase activity under the molecular function category (Fig. 3a). Additionally, the KEGG pathway enrichment analysis for the DEGs revealed that the majority of the DEGs were involved in secondary metabolites. These DEGs were mainly enriched in several metabolic pathways, including the biosynthesis of secondary metabolites, porphyrin and chlorophyll metabolism, glycolysis (amino sugar and nucleotide sugar metabolism and ascorbate and alternate metabolism), energy transmission (2-oxocarboxylic acid metabolism), and amino acid metabolism (other types of O-glycan biosynthesis) (Supplementary Fig. S3). In the bubble chart of KEGG enrichment, we found that amino acid metabolic pathways (e.g., alanine, aspartate, and glutamate metabolism; arginine biosynthesis; phenylalanine, tyrosine, and tryptophan biosynthesis; cysteine, methionine metabolism, and one carbon pool by folate) were enriched in H12h vs. P12h, and some glycometabolism pathways (glyoxylate, dicarboxylate metabolism, and the citrate cycle (TCA cycle)) were enriched in the H12h vs. P12h (Fig. 3b). Above results suggested that these metabolic pathways presumably involved in the growth of C. reinhardtii under heterotrophy.

Functional analysis of DEGs in main metabolic pathways

Further functional evaluation of DEGs was performed by analyzing the important metabolic pathways, including photosynthesis carbon fixation, glycolysis, the TCA cycle, pyruvate metabolic, and oxidative phosphorylation. The Calvin cycle is an important process of carbon fixation in photosynthesis which chloroplasts convert air-borne CO₂ into carbohydrates [34, 35]. Rubisco is a rate-limiting enzyme of the Calvin cycle, which catalyzes the carboxylation of ribulose 1, 5-diphosphate with CO₂. In this study, the expression level of Rubisco was significantly down-regulated under the P12h condition in comparison to the H12h condition shown in Fig. 4a. Crassulacean acid metabolism (CAM) is a specialized photosynthetic pathway that temporally separates the nocturnal CO₂ uptake, via phosphoenolpyruvate carboxylase (PEPC, C4 carboxylation), from the diurnal refixation by Rubisco (C3 carboxylation) [36]. The genes involved in C4 photosynthesis have been identified in Chlamydomonas reinhardtii, including PEPC, ME, MDH, and pyruvate phosphate dual kinase [37]. In this pathway, NAD-dependent malate dehydrogenase (MDN1) and Malate dehydrogenase (MME) were significantly increased from P12h to H12h.

The key reactions of glycolysis and tricarboxylic acid cycle (TCA) were summarized in Chlamydomonas reinhardtii, as shown in Fig. 5. Moreover, the expression levels of malate dehydrogenase (MDN1, MDN3) and oxoglutarate dehydrogenase E2 component (OGD2) were enhanced. Studies found that the carbon flux distribution was different in autotrophic and heterotrophic conditions [38, 39]. In the heterotrophic condition, glucose was mainly metabolized by the pentose phosphate pathway, by contrast, autotrophic condition the glycolytic pathway was utilized for microalgae [40]. The above findings were consistent with our results.

Pyruvate is the main product of cytosolic glycolysis and the primary respiratory substrate for energy production to support cell growth in most organisms [41]. It is first oxidized by the mitochondrial pyruvate dehydrogenase complex (PDC) then produces acetyl-CoA which enters the tricarboxylic acid cycle (TCA) and, finally, generates reductant equivalent for ATP production [42, 43]. Our results demonstrated that eight genes were identified involved in pyruvate metabolism, and the expression levels of ALD5 and PYK6 were declined, while the expression levels of the other six genes were significantly elevated including MME1, PDC1, ACS, MDN1, MDN3, and FUM1 from P12h to H12h in Fig. 6.

Oxidative phosphorylation of cells is the main form of energy generation to maintain vital life activities. There are four main membrane-bound complex I [44], complex II [45], complex III [46, 47], and complex IV [48] participate in mitochondrial oxidative phosphorylation. The mitochondrial complex V (F₀F₁-ATP synthase) catalyzes the phosphorylation of ADP to produce ATP by inorganic phosphate using the proton motive force generated by the electron transport chain. In bacteria, ATP synthase consists of eight subunits, α₃β₃γδϵab₂c_n, and F₁ corresponds to α₃β₃γδϵ and F₀ to ab₂c_n [49], shown in Fig. 7a. Transcriptomic results demonstrated that 17 genes were related to oxidative phosphorylation. Among them, 12 genes were involved in ATPase catalysis and the expression levels of these genes were dramatically raised from P12h to H12h in Fig. 7. These differences between photoautotrophic and heterotrophic conditions indicated that the cells may transport the excess electrons through cyclic electron transport chain under heterotrophic condition. The genes involved in ATPase were also activated in heterotrophic conditions, indicating that ATP was required for cell phosphorylation.

Molecular mechanism through which DEGs regulate between P12h and H12h

In this study, the activity and expression levels of key enzymes were analyzed in the above major metabolic pathways. Firstly, the relative expression levels of RBCL, MDH, SDH, ATPase, and SSS were measured by qRT-PCR. RBCL is the major soluble protein in plants, which catalyzes the initial step in Calvin's reductive pentose phosphate cycle [50]. The expression pattern of RBCL was slightly increased from P12h to H12h, as shown in Fig. 8a. NAD-malate dehydrogenase (MDH) plays a crucial role in several metabolic pathways including the TCA cycle, glyoxylate bypass, amino acid synthesis, and so on [51]. Succinate dehydrogenase (SDH) catalyze the oxidation of succinate to fumarate and thereby linking the TCA cycle [52]. The starch synthase (SSS) and the ATP synthase were key enzymes in the starch metabolism pathway. Moreover, the transcripts of MDH, SDH, Atpase, and SSS, were significantly increased (P < 0.05) during H12h treatment, as shown in Fig. 8. These differences between autotrophic and heterotrophic conditions indicated that glycolysis and TCA cycle, oxidative phosphorylation, and pyruvate metabolism were activated in heterotrophic conditions. The activity of some important enzymes was detached in these pathways and found that the NAD-MDH and SDH activity of the H12h group were significantly higher than P12h group (Fig. 9). In the H12h, the metabolism of sugars, lipids, and amino acids in cells were activated by TCA cycle, providing more energy for cell growth.

In this study, the physiological response of C. reinhardtii were significantly different in photoautotrophy 12h and heterotrophy 12h, P12h group was significantly higher than the H12h group. Transcriptome analyzed DEGs and revealed the variation of DEGs in several metabolic pathways involved in glycolysis, the tricarboxylic acid cycle, pyruvate, and oxidative phosphorylation from P12h to H12h. It is suggested that DEGs regulated key metabolic pathways to influence their growth differences. The qRT-PCR was used to detect important gene expression levels, including RBCL, MDH, SDH, ATPase, and SSS. These results are consistent with transcriptomic data. Additionally, key enzyme activities of Rubisco, NAD-malate dehydrogenase (NAD-MDH), and succinate dehydrogenase (SDH) had marked changes between P12h and H12h. In summary, this study comprehensively analyzed the transcriptome and molecule, we elucidated the possible molecular mechanism of both the heterotrophic and autotrophic Chlamydomonas reinhardtii. Therefore, the results of this study provided a theoretical basis and experimental basis for the growth of Chlamydomonas reinhardtii in photoautotrophy and heterotrophy.

P12h photoautotrophy 12h

H12h heterotrophy 12h

DEGs Differentially expressed genes

TCA cycle tricarboxylic acid cycle

RNA-seq Ribonucleic acid sequencing

PBS phosphate buffered saline

FPKM Fragments per kilobase of transcript per million mapped reads

GO Gene Ontology

KEGG Kyoto Encyclopedia of Genes and Genomes

NAD-MDH NAD-Malate Dehydrogenase

SSS Soluble Starch Synthase

PK Pyruvate Kinase

PCR Polymerase chain reaction

qRT-PCR Quantitative real-time PCR

PCA Principal component analysis

Acknowledgements

We are grateful for the funding of National Natural Science Foundation of China under Grant [number 41976125]; the Program for University Innovation Team of Guangdong Province [num-ber 2022KCXTD008], the Natural Science Foundation of China grants [number NSFC 42206116], and Innovation Project of Guangdong University under Grant [number 2018KCXTD012].

Authors’ contributions

Jing Chen participated in writing the manuscript and the bioinformatic analyses.

Yuanhao Chen: designed and guided the database construction.

Weiling He: Contributed to the manuscript reviewing.

Honghao Liang conceived and designed the research.

Ting Hong performed the experimental work.

Tangcheng Li conceived and designed the research.

Hong Du: Contributed to the conceptualization, experimental design, supervision and funding acquisition. All authors read and reviewed the manuscript.

Funding

This work was supported by the Natural Science Foundation of China grants (NSFC 42206116), Natural Science Foundation of China grants (41976125), Science and Technology Plan Projects of Guangdong Province (No. 2021B1212050025) and the Program for University Innovation Team of Guangdong Province (2022KCXTD008).

Data Availability

The raw sequencing data can be accessed from the NCBI Sequence Read Archive (SRA) platform. (https://www.ncbi.nlm.nih.gov/bioproject/) under accession no. PRJNA929120.

Ethics approval and consent to participate

Chlamydomonas reinhardtii strain CC-125 was obtained from the Chlamydomonas Resource Center (CRC, University of Minnesota). The study complies with all relevant institutional, national, and international guidelines and legislation in the field.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing financial interests.

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published 19 Jun, 2024

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Transcriptome analysis reveals the molecular mechanism of differences in growth between photoautotrophy and heterotrophy in Chlamydomonas reinhardtii

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Journal Publication

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Abstract

Figures

Introduction

Materials and methods

Cell strain and culture conditions

Growth measurement and morphological observation

Transcriptome analysis

Determination of key enzyme activities

Real-time quantitative PCR

Statistical analysis

Results

Analysis of transcriptome in P12h and H12h

Functional annotations and classification of DEGs

Analyses of the DEGs related to the pyruvate metabolic pathway in P12h and H12h

Analyses of the DEGs related to the oxidative phosphorylation in P12h and H12h

The relative expressions of marker genes

The change of key enzyme activities in P12h and H12h

Discussion

Transcriptomics reveals the expression of DEGs from autotrophs to heterotrophs

Functional analysis of DEGs in main metabolic pathways

Molecular mechanism through which DEGs regulate between P12h and H12h

Conclusion

List of Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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