Dysregulated RNA editing of EIF2AK2 in polycystic ovary syndrome: clinical relevance and functional implications.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive ages. Our previous study has implicated a possible link between RNA editing and PCOS, yet the actual role of RNA editing, its association with clinical features, and the underlying mechanisms remain unclear. METHODS: Ten RNA-Seq datasets containing 269 samples of multiple tissue types, including granulosa cells, T helper cells, placenta, oocyte, endometrial stromal cells, endometrium, and adipose tissues, were retrieved from public databases. Peripheral blood samples were collected from twelve PCOS and ten controls and subjected to RNA-Seq. Transcriptome-wide RNA-Seq data analysis was conducted to identify differential RNA editing (DRE) between PCOS and controls. The functional significance of DRE was evaluated by luciferase reporter assays and overexpression in human HEK293T cells. Dehydroepiandrosterone and lipopolysaccharide were used to stimulate human KGN granulosa cells to evaluate gene expression. RESULTS: RNA editing dysregulations across multiple tissues were found to be associated with PCOS in public datasets. Peripheral blood transcriptome analysis revealed 798 DRE events associated with PCOS. Through weighted gene co-expression network analysis, our results revealed a set of hub DRE events in PCOS blood. A DRE event in the eukaryotic translation initiation factor 2-alpha kinase 2 (EIF2AK2:chr2:37,100,559) was associated with PCOS clinical features such as luteinizing hormone (LH) and the ratio of LH over follicle-stimulating hormone. Luciferase assays, overexpression, and knockout of RNA editing enzyme adenosine deaminase RNA specific (ADAR) showed that the ADAR-mediated editing cis-regulated EIF2AK2 expression. EIAF2AK2 showed a higher expression after dehydroepiandrosterone and lipopolysaccharide stimulation, triggering changes in the downstrean MAPK pathway. CONCLUSIONS: Our study presented the first evidence of cross-tissue RNA editing dysregulation in PCOS and its clinical associations. The dysregulation of RNA editing mediated by ADAR and the disrupted target EIF2AK2 may contribute to PCOS development via the MPAK pathway, underlining such epigenetic mechanisms in the disease.

Does arginine aggregate formation in aqueous solutions follow a two-step mechanism?

The formation of aggregates was studied in arginine aqueous solutions using light scattering. The main driving force for aggregate formation is hydrogen bonding between the arginine (Arg) amino acids, which is partially verified using density functional theory calculations. The measurement of energy loss during this process, coupled with Cryo-EM morphology data, indicates that these aggregates are in the solid state. The aggregation occurs in two steps, with a liquid intermediate stage. The investigation of the effect of pH and solute concentration on aggregate formation for other amino acid aqueous solutions verifies that aggregate formation is amino-acid specific, while small-sized clusters formed by weak interactions lead to large-sized aggregation. The water structure around amino acid molecules sheds light on the prediction of their aggregate formation. Homochirality is observed in the aggregates; its existence sheds light on the origin of protein homochirality.

A novel derivative synchronous fluorescence method for the rapid, non-destructive and intuitive differentiation of denitrifying bacteria.

It is challenging to differentiate bacteria residing in the same habitat by direct observation. This difficulty impedes the harvest, application and manipulation of functional bacteria in environmental engineering. In this study, we developed a novel method for rapid differentiation of living denitrifying bacteria based on derivative synchronous fluorescence spectroscopy, as exemplified by three heterotrophic nitrification-aerobic denitrification bacteria having the maximum nitrogen removal efficiencies greater than 90%. The intact bacteria and their living surroundings can be analyzed as an integrated target, which eliminates the need for the complex pre-processing of samples. Under the optimal synchronous scanning parameter (Δλ = 40 nm), each bacterium possesses a unique fluorescence spectral structure and the derivative synchronous fluorescence technique can significantly improve the spectral resolution compared to other conventional fluorescence methods, which enables the rapid differentiation of different bacteria through derivative synchronous fluorescence spectra as fast as 2 min per spectrum. Additionally, the derivative synchronous fluorescence technique can extract the spectral signals contributed by bacterial extracellular substances produced in the biological nitrogen removal process. Moreover, the results obtained from our method can reflect the real-time denitrification properties of bacteria in the biological nitrogen removal process of wastewater. All these merits highlight derivative synchronous fluorescence spectroscopy as a promising analytic method in the environmental field.

Improvement in Dibenzofuran-Based Hole Transport Materials for Flexible Perovskite Solar Cells.

The π-conjugated system and the steric configuration of hole transport materials (HTMs) could greatly affect their various properties and the corresponding perovskite solar cells' efficiencies. Here, a molecular engineering strategy of incorporating different amounts of p-methoxyaniline-substituted dibenzofurans as π bridge into HTMs was proposed to develop oligomer HTMs, named mDBF, bDBF, and tDBF. Upon extending the π-conjugation of HTMs, their HOMO energy levels were slightly deepened, significantly increasing the thermal stability and hole mobility. The incorporation of p-methoxyaniline bridges built one or two additional triphenylamine propeller structures, resulting in a denser film. Here, the tDBF-based n-i-p flexible perovskite solar cells createdchampion efficiency, giving a power conversion efficiency of 19.46%. And the simple synthesis and purification process of tDBF contributed to its low manufacturing cost in the laboratory. This work provided a reference for the development of low-cost and efficient HTMs.

Study on the mechanism of efficient extracellular expression of toxic streptomyces phospholipase D in Brevibacillus choshinensis under Mg2+ stress.

BACKGROUND: Phospholipase D (PLD) has significant advantages in the food and medicine industries due to its unique transphosphatidylation. However, the high heterologous expression of PLD is limited by its cytotoxicity. The present study sought to develop an efficient and extracellular expression system of PLD in the non-pathogenic Brevibacillus choshinensis (B. choshinensis). RESULTS: The extracellular PLD was effectively expressed by the strong promoter (P2) under Mg2+ stress, with the highest activity of 10 U/mL. The inductively coupled plasma-mass spectrometry (ICP-MS) results elucidated that the over-expression of PLD by P2 promoter without Mg2+ stress induced the ionic homeostasis perturbation caused by the highly enhanced Ca2+ influx, leading to cell injury or death. Under Mg2+ stress, Ca2+ influx was significantly inhibited, and the strengths of P2 promoter and HWP gene expression were weakened. The study results revealed that the mechanism of Mg2+ induced cell growth protection and PLD expression might be related to the lowered strength of PLD expression by P2 promoter repression to meet with the secretion efficiency of B. choshinensis, and the redistribution of intracellular ions accompanied by decreased Ca2+ influx. CONCLUSIONS: The PLD production was highly improved under Mg2+ stress. By ICP-MS and qPCR analysis combined with other results, the mechanism of the efficient extracellular PLD expression under Mg2+ stress was demonstrated. The relatively low-speed PLD expression during cell growth alleviated cell growth inhibition and profoundly improved PLD production. These results provided a potential approach for the large-scale production of extracellular PLD and novel insights into PLD function.

Genetic regulation and fermentation strategy for squalene production in Schizochytrium sp.

Squalene, as an important terpenoid, is extensively used in the medicine and health care fields owing to its functions of anti-oxidation, blood lipid regulation and cancer prevention. The marine microalgae, Schizochytrium sp., which acts as an excellent strain with potential of high squalene production was selected as the starting strain. The overexpressed strain with sqs gene got the reduced biomass and lipid, while the squalene titer was increased by 79.6% ± 4.7% to 12.8 ± 0.2 mg/L. In order to further increase squalene production, the recombinant strain (HS strain) with sqs and hmgr gene co-overexpression was further constructed. The biomass and squalene titer of the HS strain were increased by 13.6% ± 1.2% and 88.8% ± 5.3%, respectively, which indicated the carbon flux of the mevalonate pathway was enhanced for squalene accumulation. Regarding the squalene synthesis is completely coupled with cell growth, fermentation strategy to prolong the logarithmic growth phase was conducive to improve squalene production. Under the condition of optimal composition and concentrated medium, the squalene titer of HS strain was 27.0 ± 1.3 mg/L, which was 2.0 times that of the basal medium condition (13.5 ± 0.4 mg/L). This study which combined the metabolic engineering and fermentation strategy provides a new strategy for squalene production in Schizochytrium sp. KEY POINTS: •The overexpression of sqs and hmgr genes promoted carbon metabolism for squalene. •The optimal and concentrated media can increase squalene yield.

Development and optimization of a microbial co-culture system for heterologous indigo biosynthesis.

BACKGROUND: Indigo is a color molecule with a long history of being used as a textile dye. The conventional production methods are facing increasing economy, sustainability and environmental challenges. Therefore, developing a green synthesis method converting renewable feedstocks to indigo using engineered microbes is of great research and application interest. However, the efficiency of the indigo microbial biosynthesis is still low and needs to be improved by proper metabolic engineering strategies. RESULTS: In the present study, we adopted several metabolic engineering strategies to establish an efficient microbial biosynthesis system for converting renewable carbon substrates to indigo. First, a microbial co-culture was developed using two individually engineered E. coli strains to accommodate the indigo biosynthesis pathway, and the balancing of the overall pathway was achieved by manipulating the ratio of co-culture strains harboring different pathway modules. Through carbon source optimization and application of biosensor-assisted cell selection circuit, the indigo production was improved significantly. In addition, the global transcription machinery engineering (gTME) approach was utilized to establish a high-performance co-culture variant to further enhance the indigo production. Through the step-wise modification of the established system, the indigo bioproduction reached 104.3 mg/L, which was 11.4-fold higher than the parental indigo producing strain. CONCLUSION: This work combines modular co-culture engineering, biosensing, and gTME for addressing the challenges of the indigo biosynthesis, which has not been explored before. The findings of this study confirm the effectiveness of the developed approach and offer a new perspective for efficient indigo bioproduction. More broadly, this innovative approach has the potential for wider application in future studies of other valuable biochemicals' biosynthesis.

Adaptive Attention Memory Graph Convolutional Networks for Skeleton-Based Action Recognition.

Graph Convolutional Networks (GCNs) have attracted a lot of attention and shown remarkable performance for action recognition in recent years. For improving the recognition accuracy, how to build graph structure adaptively, select key frames and extract discriminative features are the key problems of this kind of method. In this work, we propose a novel Adaptive Attention Memory Graph Convolutional Networks (AAM-GCN) for human action recognition using skeleton data. We adopt GCN to adaptively model the spatial configuration of skeletons and employ Gated Recurrent Unit (GRU) to construct an attention-enhanced memory for capturing the temporal feature. With the memory module, our model can not only remember what happened in the past but also employ the information in the future using multi-bidirectional GRU layers. Furthermore, in order to extract discriminative temporal features, the attention mechanism is also employed to select key frames from the skeleton sequence. Extensive experiments on Kinetics, NTU RGB+D and HDM05 datasets show that the proposed network achieves better performance than some state-of-the-art methods.

Comprehensive Utilization of Marine Microalgae for Enhanced Co-Production of Multiple Compounds.

Marine microalgae are regarded as potential feedstock because of their multiple valuable compounds, including lipids, pigments, carbohydrates, and proteins. Some of these compounds exhibit attractive bioactivities, such as carotenoids, ω-3 polyunsaturated fatty acids, polysaccharides, and peptides. However, the production cost of bioactive compounds is quite high, due to the low contents in marine microalgae. Comprehensive utilization of marine microalgae for multiple compounds production instead of the sole product can be an efficient way to increase the economic feasibility of bioactive compounds production and improve the production efficiency. This paper discusses the metabolic network of marine microalgal compounds, and indicates their interaction in biosynthesis pathways. Furthermore, potential applications of co-production of multiple compounds under various cultivation conditions by shifting metabolic flux are discussed, and cultivation strategies based on environmental and/or nutrient conditions are proposed to improve the co-production. Moreover, biorefinery techniques for the integral use of microalgal biomass are summarized. These techniques include the co-extraction of multiple bioactive compounds from marine microalgae by conventional methods, super/subcritical fluids, and ionic liquids, as well as direct utilization and biochemical or thermochemical conversion of microalgal residues. Overall, this review sheds light on the potential of the comprehensive utilization of marine microalgae for improving bioeconomy in practical industrial application.

Spatiotemporal Interaction Residual Networks with Pseudo3D for Video Action Recognition.

Action recognition is a significant and challenging topic in the field of sensor and computer vision. Two-stream convolutional neural networks (CNNs) and 3D CNNs are two mainstream deep learning architectures for video action recognition. To combine them into one framework to further improve performance, we proposed a novel deep network, named the spatiotemporal interaction residual network with pseudo3D (STINP). The STINP possesses three advantages. First, the STINP consists of two branches constructed based on residual networks (ResNets) to simultaneously learn the spatial and temporal information of the video. Second, the STINP integrates the pseudo3D block into residual units for building the spatial branch, which ensures that the spatial branch can not only learn the appearance feature of the objects and scene in the video, but also capture the potential interaction information among the consecutive frames. Finally, the STINP adopts a simple but effective multiplication operation to fuse the spatial branch and temporal branch, which guarantees that the learned spatial and temporal representation can interact with each other during the entire process of training the STINP. Experiments were implemented on two classic action recognition datasets, UCF101 and HMDB51. The experimental results show that our proposed STINP can provide better performance for video recognition than other state-of-the-art algorithms.

The role of fluconazole in the regulation of fatty acid and unsaponifiable matter biosynthesis in Schizochytrium sp. MYA 1381.

BACKGROUND: Schizochytrium has been widely used in industry for synthesizing polyunsaturated fatty acids (PUFAs), especially docosahexaenoic acid (DHA). However, unclear biosynthesis pathway of PUFAs inhibits further production of the Schizochytrium. Unsaponifiable matter (UM) from mevalonate pathway is crucial to cell growth and intracellular metabolism in all higher eukaryotes and microalgae. Therefore, regulation of UM biosynthesis in Schizochytrium may have important effects on fatty acids synthesis. Moreover, it is well known that UMs, such as squalene and ß-carotene, are of great commercial value. Thus, regulating UM biosynthesis may also allow for an increased valuation of Schizochytrium. RESULTS: To investigate the correlation of UM biosynthesis with fatty acids accumulation in Schizochytrium, fluconazole was used to block the sterols pathway. The addition of 60 mg/L fluconazole at 48 h increased the total lipids (TLs) at 96 h by 16% without affecting cell growth, which was accompanied by remarkable changes in UMs and NADPH. Cholesterol content was reduced by 8%, and the squalene content improved by 45% at 72 h, which demonstrated fluconazole's role in inhibiting squalene flow to cholesterol. As another typical UM with antioxidant capacity, the ß-carotene production was increased by 53% at 96 h. The increase of squalene and ß-carotene could boost intracellular oxidation resistance to protect fatty acids from oxidation. The NADPH was found to be 33% higher than that of the control at 96 h, which meant that the cells had more reducing power for fatty acid synthesis. Metabolic analysis further confirmed that regulation of sterols was closely related to glucose absorption, pigment biosynthesis and fatty acid production in Schizochytrium. CONCLUSION: This work first reported the effect of UM biosynthesis on fatty acid accumulation in Schizochytrium. The UM was found to affect fatty acid biosynthesis by changing cell membrane function, intracellular antioxidation and reducing power. We believe that this work provides valuable insights in improving PUFA and other valuable matters in microalgae.

De novo phenol bioproduction from glucose using biosensor-assisted microbial coculture engineering.

Microbial biosynthesis has been extensively adapted for the production of commodity chemicals using renewable feedstocks. This study integrated metabolite biosensors into rationally designed microbial cocultures to achieve high-efficiency bioproduction of phenol from simple carbon substrate glucose. Specifically, two sets of E. coli-E. coli cocultures were first constructed for accommodation of two independent phenol biosynthesis pathways via 4-hydroxybenzoate (4HB) and tyrosine (TYR), respectively. Biosensor-assisted microbial cell selection mechanisms were subsequently incorporated into the coculture systems to address the insufficient pathway intermediate provision that limited the overall bioproduction. For the 4HB- and TYR-dependent pathways, this approach improved the phenol production by 2.3- and 3.9-fold, respectively, compared to the monoculture controls. Notably, the use of biosensor-assisted cell selection strategy in monocultures resulted in reduced phenol production, highlighting the advantage of coculture engineering for coupling with biosensing. After stepwise optimization, the phenol bioproduction yield of the engineered coculture's reached 0.057 g/g glucose. Furthermore, the coculture biosynthesis was successfully scaled up at both shake flask and bioreactor levels. Overall, the findings of this study demonstrate the outstanding potential of coupling biosensing and modular coculture engineering for advancing microbial biosynthesis of valuable molecules from renewable carbon substrates.

Comparison of physics-based and data-driven modelling techniques for dynamic optimisation of fed-batch bioprocesses.

The development of digital bioprocessing technologies is critical to operate modern industrial bioprocesses. This study conducted the first investigation on the efficiency of using physics-based and data-driven models for the dynamic optimisation of long-term bioprocess. More specifically, this study exploits a predictive kinetic model and a cutting-edge data-driven model to compute open-loop optimisation strategies for the production of microalgal lutein during a fed-batch operation. Light intensity and nitrate inflow rate are used as control variables given their key impact on biomass growth and lutein synthesis. By employing different optimisation algorithms, several optimal control sequences were computed. Due to the distinct model construction principles and sophisticated process mechanisms, the physics-based and the data-driven models yielded contradictory optimisation strategies. The experimental verification confirms that the data-driven model predicted a closer result to the experiments than the physics-based model. Both models succeeded in improving lutein intracellular content by over 40% compared to the highest previous record; however, the data-driven model outperformed the kinetic model when optimising total lutein production and achieved an increase of 40-50%. This indicates the possible advantages of using data-driven modelling for optimisation and prediction of complex dynamic bioprocesses, and its potential in industrial bio-manufacturing systems.

Efficient Corrections for DFT Noncovalent Interactions Based on Ensemble Learning Models.

Machine learning has exhibited powerful capabilities in many areas. However, machine learning models are mostly database dependent, requiring a new model if the database changes. Therefore, a universal model is highly desired to accommodate the widest variety of databases. Fortunately, this universality may be achieved by ensemble learning, which can integrate multiple learners to meet the demands of diversified databases. Therefore, we propose a general procedure for learning ensemble establishment based on noncovalent interactions (NCIs) databases. Additionally, accurate NCI computation is quite demanding for first-principles methods, for which a competent machine learning model can be an efficient solution to obtain high NCI accuracy with minimal computational resources. In regard to these aspects, multiple schemes of ensemble learning models (Bagging, Boosting, and Stacking frameworks), are explored in this study. The models are based on various low levels of density functional theory (DFT) calculations for the benchmark databases S66, S22, and X40. All NCIs computed by the DFT calculations can be improved to high-level accuracy (root-mean-square error RMSE = 0.22 kcal/mol in contrast to CCSD(T)/CBS benchmark) by established ensemble learning models. Compared with single machine learning models, ensemble models show better accuracy (RMSE of the best model is further lowered by ∼25%), robustness and goodness-of-fit according to evaluation parameters suggested by the OECD. Among ensemble learning models, heterogeneous Stacking ensemble models show the most valuable application potential. The standardized procedure of constructing learning ensembles has been well utilized on several NCI data sets, and this procedure may also be applicable for other chemical databases.

Advances in heterologous biosynthesis of plant and fungal natural products by modular co-culture engineering.

Heterologous biosynthesis has been long pursued as a viable approach for high efficiency production of natural products with various industrial values. Conventional methods for heterologous biosynthesis use the mono-culture of an engineered microbe for accommodating the whole target biosynthetic pathway to produce the desired product. The emergence of modular co-culture engineering, which divides the pathway between multiple co-culture strains, presents a new perspective to conduct heterologous biosynthesis and improve the bioproduction performance of natural products. This review highlights recent advances in utilizing the modular co-culture engineering approaches to address the challenges of plant and fungal natural product biosynthesis. Potential directions for future research in this promising field are also discussed.

Compartmentalisation of [FeFe]-hydrogenase maturation in Chlamydomonas reinhardtii.

Molecular hydrogen (H2 ) can be produced in green microalgae by [FeFe]-hydrogenases as a direct product of photosynthesis. The Chlamydomonas reinhardtii hydrogenase HYDA1 contains a catalytic site comprising a classic [4Fe4S] cluster linked to a unique 2Fe sub-cluster. From in vitro studies it appears that the [4Fe4S] cluster is incorporated first by the housekeeping FeS cluster assembly machinery, followed by the 2Fe sub-cluster, whose biosynthesis requires the specific maturases HYDEF and HYDG. To investigate the maturation process in vivo, we expressed HYDA1 from the C. reinhardtii chloroplast and nuclear genomes (with and without a chloroplast transit peptide) in a hydrogenase-deficient mutant strain, and examined the cellular enzymatic hydrogenase activity, as well as in vivo H2 production. The transformants expressing HYDA1 from the chloroplast genome displayed levels of H2 production comparable to the wild type, as did the transformants expressing full-length HYDA1 from the nuclear genome. In contrast, cells equipped with cytoplasm-targeted HYDA1 produced inactive enzyme, which could only be activated in vitro after reconstitution of the [4Fe4S] cluster. This indicates that the HYDA1 FeS cluster can only be built by the chloroplastic FeS cluster assembly machinery. Further, the expression of a bacterial hydrogenase gene, CPI, from the C. reinhardtii chloroplast genome resulted in H2 -producing strains, demonstrating that a hydrogenase with a very different structure can fulfil the role of HYDA1 in vivo and that overexpression of foreign hydrogenases in C. reinhardtii is possible. All chloroplast transformants were stable and no toxic effects were seen from HYDA1 or CPI expression.

Metallapentalenofuran: Shifting Metallafuran Rings Promoted by Substituent Effects.

Bulky substituents play important roles in controlling the reaction pathways or producing selected products. This work reports that the shift of metallafuran rings in a metallapentalenofuran complex can be promoted by the substituent effect via a reversible C-H bond reductive elimination and oxidative addition. The starting osmapentalyne, a so-called 7-carbon carbolong complex, was produced by the oxidation of a metallapentalenofuran with FeCl3 . It was then allowed to react with nucleophiles, followed by a C-H activation, to give the aforementioned metallapentalenofuran complex. This work enriches the family of carbolong complexes and reveals a new strategy to promote, but not prevent reactions by the bulky substituents.

Trehalose improves rabbit sperm quality during cryopreservation.

High levels of reactive oxygen species are associated with spermatozoa cryopreservation, which bring damage to functional spermatozoa. The aim of the present study was to investigate whether and how the freezing extenders supplemented with trehalose was beneficial for the survival of rabbit spermatozoa. semen was diluted with Tris-citrate-glucose extender addition of different concentrations of trehalose. Addition of 100 mM trehaose significantly improved post-thaw rabbit sperm parameters, such as motility, acrosome integriy, membrane integrity and mitochondrial membrane potential. Moreover, when freezing extenders supplemented with trehalose, activities of catalase (CAT), superoxide dismutase (SOD) and total antioxidant capacity (T-AOC) of post-thaw spermatozoa were enhanced, meanwhile, reactive oxygen species (ROS) level and Malondialdehyde (MDA) content were decreased. The results suggest that freezing extenders supplemented with 100 mM trehalose resulted in less ROS level and MDA content, higher motility and mitochondrial membrane potential as well as the integrity of acrosome and plasma membrane. Supplementation of trehalose with freezing extenders is beneficial to the rabbit breeding industry.

Sequencing and Characterization of Novel PII Signaling Protein Gene in Microalga Haematococcus pluvialis.

The PII signaling protein is a key protein for controlling nitrogen assimilatory reactions in most organisms, but little information is reported on PII proteins of green microalga Haematococcus pluvialis. Since H. pluvialis cells can produce a large amount of astaxanthin upon nitrogen starvation, its PII protein may represent an important factor on elevated production of Haematococcus astaxanthin. This study identified and isolated the coding gene (HpGLB1) from this microalga. The full-length of HpGLB1 was 1222 bp, including 621 bp coding sequence (CDS), 103 bp 5' untranslated region (5' UTR), and 498 bp 3' untranslated region (3' UTR). The CDS could encode a protein with 206 amino acids (HpPII). Its calculated molecular weight (Mw) was 22.4 kDa and the theoretical isoelectric point was 9.53. When H. pluvialis cells were exposed to nitrogen starvation, the HpGLB1 expression was increased 2.46 times in 48 h, concomitant with the raise of astaxanthin content. This study also used phylogenetic analysis to prove that HpPII was homogeneous to the PII proteins of other green microalgae. The results formed a fundamental basis for the future study on HpPII, for its potential physiological function in Haematococcus astaxanthin biosysthesis.

Proteomic analysis of astaxanthin biosynthesis in Xanthophyllomyces dendrorhous in response to low carbon levels.

The ratio of carbon to nitrogen (C/N) in media plays a crucial role in the production of microbial carotenoids. However, the effects of a high C/N ratio on carotenoid production are ambiguous, and the mechanism of how C/N ratio affects astaxanthin accumulation in X. dendrorhous is unclear. In this study, the influence of C/N ratio on astaxanthin biosynthesis in X. dendrorhous at a fixed nitrogen concentration was investigated, and comparative proteomics were applied to address how C/N ratio affects cell growth and astaxanthin accumulation in X. dendrorhous. The results showed that cell growth and astaxanthin accumulation in X. dendrorhous were strongly related to the ratio of carbon to nitrogen with increasing C/N ratio in medium. However, the astaxanthin content per cell showed an inverse relationship, decreasing with an increasing C/N ratio. Differential proteomics showed the proteins with highest degree of change in expression under varying C/N ratios were mainly involved in carbohydrate metabolic pathways and carotenogenesis metabolism. In addition, several redox- and stress-associated proteins were up-regulated along with the carotenogenesis proteins, implying the environmental stress may affect metabolism and astaxanthin synthesis. A possible regulatory mechanism in response to glucose in X. dendrorhous is discussed.