RESUMO
Metacaspases are cysteine proteases present in plants, fungi and protists. While the association of metacaspases with cell death is studied in a range of organisms, their native substrates are largely unknown. Here, we explored the in vivo proteolytic landscape of the two metacaspases, CrMCA-I and CrMCA-II, present in the green freshwater alga Chlamydomonas reinhardtii, using mass spectrometry-based degradomics approach, during control conditions and salt stress. Comparison between the cleavage events of CrMCA-I and CrMCA-II in metacaspase mutants revealed unique cleavage preferences and substrate specificity. Degradome analysis demonstrated the relevance of the predicted metacaspase substrates to the physiology of C. reinhardtii cells and its adaptation during salt stress. Functional enrichment analysis indicated an involvement of CrMCA-I in the catabolism of carboxylic acids, while CrMCA-II plays an important role in photosynthesis and translation. Altogether, our findings suggest distinct cellular functions of the two metacaspases in C. reinhardtii during salt stress response.
Assuntos
Chlamydomonas reinhardtii , Proteólise , Estresse Salino , Chlamydomonas reinhardtii/genética , Chlamydomonas reinhardtii/efeitos dos fármacos , Chlamydomonas reinhardtii/enzimologia , Chlamydomonas reinhardtii/metabolismo , Proteólise/efeitos dos fármacos , Caspases/metabolismo , Caspases/genética , Proteínas de Plantas/metabolismo , Proteínas de Plantas/genéticaRESUMO
Many eukaryotic microalgae modify their metabolism in response to nutrient stresses such as phosphorus (P) starvation, which substantially induces storage metabolite biosynthesis, but the genetic mechanisms regulating this response are poorly understood. Here, we show that P starvation-induced lipid and starch accumulation is inhibited in a Chlamydomonas reinhardtii mutant lacking the transcription factor Pi Starvation Response1 (PSR1). Transcriptomic analysis identified specific metabolism transcripts that are induced by P starvation but misregulated in the psr1 mutant. These include transcripts for starch and triacylglycerol synthesis but also transcripts for photosynthesis-, redox-, and stress signaling-related proteins. To further examine the role of PSR1 in regulating lipid and starch metabolism, PSR1 complementation lines in the psr1 strain and PSR1 overexpression lines in a cell wall-deficient strain were generated. PSR1 expression in the psr1 lines was shown to be functional due to rescue of the psr1 phenotype. PSR1 overexpression lines exhibited increased starch content and number of starch granules per cell, which correlated with a higher expression of specific starch metabolism genes but reduced neutral lipid content. Furthermore, this phenotype was consistent in the presence and absence of acetate. Together, these results identify a key transcriptional regulator in global metabolism and demonstrate transcriptional engineering in microalgae to modulate starch biosynthesis.
Assuntos
Chlamydomonas reinhardtii/metabolismo , Proteínas de Ligação a DNA/metabolismo , Proteínas Nucleares/metabolismo , Fósforo/metabolismo , Proteínas de Plantas/metabolismo , Carbono/metabolismo , Chlamydomonas reinhardtii/genética , Chlamydomonas reinhardtii/ultraestrutura , Proteínas de Ligação a DNA/genética , Perfilação da Expressão Gênica , Genes de Plantas , Teste de Complementação Genética , Metabolismo dos Lipídeos/genética , Modelos Biológicos , Mutação , Proteínas Nucleares/genética , Proteínas de Plantas/genética , Amido/metabolismoRESUMO
Microalgae are highly diverse photosynthetic organisms with higher growth rate and simple nutritional requirements. They are evolved with an efficiency to adapt to a wide range of environmental conditions, resulting in a variety of genetic diversity. Algae accounts for nearly half of global photosynthesis, which makes them a crucial player for CO2 sequestration. In addition, they have metabolic capacities to produce novel secondary metabolites of pharmaceutical, nutraceutical and industrial applications. Studies have explored the inherent metabolic capacities of microalgae with altered growth conditions for the production of primary and secondary metabolites. However, the production of the targeted metabolites at higher rates is not guaranteed just with the inherent genetic potentials. The strain improvement using genetic engineering is possible hope to overcome the conventional methods of culture condition improvements for metabolite synthesis. Although the advanced gene editing tools are available, the gene manipulation of microalgae remains relatively unexplored. Among the performed gene manipulations studies, most of them focus on primary metabolites with limited focus on secondary metabolite production. The targeted genes can be overexpressed to enhance the production of the desired metabolite or redesigning them using the synthetic biology. A mutant (KOR1) rich in carotenoid and lipid content was developed in a recent study employing mutational breeding in microalgae (Kato, Commun. Biol, 2021, 4, 450). There are lot of challenges in genetic engineering associated with large algal diversity but the numerous applications of secondary metabolites make this field of research very vital for the biotech industries. This review, summarise all the genetic engineering studies and their significance with respect to secondary metabolite production from microalgae. Further, current genetic engineering strategies, their limitations and future strategies are also discussed.
RESUMO
Mycosporine-like amino acids (MAAs), are secondary metabolites, first reported in 1960 and found to be associated with the light-stimulated sporulation in terrestrial fungi. MAAs are nitrogenous, low molecular weight, water soluble compounds, which are highly stable with cyclohexenone or cycloheximine rings to store the free radicals. Microalgae are considered as a good source of different kinds of MAAs, which in turn, has its own applications in various industries due to its UV absorbing, anti-oxidant and therapeutic properties. Microalgae can be easily cultivated and requires a very short generation time, which makes them environment friendly source of biomolecules such as mycosporine-like amino acids. Modifying the cultural conditions along withmanipulation of genes associated with mycosporine-like amino acids biosynthesis can help to enhance MAAs synthesis and, in turn, can make microalgae suitable bio-refinery for large scale MAAs production. This review focuses on properties and therapeutic applications of mycosporine like amino acids derived from microalgae. Further attention is drawn on various culture and genetic engineering approaches to enhance the MAAs production in microalgae.
Assuntos
Aminoácidos , Microalgas , Antioxidantes , Raios UltravioletaRESUMO
Microalgae are diverse microorganisms that are of interest as novel sources of metabolites for various industrial, nutritional, and pharmaceutical applications. Recent studies have demonstrated transcriptional engineering of some metabolic pathways. We propose here that transcriptional engineering could be a viable means to manipulate the biosynthesis of specific high-value metabolic products.
Assuntos
Proteínas de Algas/genética , Produtos Biológicos/metabolismo , Melhoramento Genético/métodos , Engenharia Metabólica/métodos , Microalgas/fisiologia , Transcriptoma/genética , Proteínas de Algas/metabolismo , Produtos Biológicos/química , Produtos Biológicos/isolamento & purificação , Fatores de Transcrição/genéticaRESUMO
Microalgae produce metabolites that could be useful for applications in food, biofuel or fine chemical production. The identification and development of suitable strains require analytical methods that are accurate and allow rapid screening of strains or cultivation conditions. We demonstrate the use of Fourier transform infrared (FT-IR) spectroscopy to screen mutant strains of Chlamydomonas reinhardtii. These mutants have knockdowns for one or more nutrient starvation response genes, namely PSR1, SNRK2.1 and SNRK2.2. Limitation of nutrients including nitrogen and phosphorus can induce metabolic changes in microalgae, including the accumulation of glycerolipids and starch. By performing multivariate statistical analysis of FT-IR spectra, metabolic variation between different nutrient limitation and non-stressed conditions could be differentiated. A number of mutant strains with similar genetic backgrounds could be distinguished from wild type when grown under specific nutrient limited and replete conditions, demonstrating the sensitivity of FT-IR spectroscopy to detect specific genetic traits. Changes in lipid and carbohydrate between strains and specific nutrient stress treatments were validated by other analytical methods, including liquid chromatography-mass spectrometry for lipidomics. These results demonstrate that the PSR1 gene is an important determinant of lipid and starch accumulation in response to phosphorus starvation but not nitrogen starvation. However, the SNRK2.1 and SNRK2.2 genes are not as important for determining the metabolic response to either nutrient stress. We conclude that FT-IR spectroscopy and chemometric approaches provide a robust method for microalgae screening.
RESUMO
Fourier Transform Infrared (FT-IR) spectroscopy is a robust method for macromolecular analysis and differentiation of microorganisms. However, most studies are performed in controlled conditions and it is unclear whether this tool is appropriate for the identification of eukaryotic microalgae species from variable environments. In order to address this, nine closely-related species of marine and freshwater microalgae were grown under controlled (non-stressed) and variable (non-stressed and stressed) conditions, including nutrient-stressed and wastewater-stressed conditions. Following optimization of data processing methods, FT-IR spectra from all species and conditions were compared. The substantial metabolic changes that were caused by nutrient starvation restricted the ability of FT-IR spectroscopy to differentiate the microalgal species grown under variable conditions efficiently. Comparison of unsupervised and supervised multivariate data analysis methods found that principal component-discriminant function analysis was able best to differentiate between some species under controlled conditions but still gave poor differentiation under variable environmental conditions.