Effects of abiotic stressors on lutein production in the green microalga Dunaliella salina.

BackgroundRecent years have witnessed a rising trend in exploring microalgae for valuable carotenoid products as the demand for lutein and many other carotenoids in global markets has increased significantly. In green microalgae lutein is a major carotenoid protecting cellular components from damage incurred by reactive oxygen species under stress conditions. In this study, we investigated the effects of abiotic stressors on lutein accumulation in a strain of the marine microalga D. salina which had been selected for growth under stress conditions of combined blue and red lights by adaptive laboratory evolution.ResultsNitrate concentration, salinity and light quality were selected as three representative influencing factors and their impact on lutein production in batch cultures of D. salina was evaluated using response surface analysis. D. salina was found to be more tolerant to hyper-osmotic stress than to hypo-osmotic stress which caused serious cell damage and death in a high proportion of cells while hyper-osmotic stress increased the average cell size of D. salina only slightly. Two models were developed to explain how lutein productivity depends on the stress factors and for predicting the optimal conditions for lutein productivity. Among the three stress variables for lutein production, stronger interactions were found between nitrate concentration and salinity than between light quality and the other two. The predicted optimal conditions for lutein production were close to the original conditions used for adaptive evolution of D. salina. This suggests that the conditions imposed during adaptive evolution may have selected for the growth optima arrived at.ConclusionsThis study shows that systematic evaluation of the relationship between abiotic environmental stresses and lutein biosynthesis can help to decipher the key parameters in obtaining high levels of lutein productivity in D. salina. This study may benefit future stress-driven adaptive laboratory evolution experiments and a strategy of applying stress in a step-wise manner can be suggested for a rational design of experiments

Áhrif lykkjusvæða á kuldaaðlögun alkalísks fosfatasa úr Vibrio örveru

Lífverur finnast á mjög harðbýlum svæðum jarðar, svo sem við mjög há eða lág hitastig, háa seltu sjávar, eða öfgafull sýrustig. Mörg prótein þurfa að aðlagast slíkum aðstæðum með breytingum í innri gerð. Samanburður á því sem breyst hefur í amínósýruröð með skyldum próteinum gefur upplýsingar um þætti sem ráða mestu um virkni þeirra. Kuldakær ensím hafa oftast meiri sveigjanleika innan heildarbyggingar sinnar miðað við hitaþolin ensím, sem kemur í veg fyrir að nauðsynlegar hreyfingar frjósi. Nokkrir þættir stuðla að auknum sveigjanleika þeirra. Sem dæmi hafa kuldaaðlöguð ensím gjarnan færri vetnistengi, færri saltbrýr, og fleiri yfirborðshleðslur. Kuldakær ensím hafa einnig oft stærri yfirborðslykkjur samanborið við samsvarandi ensím úr miðlungs- og hitakærum lífverum. Í þessu verkefni var sjónum beint að hlutverki yfirborðslykkju við mótun séreiginleika sem fundist hafa í alkalískum fosfatasa úr Vibrio sjávarörveru. Gerðar voru staðbundnar breytingar í amínósýruröð lykkjunnar til að skoða betur áhrif hennar á stöðugleika og virkni ensímsins. Fimm punktbreytingar voru framkvæmdar ásamt einni lykkjustyttingu. Við þessar stökkbreytingar voru vetnistengi sem lykkjan myndar við kjarna næstu undireiningu ýmist rofin eða vetnistengjum bætt við (F335Y). Tvö stökkbrigði (F355Y og Y346F) sýndu svipaða virkni og stöðugleika samanborið við villigerð. Hin stökkbrigðin þrjú (R336L, S79A og S79A/S87G) ásamt lykkjuúrfellingunni (Δ337-341;Ser-Gly-Glu-Ala-Phe) reyndust óstöðugari. Rofin vetnistengi af völdum stökkbreytinganna eru líkleg ástæða fyrir hækkun í kcat, lækkaðs T50% gildis og lækkunnar bræðslumarks (Tm). Allt að 6-7°C lækkun í Tm mældist fyrir stökkbrigðin samanborið við villigerð. Lykkjan og vetnistengin sem hún myndar við næstu undireiningu eru því greinilega mikilvæg fyrir stöðugleika og virkni ensímsins. Kvikar hreyfingar ensímsins voru einnig kannaðar með tölvureikningum.Organisms can be found in the harshest environments on Earth, such as at very high or low temperatures, at high salinity, or extreme acidity. Proteins of these organisms have adapted to these environments by changes in amino acid composition. Psychrophilic enzymes are found to have greater overall flexibility compared with thermophilic proteins, as flexibility is an important factor in allowing necessary dynamic movement at low temperatures. Several factors contribute to their greater flexibility. As an example, cold adapted enzymes typically have fewer hydrogen bonds, fewer salt bridges, and more surface charges. Psychrophilic enzymes also tend to have larger surface loops compared with their homologous enzymes from thermostable organisms. This project focuses on the role of a large surface loop on the activity and stability of alkaline phosphatase from a cold adapted Vibrio marine bacterium. Site directed mutagenesis was carried out on the large surface loop. Five point mutations were made and one loop deletion. These mutations were chosen to understand the role of hydrogen bonding from the loop to the next monomer. Hydrogen bonds were either added (F335Y) to this area or deleted. Two mutants (F355Y and Y346F) showed similar activity and stability compared with wild type. The three other point mutations (R336L, S79A and S79A/S87G) and the loop deletion (Δ337-341;Ser-Gly-Glu-Ala-Phe) were found to cause lower stablility than that of wild type. The putative deletion of hydrogen bonds resulted in higher kcat, lower T50%, and lower melting point (Tm). The new variants were found to have 6-7°C lower Tm than wild type. The large surface loop and its hydrogen bonding with the next monomer was found to be important for the stability and activity of the Vibrio alkaline phosphatase. Molecular movement analyses were also used get a better understanding of the movements of the enzyme.Ranní

Science Lecture theatre, Monash University, 1962, architects Bates Smart & McCutcheon [picture] /

Condition: Good.; Title devised by cataloguer based on inscription on reverse.; Part of Wolfgang Sievers photographic archive.; Sievers number: 3236 AZ.; Also available in an electronic version via the Internet at: http://nla.gov.au/nla.pic-vn4191701

Prediction of intracellular metabolic states from extracellular metabolomic data

Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRF-CEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well-suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context

Prediction of intracellular metabolic states from extracellular metabolomic data.

Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRF-CEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well-suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context