ABSTRACT
Chromochloris zofingiensis represents an industrially relevant and unique green alga, given its capability of synthesizing triacylglycerol (TAG) and astaxanthin simultaneously for storage in lipid droplets (LDs). To further decipher lipid metabolism, the nitrogen deprivation (ND)-induced LDs from C. zofingiensis were isolated, purified, and subjected to proteomic analysis. Intriguingly, many C. zofingiensis LD proteins had no orthologs present in LD proteome of the model alga Chlamydomonas reinhardtii. Seven novel LD proteins (i.e., two functionally unknown proteins, two caleosins, two lipases, and one l-gulonolactone oxidase) and the major LD protein (MLDP), which were all transcriptionally up-regulated by ND, were selected for further investigation. Heterologous expression in yeast demonstrated that all tested LD proteins were localized to LDs and all except the two functionally unknown proteins enabled yeast to produce more TAG. MLDP could restore the phenotype of mldp mutant strain and enhance TAG synthesis in wild-type strain of C. reinhardtii. Although MLDP and caleosins had a comparable abundance in LDs, they responded distinctly to ND at the transcriptional level. The two lipases, instead of functioning as TAG lipases, likely recycled polar lipids to support TAG synthesis. For the first time, we reported that l-gulonolactone oxidase was abundant in LDs and facilitated TAG accumulation. Moreover, we also proposed a novel working model for C. zofingiensis LDs. Taken together, our work unravels the unique characteristics of C. zofingiensis LDs and provides insights into algal LD biogenesis and TAG synthesis, which would facilitate genetic engineering of this alga for TAG improvement.
ABSTRACT
Objective To learn the impacts of major diagnosis, other diagnoses, major surgery and other surgeries on the grouping of DRGs, and to optimize the DRGs data grouping quality by analyzing the main influencing factors of DRGs.Methods Based on regrouping results of the 1 940 questionable cases which have been corrected, using SPSS 13.0 to study the impacts of the questions found on the grouping of DRGs.Results 438 Patient records affecting DRGs grouping were regrouped according to major diagnosis, other diagnoses, major surgery and other surgeries.Influences of the above four groups on the grouping vary in general For comparison between two groups, P＞0.007 1 between main surgery and other surgeries;while P＜0.007 1 for comparison between other groups.Conclusion The highest influence of grouping was found in questionable major diagnosis, much higher than such other factors as other diagnoses, major surgery and other surgeries.This conclusion conforms to the steps of basic DRGs grouping logic-sorting the eases according to major diagnosis first of all Correct naming of surgery influences DRGs grouping, but the influence extent of major surgery and other surgeries is close.