scholarly journals Novel Enzymatic Fluorometric Methods for High-throughput and Sensitive Measurements of All Major Phospholipid Classes in Cells

Oleoscience ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 313-320
Author(s):  
Shin-ya MORITA
2017 ◽  
Vol 9 (34) ◽  
pp. 28168-28179 ◽  
Author(s):  
Chunguang Miao ◽  
Eric S. Schiffhauer ◽  
Evelyn I. Okeke ◽  
Douglas N. Robinson ◽  
Tianzhi Luo

1972 ◽  
Vol 127 (2) ◽  
pp. 375-385 ◽  
Author(s):  
A. R. Neill ◽  
C. J. Masters

The incorporation of 14C-labelled myristic, palmitic, stearic, oleic and linoleic acids in vitro into the lipids of bovine spermatozoa was measured at intervals from 2min to 2h. All acids were rapidly incorporated into diglycerides, myristic acid being metabolized to the greatest extent. Whereas the low incorporation of acids into total phospholipids reflected the relative stability of the major phospholipid fractions in sperm, the minor phospholipids, particularly phosphatidylinositol, showed comparatively high metabolic activity. Although, in general, saturated acids were incorporated more actively than unsaturated substrates, stearic acid was poorly incorporated into all lipids except phosphatidylinositol. In regard to fatty acid composition of sperm lipids it was notable that diglycerides contained myristic acid as the major component, and this acid was also a prominent moiety of phosphatidylinositol. Docosahexaenoic acid was the principal fatty acid of the major phospholipid classes. These findings have been discussed in relation to the role of lipids in the metabolism of spermatozoa.


2020 ◽  
Author(s):  
Xi Xiang ◽  
Kunli Qu ◽  
Xue Liang ◽  
Xiaoguang Pan ◽  
Jun Wang ◽  
...  

AbstractThe CRISPR RNA-guided endonucleases Cas9, and Cas9-derived adenine/cytosine base editors (ABE/CBE), have been used in both research and therapeutic applications. However, broader use of this gene editing toolbox is hampered by the great variability of efficiency among different target sites. Here we present TRAP-seq, a versatile and scalable approach in which the CRISPR gRNA expression cassette and the corresponding surrogate site are captured by Targeted Reporter Anchored Positional Sequencing in cells. TRAP-seq can faithfully recapitulate the CRISPR gene editing outcomes introduced to the corresponding endogenous genome site and most importantly enables massively parallel quantification of CRISPR gene editing in cells. We demonstrate the utility of this technology for high-throughput quantification of SpCas9 editing efficiency and indel outcomes for 12,000 gRNAs in human embryonic kidney cells. Using this approach, we also showed that TRAP-seq enables high throughput quantification of both ABE and CBE efficiency at 12,000 sites in cells. This rich amount of ABE/CBE outcome data enable us to reveal several novel nucleotide features (e.g. preference of flanking bases, nucleotide motifs, STOP recoding types) affecting base editing efficiency, as well as designing improved machine learning-based prediction tools for designing SpCas9, ABE and CBE gRNAs of high efficiency and accuracy (>70%). We have integrated all the 12,000 CRISPR gene editing outcomes for SpCas9, ABE and CBE into a CRISPR-centered portal: The Human CRISPR Atlas. This study extends our knowledge on CRISPR gene and base editing, and will facilitate the application and development of CRISPR in both research and therapy.


PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0173246 ◽  
Author(s):  
Gunhild Sommer ◽  
Alena Fedarovich ◽  
Venkatesh Kota ◽  
Reycel Rodriguez ◽  
Charles D. Smith ◽  
...  

2018 ◽  
Author(s):  
Bin Xiong ◽  
Yiben Yang ◽  
Frank R. Fineis ◽  
Ji-Ping Wang

AbstractRNA-seq is a high-throughput assay to profile transcriptional activities in cells. Here we show that transcript degradation is gene-/sample-specific and presents a common and major source that may substantially bias the results in RNA-seq analysis. Most existing global normalization approaches are ineffective to correct for the degradation bias. We propose a novel pipeline named DegNorm (stands for degradation normalization) to adjust read counts for transcript degradation heterogeneity on a gene-by-gene basis while simultaneously controlling the sequencing depth. The robust and effective performance of this method is demonstrated in an extensive set of real RNA-seq data and simulated data.


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