[
Phytomedicine,
2019]
BACKGROUND: Glochidion zeylanicum (GZ), a common plant in Thailand and Eastern Asia, is rich in antioxidants. However, the possible anti-aging and oxidative stress resistance properties of GZ leaf extracts (hexane and methanol extracts) have not been reported. PURPOSE: We aimed to provide the first science-based evidence of the beneficial effects of GZ on anti-aging and oxidative stress resistance in the Caenorhabditis elegans model. METHODS: The phytochemical composition of the hexane and methanol extracts were analyzed using GLC-MS and LC-MS. Fingerprinting analysis of the extract was performed by RP-HPLC. We determined total phenolics, flavonoids, and antioxidant properties via DPPH and ABTS assays. Oxidative stress resistance, anti-aging and lifespan were studied in C. elegans treated with leaf extracts. RESULTS: GZ leaf extracts protected the worms against oxidative stress and attenuated ROS accumulation. The expression of stress-response genes, such as SOD-3, and GST-4 were up-regulated, whereas HSP-16.2 was down-regulated after GZ treatment. The oxidative stress resistance properties of GZ possibly involved the DAF-16/FoxO and SKN-1/Nrf-2 transcription factors. GZ leaf extracts improved pharyngeal pumping function and autofluorescent pigment attenuation suggesting anti-aging properties. GZ leaf extracts modulated the lifespan extension in C. elegans. CONCLUSION: This study reports novel anti-aging and antioxidant activities of GZ leaf extracts, suggesting a novel bioactivity for a medicinally important plant and supplementary drug against oxidative stress.
[
Worm Breeder's Gazette,
1990]
The C. elegans DNA sequence database is growing large enough to permit preliminary compilations and predictions which should be useful for analyzing new sequences. We extracted the DNA sequence flanking the ATG initiation codons from 54 C. elegans genes (34 were available in GenBank (Release 61.0)); after alignment they formed the matrix shown below, which yielded the consensus (A/c)A(a/c)(A/C)ATG (lower case implies weakly conserved). While this is obviously a small sample size the result is significantly different from the vertebrate consensus derived by Kozak(1) (N=699). The total information content in these two matrices(2, 3) differs by 1 bit (C. elegans ~7.6 bits ( genome=36% G+C), vertebrates ~8.6 bits (genome=40% G+C)), although the distributions are roughly homologous (see graph below; baseline ~0.06 bits). Because random sequences will contain many spurious homologies this consensus will be most useful for evaluating suspected initiation codons. The following sequences were used to generate the C. elegans matrix:
act-1,
act-3,
ama-1,
cal-1,
col-2,
col-7,
col-14,
deb-1, pd-2,
gpd-3,
gpd-4,
glp-1,
gyt-1,
his-1,
his-3,
his-9,
his-10,
hts-11,
hts-12,
hsp-1,
hsp-6,
hsp16-1,
hsp16-2,
hsp16-41,
hsp16-48,
mec-3,
lin-12,
msp-74,
myo-1,
myo-3,
unc-54,
vit-2,
vit-5, al msp sequences were not incorporated. If you are interested in increasing the utility of this 'ribosome binding site' (RBS) consensus please send us your sequences and we will incorporate them into the matrix and redistribute the results. [See Figure 1]
[
Nucleic Acids Res,
1994]
We have examined an aging population of Caenorhabditis elegans via a PCR assay to determine if deletions in the mitochondrial genome occur in the nematode. We detected eight such deletions, identified the breakpoints of four of these, and discovered direct repeats of 4-8 base pairs at the site of all four deletions. Six of the eight repeats involved in the deletions are located in car immediately adjacent to tRNAs. Without a biochemical bias, the probability of direct repeats being present at all four breakpoints was 4x10(-6).
[
International C. elegans Meeting,
2001]
We have initiated experiments designed to understand the regulatory regions of C. elegans genes using known muscle genes of C. elegans as a model. Two approaches are being used to pursue this goal. The first approach is to computationally compare the muscle genes from C. elegans to the orthologous muscle sequences from C. briggsae . This comparison is useful because the patterns of gene regulation and regulatory elements are often conserved across species. The C. briggsae orthologue are found by making a probe from the C. elegans muscle gene and probing the C. briggsae fosmid filter available from Incyte. The most promising positive clones are determined by fingerprinting and these are sequenced by the Genome Sequencing Center. To compare the orthologous sequences from C. elegans and C. briggsae , we will use pairwise alignment methods like BlastZ(4) or Bayes aligner(5) to identify regions of interest. Local multiple alignment programs can then be used to search for common regulatory elements in these regions. Since the local multiple alignment methods work best with sequences which are only 1000-2000 nucleotides long, phylogenetic footprinting will be useful in identifying shorter regions from much longer regions(10,000-20,000 nucleotides). The second approach is to use a combination of computational methods to identify potential muscle specific regulatory elements from the known set of C. elegans muscle genes. Local multiple sequence alignment methods like Consensus(1), Ann-Spec(2) and Co-Bind(3) are being used to identify these potential regulatory elements. Using the above method we have already identified several potential regulatory elements which show high degree of specificity for the muscle genes. The regulatory elements that these computational methods predict can then be used to screen the C. elegans genome for new genes that are expressed in muscle cells. To test our results we have developed a method to examine the expression patterns of genes in C. elegans using gfp promoter fusions. We are including in our promoter fusions 6,000 nucleotides upstream of the start methionine, all of the first exon and all the first intron. In our initial experiments, known muscle genes tested in this manner show muscle-like expression. We can now use this method to test the requirement for regulatory regions predicted by the computational work to determine if they convey muscle specific expression. In addition, we can use this method to test genes we predict to be, but not previously known to be, expressed in muscle. Furthermore, we are developing these methods to allow for the rapid production of these promoter fusions so that ultimately, a genome wide program to categorize all C. elegans genes by gfp and automated lineaging can be done. 1. Hertz, G.Z., and Stormo, G.D. (1999) Bioinformatics, vol. 15, pp. 563-577 2. Workman, C.T., and Stormo, G.D. (2000) Pacific Symposium on Biocomputing, vol 5, pp. 464-475 3. GuhaThakurta, D., and Stormo, G.D. (2001) Bioinformatics, in press. 4. Schwartz, S. et.al. (2000) Genome Research, vol. 10, pp. 577-586. 5. Zhu, J., Liu, J.S., and Lawrence, C.E. (1998) vol. 14, pp. 25-39.