Three optimized assays for the evaluation of compounds that can rescue p53 mutants.
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ABSTRACT:
SUBMITTER: Wu J
PROVIDER: S-EPMC8339244 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Many biomedical problems relate to mutant functional properties across a sequence space of interest, e.g., flu, cancer, and HIV. Detailed knowledge of mutant properties and function improves medical treatment and prevention. A functional census of p53 cancer rescue mutants would aid the search for cancer treatments from p53 mutant rescue. We devised a general methodology for conducting a functional census of a mutation sequence space by choosing informative mutants early. The methodology was tested in a double-blind predictive test on the functional rescue property of 71 novel putative p53 cancer rescue mutants iteratively predicted in sets of three (24 iterations). The first double-blind 15-point moving accuracy was 47 percent and the last was 86 percent; r = 0.01 before an epiphanic 16th iteration and r = 0.92 afterward. Useful mutants were chosen early (overall r = 0.80). Code and data are freely available (http://www.igb.uci.edu/research/research.html, corresponding authors: R.H.L. for computation and R.K.B. for biology).
| S-EPMC2748235 | biostudies-literature
Project description:The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain ("cancer mutants"). Activity can be restored by second-site suppressor mutations ("rescue mutants"). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r(2)?=?0.77) with reported values of experimentally measured ??G protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants.
| S-EPMC3197647 | biostudies-literature
Project description:BackgroundSingle nucleotide polymorphisms (SNPs) are the most common form of genetic variability in the human genome and play a prominent role in the heritability of phenotypes. Especially rare alleles with frequencies less than 5% may exhibit a particularly strong influence on the development of complex diseases. The detection of rare alleles by standard DNA sequencing is time-consuming and cost-intensive. Here we discuss an alternative approach for a high throughput detection of rare mutations in large population samples using Ecotilling embedded in a collection of bioinformatic analysis tools. Ecotilling originally was introduced as TILLING for the screening for rare chemically induced mutations in plants and later adopted for human samples, showing an outstanding suitability for the detection of rare alleles in humans. An actual problem in the use of Ecotilling for large mutation screening projects in humans without bioinformatic support is represented by the lack of solutions to quickly yet comprehensively evaluate each newly found variation and place it into the correct genomic context.ResultsWe present an optimized strategy for the design, evaluation and interpretation of Ecotilling results by integrating several mostly freely available bioinformatic tools. A major focus of our investigations was the evaluation and meaningful economical combination of these software tools for the inference of different possible regulatory functions for each newly detected mutation.ConclusionOur streamlined procedure significantly facilitates the experimental design and evaluation of Ecotilling assays and strongly improves the decision process on prioritizing the newly found SNPs for further downstream analysis.
| S-EPMC2586031 | biostudies-literature
Project description:The majority of TP53 missense mutations identified in cancer patients are in the DNA-binding domain and are characterized as either structural or contact mutations. These missense mutations exhibit inhibitory effects on wild-type p53 activity. More importantly, these mutations also demonstrate gain-of-function (GOF) activities characterized by increased metastasis, poor prognosis, and drug resistance. To better understand the activities by which TP53 mutations, identified in Li-Fraumeni syndrome, contribute to tumorigenesis, we generated mice harboring a novel germline Trp53R245W allele (contact mutation) and compared them with existing models with Trp53R172H (structural mutation) and Trp53R270H (contact mutation) alleles. Thymocytes from heterozygous mice showed that all three hotspot mutations exhibited similar inhibitory effects on wild-type p53 transcription in vivo, and tumors from these mice had similar levels of loss of heterozygosity. However, the overall survival of Trp53R245W/+ and Trp53R270H/+ mice, but not Trp53R172H/+ mice, was significantly shorter than that of Trp53+/- mice, providing strong evidence for p53-mutant-specific GOF contributions to tumor development. Furthermore, Trp53R245W/+ and Trp53R270H/+ mice had more osteosarcoma metastases than Trp53R172H/+ mice, suggesting that these two contact mutants have stronger GOF in driving osteosarcoma metastasis. Transcriptomic analyses using RNA sequencing data from Trp53R172H/+, Trp53R245W/+, and Trp53R270H/+ primary osteosarcomas in comparison with Trp53+/- indicated that GOF of the three mutants was mediated by distinct pathways. Thus, both the inhibitory effect of mutant over wild-type p53 and GOF activities of mutant p53 contributed to tumorigenesis in vivo. Targeting p53 mutant-specific pathways may be important for therapeutic outcomes in osteosarcoma.Significancep53 hotspot mutants inhibit wild-type p53 similarly but differ in their GOF activities, with stronger tumor-promoting activity in contact mutants and distinct protein partners of each mutant driving tumorigenesis and metastasis.
| S-EPMC9117479 | biostudies-literature
Project description:TODO: STUDY ABSTRACT AS IT COULD APPEAR IN A
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| EGAS00001002463 | EGA
Project description:Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clinical potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Experimentally measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of molecular and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clinical knowledge for the development of "lookup tables" of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis.
| S-EPMC5590843 | biostudies-literature
Project description:BackgroundOne of the most commonly used molecular test for malaria diagnosis is the polymerase chain reaction (PCR)-based amplification of the 18S ribosomal DNA (rDNA) gene. Published diagnostic assays based on the 18S gene include the "gold standard" nested assay, semi-nested multiplex assay, and one tube multiplex assay. To our knowledge, no one has reported whether the two multiplex methods are better at detecting mixed Plasmodium infections compared to the nested assay using known quantities of DNA in experimentally mixed cocktails.FindingsHere we evaluated three PCR assays (nested, semi-nested multiplex, and one-tube multiplex) for the simultaneous detection of human malaria parasites using experimentally mixed cocktails of known quantities of laboratory derived DNA. All three assays detected individual species with high sensitivity and specificity when DNA was from any one single species; however, experimentally mixed DNA cocktails with all four species present were correctly identified most consistently with the nested method. The other two methods failed to consistently identify all four species correctly, especially at lower concentrations of DNA -subclinical levels of malaria (DNA equivalent to or less than 10 parasites per microliter).ConclusionsThe nested PCR method remains the method of choice for the detection of mixed malaria infections and especially of sub-clinical infections. Further optimization and/or new molecular gene targets may improve the success rate of detecting multiple parasite species simultaneously using traditional PCR assays.
| S-EPMC2853551 | biostudies-literature
Project description:Chromosome conformation capture (3C)-based assays are used to map chromatin interactions genome-wide. Quantitative analyses of chromatin interaction maps can lead to insights into the spatial organization of chromosomes and the mechanisms by which they fold. A number of protocols such as in situ Hi-C and Micro-C are now widely used and these differ in key experimental parameters including cross-linking chemistry and chromatin fragmentation strategy. To understand how the choice of experimental protocol determines the ability to detect and quantify aspects of chromosome folding we have performed a systematic evaluation of experimental parameters of 3C-based protocols. We find that different protocols capture different 3D genome features with different efficiencies. First, the use of crosslinkers such as DSG in addition to formaldehyde improves signal-to-noise allowing detection of thousands of additional loops and strengthening compartment signal. Second, fragmenting chromatin to the level of nucleosomes using MNase allows detection of more loops. On the other hand, protocols that generate larger multi-kb fragments produce stronger compartmentalization signals. We confirmed our results in multiple cell states such as pluripotent and differentiated cells as well as cell cycle stages; Mitosis and G1. Based on these insights we developed Hi-C 3.0, a single protocol that can be used to both efficiently detect chromatin loops and to quantify compartmentalization. Finally, this study produced ultra-deeply sequenced reference interaction maps using in situ Hi-C, Micro-C and Hi-C 3.0 for commonly cell lines in the 4D Nucleome Project.
2021-03-08 | GSE163666 | GEO
Project description: Not available
| S-EPMC11345693 | biostudies-literature
Project description:One home-developed assay and two commercial assays for the rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) were compared by use of a collection of clinical isolates displaying highly diverse genetic backgrounds. Our results suggest that users of orfX-staphylococcal cassette chromosome mec-based assays should repeatedly monitor the local epidemiology to minimize the risks of detection bias and the omission of emerging MRSA clones.
| S-EPMC1933053 | biostudies-literature