SummaryIn organisms with a soma-germ demarcation, the germline must be 'preserved' such that harmful damage is not transmitted to the offspring. Keeping the progeny free of damage may be achieved by gametes enjoying elevated, and ⁄ or more functional, homeostatic maintenance systems. This possibility was approached here by testing whether the soma and maturating oocytes (eggs) dissected from female Drosophila melanogaster in reproductive ages display differential capacities for protein quality control and whether these capacities change during aging and mating. Eggs exhibited a high capacity to prevent protein aggregation, strong capacity for 26S proteasome-dependent degradation and reduced levels of oxidatively damaged (carbonylated) proteins compared to the soma. The capacity to prevent protein aggregation was not affected in either soma or eggs by age and ⁄ or mating, while the 26S proteasome capacity declined in the soma but was maintained in the eggs of aged females. However, the levels of carbonylated proteins increased with age in both soma and eggs, and this increase was more pronounced in females allowed to mate continuously. Furthermore, the levels of carbonylated proteins in the eggs of mated flies correlated negatively with the propensity of the eggs to develop into an adult fly. In young flies, mating caused a decrease in 26S proteasome capacity and an increase in protein carbonylation in the soma, but not in the eggs. These results are in line with trade-off theories of aging where aging is considered a consequence of investment in reproduction over somatic maintenance.
Introduction Reverse transcriptase quantitative PCR (RT‐qPCR) is considered the method of choice for measurable residual disease (MRD) assessment in NPM1‐mutated acute myeloid leukemia (AML). MRD can also be determined with DNA‐based methods offering certain advantages. We here compared the DNA‐based methods quantitative PCR (qPCR), droplet digital PCR (ddPCR), and targeted deep sequencing (deep seq) with RT‐qPCR. Methods Of 110 follow‐up samples from 30 patients with NPM1‐mutated AML were analyzed by qPCR, ddPCR, deep seq, and RT‐qPCR. To select DNA MRD cutoffs for bone marrow, we performed receiver operating characteristic analyses for each DNA method using prognostically relevant RT‐qPCR cutoffs. Results The DNA‐based methods showed strong intermethod correlation, but were less sensitive than RT‐qPCR. A bone marrow cutoff at 0.1% leukemic DNA for qPCR or 0.05% variant allele frequency for ddPCR and deep seq offered optimal sensitivity and specificity with respect to 3 log10 reduction of NPM1 transcripts and/or 2% mutant NPM1/ABL. With these cutoffs, MRD results agreed in 95% (191/201) of the analyses. Although more sensitive, RT‐qPCR failed to detect leukemic signals in 10% of samples with detectable leukemic DNA. Conclusion DNA‐based MRD techniques may complement RT‐qPCR for assessment of residual leukemia. DNA‐based methods offer high positive and negative predictive values with respect to residual leukemic NPM1 transcripts at levels of importance for response to treatment. However, moving to DNA‐based MRD methods will miss a proportion of patients with residual leukemic RNA, but on the other hand some MRD samples with detectable leukemic DNA can be devoid of measurable leukemic RNA.
Initial efforts to sequence the genome of the marine diatom Skeletonema marinoi were hampered by the presence of genetic material from bacteria, and there was sufficient material from some of these bacteria to enable the assembly of full chromosomes. Here, we report the genome of strain SMS9, one such bacterial species identified in a non-axenic culture of S. marinoi strain ST54. Its 5,482,391 bp circular chromosome contains 4,641 CDSs, and has a G+C content of 35.6%. Based on 16S rRNA comparison, phylotaxonomic analysis, and the genome similarity metrics dDDH and OrthoANI, we place this strain in the genus Kordia , and to the best of our knowledge, this is the first Kordia species to be initially described from European waters. As attempts to culture this strain have failed, however, the specifics of its relationship with S. marinoi are still uncertain.
For detection of measurable residual disease (MRD) in acute myeloid leukemia with NPM1 mutations, RT-qPCR with quantification of leukemic transcripts is currently considered the method of choice; however, MRD can also be determined with DNA-based methods, offering certain advantages. For example, digital droplet PCR (ddPCR) and targeted deep sequencing (deep seq) do neither require standard curves nor reference genes and are thus less labor intense than RT-qPCR. Also, deep seq allows for quantification independently of type of NPM1 mutation. In addition, DNA-based techniques enable MRD assessment of other mutations, beyond the reach of RT-qPCR, which is limited to analyses of highly expressed genes or fusion transcripts (e.g. core binding factor leukemias). With the rapid development of highly sensitive DNA-based techniques for MRD detection, there is a need to establish clinically relevant cut-offs for accurate interpretation of MRD results and risk stratification. Here, we compare and provide MRD cut-offs for three different DNA-based MRD methods for NPM1 mutations: quantitative PCR (qPCR), ddPCR and deep seq. To compare the DNA-based methods with RT-qPCR, we analyzed 110 follow-up peripheral blood (PB) or bone marrow (BM) samples from 32 AML patients harboring NPM1 mutation type A. First, we compared the mere detectability of leukemic signals (without reference to specific MRD cut-off points). We found a high correlation between results from RT-qPCR and the three DNA-based methods (Rs=0.936 for RT-qPCR vs qPCR, Rs=0.774 for RT-qPCR vs ddPCR and Rs=0.743 for RT-qPCR vs deep seq, p<0.001). As expected, RT-qPCR was the most sensitive method. Among the DNA-based methods, qPCR was the most sensitive, detecting leukemic DNA in 95% (55/58) of the RT-qPCR positive samples, compared to 72% (42/58) and 62% (36/58) for ddPCR and deep seq, respectively. Interestingly, the transcript level for a given amount of measurable leukemic DNA (RNA copy number per leukemic DNA molecule) fluctuated considerably between different follow-up samples for certain patients. In some cases, the RNA/DNA ratio exceeded a hundredfold difference between different follow-up time points in both PB and BM. Hence, transcript analysis may be more complex than just a simple measurement of leukemic cell burden, which in turn may influence accurate risk stratification and treatment decisions, if relying on RT-qPCR measurements alone. To select adequate DNA MRD cut-offs, we performed ROC curve analyses for each method at various DNA cut-offs, comparing them with the gold standard RT-qPCR cut-off. In BM, this cut-off can be defined as a less than 3 log reduction of mutated NPM1 transcripts vs diagnosis, separating MRDhigh from MRDlow/undetectable (sometimes inaccurately termed "MRD-positivity" and "MRD-negativity", respectively). In PB, the mere detectability of mutated NPM1 transcripts is considered the relevant cut-off. DNA cut-offs were chosen based on the area under the curve (AUC) for the ROC analyses (Table 1), and influenced by available literature including recommendations of prognostically relevant MRD levels. For qPCR, a cut-off at 0.1% leukemic DNA was judged relevant in BM. For ddPCR and deep seq, 0.05% was chosen to adjust for measuring allelic ratio (variant allele frequency (VAF)) rather than mutant DNA alone. In PB, the selected cut-off was detectable leukemic signal irrespective of DNA method. We next determined the accuracy of the selected cut-offs, for identification of samples with clinically relevant MRD, by comparing them with the gold standard RT-qPCR. In general, the selected DNA cut-off values generated high specificity as well as high positive and negative predictive values (Table 1). The vast majority of all MRD analyses (93% (368/395)) showed concordant results irrespective of MRD method. In BM samples, MRD assessment by the DNA based methods agreed with MRD status as determined by RT-qPCR (MRDhigh high vs MRDlow/undetectable) in 93% (62/67) of the analyses for qPCR, 96% (64/67) for ddPCR, and 97% (65/67) for deep seq. In PB, the agreement was 95% (41/43), 88% (38/43) and 86% (37/43), respectively. In summary, we found strong agreement between different MRD methods and based on this could provide clinically relevant cut-offs for risk stratification. Thus, in BM follow-up samples from AML patients with NPM1 mutation, we propose 0.1% leukemic DNA as cut-off for qPCR and 0.05% VAF for ddPCR and deep seq. Disclosures No relevant conflicts of interest to declare.
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