No abstract

Aflatoxin B1 (AFB1) and zearalenone (ZEN) are two predominant mycotoxins ubiquitously found in corn, peanuts, and other grains, which pose a great threat to human health. Therefore, safe and effective methods for detoxification of these mycotoxins are urgently needed. To achieve simultaneous degradation of multiple mycotoxins, a fusion enzyme ZPF1 was constructed by linking zearalenone hydrolase and manganese peroxidase with a linker peptide GGGGS. This fusion enzyme was secretory expressed successfully in the newly constructed food-grade recombinant strain Kluyveromyces lactis GG799(pKLAC1-ZPF1), and was investigated with the mycotoxins degradation efficiency in two reaction systems. Results showed that both AFB1 and ZEN can be degraded by ZPF1 in reaction system 1 (70.0 mmol/L malonic buffer with 1.0 mmol/L MnSO4, 0.1 mmol/L H2O2, 5.0 µg/mL AFB1 and ZEN, respectively) with the ratios of 46.46% and 38.76%, respectively. In reaction system 2 (50.0 mmol/L Tris–HCl, with 5.0 µg/mL AFB1 and ZEN, respectively), AFB1 cannot be degraded while ZEN can be degraded with the ratio of 35.38%. To improve the degradation efficiency of these mycotoxins, optimization of the induction and degradation conditions were fulfilled subsequently. The degradation ratios of AFB1 and ZEN by ZPF1 in reaction system 1 reached 64.11% ± 2.93% and 46.21% ± 3.17%, respectively. While in reaction system 2, ZEN was degraded by ZPF1 at a ratio of 41.45% ± 3.34%. The increases of degradation ratios for AFB1 and ZEN in reaction system 1 were 17.65% and 7.45%, respectively, while that for ZEN in reaction system 2 was 6.07%, compared with the unoptimized results.

Key message Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Abstract Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI-and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.