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Ting Lu

Publications and source records attributed to Ting Lu.

2 recordsLinked to original sources

Mammalian DNA methyltransferases in DNA methylation and imprinted gene expression in extraembryonic ectoderm of post-implantation embryos.

DNA methylation in mammals is mainly catalyzed by three DNA methyltransferases (DNMTs). Conventionally, DNMT1 is considered the primary DNMT protein for maintenance DNA methylation, whereas DNMT3A and DNMT3B function in de novo DNA methylation. In two previous studies, we demonstrated that DNMT3A and DNMT3B maintain genome-wide DNA methylation in embryonic stem (ES) cells and in the epiblast of post-implantation embryos. Interestingly, DNMT3A and DNMT3B also sustain genome-wide DNA methylation in the extraembryonic ectoderm (EXE) of post-implantation embryos, including repeats, genic and intergenic regions. Although DNMT1 plays a major role in maintaining DNA methylation at the imprinting control regions (ICRs) in the imprinted regions, DNMT3A and DNMT3B are required for preserving DNA methylation at the ICRs of a subset of imprinted regions in EXE, similar to the observations in ES cells and epiblast. Surprisingly, de novo DNA methylation mediated by DNMT3A and DNMT3B leads to increased DNA methylation at a large subset of imprinted regions. These results are consistent with what we previously elucidated in the epiblast of post-implantation embryos. Importantly, loss of DNA methylation at the ICR of an imprinted region, resulting from the absence of DNMT1 or two DNMT3 proteins, causes allelic expression switch of the corresponding imprinted genes in that imprinted region. This study provides further evidence that DNMT3A and DNMT3B exert both maintenance and de novo DNA methylation functions across the genome in post-implantation embryos. It also validates some previous findings for DNA methylation-dependent allelic expression switch of imprinted genes.

DNA methylation

Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism.

Microbial metabolism is a complex, emergent system driven by the coordinated interplay of intricate and dynamic molecular processes. To elucidate cellular behavior and enable biotechnological applications, quantitative models that address the inherent complexity of metabolism have been developed from a resource allocation perspective. Here, we synthesize recent advances in coarse-grained resource allocation frameworks and their applications in understanding microbial physiology and guiding gene circuit design. These frameworks reveal global regulatory constraints and predict cellular adaptation to nutrient and environmental changes. In addition, they enable the quantification of metabolic costs, the dissection of circuit-host interactions, and the development of strategies for burden mitigation. Collectively, these modeling frameworks provide a powerful platform for uncovering quantitative principles of microbial growth and engineering robust synthetic biological systems.

coarse-grained modeling