Biology subjects

Feizi, A.

Publications and source records attributed to Feizi, A..

2 recordsLinked to original sources

bioRxiv2018

Asymmetric perirenal brown adipose dormancy in adult humans is defined by local sympathetic activity

We here detect dormant brown adipose tissue (BAT) in adult humans, occurring in most of the perirenal fat depot and characterized by a unilocular morphology. This phenotype was contrasted by multilocular BAT accumulating near the adrenal gland. Transcriptomic analysis revealed a gene expression profile of unilocular BAT that was approaching, yet was still distinct from, the expression profile of subcutaneous white adipose tissue (WAT). Candidate gene signatures were recapitulated in a murine model of unilocular brown fat induced by thermoneutrality and high fat diet. We identified SPARC as a candidate adipokine representing a dormant BAT state in the absence of sympathetic activation and CLSTN3 as a novel marker for multilocular BAT. Brown fat precursor cells were present in the entire perirenal fat depot, regardless of state. When differentiated in vitro, these cells responded to acute norepinephrine stimulation by increasing UCP1 gene expression and uncoupled respiration, confirming a BAT phenotype. We thus propose a mechanism for the reduction of functionally competent BAT in adult humans and we provide a solid data set for future research on factors that can reactivate dormant BAT as a potential strategy for combatting obesity and metabolic disease.

physiology↗

bioRxiv2018

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.

systems biology↗