Lipid droplet biogenesis and functions in health and disease.

Ubiquitous yet unique, lipid droplets are intracellular organelles that are increasingly being recognized for their versatility beyond energy storage. Advances uncovering the intricacies of their biogenesis and the diversity of their physiological and pathological roles have yielded new insights into lipid droplet biology. Despite these insights, the mechanisms governing the biogenesis and functions of lipid droplets remain incompletely understood.

PI(3)P and DFCP1 regulate the biogenesis of lipid droplets.

The biogenesis of lipid droplets (LDs), key organelles for cellular lipid storage and homeostasis, remains poorly understood. Seipin is essential to normal LD biogenesis but exactly how it regulates LD initiation remains to be elucidated. Our previous results suggested that seipin may bind anionic phospholipids such as PI(3)P.

Insulin signaling requires glucose to promote lipid anabolism in adipocytes.

Adipose tissue is essential for metabolic homeostasis, balancing lipid storage and mobilization based on nutritional status. This is coordinated by insulin, which triggers kinase signaling cascades to modulate numerous metabolic proteins, leading to increased glucose uptake and anabolic processes like lipogenesis. Given recent evidence that glucose is dispensable for adipocyte respiration, we sought to test whether glucose is necessary for insulin-stimulated anabolism.

Serine 474 phosphorylation is essential for maximal Akt2 kinase activity in adipocytes.

The Ser/Thr protein kinase Akt regulates essential biological processes such as cell survival, growth, and metabolism. Upon growth factor stimulation, Akt is phosphorylated at Ser; however, how this phosphorylation contributes to Akt activation remains controversial. Previous studies, which induced loss of Ser phosphorylation by ablating its upstream kinase mTORC2, have implicated Ser phosphorylation as a driver of Akt substrate specificity.

ABHD15 regulates adipose tissue lipolysis and hepatic lipid accumulation.

Objective: Insulin suppresses adipose tissue lipolysis after a meal, playing a key role in metabolic homeostasis. This is mediated via the kinase Akt and its substrate phosphodiesterase 3B (PDE3B). Once phosphorylated and activated, PDE3B hydrolyses cAMP leading to the inactivation of cAMP-dependent protein kinase (PKA) and suppression of lipolysis.

Oxysterol-binding protein-related protein 5 (ORP5) promotes cell proliferation by activation of mTORC1 signaling.

Oxysterol-binding protein (OSBP) and OSBP-related proteins (ORPs) constitute a large family of proteins that mainly function in lipid transport and sensing. ORP5 is an endoplasmic reticulum (ER)-anchored protein implicated in lipid transfer at the contact sites between the ER and other membranes. Recent studies indicate that ORP5 is also involved in cancer cell invasion and tumor progression.

Evaluation of computational programs to predict HLA genotypes from genomic sequencing data.

Motivation: Despite being essential for numerous clinical and research applications, high-resolution human leukocyte antigen (HLA) typing remains challenging and laboratory tests are also time-consuming and labour intensive. With next-generation sequencing data becoming widely accessible, on-demand in silico HLA typing offers an economical and efficient alternative.

Results: In this study we evaluate the HLA typing accuracy and efficiency of five computational HLA typing methods by comparing their predictions against a curated set of > 1000 published polymerase chain reaction-derived HLA genotypes on three different data sets (whole genome sequencing, whole exome sequencing and transcriptomic sequencing data).

How difficult is inference of mammalian causal gene regulatory networks?

Gene regulatory networks (GRNs) play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart) and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles.