Davide Chiarugi

Recent work has shown that the prevalence and character of metabolic diseases differs between male and female mammals. This strongly suggests that the control mechanisms that govern, for example lipid metabolism, differ between the sexes. If true, a one-size-fits-all approach to treating metabolic disease will not be effective in all patients. We tested three hypotheses to understand how the lipid metabolism of male and female mammals may differ. First, whether endogenous fatty acid biosynthesis differed between tissues in the same male and female mice. Second, whether the system-level control of lipid pathways differed between the sexes. Third, whether lipid composition differs between males and females at a population level. We found that fatty acid biosynthesis was distinct in male and female mice across tissues. Systemic control of phospholipid and triglyceride metabolism also differed between the sexes. A human population showed that both phospholipid and triglyceride metabolism differed between males and females.

Reduced femoral cortical thickness index predicts future fragility fractures in Gaucher disease better than dual-energy x-ray absorptiometry. Background Patients with Gaucher disease (GD) have a high risk of fragility fractures. Routine evaluation of bone involvement in these patients includes radiography and repeated dual-energy x-ray a...

In recent years, the Ribosome profiling technique (Ribo–seq) has emerged as a powerful method for globally monitoring the translation process in vivo at single nucleotide resolution. Based on deep sequencing of mRNA fragments, Ribo–seq allows to obtain profiles that reflect the time spent by ribosomes in translating each part of an open reading frame. Unfortunately, the profiles produced by this method can vary significantly in different experimental setups, being characterized by a poor reproducibility. To address this problem, we have employed a statistical method for the identification of highly reproducible Ribo–seq profiles, which was tested on a set of E. coli genes. State-of-the-art artificial neural network models have been used to validate the quality of the produced sequences. Moreover, new insights into the dynamics of ribosome translation have been provided through a statistical analysis on the obtained sequences.

Background: The paternal diet affects lipid metabolism in offspring for at least two generations through nutritional programming. However, we do not know how this is propagated to the offspring. Objectives: We tested the hypothesis that the changes in lipid metabolism that are driven by paternal diet are propagated through spermatozoa and not seminal plasma. Methods: We applied an updated, purpose-built computational network analysis tool to characterise control of lipid metabolism systemically (Lipid Traffic Analysis v2.3) on a known mouse model of paternal nutritional programming. Results: The analysis showed that the two possible routes for programming effects, the sperm (genes) and seminal plasma (influence on the uterine environment), both have a distinct effect on the offspring’s lipid metabolism. Further, the programming effects in offspring suggest that changes in lipid distribution are more important than alterations in lipid biosynthesis. Conclusions: These results show how the uterine environment and genes both affect lipid metabolism in offspring, enhancing our understanding of the link between parental diet and metabolism in offspring.

The aim of the current study was to test the hypothesis that maternal lipid metabolism was modulated during normal pregnancy and that these modulations are altered in gestational diabetes mellitus (GDM). We tested this hypothesis using an established mouse model of diet-induced obesity with pregnancy-associated loss of glucose tolerance and a novel lipid analysis tool, Lipid Traffic Analysis, that uses the temporal distribution of lipids to identify differences in the control of lipid metabolism through a time course. Our results suggest that the start of pregnancy is associated with several changes in lipid metabolism, including fewer variables associated with de novo lipogenesis and fewer PUFA-containing lipids in the circulation. Several of the changes in lipid metabolism in healthy pregnancies were less apparent or occurred later in dams who developed GDM. Some changes in maternal lipid metabolism in the obese-GDM group were so late as to only occur as the control dams’ systems began to switch back towards the non-pregnant state. These results demonstrate that lipid metabolism is modulated in healthy pregnancy and the timing of these changes is altered in GDM pregnancies. These findings raise important questions about how lipid metabolism contributes to changes in metabolism during healthy pregnancies. Furthermore, as alterations in the lipidome are present before the loss of glucose tolerance, they could contribute to the development of GDM mechanistically.

Plasma‐plasma comparisons are the mainstay of investigations of the molecular origins of disease. However, a variety of conditions and phenotypes, including most metabolic disease, arise because of system‐wide changes. It is not possible to characterise these from the molecular composition of the circulation alone. We therefore devised a novel analytical approach to be able to understand system‐wide changes in molecular metabolism. The computational tool we have developed is called Lipid Traffic Analysis (LTA). This was used to test the hypothesis that altered paternal diet programmed the lipid metabolism in offspring. Detailed lipid profiles were acquired from serum, liver, brain, heart and abdominal adipose tissues from F1 neonate (3 weeks), F1 adult (16 weeks) and F2 neonate offspring. LTA characterised the number, type and abundance of lipid variables in and between tissues, finding a variety of reprogrammings associated with a high carbohydrate paternal diet. These results are important because they describe the long‐term metabolic result of parental dietary intake not ascribed to mothers. The novel analytical tool used is important because it offers unparalleled insight into possible mechanisms for alterations in lipid metabolism throughout organisms. We are currently using Lipid Traffic Analysis to answer questions about changes to lipid metabolism in maternally‐driven nutritional programming in mice and diet‐driven changes in both lipid and sterol metabolism in honeybees.

In this paper we present an investigation of parental-diet-driven metabolic programming in offspring using a novel computational network analysis tool. The impact of high paternal carbohydrate intake on offsprings’ phospholipid and triglyceride metabolism in F1 and F2 generations is described. Detailed lipid profiles were acquired from F1 neonate (3 weeks), F1 adult (16 weeks) and F2 neonate offspring in serum, liver, brain, heart and abdominal adipose tissues by MS and NMR. Using a purpose-built computational tool for analysing both phospholipid and fat metabolism as a network, we characterised the number, type and abundance of lipid variables in and between tissues (Lipid Traffic Analysis), finding a variety of reprogrammings associated with paternal diet. These results are important because they describe the long-term metabolic result of dietary intake by fathers. This analytical approach is important because it offers unparalleled insight into possible mechanisms for alterations in lipid metabolism throughout organisms.

Increasing brown adipose tissue (BAT) mass and activation has been proposed as a potential therapeutic strategy to treat obesity and associated cardiometabolic complications. Given that obese and diabetic patients possess low amounts of BAT, an efficient way to expand their BAT mass would be necessary if BAT is to be useful. Currently, there is limited knowledge about how human BAT develops, differentiates, and is optimally activated. Moreover, to have access to human BAT is challenging, given its low volume and being anatomically dispersed. These constrain makes detailed mechanistic studies related to BAT development and function in humans virtually impossible. To overcome these limitations, we have developed a human-relevant new protocol for the differentiation of human pluripotent stem cells (hPSCs) into brown adipocytes (BAs). Unique to this protocol is that it is chemically-defined to recapitulate a physiological step-by-step developmental path of BAT that captures transient paraxial mesoderm and BAT progenitor states, on its way to reaching the adipocyte stage finally. These hPSC-derived BAs express brown adipocyte and thermogenic markers, are insulin sensitive, and respond to β-adrenergic stimuli. This new protocol is a scalable tool to study human BAs during development.