Interleukin-33 Signaling Controls the Development of Iron-Recycling Macrophages.

Splenic red pulp macrophages (RPMs) contribute to erythrocyte homeostasis and are required for iron recycling. Heme induces the expression of SPIC transcription factor in monocyte-derived macrophages and promotes their differentiation into RPM precursors, pre-RPMs. However, the requirements for differentiation into mature RPMs remain unknown. Here, we have demonstrated that interleukin (IL)-33 associated with erythrocytes and co-cooperated with heme to promote the generation of mature RPMs through activation of the MyD88 adaptor protein and ERK1/2 kinases downstream of the IL-33 receptor, IL1RL1. IL-33- and IL1RL1-deficient mice showed defective iron recycling and increased splenic iron deposition. Gene expression and chromatin accessibility studies revealed a role for GATA transcription factors downstream of IL-33 signaling during the development of pre-RPMs that retained full potential to differentiate into RPMs. Thus, IL-33 instructs the development of RPMs as a response to physiological erythrocyte damage with important implications to iron recycling and iron homeostasis.

Radiographic Cortical Thickness Index Predicts Fragility Fracture in Gaucher Disease.

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 absorptiometry (DXA). However, osteonecrosis and bone fracture may affect the accuracy of DXA. Purpose To assess the utility of DXA and radiographic femoral cortical thickness measurements as predictors of fragility fracture in patients with GD with long-term follow-up (up to 30 years). Materials and Methods Patients with GD age 16 years and older with a detailed medical history, at least one bone image (DXA and/or radiographs), and minimum 2 years follow-up were retrospectively identified using three merged UK-based registries (Gaucherite study, enrollment 2015-2017; Clinical Bone Registry, enrollment 2003-2006; and Mortality Registry, enrollment 1993-2019). Cortical thickness index (CTI) and canal-to-calcar ratio (CCR) were measured by two independent observers, and inter- and intraobserver reliability was calculated. The fracture-predictive value of DXA, CTI, CCR, and cutoff values were calculated using receiver operating characteristic curves. Statistical differences were assessed using univariable and multivariable analysis. Results Bone imaging in 247 patients (123 men, 124 women; baseline median age, 39 years; IQR, 27-50 years) was reviewed. The median follow-up period was 11 years (IQR, 7-19 years; range, 2-30 years). Thirty-five patients had fractures before or at first bone imaging, 23 patients had fractures after first bone imaging, and 189 patients remained fracture-free. Inter- and intraobserver reproducibility for CTI/CCR measurements was substantial (range, 0.96-0.98). In the 212 patients with no baseline fracture, CTI (cutoff, ≤0.50) predicted future fractures with higher sensitivity and specificity (area under the receiver operating characteristic curve [AUC], 0.96; 95% CI: 0.84, 0.99; sensitivity, 92%; specificity, 96%) than DXA T-score at total hip (AUC, 0.78; 95% CI: 0.51, 0.91; sensitivity, 64%; specificity, 93%), femoral neck (AUC, 0.73; 95% CI: 0.50, 0.86; sensitivity, 64%; specificity, 73%), lumbar spine (AUC, 0.69; 95% CI: 0.49, 0.82; sensitivity, 57%; specificity, 63%), and forearm (AUC, 0.78; 95% CI: 0.59, 0.89; sensitivity, 70%; specificity, 70%). Conclusion Radiographic cortical thickness index of 0.50 or less was a reliable independent predictor of fracture risk in Gaucher disease. Clinical trial registration no. NCT03240653 © RSNA, 2022 Supplemental material is available for this article.

Lipid Remodeling in Hepatocyte Proliferation and Hepatocellular Carcinoma.

BACKGROUND AND AIMS: Hepatocytes undergo profound metabolic rewiring when primed to proliferate during compensatory regeneration and in hepatocellular carcinoma (HCC). However, the metabolic control of these processes is not fully understood. In order to capture the metabolic signature of proliferating hepatocytes, we applied state-of-the-art systems biology approaches to models of liver regeneration, pharmacologically and genetically activated cell proliferation, and HCC. APPROACH AND RESULTS: Integrating metabolomics, lipidomics, and transcriptomics, we link changes in the lipidome of proliferating hepatocytes to altered metabolic pathways including lipogenesis, fatty acid desaturation, and generation of phosphatidylcholine (PC). We confirm this altered lipid signature in human HCC and show a positive correlation of monounsaturated PC with hallmarks of cell proliferation and hepatic carcinogenesis. CONCLUSIONS: Overall, we demonstrate that specific lipid metabolic pathways are coherently altered when hepatocytes switch to proliferation. These represent a source of targets for the development of therapeutic strategies and prognostic biomarkers of HCC.

Paternal nutritional programming of lipid metabolism is propagated through sperm and seminal plasma.

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.

A comparative transcriptomic analysis of glucagon-like peptide-1 receptor- and glucose-dependent insulinotropic polypeptide receptor-expressing cells in the hypothalamus

OBJECTIVE: The hypothalamus is a key region of the brain implicated in homeostatic regulation, and is an integral centre for the control of feeding behaviour. Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are incretin hormones with potent glucoregulatory function through engagement of their respective cognate receptors, GLP-1R and GIPR. Recent evidence indicates that there is a synergistic effect of combining GIP- and GLP-1-based pharmacology on appetite and body weight. The mechanisms underlying the enhanced weight loss exhibited by GIPR/GLP-1R co-agonism are unknown. Gipr and Glp1r are expressed in the hypothalamus in both rodents and humans. To better understand incretin receptor-expressing cell populations, we compared the cell types and expression profiles of Gipr- and Glp1r-expressing hypothalamic cells using single-cell RNA sequencing. METHODS: Using Glp1r-Cre or Gipr-Cre transgenic mouse lines, fluorescent reporters were introduced into either Glp1r- or Gipr-expressing cells, respectively, upon crossing with a ROSA26-EYFP reporter strain. From the hypothalami of these mice, fluorescent Glp1rEYFP+ or GiprEYFP+ cells were FACS-purified and sequenced using single-cell RNA sequencing. Transcriptomic analysis provided a survey of both non-neuronal and neuronal cells, and comparisons between Glp1rEYFP+ and GiprEYFP + populations were made. RESULTS: A total of 14,091 Glp1rEYFP+ and GiprEYFP+ cells were isolated, sequenced and taken forward for bioinformatic analysis. Both Glp1rEYFP+ and GiprEYFP+ hypothalamic populations were transcriptomically highly heterogeneous, representing vascular cell types, oligodendrocytes, astrocytes, microglia, and neurons. The majority of GiprEYFP+ cells were non-neuronal, whereas the Glp1rEYFP+ population was evenly split between neuronal and non-neuronal cell types. Both Glp1rEYFP+ and GiprEYFP+ oligodendrocytes express markers for mature, myelin-forming oligodendrocytes. While mural cells are represented in both Glp1rEYFP+ and GiprEYFP+ populations, Glp1rEYFP+ mural cells are largely smooth muscle cells, while the majority of GiprEYFP+ mural cells are pericytes. The co-expression of regional markers indicate that clusters of Glp1rEYFP+ and GiprEYFP+ neurons have been isolated from the arcuate, ventromedial, lateral, tuberal, suprachiasmatic, and premammillary nuclei of the hypothalamus. CONCLUSIONS: We have provided a detailed comparison of Glp1r and Gipr cells of the hypothalamus with single-cell resolution. This resource will provide mechanistic insight into how engaging Gipr- and Glp1r-expressing cells of the hypothalamus may result in changes in feeding behaviour and energy balance.

Lipid Metabolism Is Dysregulated before, during and after Pregnancy in a Mouse Model of Gestational Diabetes.

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.

Quantitative assessment of ribosome drop-off in E. coli.

Premature ribosome drop-off is one of the major errors in translation of mRNA by ribosomes. However, repeated analyses of Ribo-seq data failed to quantify its strength inE. coli Relying on a novel highly sensitive data analysis method we show that a significant rate of ribosome drop-off is measurable and can be quantified also when cells are cultured under non-stressing conditions. Moreover, we find that the drop-off rate is highly variable, depending on multiple factors. In particular, under environmental stress such as amino acid starvation or ethanol intoxication, the drop-off rate markedly increases.

A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length.

Ribosomes are the molecular machinery that catalyse all the fundamental steps involved in the translation of mRNAs into proteins. Given the complexity of this process, the efficiency of protein synthesis depends on a large number of factors among which ribosome drop-off (i.e. the premature detachment of the ribosome from the mRNA template) plays an important role. However, an in vitro quantification of the extent to which ribosome drop-off occurs is not trivial due to difficulties in obtaining the needed experimental evidence. In this work we focus on the study of ribosome drop-off in Saccharomyces cerevisiae by using 'Ribofilio', a novel software tool that relies on a high sensitive strategy to estimate the ribosome drop-off rate from ribosome profiling data. Our results show that ribosome drop-off events occur at a significant rate also when S. cerevisiae is cultured in standard conditions. In this context, we also identified a correlation between the ribosome drop-off rate and the genes length: the longer the gene, the lower the drop-off rate.

Systemic analysis of lipid metabolism from individuals to multi-organism systems.

Lipid metabolism is recognised as being central to growth, disease and health. Lipids, therefore, have an important place in current research on globally significant topics such as food security and biodiversity loss. However, answering questions in these important fields of research requires not only identification and measurement of lipids in a wider variety of sample types than ever before, but also hypothesis-driven analysis of the resulting 'big data'. We present a novel pipeline that can collect data from a wide range of biological sample types, taking 1 000 000 lipid measurements per 384 well plate, and analyse the data systemically. We provide evidence of the power of the tool through proof-of-principle studies using edible fish (mackerel, bream, seabass) and colonies of Bombus terrestris. Bee colonies were found to be more like mini-ecosystems and there was evidence for considerable changes in lipid metabolism in bees through key developmental stages. This is the first report of either high throughput LCMS lipidomics or systemic analysis in individuals, colonies and ecosystems. This novel approach provides new opportunities to analyse metabolic systems at different scales at a level of detail not previously feasible, to answer research questions about societally important topics.

A mouse model of gestational diabetes shows dysregulated lipid metabolism post-weaning, after return to euglycaemia.

BACKGROUND: Gestational diabetes is associated with increased risk of type 2 diabetes mellitus and cardiovascular disease for the mother in the decade after delivery. However, the molecular mechanisms that drive these effects are unknown. Recent studies in humans have shown that lipid metabolism is dysregulated before diagnosis of and during gestational diabetes and we have shown previously that lipid metabolism is also altered in obese female mice before, during and after pregnancy. These observations led us to the hypothesis that this persistent dysregulation reflects an altered control of lipid distribution throughout the organism. METHODS: We tested this in post-weaning (PW) dams using our established mouse model of obese GDM (high fat, high sugar, obesogenic diet) and an updated purpose-built computational tool for plotting the distribution of lipid variables throughout the maternal system (Lipid Traffic Analysis v2.3). RESULTS: This network analysis showed that unlike hyperglycaemia, lipid distribution and traffic do not return to normal after pregnancy in obese mouse dams. A greater range of phosphatidylcholines was found throughout the lean compared to obese post-weaning dams. A range of triglycerides that were found in the hearts of lean post-weaning dams were only found in the livers of obese post-weaning dams and the abundance of odd-chain FA-containing lipids differed locally in the two groups. We have therefore shown that the control of lipid distribution changed for several metabolic pathways, with evidence for changes to the regulation of phospholipid biosynthesis and FA distribution, in a number of tissues. CONCLUSIONS: We conclude that the control of lipid metabolism is altered following an obese pregnancy. These results support the hypothesis that obese dams that developed GDM maintain dysregulated lipid metabolism after pregnancy even when glycaemia returned to normal, and that these alterations could contribute to the increased risk of later type 2 diabetes and cardiovascular disease.

Dietary PUFAs drive diverse system-level changes in lipid metabolism.

OBJECTIVE: Polyunsaturated fatty acid (PUFA) supplements have been trialled as a treatment for a number of conditions and produced a variety of results. This variety is ascribed to the supplements, that often comprise a mixture of fatty acids, and to different effects in different organs. In this study, we tested the hypothesis that the supplementation of individual PUFAs has system-level effects that are dependent on the molecular structure of the PUFA. METHODS: We undertook a network analysis using Lipid Traffic Analysis to identify both local and system-level changes in lipid metabolism using publicly available lipidomics data from a mouse model of supplementation with FA(20:4n-6), FA(20:5n-3), and FA(22:6n-3); arachidonic acid, eicosapentaenoic acid, and docosahexaenoic acid, respectively. Lipid Traffic Analysis is a new computational/bioinformatics tool that uses the spatial distribution of lipids to pinpoint changes or differences in control of metabolism, thereby suggesting mechanistic reasons for differences in observed lipid metabolism. RESULTS: There was strong evidence for changes to lipid metabolism driven by and dependent on the structure of the supplemented PUFA. Phosphatidylcholine and triglycerides showed a change in the variety more than the total number of variables, whereas phosphatidylethanolamine and phosphatidylinositol showed considerable change in both which variables and the number of them, in a highly PUFA-dependent manner. There was also evidence for changes to the endogenous biosynthesis of fatty acids and to both the elongation and desaturation of fatty acids. CONCLUSIONS: These results show that the full biological impact of PUFA supplementation is far wider than any single-organ effect and implies that supplementation and dosing with PUFAs require a system-level assessment.

Lipid Traffic Analysis reveals the impact of high paternal carbohydrate intake on offsprings' lipid metabolism.

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.

Phenotypic characterization of Adig null mice suggests roles for adipogenin in the regulation of fat mass accrual and leptin secretion.

Adipogenin (Adig) is an adipocyte-enriched transmembrane protein. Its expression is induced during adipogenesis in rodent cells, and a recent genome-wide association study associated body mass index (BMI)-adjusted leptin levels with the ADIG locus. In order to begin to understand the biological function of Adig, we studied adipogenesis in Adig-deficient cultured adipocytes and phenotyped Adig null (Adig-/-) mice. Data from Adig-deficient cells suggest that Adig is required for adipogenesis. In vivo, Adig-/- mice are leaner than wild-type mice when fed a high-fat diet and when crossed with Ob/Ob hyperphagic mice. In addition to the impact on fat mass accrual, Adig deficiency also reduces fat-mass-adjusted plasma leptin levels and impairs leptin secretion from adipose explants, suggesting an additional impact on the regulation of leptin secretion.

Unraveling the Developmental Roadmap toward Human Brown Adipose Tissue.

Increasing brown adipose tissue (BAT) mass and activation is a therapeutic strategy to treat obesity and complications. Obese and diabetic patients possess low amounts of BAT, so an efficient way to expand their mass is necessary. There is limited knowledge about how human BAT develops, differentiates, and is optimally activated. Accessing human BAT is challenging, given its low volume and anatomical dispersion. These constraints make detailed BAT-related developmental and functional mechanistic studies in humans virtually impossible. We have developed and characterized functionally and molecularly a new chemically defined protocol for the differentiation of human pluripotent stem cells (hPSCs) into brown adipocytes (BAs) that overcomes current limitations. This protocol recapitulates step by step the physiological developmental path of human BAT. The BAs obtained express BA and thermogenic markers, are insulin sensitive, and responsive to ß-adrenergic stimuli. This new protocol is scalable, enabling the study of human BAs at early stages of development.

Glucose-Dependent Insulinotropic Polypeptide Receptor-Expressing Cells in the Hypothalamus Regulate Food Intake.

Ambiguity regarding the role of glucose-dependent insulinotropic polypeptide (GIP) in obesity arises from conflicting reports asserting that both GIP receptor (GIPR) agonism and antagonism are effective strategies for inhibiting weight gain. To enable identification and manipulation of Gipr-expressing (Gipr) cells, we created Gipr-Cre knockin mice. As GIPR-agonists have recently been reported to suppress food intake, we aimed to identify central mediators of this effect. Gipr cells were identified in the arcuate, dorsomedial, and paraventricular nuclei of the hypothalamus, as confirmed by RNAscope in mouse and human. Single-cell RNA-seq identified clusters of hypothalamic Gipr cells exhibiting transcriptomic signatures for vascular, glial, and neuronal cells, the latter expressing somatostatin but little pro-opiomelanocortin or agouti-related peptide. Activation of Gq-DREADDs in hypothalamic Gipr cells suppressed food intake in vivo, which was not obviously additive with concomitant GLP1R activation. These data identify hypothalamic GIPR as a target for the regulation of energy balance.

Comparison of Human and Murine Enteroendocrine Cells by Transcriptomic and Peptidomic Profiling.

Enteroendocrine cells (EECs) produce hormones such as glucagon-like peptide 1 and peptide YY that regulate food absorption, insulin secretion, and appetite. Based on the success of glucagon-like peptide 1-based therapies for type 2 diabetes and obesity, EECs are themselves the focus of drug discovery programs to enhance gut hormone secretion. The aim of this study was to identify the transcriptome and peptidome of human EECs and to provide a cross-species comparison between humans and mice. By RNA sequencing of human EECs purified by flow cytometry after cell fixation and staining, we present a first transcriptomic analysis of human EEC populations and demonstrate a strong correlation with murine counterparts. RNA sequencing was deep enough to enable identification of low-abundance transcripts such as G-protein-coupled receptors and ion channels, revealing expression in human EECs of G-protein-coupled receptors previously found to play roles in postprandial nutrient detection. With liquid chromatography-tandem mass spectrometry, we profiled the gradients of peptide hormones along the human and mouse gut, including their sequences and posttranslational modifications. The transcriptomic and peptidomic profiles of human and mouse EECs and cross-species comparison will be valuable tools for drug discovery programs and for understanding human metabolism and the endocrine impacts of bariatric surgery.

On deducing causality in metabolic networks.

BACKGROUND: Metabolic networks present a complex interconnected structure, whose understanding is in general a non-trivial task. Several formal approaches have been developed to support the investigation of such networks. One of the relevant problems in this context is the comprehension of causality dependencies amongst the molecules involved in the metabolic process. RESULTS: We apply techniques from formal methods and computational logic to develop an abstract qualitative model of metabolic networks in order to determine possible causal dependencies. Keeping in mind both expressiveness and ease of use, we aimed at providing: i) a minimal notation to represent causality in biochemical interactions, and ii) an automated tool allowing human experts to easily vary conditions of in silico experiments. We exploit a reading of chemical reactions in terms of logical implications: starting from a description of a metabolic network in terms of reaction rules and initial conditions, chains of reactions, causally depending one from the another, can be automatically deduced. Both the components of the initial state and the clauses ruling reactions can be easily varied and a new trial of the experiment started, according to a what-if investigation strategy. Our approach aims at exploiting computational logic as a formal modeling framework, amongst the several available, that is naturally close to human reasoning. It directly leads to executable implementations and may support, in perspective, various reasoning schemata. Indeed, our abstractions are supported by a computational counterpart, based on a Prolog implementation, which allows for a representation language closely correspondent to the adopted chemical abstract notation. The proposed approach has been validated by results regarding gene knock-out and essentiality for a model of the metabolic network of Escherichia coli K12, which show a relevant coherence with available wet-lab experimental data. CONCLUSIONS: Starting from the presented work, our goal is to provide an effective analysis toolkit, supported by an efficient full-fledged computational counterpart, with the aim of fruitfully driving in vitro experiments by effectively pruning non promising directions.

A computational approach to the functional screening of genomes.

Comparative genomics usually involves managing the functional aspects of genomes, by simply comparing gene-by-gene functions. Following this approach, Mushegian and Koonin proposed a hypothetical minimal genome, Minimal Gene Set (MGS), aiming for a possible oldest ancestor genome. They obtained MGS by comparing the genomes of two simple bacteria and eliminating duplicated or functionally identical genes. The authors raised the fundamental question of whether a hypothetical organism possessing MGS is able to live or not. We attacked this viability problem specifying in silico the metabolic pathways of the MGS-based prokaryote. We then performed a dynamic simulation of cellular metabolic activities in order to check whether the MGS-prokaryote reaches some equilibrium state and produces the necessary biomass. We assumed these two conditions to be necessary for a living organism. Our simulations clearly show that the MGS does not express an organism that is able to live. We then iteratively proceeded with functional replacements in order to obtain a genome composition that gives rise to equilibrium. We ruled out 76 of the original 254 genes in the MGS, because they resulted in duplication from a functional point of view. We also added seven genes not present in the MGS. These genes encode for enzymes involved in critical nodes of the metabolic network. These modifications led to a genome composed of 187 elements expressing a virtually living organism, Virtual Cell (ViCe), that exhibits homeostatic capabilities and produces biomass. Moreover, the steady-state distribution of the concentrations of virtual metabolites that resulted was similar to that experimentally measured in bacteria. We conclude then that ViCe is able to "live in silico."

Degradation Parameters from Pulse-Chase Experiments.

Pulse-chase experiments are often used to study the degradation of macromolecules such as proteins or mRNA. Considerations for the choice of pulse length include the toxicity of the pulse to the cell and maximization of labeling. In the general case of non-exponential decay, varying the length of the pulse results in decay patterns that look different. Analysis of these patterns without consideration to pulse length would yield incorrect degradation parameters. Here we propose a method that constructively includes pulse length in the analysis of decay patterns and extracts the parameters of the underlying degradation process. We also show how to extract decay parameters reliably from measurements taken during the pulse phase.