Epigenetically active chromatin in neonatal iWAT reveals GABPα as a potential regulator of beige adipogenesis.

Background: Thermogenic beige adipocytes, which dissipate energy as heat, are found in neonates and adults. Recent studies show that neonatal beige adipocytes are highly plastic and contribute to >50% of beige adipocytes in adults. Neonatal beige adipocytes are distinct from recruited beige adipocytes in that they develop independently of temperature and sympathetic innervation through poorly defined mechanisms. Methods: We characterized the neonatal beige adipocytes in the inguinal white adipose tissue (iWAT) of C57BL6 postnatal day 3 and 20 mice (P3 and P20) by imaging, genome-wide RNA-seq analysis, ChIP-seq analysis, qRT-PCR validation, and biochemical assays. Results: We found an increase in acetylated histone 3 lysine 27 (H3K27ac) on the promoter and enhancer regions of beige-specific gene UCP1 in iWAT of P20 mice. Furthermore, H3K27ac ChIP-seq analysis in the iWAT of P3 and P20 mice revealed strong H3K27ac signals at beige adipocyte-associated genes in the iWAT of P20 mice. The integration of H3K27ac ChIP-seq and RNA-seq analysis in the iWAT of P20 mice reveal epigenetically active signatures of beige adipocytes, including oxidative phosphorylation and mitochondrial metabolism. We identify the enrichment of GA-binding protein alpha (GABPα) binding regions in the epigenetically active chromatin regions of the P20 iWAT, particularly on beige genes, and demonstrate that GABPα is required for beige adipocyte differentiation. Moreover, transcriptomic analysis and glucose oxidation assays revealed increased glycolytic activity in the neonatal iWAT from P20. Conclusions: Our findings demonstrate that epigenetic mechanisms regulate the development of peri-weaning beige adipocytes via GABPα. Further studies to better understand the upstream mechanisms that regulate epigenetic activation of GABPα and characterization of the metabolic identity of neonatal beige adipocytes will help us harness their therapeutic potential in metabolic diseases.

metGWAS 1.0: an R workflow for network-driven over-representation analysis between independent metabolomic and meta-genome-wide association studies.

MOTIVATION: The method of genome-wide association studies (GWAS) and metabolomics combined provide an quantitative approach to pinpoint metabolic pathways and genes linked to specific diseases; however, such analyses require both genomics and metabolomics datasets from the same individuals/samples. In most cases, this approach is not feasible due to high costs, lack of technical infrastructure, unavailability of samples, and other factors. Therefore, an unmet need exists for a bioinformatics tool that can identify gene loci-associated polymorphic variants for metabolite alterations seen in disease states using standalone metabolomics. RESULTS: Here, we developed a bioinformatics tool, metGWAS 1.0, that integrates independent GWAS data from the GWAS database and standalone metabolomics data using a network-based systems biology approach to identify novel disease/trait-specific metabolite-gene associations. The tool was evaluated using standalone metabolomics datasets extracted from two metabolomics-GWAS case studies. It discovered both the observed and novel gene loci with known single nucleotide polymorphisms when compared to the original studies. AVAILABILITY AND IMPLEMENTATION: The developed metGWAS 1.0 framework is implemented in an R pipeline and available at: https://github.com/saifurbd28/metGWAS-1.0.

Heterogeneity in Early Postpartum Metabolic Profiles Among Women with GDM Who Progressed to Type 2 Diabetes During 10-Year Follow-Up: The SWIFT Study.

GDM is a strong risk factor for progression to T2D after pregnancy. Although both GDM and T2D exhibit heterogeneity, the link between the distinct heterogeneity of GDM and incident T2D has not been established. Herein, we evaluate early postpartum profiles of women with recent GDM who later developed incident T2D using a soft clustering method, followed by the integration of both clinical phenotypic variables and metabolomics to characterize these heterogeneous clusters/groups clinically and their molecular mechanisms. We identified three clusters based on two indices of glucose homeostasis at 6-9 weeks postpartum - HOMA-IR and HOMA-B among women who developed incident T2D during the 12-year follow-up. The clusters were classified as follows: pancreatic beta-cell dysfunction group (cluster-1), insulin resistant group (cluster-3), and a combination of both phenomena (cluster-2) comprising the majority of T2D. We also identified postnatal blood test parameters to distinguish the three clusters for clinical testing. Moreover, we compared these three clusters in their metabolomics profiles at the early stage of the disease to identify the mechanistic insights. A significantly higher concentration of a metabolite at the early stage of a T2D cluster than other clusters indicates its essentiality for the particular disease character. As such, the early-stage characters of T2D cluster-1 pathology include a higher concentration of sphingolipids, acyl-alkyl phosphatidylcholines, lysophosphatidylcholines, and glycine, indicating their essentiality for pancreatic beta-cell function. In contrast, the early-stage characteristics of T2D cluster-3 pathology include a higher concentration of diacyl phosphatidylcholines, acyl-carnitines, isoleucine, and glutamate, indicating their essentiality for insulin actions. Notably, all these biomolecules are found in the T2D cluster-2 with mediocre concentrations, indicating a true nature of a mixed group. In conclusion, we have deconstructed incident T2D heterogeneity and identified three clusters with their clinical testing procedures and molecular mechanisms. This information will aid in adopting proper interventions using a precision medicine approach.

Integration of AI and traditional medicine in drug discovery.

AI integration in plant-based traditional medicine could be used to overcome drug discovery challenges.

Diminished Sphingolipid Metabolism, a Hallmark of Future Type 2 Diabetes Pathogenesis, Is Linked to Pancreatic ß Cell Dysfunction.

Gestational diabetes mellitus (GDM) is the top risk factor for future type 2 diabetes (T2D) development. Ethnicity profoundly influences who will transition from GDM to T2D, with high risk observed in Hispanic women. To better understand this risk, a nested 1:1 pair-matched, Hispanic-specific, case-control design was applied to a prospective cohort with GDM history. Women who were non-diabetic 6-9 weeks postpartum (baseline) were monitored for the development of T2D. Metabolomics were performed on baseline plasma to identify metabolic pathways associated with T2D risk. Notably, diminished sphingolipid metabolism was highly associated with future T2D. Defects in sphingolipid metabolism were further implicated by integrating metabolomics and genome-wide association data, which identified two significantly enriched T2D-linked genes, CERS2 and CERS4. Follow-up experiments in mice and cells demonstrated that inhibiting sphingolipid metabolism impaired pancreatic ß cell function. These data suggest early postpartum alterations in sphingolipid biosynthesis contribute to ß cell dysfunction and T2D risk.

The magnesium transporter NIPAL1 is a pancreatic islet-expressed protein that conditionally impacts insulin secretion.

Type 2 diabetes is a chronic metabolic disease characterized by pancreatic ß-cell dysfunction and peripheral insulin resistance. Among individuals with type 2 diabetes, ∼30% exhibit hypomagnesemia. Hypomagnesemia has been linked to insulin resistance through reduced tyrosine kinase activity of the insulin receptor; however, its impact on pancreatic ß-cell function is unknown. In this study, through analysis of several single-cell RNA-sequencing data sets in tandem with quantitative PCR validation in both murine and human islets, we identified NIPAL1 (NIPA-like domain containing 1), encoding a magnesium influx transporter, as an islet-enriched gene. A series of immunofluorescence experiments confirmed NIPAL1's magnesium-dependent expression and that it specifically localizes to the Golgi in Min6-K8 cells, a pancreatic ß-cell-like cell line (mouse insulinoma 6 clone K8). Under varying magnesium concentrations, NIPAL1 knockdown decreased both basal insulin secretion and total insulin content; in contrast, its overexpression increased total insulin content. Although the expression, distribution, and magnesium responsiveness of NIPAL1 in α-TC6 glucagonoma cells (a pancreatic α-cell line) were similar to the observations in Min6-K8 cells, no effect was observed on glucagon secretion in α-TC6 cells under the conditions studied. Overall, these results suggest that NIPAL1 expression is regulated by extracellular magnesium and that down-regulation of this transporter decreases glucose-stimulated insulin secretion and intracellular insulin content, particularly under conditions of hypomagnesemia.

Isoniazid and host immune system interactions: A proposal for a novel comprehensive mode of action.

The known mode of action of isoniazid (INH) is to inhibit bacterial cell wall synthesis following activation by the bacterial catalase-peroxidase enzyme KatG in Mycobacterium tuberculosis (Mtb). This simplistic model fails to explain (a) how isoniazid penetrates waxy granulomas with its very low lipophilicity, (b) how isoniazid kills latent Mtb lacking a typical cell wall, and (c) why isoniazid treatment time is remarkably long in contrast to most other antibiotics. To address these questions, a novel comprehensive mode of action of isoniazid has been proposed here. Briefly, isoniazid eradicates latent tuberculosis (TB) by prompting slow differentiation of pro-inflammatory monocytes and providing protection against reactive species-induced "self-necrosis" of phagocytes. In the case of active TB, different immune cells form INH-NAD+ adducts to inhibit Mtb's cell wall biosynthesis. This additionally suggests that the antibacterial properties of INH do not rely on KatG of Mtb. As such, isoniazid-resistant TB needs to be re-evaluated.

Unbiased data analytic strategies to improve biomarker discovery in precision medicine.

Omics technologies promised improved biomarker discovery for precision medicine. The foremost problem of discovered biomarkers is irreproducibility between patient cohorts. From a data analytics perspective, the main reason for these failures is bias in statistical approaches and overfitting resulting from batch effects and confounding factors. The keys to reproducible biomarker discovery are: proper study design, unbiased data preprocessing and quality control analyses, and a knowledgeable application of statistics and machine learning algorithms. In this review, we discuss study design and analysis considerations and suggest standards from an expert point-of-view to promote unbiased decision-making in biomarker discovery in precision medicine.

Correction to: The discovery of novel predictive biomarkers and early-stage pathophysiology for the transition from gestational diabetes to type 2 diabetes.

Unfortunately, the graph in Fig. 5f became misaligned during typesetting.

Isoniazid induces a monocytic-like phenotype in HL-60 cells.

Isoniazid (INH) is one of the oldest drugs for the treatment of tuberculosis (TB) and is of continual clinical and research interest. The aim of the current study is to investigate the ability of INH to induce monocyte differentiation and the underlying signaling pathway involved in this phenomenon using HL-60 cells. In this study, HL-60 cells were treated with different non-cytotoxic concentrations of INH or vitamin D (a well-known inducer of monocytic differentiation) to determine key functional changes in the phenotype of these cells using several biochemical and cytobiological experiments. HL-60 cells are derived from human promyelocytic leukemia and bear some resemblance to promyelocytes, which differentiate into various cell types. INH-induced differentiation was confirmed to occur in a concentration-dependent manner through several functional markers such as nonspecific esterase activity, NADPH oxidase activity and expression of surface markers CD14 and CD16 (characteristic of monocytes). INH-induced monocytic-like differentiation in HL-60 cells and demonstrated that at least 25% of cells were differentiated within the range of the pharmacological concentrations of INH. To determine the effects of INH on HL-60 cells, we applied quantitative proteomics that revealed 32 proteins were altered significantly in pathways that could involve differentiation signals. Lastly, INH activated the ERK-1/MAPK signaling pathway based on detection of phosphorylated ERK-1. These in vitro findings in HL-60 cells warrant further study using promyelocytes or hematopoietic stem cells to evaluate the physiological capability of INH to induce monocytic differentiation that may aid in host defense against TB.

The discovery of novel predictive biomarkers and early-stage pathophysiology for the transition from gestational diabetes to type 2 diabetes.

AIMS/HYPOTHESIS: Gestational diabetes mellitus (GDM) affects up to 20% of pregnancies, and almost half of the women affected progress to type 2 diabetes later in life, making GDM the most significant risk factor for the development of future type 2 diabetes. An accurate prediction of future type 2 diabetes risk in the early postpartum period after GDM would allow for timely interventions to prevent or delay type 2 diabetes. In addition, new targets for interventions may be revealed by understanding the underlying pathophysiology of the transition from GDM to type 2 diabetes. The aim of this study is to identify both a predictive signature and early-stage pathophysiology of the transition from GDM to type 2 diabetes. METHODS: We used a well-characterised prospective cohort of women with a history of GDM pregnancy, all of whom were enrolled at 6-9 weeks postpartum (baseline), were confirmed not to have diabetes via 2 h 75 g OGTT and tested anually for type 2 diabetes on an ongoing basis (2 years of follow-up). A large-scale targeted lipidomic study was implemented to analyse ~1100 lipid metabolites in baseline plasma samples using a nested pair-matched case-control design, with 55 incident cases matched to 85 non-case control participants. The relationships between the concentrations of baseline plasma lipids and respective follow-up status (either type 2 diabetes or no type 2 diabetes) were employed to discover both a predictive signature and the underlying pathophysiology of the transition from GDM to type 2 diabetes. In addition, the underlying pathophysiology was examined in vivo and in vitro. RESULTS: Machine learning optimisation in a decision tree format revealed a seven-lipid metabolite type 2 diabetes predictive signature with a discriminating power (AUC) of 0.92 (87% sensitivity, 93% specificity and 91% accuracy). The signature was highly robust as it includes 45-fold cross-validation under a high confidence threshold (1.0) and binary output, which together minimise the chance of data overfitting and bias selection. Concurrent analysis of differentially expressed lipid metabolite pathways uncovered the upregulation of α-linolenic/linoleic acid metabolism (false discovery rate [FDR] 0.002) and fatty acid biosynthesis (FDR 0.005) and the downregulation of sphingolipid metabolism (FDR 0.009) as being strongly associated with the risk of developing future type 2 diabetes. Focusing specifically on sphingolipids, the downregulation of sphingolipid metabolism using the pharmacological inhibitors fumonisin B1 (FB1) and myriocin in mouse islets and Min6 K8 cells (a pancreatic beta-cell like cell line) significantly impaired glucose-stimulated insulin secretion but had no significant impact on whole-body glucose homeostasis or insulin sensitivity. CONCLUSIONS/INTERPRETATION: We reveal a novel predictive signature and associate reduced sphingolipids with the pathophysiology of transition from GDM to type 2 diabetes. Attenuating sphingolipid metabolism in islets impairs glucose-stimulated insulin secretion.

Global protein expression dataset acquired during isoniazid-induced cytoprotection against H2O2 challenge in HL-60 cells.

Isoniazid (INH) is one of the first-line anti-tuberculosis drugs. Its effect on oxidative stress, however, is unknown. Here we used a model of oxidative stress by employing glucose/glucose oxidase (GOx), which (based on the availability of glucose and oxygen) is known to produce H2O2. This reaction induces oxidative stress culminating in necrotic cell death in HL-60 cells (a human promyelocytic leukemia cell line). The changes in protein levels have been quantified using global proteome expression changes through stable isotope labeling by amino acids in cell culture (SILAC) followed by LC-MS/MS analysis. A total of 1459 and 1712 proteins were identified in forward and reverse experiments, respectively. However, only 390 proteins were reproducibly identified in both samples. These 390 proteins were taken into account for further analysis which has been described in "Cytoprotective effect of isoniazid against H2O2 derived injury in HL-60 cells" [1].

Metabolism of isoniazid by neutrophil myeloperoxidase leads to isoniazid-NAD(+) adduct formation: A comparison of the reactivity of isoniazid with its known human metabolites.

The formation of isonicotinyl-nicotinamide adenine dinucleotide (INH-NAD(+)) via the mycobacterial catalase-peroxidase enzyme, KatG, has been described as the major component of the mode of action of isoniazid (INH). However, there are numerous human peroxidases that may catalyze this reaction. The role of neutrophil myeloperoxidase (MPO) in INH-NAD(+) adduct formation has never been explored; this is important, as neutrophils are recruited at the site of tuberculosis infection (granuloma) through infected macrophages' cell death signals. In our studies, we showed that neutrophil MPO is capable of INH metabolism using electron paramagnetic resonance (EPR) spin-trapping and UV-Vis spectroscopy. MPO or activated human neutrophils (by phorbol myristate acetate) catalyzed the oxidation of INH and formed several free radical intermediates; the inclusion of superoxide dismutase revealed a carbon-centered radical which is considered to be the reactive metabolite that binds with NAD(+). Other human metabolites, including N-acetyl-INH, N-acetylhydrazine, and hydrazine did not show formation of carbon-centered radicals, and either produced no detectable free radicals, N-centered free radicals, or superoxide, respectively. A comparison of these free radical products indicated that only the carbon-centered radical from INH is reducing in nature, based on UV-Vis measurement of nitroblue tetrazolium reduction. Furthermore, only INH oxidation by MPO led to a new product (λmax=326nm) in the presence of NAD(+). This adduct was confirmed to be isonicotinyl-NAD(+) using LC-MS analysis where the intact adduct was detected (m/z=769). The findings of this study suggest that neutrophil MPO may also play a role in INH pharmacological activity.

Cytoprotective effect of isoniazid against H2O2 derived injury in HL-60 cells.

To combat tuberculosis (TB), host phagocytic cells need to survive against self-generating oxidative stress-induced necrosis. However, the effect of isoniazid (INH) in protecting cells from oxidative stress-induced necrosis has not been previously investigated. In this in vitro study, the cytotoxic effect of H2O2 generation using glucose oxidase (a model of oxidative stress) was found to be abrogated by INH in a concentration-dependent manner in HL-60 cells (a human promyelocytic leukemia cell). In cells treated with glucose oxidase, both ATP and mitochondrial membrane potential were found to be decreased. However, treatment with INH demonstrated small but significant attenuation in decreasing ATP levels, and complete reversal for the decrease in mitochondrial membrane potential. Quantitative proteomics analysis identified up-regulation of 15 proteins and down-regulation of 14 proteins which all together suggest that these proteomic changes signal for increasing cellular replication, structural integrity, ATP synthesis, and inhibiting cell death. In addition, studies demonstrated that myeloperoxidase (MPO) was involved in catalyzing INH-protein adduct formation. Unexpectedly, these covalent protein adducts were correlated with INH-induced cytoprotection in HL-60 cells. Further studies are needed to determine whether the INH-protein adducts were causative in the mechanism of cytoprotection.

Proteomic profile of aminoglutethimide-induced apoptosis in HL-60 cells: Role of myeloperoxidase and arylamine free radicals.

In this study, the cellular effects resulting from the metabolism of aminoglutethimide by myeloperoxidase were investigated. Human promyelocytic leukemia (HL-60) cells were treated with aminoglutethimide (AG), an arylamine drug that has a risk of adverse drug reactions, including drug-induced agranulocytosis. HL-60 cells contain abundant amounts of myeloperoxidase (MPO), a hemoprotein, which catalyzes one-electron oxidation of arylamines using H2O2 as a cofactor. Previous studies have shown that arylamine metabolism by MPO results in protein radical formation. The purpose of this study was to determine if pathways associated with a toxic response could be determined from conditions that produced protein radicals. Conditions for AG-induced protein radical formation (with minimal cytotoxicity) were optimized, and these conditions were used to carry out proteomic studies. We identified 43 proteins that were changed significantly upon AG treatment among which 18 were up-regulated and 25 were down-regulated. The quantitative proteomic data showed that AG peroxidative metabolism led to the down-regulation of critical anti-apoptotic proteins responsible for inhibiting the release of pro-apoptotic factors from the mitochondria as well as cytoskeletal proteins such as nuclear lamina. This overall pro-apoptotic response was confirmed with flow cytometry which demonstrated apoptosis to be the main mode of cell death, and this was attenuated by MPO inhibition. This response correlated with the intensity of AG-induced protein radical formation in HL-60 cells, which may play a role in cell death signaling mechanisms.

Phenylbutazone Oxidation via Cu,Zn-SOD Peroxidase Activity: An EPR Study.

We investigated the effect of Cu,Zn-superoxide dismutase (Cu,Zn-SOD)-peroxidase activity on the oxidation of the nonsteroidal anti-inflammatory drug phenylbutazone (PBZ). We utilized electron paramagnetic resonance (EPR) spectroscopy to detect free radical intermediates of PBZ, UV-vis spectrophotometry to monitor PBZ oxidation, oxygen analysis to determine the involvement of C-centered radicals, and LC/MS to determine the resulting metabolites. Using EPR spectroscopy and spin-trapping with 5,5-dimethyl-1-pyrroline-N-oxide (DMPO), we found that the spin adduct of CO3(•-) (DMPO/(•)OH) was attenuated with increasing PBZ concentrations. The resulting PBZ radical, which was assigned as a carbon-centered radical based on computer simulation of hyperfine splitting constants, was trapped by both DMPO and MNP spin traps. Similar to Cu,Zn-SOD-peroxidase activity, an identical PBZ carbon-centered radical was also detected with the presence of both myeloperoxidase (MPO/H2O2) and horseradish peroxidase (HRP/H2O2). Oxygen analysis revealed depletion in oxygen levels when PBZ was oxidized by SOD peroxidase-activity, further supporting carbon radical formation. In addition, UV-vis spectra showed that the λmax for PBZ (λ = 260 nm) declined in intensity and shifted to a new peak that was similar to the spectrum for 4-hydroxy-PBZ when oxidized by Cu,Zn-SOD-peroxidase activity. LC/MS evidence supported the formation of 4-hydroxy-PBZ when compared to that of a standard, and 4-hydroperoxy-PBZ was also detected in significant yield. These findings together indicate that the carbonate radical, a product of SOD peroxidase activity, appears to play a role in PBZ metabolism. Interestingly, these results are similar to findings from heme peroxidase enzymes, and the context of this metabolic pathway is discussed in terms of a mechanism for PBZ-induced toxicity.

Current status and future prospects of toxicogenomics in drug discovery.

In drug discovery and development (DDD), the efficacy, safety and cost of new chemical entities are the main concerns of the pharmaceutical industry. Continuously updated and stricter recommendations imposed by regulatory authorities result in greater challenges being faced by the industry. Reliable high-throughput techniques integrated with well-designed analytical tools at all stages of DDD (termed 'next-generation DDD') could be a possible approach to obtaining new drug approval by cutting costs as well as ensuring the highest level of patient safety. In this review, we describe the various components of holistic toxicogenomics with examples of applications, and discuss the various analytical tools and platforms to illustrate the current status and prospects of next-generation DDD.