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Sort 2 diabetes disrupts circadian orchestration of lipid metabolism and membrane fluidity in human pancreatic islets


Current proof means that circadian clocks guarantee temporal orchestration of lipid homeostasis and play a task in pathophysiology of metabolic illnesses in people, together with sort 2 diabetes (T2D). Nonetheless, circadian regulation of lipid metabolism in human pancreatic islets has not been explored. Using lipidomic analyses, we carried out temporal profiling in human pancreatic islets derived from 10 nondiabetic (ND) and 6 T2D donors. Amongst 329 detected lipid species throughout 8 main lipid lessons, 5% exhibited circadian rhythmicity in ND human islets synchronized in vitro. Two-time point-based lipidomic analyses in T2D human islets revealed international and temporal alterations in phospho- and sphingolipids. Key enzymes regulating turnover of sphingolipids have been rhythmically expressed in ND islets and exhibited altered ranges in ND islets bearing disrupted clocks and in T2D islets. Strikingly, mobile membrane fluidity, measured by a Nile Crimson spinoff NR12S, was lowered in plasma membrane of T2D diabetic human islets, in ND donors’ islets with disrupted circadian clockwork, or handled with sphingolipid pathway modulators. Furthermore, inhibiting the glycosphingolipid biosynthesis led to sturdy discount of insulin secretion triggered by glucose or KCl, whereas inhibiting earlier steps of de novo ceramide synthesis resulted in milder inhibitory impact on insulin secretion by ND islets. Our information recommend that circadian clocks operative in human pancreatic islets are required for temporal orchestration of lipid homeostasis, and that perturbation of temporal regulation of the islet lipid metabolism upon T2D results in altered insulin secretion and membrane fluidity. These phenotypes have been recapitulated in ND islets bearing disrupted clocks.


Inner circadian clocks have advanced in most residing beings to permit anticipation of day by day mild modifications as a result of Earth rotation. In mammals, this physique timekeeping system depends on a central pacemaker residing in paired suprachiasmatic nuclei within the hypothalamus and a number of peripheral clocks within the organs [1,2]. It includes myriads of cell-autonomous oscillators operative in most cells that guarantee temporal orchestration of all points of physiology and metabolism [3,4]. On the identical time, a dramatic rise in cardiometabolic illnesses together with weight problems and kind 2 diabetes (T2D) worldwide has been related to the 24/7 life-style of our society that results in power desynchrony between inner circadian system and exterior synchronizing cues (mild, consuming) dubbed circadian misalignment [3,5,6].

In pancreatic islets, research in mouse fashions revealed that purposeful molecular oscillators are indispensable for absolute and temporal regulation of insulin and glucagon secretion [79], and for compensatory β-cell regeneration [10]. Surprisingly, the circadian clocks in neighboring α- and β-cells aren’t section aligned, and so they exhibit cell-specific circadian response to physiologically related synchronizers corresponding to adrenalin, glucagon, GLP1, or somatostatin [8,11]. Persistently, clock-deficient mice present extreme perturbations of glucose and lipid metabolism which might be exacerbated upon islet-specific clock disruption and lack of β-cell regenerative capability following large ablation [7,10,12]. In people, cell-autonomous clocks operative in α- and β-cells orchestrate the rhythmic sample of proinsulin, insulin, and glucagon secretion [1315]. Disruption of purposeful oscillators in human islet cells from ND (nondiabetic) donors, mediated by small interfering RNA (siRNA) focusing on of CLOCK, resulted in strongly diminished absolute ranges and perturbed rhythmicity of basal insulin secretion exerted through lowered secretory granule docking and exocytosis [13,15]. Most strikingly, our current research reveals that the circadian clockwork is compromised in human α- and β-cells in T2D. Clock perturbation in T2D islets was paralleled with altered temporal profiles of insulin and glucagon secretion [15].

Lipid metabolites are concerned in power homeostasis, membrane perform, and signaling, thus enjoying important roles in regulating physique metabolism and in pathophysiology of metabolic issues [1620]. Mass spectrometry–based mostly shotgun lipidomics permits quantification of over 1,000 phospholipids, sphingolipids, and triacylglycerides with excessive accuracy [21,22]. Utilizing this highly effective strategy, it has been demonstrated that in mouse liver, a big portion of lipid species throughout all main lipid lessons show a circadian rhythm, and this rhythmicity is pushed by each circadian clocks and feeding [23]. In people, metabolomics and lipidomics of serial blood samples urged diurnal profiles for a large panel of metabolites and lipids [2426]. Lipidomics of serial human skeletal muscle biopsies obtained throughout 24 h [27] revealed that about 20% of the lipid species throughout all main lipid lessons show a circadian rhythm in ND sufferers [28,29]. Strikingly, the rhythmicity of the lipid metabolites has been preserved in human skeletal myotubes differentiated and synchronized in vitro, highlighting that major cells synchronized in vitro signify invaluable fashions for finding out temporal regulation of lipid metabolism in people [27]. Oscillating lipids in each skeletal muscle tissue and in cultured myotubes weren’t solely restricted to energy-controlling storage lipids corresponding to triglycerides, but in addition comprised membrane and signaling lipids of various mobile compartments [29]. In keeping with these findings, parallel RNA-seq analyses based mostly on the identical experimental design urged that key enzymes regulating lipid biosynthesis and glucose metabolism within the skeletal muscle exhibited rhythmic profiles [30]. Moreover, our earlier works recommend that cell-autonomous circadian oscillators are indispensable for the right coordination of glucose uptake and temporal lipid profiles in human muscle, since glucose uptake was lowered and the lipid oscillations have been blunted upon siClock-mediated disruption of the skeletal myotube oscillator [29,30].

Dysregulation of lipid metabolism performs a key function in pathophysiology of metabolic illnesses. Lipidomic approaches have pointed to novel mechanistic insights into pathophysiology of weight problems and T2D [16,17,20,26,3134]. The sample of lipid alterations was tissue and illness particular, permitting to outline distinct lipid signatures related to weight problems or T2D [35]. The blood ranges of ceramides species and 1-deoxysphingolipids have been proposed as T2D biomarker candidates or therapeutic targets [3641]. Whereas the roles of lipid metabolites in β-cell perform and dysfunction upon T2D growth have been raised in a number of research carried out in immortalized cell strains [42,43] but in addition in mouse fashions and in people [44], no information on human islet lipidomics and its regulation by the circadian system have been offered to this point. To fill this hole, we aimed to uncover molecular determinants of circadian regulation of lipid homeostasis in human pancreatic islets beneath physiological circumstances and upon T2D. Using lipidomic approaches, we exhibit the circadian rhythmicity of phospho- and sphingolipids in human pancreatic islets from ND donors synchronized in vitro. Most significantly, we offer a novel hyperlink between disruption of circadian clock, temporal coordination of lipid metabolism in human pancreatic islet, and islet dysfunction upon T2D in people, highlighting each molecular oscillator and sphingolipid metabolites as vital therapeutic targets for metabolic illnesses.


Circadian lipidomics of human pancreatic islets synchronized in vitro

To look at the function of cell-autonomous circadian oscillators operative in human pancreatic islets in temporal orchestration of the islet lipid homeostasis, we carried out lipidomic evaluation of intact human pancreatic islets synchronized in vitro. Islets obtained from 6 ND donors (see Desk 1 for donor traits) have been synchronized by a forskolin pulse and picked up throughout 24 h in accordance with the experimental design offered in Fig 1A. Rhythmic expression of key core clock transcripts validated environment friendly in vitro synchronization of human pancreatic islets (S1 Fig). Out of 711 measured lipids, a complete of 410 lipid species clustered in 8 main lipid lessons have been detected throughout all donors (S2A and S2B Fig and S1 Information). The proportion of lipids exhibiting diurnal oscillations in accordance with the METACYCLE algorithm assorted from 0.98% to 14.88% among the many donors (Fig 1B and S2 Information). A peak of accumulation of rhythmic lipids was noticed 12 h to 16 h following in vitro synchronization in a lot of the donors (Figs 1C and S2C). When the lipid species have been clustered by lipid class, the distribution of the rhythmic lipids indicated that sure lipid lessons have been preferentially topic to circadian oscillations, though this distribution assorted throughout the donors (S2D Fig). Phosphatidylinositol (PI) lipids have been notably enriched among the many cyclic species in all donors (Figs 1B and S2D), even when the general variety of rhythmic lipid species was low, like in donor 5. We additional investigated the abundance of various PI lipids all through the circadian cycle. Lyso-, diacyl-, and ether-containing PIs displayed a typical sample of oscillation with a peak at 12 h and a nadir at 32 h after synchronization and as much as 2-fold circadian amplitude (Fig 1D). We recognized 3 particular person lipids considerably rhythmic (p < 0.05) in a minimum of 3 islet batches out of 6, all of them belonging to the PI lipid class: PI(O-)44:4, PI28:3, and PI40:2 (Figs 1E and S2E–S2G), the previous being rather more considerable than the others on this lipid class (S2H Fig). Noteworthy, the diploma of desaturation of those lipids influenced their temporal profiles. Certainly, whereas PI saturated of their fatty acyl chains (known as saturated fatty acids (SFAs)) exhibited circadian rhythmicity with a single peak of abundance at 12 h after in vitro synchronization, the MUFA and PUFA (respectively monounsaturated and polyunsaturated) PIs displayed profiles nearer to what we observe for different lipid lessons following synchronization (Figs 1F and 1G and S2I–S2K). Certainly, the phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidylserine (PS), probably the most considerable lessons of membrane lipids together with the PI, exhibited vital temporal modifications of their ranges throughout 24 h, however with no clear circadian sample (S2I Fig). The PC/PE ratio, an indicator of cell membrane integrity, was comparatively fixed all through the circadian cycle (S2L Fig).


Fig 1. Identification of rhythmic lipid metabolites in human islets.

(A) Experimental design for the gathering of human pancreatic islets synchronized with forskolin pulse and harvested on the indicated 7 time factors (n = 6 donors; asterisks point out assortment time). (B) Proportion of circadian rhythmic lipid species in accordance with METACYCLE in pancreatic islets in every of the analyzed donors and corresponding heatmaps over the 7 time factors. Normalized z-scores of lipid metabolites are indicated in yellow (excessive) and blue (low). See additionally S2 Information. (C) Common temporal ranges of rhythmic lipids (normalized z-scores) proven in (B) for every islet donors. All profiles have been certified circadian rhythmic (p < 0.05), aside from donor 5. Information are represented as imply ± SEM, n = variety of rhythmic lipids for every donor. See additionally S2 Information. (D) Common temporal profiles of PI species clustered by subclasses (Lyso-, Diacyl, Ether-PI). LysoPI abundance shows a big circadian profile (p < 0.05). See additionally S1 Information. (E) Consultant islet lipids recognized as circadian rhythmic in 3 donors: PI(-O) 44:0, PI28:3, and PI40:2. Particular person lipid profiles (prime panels) with coloured traces equivalent to the donors exhibiting a circadian rhythmic profile (p worth < 0.05); common lipid profiles (backside panels). See additionally S1 Information. (F) Common temporal profiles of SFA PI phospholipid species. See additionally S1 Information. (G) Common temporal profiles of PI phospholipid species sorted by diploma of saturation, from MUFA lipids to PUFA lipids. See additionally S1 Information. (H) Common temporal profiles of ceramide species by subclasses: HexDHCer, DHCer, HexCer, and Cer. DHCer abundance shows a big circadian profile (p < 0.05). See additionally S1 Information. Lipid concentrations of PI proven in (F, G) have been corrected for sophistication II isotopic overlaps by performing extra deisotoping evaluation on the normalized values. Information for (D–H) are represented as imply ± SEM, n = 6. See additionally S2 Fig. MUFA, monounsaturated fatty acid; PI, phosphatidylinositol; PUFA, polyunsaturated fatty acid; SFA, saturated fatty acid.

As well as, we noticed heterogenous temporal profiles of assorted sphingolipids (SL) (S2J Fig). Dihydroceramides exhibit a considerably rhythmic accumulation all through the 24 h in accordance with METACYCLE, and their temporal accumulation “across the clock” virtually overlapped with the one of many ceramides (Cer), hexosylceramides (HexCer), and hexosyldihydroceramides (HexDHCer) (Fig 1H). This related variation of abundance among the many ceramides lessons suggests a rhythmic de novo synthesis of the ceramides in pancreatic islets (Fig 1H). In distinction, the profile of the sphingomyelins (SM), probably the most considerable SL, was nearer to that of the glycerophospholipids and cardiolipins (S2I–S2K Fig). General, lipid ranges strongly modified over the course of 24 h, with variability noticed among the many islet donors. Importantly, the PI, and to a lesser extent, the Cer and HexCer exhibited oscillatory profiles all through all of the donors, suggesting a widespread influence of the circadian oscillator on these lipid lessons metabolism in human pancreatic islets.

Lipidomic profiling reveals main modifications in lipid metabolites at 2 time factors in human T2D pancreatic islets synchronized in vitro

After figuring out circadian rhythmic lipid metabolites within the pancreatic islets from ND donors cultured and synchronized in vitro, we subsequent tried to measure their temporal alterations in T2D islets. Since we weren’t capable of conduct a whole across the clock research on T2D human islets as a result of lack of fabric, lipid profiles have been assessed at 2 reverse time factors, 12 h and 24 h following synchronization by forskolin pulse (n = 5 T2D donors) and in comparison with the ND islet counterpart (n = 4, see Desk 1 and S3 Information). The chosen time factors correspond to peak and trough of the core clock gene BMAL1 expression stage (S1 Fig) and of the rhythmic profiles obtained for lipid species in a lot of the examined ND donors (4 out of 6 donors, Fig 1C). To evaluate whether or not T2D is characterised by international modifications in lipid homeostasis in human islets, because it was the case in different metabolic tissues [35], we first averaged the degrees of lipids detected on the 2 time factors and in contrast these to the lipid class distribution in ND islets (Fig 2A–2D). Hierarchical clustering evaluation of the highest 30 lipid stage modifications reveals an imperfect separation of the samples collected from T2D and ND donors, because the islet lipids from donor ND 10 clustered nearer to the T2D counterpart than the opposite 3 ND people (Fig 2A). General, we noticed a concomitant development of decreased PE lipid ranges and elevated PC ranges within the T2D islet group, leading to a development towards a rise PC/PE ratio that didn’t attain statistical significance (Fig 2C and 2D). Cer and HexCer exhibited a bent towards improve within the T2D group, whereas a number of PI lipids have been down-regulated (Fig 2A and 2B and 2E–2G). As a result of numerous phospholipid species (PE, PI, PC) have been both up- or down-regulated in T2D islets (Fig 2A–2G), no vital change in general quantity per lipid class was noticed between T2D and ND islets (Fig 2C).


Fig 2. Lipidomic analyses of human islets derived from T2D versus ND donors cultured and synchronized in vitro.

(A) Hierarchical clustering evaluation (Distance Measure: Euclidian; Clustering algorithm: Ward) of prime 30 islet lipids with most contrasting patterns between T2D and management ND counterpart. For every donor, islet lipids ranges measured at 12 h and 24 h after forskolin synchronization have been averaged (n = 5 for the islets from T2D donors and n = 4 for the islets from ND donors). (B) Volcano plots of differentially considerable islet lipids (fold change ≥ 1.5 and p < 0.05, Welch’s corrected) between T2D (n = 5) and ND donors (n = 4). Coloured dots spotlight vital up- or down-regulated particular person lipid species. (C) Lipid class repartition (PC, PE, PI, PS, CL, HexCer, Cer, and SM) in human islets from ND and T2D donors (in mol%), synchronized in vitro and picked up at 12 h and 24 h after in vitro synchronization. The information signify the typical of the two time factors (n = 5 for the islets from T2D donors and n = 4 for the islets from ND donors, imply ± SEM). (D) Comparability of the PC/PE ratio in islets from ND (n = 4) versus islets from T2D donors (n = 5). The information signify the typical of the two time factors (12 h and 24 h) ± SEM. (E, F) Consultant examples of particular person lipids (PI44:1 and HexCer34:1(-H2O)) down- (E) and up- (F) regulated within the islets from T2D donors in comparison with islets from ND donors. The information signify the log2 fold change. (G) DHCer42:0(-H2O) ranges in T2D versus ND islets synchronized in vitro and picked up after 12 h. (H, I) Abundance of considerably differentially regulated lipids between the management and the T2D teams at 12 h (H) and 24 h (I). Every bar represents the sum of the considerably differentially regulated particular person lipids proven in Fig 3E and 3F, as proportion of the entire lipids detected from the identical class on the identical time level. Information are represented as imply ± SEM. (J, Ok) Relative stage modifications (mol%) of DHCer, Cer, HexDHCer, and HexCer in islets from T2D (n = 5) and ND (n = 4) donors collected 12 h (J) and 24 h (Ok) after synchronization, imply ± SEM. (L, M) Consultant examples of particular person lipids (HexCer34:1(-H2O) and PI44:1) up- (L) and down- (M) regulated in T2D versus ND islets synchronized in vitro and picked up after 24 h. The information signify the log2 fold change. (N, O) Relative PC (N) and PE (O) stage modifications (mol%) in islets from T2D and ND donors collected 24 h after synchronization. Lipids are clustered in accordance with the character of the fatty acid linkage (diacyl versus alkyl-acyl (ether) or monoacyl (lyso)). T2D donors (n = 5) and ND donors (n = 4), imply ± SEM. (P, Q) Relative PE stage modifications (in pmol/nmol of phosphate with lipid concentrations corrected for sophistication II isotopic overlaps) in islets from T2D and ND donors collected 12 h (P) and 24 h (Q) after synchronization represented in accordance with the diploma of saturation. T2D donors (n = 5) and ND donors (n = 4), imply ± SEM. Statistical analyses for (C, D, H–Ok, and N–Q) are unpaired t check with Welch’s correction. *p < 0.05, **p < 0.01. See additionally S3 Information. Cer, ceramide; CL, cardiolipin; DHCer, dihydroceramide; HexCer, hexosylceramide; HexDHCer, hexosyldihydroceramide; ND, nondiabetic; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PI, phosphatidylinositol; PS, phosphatidylserine; SM, sphingomyelin; T2D, sort 2 diabetes.

Assuming that variations between the T2D and ND islets may very well be masked as a result of common evaluation throughout 2 time factors, we subsequent analyzed the islet lipids stage at 12 h and 24 h individually. On this case, the hierarchical clustering confirmed a transparent separation of the samples in accordance with the donor group (T2D and ND) at each time factors (Fig 3A and 3B), with the next variety of vital differentially considerable lipids (DALs) noticed at 24 h (5 totally different lipids at 12 h versus 12 at 24 h, with fold change > 1.5 and p < 0.05) (Fig 3C and 3D). Not one of the lipids differentially considerable between the teams was frequent throughout the two time factors (Fig 3E and 3F), additional highlighting the significance of temporal evaluation, even when carried out in 2 time factors solely. Strikingly, a number of HexCer, representing roughly 40% of all lipids of this class (Fig 2H and 2I), have been considerably differentially regulated between the T2D and ND teams (Fig 3F). Persistently, wanting on the ranges of all main lipid lessons (Fig 3G and 3H), we seen the next stage of whole HexCer within the T2D group in comparison with the ND group at each time factors with marked distinction at 24 h (Figs 2J–2L and 3I). A number of C16, C22, and C24 containing HexCer species have been notably elevated 24 h after synchronization within the islets from the T2D donors in comparison with ND counterparts (Fig 3J). Whereas the ceramide ranges have been solely barely elevated in T2D islets, considerable DHCer species have been elevated within the T2D teams at 12 h after synchronization (Fig 2H and 2J and 2K).

Among the many phospholipids, few metabolites have been down-regulated within the T2D group that principally belonged to the PE and PI lipid lessons (Figs 2M and 3E), in settlement with the beforehand noticed international variations (Fig 2A and 2B). At 24 h, the concomitant improve of PC and reduce of diacyl PE ranges (Fig 2N and 2O) resulted in a big improve of the PC/PE ratio, identified to affect mobile calcium homeostasis and ER perform [45] (Fig 3K). An identical change has been noticed at 12 h; nevertheless, it didn’t attain statistical significance (Fig 3L). Whereas all unsaturated PE subspecies, no matter their diploma of saturation, exhibited the development towards the lower within the T2D group, this distinction didn’t attain significance for PUFA 4 (at each time factors) and PUFA 5 to six (at 24 h) (Fig 3M and 3N). In distinction, this distinction was extremely vital for PUFA 3, even after deisotoping correction of the lipid indicators (Fig 2P and 2Q). Since improve in PUFAs throughout the membrane enhances membrane fluidity [46], the lower within the PUFA-PE content material may be indicative of defects in plasma membrane bodily properties within the islets derived from T2D sufferers. Collectively, these experiments reveal main alterations within the pancreatic islet lipid homeostasis in T2D sufferers, doubtlessly indicative of an elevated irritation and ER stress and lowered membrane plasticity.


Fig 3. Comparability of human islet lipidome from T2D and ND donors at 12 and 24 h after in vitro synchronization.

(A, B) Hierarchical clustering evaluation (Distance Measure: Euclidian; Clustering algorithm: Ward) of prime 50 islet lipids with most contrasting patterns between T2D and management sufferers at 12 h (A) and 24 h (B) after forskolin synchronization. (C, D) Volcano plots of differentially considerable islet lipids (fold change ≥ 1.5 and p < 0.05, Welch’s corrected) at 12 h (C) and 24 h (D), between T2D and ND donors. Coloured dots spotlight vital up- or down-regulated particular person lipid species. (E, F) Venn diagrams assessing the down-regulated (E) and up-regulated (F) lipid species shared by the two indicated time factors in islets collected from T2D donors. (G, H) Lipid class repartition (PC, PE, PI, PS, CL, HexCer, Cer, and SM) in human islets from ND and T2D donors (in mol%), synchronized in vitro and picked up at 12 h (G) and 24 h (H). (I) Comparability of the relative HexCer stage modifications (mol%) in ND versus T2D islets collected at 12 h and 24 h after synchronization. (J) Comparability of the relative HexCer stage modifications, sorted by variety of carbons, over the entire of islet lipids (mol%) measured in ND and T2D islets collected at 24 h after synchronization. (Ok, L) Ratio between PC and PE at 12 h (L) and 24 h (Ok) after synchronization. (M, N) Relative PE stage modifications (mol%) in islets from T2D and ND donors collected 12 h (M) and 24 h (N) after synchronization represented in accordance with the diploma of saturation. Statistics for (G–N) are unpaired 2-tailed t check with Welch’s correction. T2D donors (n = 5) and ND donors (n = 4), information are represented as imply ± SEM. * p < 0.05. ** p < 0.01. See additionally S3 Information. Cer, ceramide; CL, cardiolipin; HexCer, hexosylceramide; ND, nondiabetic; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PI, phosphatidylinositol; PS, phosphatidylserine; SM, sphingomyelin; T2D, sort 2 diabetes.

Diurnal ceramide ranges correlate with transcript profiles encoding key enzymes concerned of their turnover

Our information reveal that HexCer show each a rhythmic accumulation sample across the clock in islets from ND sufferers synchronized in vitro and better ranges in islets from T2D sufferers. To discover the molecular determinants, we investigated the temporal gene expression profile of UDP-glucose ceramide glucosyltransferase (UGCG), a key enzyme concerned in glucosylceramide biosynthesis that catalyzes the switch of glucose from UDP-glucose to ceramide. Strikingly, the UGCG mRNA expression measured across the clock within the islets from ND donors exhibited a rhythmic profile (p = 0.05 as assessed by JTK_Cycle) with the trough round 20 to 24 h following in vitro synchronization, corroborating the temporal profile of BMAL1 transcript (S1 Fig), and recapitulating the diurnal accumulation profile of HexCer (Fig 4A). Remarkably, we observe a concordance between the upper stage of HexCer within the T2D group at 24 h and the UGCG transcript up-regulation in the identical group in comparison with the ND group (Fig 4B).


Fig 4. Diurnal ceramide ranges correlate with transcript profiles encoding for key enzymes concerned of their biosynthesis.

(A) Common temporal profiles of HexCer species (left, n = 6) and RT-qPCR temporal gene expression profile of UGCG (proper, n = 3). See additionally S1 and S4 Information. (B) Comparability of the relative HexCer stage modifications (mol%) in ND versus T2D islets collected at 24 h after in vitro synchronization (left, n = 6) with the UGCG expression measured in ND and T2D islets (proper, n = 9). See additionally S3 and S4 Information. (C) Common temporal profiles of ceramide species (left, n = 6), DHCer (center, n = 6), and RT-qPCR temporal gene expression profile of CERS2 (proper, n = 3). See additionally S1 and S4 Information. (D) Comparability of the relative ceramide (left) and DHCer (center) stage modifications (mol%) in ND versus T2D islets collected 12 h and 24 h after synchronization (n = 6) with the CERS2 expression measured in ND and T2D islets (proper, n = 9). See additionally S3 and S4 Information. (E) Comparability of the relative ranges of PC (mol%) in ND versus T2D islets collected 12 h and 24 h after synchronization (left, n = 6) with the CEPT1 (center) and CHKA (proper) expression measured in ND and T2D islets (n = 9). See additionally S3 and S4 Information. The R numerical worth signifies the corresponding Pearson correlation coefficient and its related p-value. Transcript ranges have been normalized to HPRT and 9S expression. Information are represented as imply ± SEM, unpaired 2-tailed t check; p * < 0.05, p ** < 0.01. DHCer, dihydroceramide; HexCer; hexosylceramide; HPRT, hypoxanthine-guanine phosphoribosyltransferase; ND, nondiabetic; PC, phosphatidylcholine; T2D, sort 2 diabetes.

We subsequent assessed whether or not a correlation exists between the degrees of Cer and DHCer lipid lessons and the temporal mRNA profiles of ceramide synthases, concerned in N-acylation of sphinganine and sphingosine bases to kind DHCer and Cer. Ceramide synthase 2 (CerS2), probably the most considerable and ubiquitously expressed ceramide synthase [16,4749] shows temporal variation in its mRNA expression that correlates with the ceramide and DHCer accumulation profiles (Fig 4C). As well as, the tendency for the next quantity of Cer and DHCer in islets from the T2D donors in comparison with their counterparts that was particularly pronounced for DHCer at 12 h after synchronization, concordantly with the numerous improve of CerS2 transcript in T2D islets (Fig 4D).

Past the enzymes concerned in lipid metabolism that exhibited oscillatory patterns, we additionally analyzed the connection between the enzymes that have been considerably differentially expressed in islets from T2D in comparison with ND donors and the corresponding lipid class abundance in every group. CEPT1 and CHKA genes code for choline/ethanolamine phosphotransferase and choline kinase alpha enzymes, respectively, which might be concerned in PC biosynthesis through the CDP-choline pathway. Apparently, the slight improve in PC ranges within the T2D group, extra pronounced at 24 h and contributing to a big improve within the PC/PE ratio presently level (Fig 3K), was related to an up-regulation of each CEPT1 and CHKA mRNA expression within the T2D group in comparison with the ND counterpart (Fig 4E).

Lipid membrane fluidity of the human pancreatic islet cells is diminished in T2D islets and in ND islets upon circadian clock disruption

Collectively, the alterations in lipid metabolites that we noticed in human pancreatic islets derived from T2D donors pointed towards a risk of perturbed membrane group and fluidity in T2D islet cells, which may influence their secretory perform. We subsequently measured membrane fluidity in human islet cells from T2D donors in comparison with ND counterpart (Fig 5A) by bioimaging utilizing a Nile crimson spinoff NR12S that’s thought to penetrate solely the outer leaflet of the plasma membrane [50]. Fluorescence emission of NR12S is delicate to the membrane surroundings in a approach that in additional ordered membranes fluorescence emission is blue shifted, whereas in disordered membranes the fluorescence emission spectra is crimson shifted [50]. This shift in emission profile between liquid-disordered and liquid-ordered phases permits a quantitative evaluation of membrane order by calculating the ratio of the fluorescence depth recorded in 2 spectral channels, generally known as the generalized polarization (GP) worth [51]. GP quantification of NR12S fluorescence emission from ND and T2D islet cell photographs revealed vital improve in membrane rigidity in T2D islet cells as in comparison with ND counterparts (Fig 5A).


Fig 5. Lipid membrane fluidity of the human pancreatic islet cells is attenuated in T2D islets, in ND islets upon siClock-mediated clock disruption, and in ND islets following perturbation of ceramide metabolism by PDMP or myriocin.

Reside cell imaging of human islet cells stained with NR12S dye. (A) Consultant ND (left) and T2D (proper) human islet cells. The graph on the fitting summarizes the quantification of fluorescence GP ratio for n = 4 ND and n = 3 T2D donors. (B) Consultant photographs of ND islet cells transfected with scrambled siRNA (siControl, left) bearing purposeful clocks and siClock focusing on CLOCK protein that bear perturbed oscillators (proper). The graph on the fitting summarizes the quantification of fluorescence GP ratio for n = 3 donors. (C) Consultant photographs of nontreated management ND islet cells (left), cells following 1-h remedy with PDMP (center) or myriocin (proper). The graph summarizes the quantification of fluorescence GP ratio for n = 3 human donors. Word the numerous up-regulation of membrane rigidity for T2D islet cells (A), ND cells with compromised clocks (B, siClock), and ND cells with impaired sphingolipid metabolism (C, PDMP and myriocin). Graph information are represented as imply ± SEM; unpaired 2-tailed t check as in comparison with management, p * < 0.05, p ** < 0.01. See additionally S3 Fig and S4 Information. GP, generalized polarization; ND, nondiabetic; siRNA, small interfering RNA; T2D, sort 2 diabetes.

We now have not too long ago demonstrated that purposeful perturbation of insulin secretion by human pancreatic islets derived from T2D islets was recapitulated in ND human islet cells upon cell-autonomous clock disruption, each when it comes to diminished absolute secretion and perturbed rhythmic profile, indicating that islet mobile clock disruption could participate in pathophysiology of T2D in people [13,15]. Whether or not such a parallel holds true for the modifications in lipid homeostasis stays unexplored. Disruption of circadian oscillators in ND islet cells by transfection of siRNA focusing on CLOCK following our beforehand validated protocols [13,52] led to considerably elevated expression of UGCG (S3A Fig), equally to the noticed improve on this enzyme in T2D islets (Fig 4B). Furthermore, KEGG pathway enrichment evaluation of all considerably up-regulated transcripts in clock-compromised islets revealed activation of sphingolipid metabolism pathway (p = 0.0575; S3B Fig). To uncover modifications in membrane fluidity in siClock-transfected ND islet cells bearing disrupted oscillators, NR12S fluorescence has been in contrast between clock-compromised cells and management counterparts transfected with scrambled siManagement RNA (Fig 5B, left). Strikingly, membrane fluidity was considerably lowered (Fig 5B, proper), pinpointing that disruption of circadian oscillators in islet cells derived from ND donors results in elevated membrane rigidity, thus recapitulating the phenotype noticed in T2D islets (examine Fig 5B to 5A).

Perturbation of ceramide metabolism impacts insulin secretion by human pancreatic islets and reduces lipid membrane fluidity

On condition that main modifications that we noticed in lipid homeostasis within the islets from T2D donors have been associated to altered sphingolipid ranges, we subsequent assessed the influence of inhibiting ceramide de novo synthesis by myriocin on the islet perform. Utility of myriocin to ND islet cells resulted in better GP values of NR12S emission as in comparison with nontreated management (Fig 5C), suggesting improve in membrane rigidity of those cells. To evaluate the impact of myriocin on induced insulin secretion by human pancreatic islets, we carried out glucose-stimulated insulin secretion (GSIS) and KCL-stimulated insulin secretion (KSIS) checks. Utility of myriocin to ND in addition to to T2D islet cells led to compromised insulin secretion beneath low glucose circumstances and a bent to inhibiting each GSIS and KSIS that didn’t attain statistical significance (Fig 6A–6C). We subsequent studied lipid membrane fluidity, GSIS and KSIS within the presence of PDMP that inhibits UCGC, the important thing enzyme of glycosphingolipid biosynthesis. Just like myriocin, software of PDMP to ND islet cells considerably elevated GP values of NR12S emission (Fig 5C). Strikingly, insulin secretion by ND islets was strongly compromised within the presence of PDMP at basal glucose ranges, and after stimulation by excessive glucose, or by KCL (Fig 6D and 6E). An identical impact was noticed when PDMP was utilized to islet cells remoted from T2D sufferers (S4 Fig). Neither myriocin nor PDMP exerted a big impact on the islet cell insulin content material (Fig 6A and 6B and 6D, proper graphs).


Fig 6. Inhibitors of sphingolipid synthesis, PDMP and myriocin, perturb insulin secretion and circadian oscillations by human pancreatic islets.

Inhibitory results of myriocin (A–C) and ceramide analog PDMP (D, E) on basal (1 h at 2.8 mmol glucose), glucose-induced (1 h at 16.7 mmol), and KCL-induced (1 h at 30 mmol KCL) insulin secretion in human islet cells in vitro. Information signify values normalized (Ins/residual Ins) to the entire residual insulin content material (whole residual Ins (mU/L) offered on adjoining graphs) and are expressed as imply ± SEM for n = 7 ND donors (A), n = 3 T2D donors (B), n = 3 ND donors (C), n = 5 ND donors (D), and n = 3 ND donors (E). The distinction is examined by paired 2-tailed t check; p* < 0.05, p** < 0.01. See additionally S4 Fig. (F) Consultant uncooked (left) and detrended (proper) Per2-luc bioluminescence profiles of human islets within the presence of myriocin or PDMP throughout all the bioluminescence recording. (G) Impact of myriocin and PDMP on principal circadian parameters (section, interval size, and amplitude) of Per2-luc oscillations. Information are represented as imply ± SEM, n = 4 ND donors. The distinction is examined by 2-way ANOVA check with Bonferroni posttest; p * < 0.05 (as in comparison with the management counterpart synchronized with forskolin within the absence of those compounds). See additionally S5 Fig and S4 Information. ND, nondiabetic; T2D, sort 2 diabetes.

Ceramide turnover inhibitors myriocin and PDMP alter circadian oscillations in human pancreatic islets synchronized in vitro

For the reason that ceramide ranges exhibited circadian rhythmicity in ND islets on one hand and have been strongly perturbed in T2D islets on the opposite, we subsequent explored whether or not disrupted turnover of ceramides could suggestions on the islet molecular clockwork. To this finish, we recorded circadian bioluminescence of a Period2-luciferase (Per2-luc) lentiviral assemble expressed in ND islet cells synchronized in vitro [14,15] within the presence of myriocin or PDMP within the recording medium (Fig 6F). Utility of myriocin resulted in interval shortening and section advance of circadian oscillations of Per2-luc, whereas PDMP had no vital impact on the islet cell rhythmicity (Fig 6G). In distinction to myriocin that didn’t considerably have an effect on cell mortality, PDMP confirmed a transparent tendency to stimulate islet cell apoptosis following steady 5-day publicity that didn’t attain statistical significance as in comparison with forskolin-treated management (S5 Fig).


Our research reveals that in human pancreatic islets derived from ND donors, about 5% of the lipid metabolites throughout all main lipid lessons exhibited pronounced circadian oscillations following in vitro synchronization. In our earlier lipidomic evaluation, we report that in synchronized human major myotubes, the circadian oscillating lipid species have been extra considerable, reaching as much as 18.6% [29]. Such discrepancy could replicate tissue-specific lipid composition or stem from the excessive inter-donor variability, low variety of the islet donors (n = 6), restricted quantity of beginning materials, and islet mobile heterogeneity.

Among the many totally different lipid species thought of circadian in our evaluation, we report main oscillations of PIs and SLs. PI metabolites are each parts of mobile membranes and signaling molecules which might be important for secretory perform of endocrine β-cells. Certainly, PI lipids generate soluble inositol second messengers concerned within the mobilization of intracellular Ca2+ shops and the recruitment of different signaling proteins regulating formation and secretion of granules on the plasma membrane [53]. Furthermore, stimulation of insulin secretion influences PI metabolism in plasma membranes of MIN6 β-cell line [54,55]. We now have beforehand proven that in vitro synchronized human islets exhibit a circadian profile of insulin secretion, with a respective peak and nadir showing 12 h and 24 h after synchronization [13,15]. This circadian sample of insulin secretion positively correlates with the temporal profile of PI abundance, additionally exhibiting a peak 12 h after forskolin pulse (Fig 1D). We speculate that the circadian oscillations of PI could take part in regulation of temporal secretion of insulin by β-cells. Furthermore, islets derived from T2D donors exhibited a slight lower in whole PIs and a big diminution of a number of particular person considerable PI metabolites (Figs 2M and 3A–3E) concomitant with attenuated insulin secretion, additional supporting a task of those PIs within the insulin launch defects in diabetic β-cells.

Cer and HexCer are 2 extra main lipid lessons exhibiting temporal variations in synchronized human islets, suggesting rhythmic group of sphingolipid metabolism. Moreover, the abundance of the entire DHCer species exhibited circadian oscillations (Fig 1H). These temporal variations are correlated with the rhythmic transcription of CERS2 and UGCG, the important thing enzymes concerned in ceramide and glucosylceramide synthesis (Fig 4A and 4C), in addition to with the expression of core clock transcripts (S1 Fig). Of notice, in some cases, mRNA measurements have been carried out on the islets derived from totally different donors from these utilized for the lipidomics analyses (see Desk 1). In keeping with these outcomes, a large-scale RNA-seq screening of circadian transcripts in in vitro synchronized human islets reveal circadian rhythmic regulation of transcripts coding for key parts of the sphingolipid metabolism (CERKL, SGPL1, NEU2, NEU3, CERS6, CERS4) [7], additional highlighting a circadian regulation of this pathway on the transcriptional stage. Concordantly, we additionally noticed an up-regulation of CERK, SGPL1 [13], and UGCG transcripts upon siClock situation (S3 Fig), implying interconnection between the islet clockwork and regulation of ceramide synthesis. This discovering is according to our evaluation of the human skeletal muscle lipid content material upon CLOCK depletion [30] displaying that UGCG expression is considerably up-regulated in siClock-transfected major myotubes in comparison with siManagement-transfected ones. Accordingly, we noticed a big improve of the entire HexCer in CLOCK-depleted skeletal muscle myotubes [29].

The interplay between molecular clock and sphingolipids appears to be bidirectional since lower in sphingolipid ranges by myriocin resulted in shortening of a circadian interval size and section advance in human islets (Fig 6F and 6G). Periodicity of clock equipment requires purposeful interactions of all its molecular parts and will depend on their expression and/or posttranscriptional modifications. For instance, deletion or mutation of detrimental limb part PER2 results in a shortening of interval size [56,57]. Nonetheless, our information point out that myriocin did not considerably down-regulate Per2-Luc expression, thus not supporting the concept myriocin could exert its impact through modulation of PER2 absolute ranges. Then again, phosphorylation of PER2 at totally different websites modulates the interval size [58] and mutations related to differential phosphorylation of human PER2 underlies familial superior sleep section syndrome [59]. Sphingolipids are thought of to play an vital function in intracellular signaling using lipid–protein interactions [60,61]. A number of protein candidates have been proven to work together with ceramides, sphingosine 1 phosphate (S1P), and glycosphingolipids. These comprise insulin receptor, ceramide-activated Ser-Thr phosphatases (PP1, PP2a), protein kinase B, protein kinase C zeta, and others [6062]. It’s not clear whether or not core clock parts could also be direct or oblique targets of sphingolipid species [58]. Additional research could be required to shed a lightweight on the mechanisms underlying modulatory impact of sphingolipids on the molecular clock equipment.

Perturbation of islet sphingolipid metabolism takes half in pathogenesis of T2D early in illness growth [53,63,64], in addition to in T1D [65]. As a result of restricted availability of human islets derived from T2D donors, we have been unable to carry out full across the clock experiments for this half and compromised on 2-time level design. Consequently, the temporal modifications in lipid metabolites which might be peaking at CT6 and CT18 have been possible missed in T2D islets. The comparability of the lipid content material between T2D and ND islets in 2 time factors revealed an vital modification of the sphingolipid fraction within the T2D islets (Fig 3). In keeping with altered ranges of sphingolipids, expression of CERS2 and UGCG was additionally up-regulated in T2D islets as in comparison with ND counterparts (Fig 4B and 4D). Ceramide accumulation, specifically in skeletal muscle and white adipose tissue, is related to impaired insulin signaling and T2D [38,48,66]. Nonetheless, in our case, probably the most placing distinction between T2D and ND islet lipid content material depends on the degrees of HexCer, and to some extent on DHCer. UGCG enzyme positioned in Golgi is crucial for the formation of glucosylceramides (GlcCer), precursors for many advanced glycosphingolipids [67]. These glycosylated sphingolipids primarily localize within the exterior leaflet of the plasma membrane. They’re concerned in numerous mobile processes, together with calcium homeostasis [68], membrane trafficking, and formation of membrane microdomains [69,70] that play vital roles within the dynamic aggregation of membrane receptors, as demonstrated for the insulin receptor in mouse adipocytes [71,72]. Noteworthy, β-cell metabolic stress induced by acute palmitate remedy stimulates Cer manufacturing, whereas longer (48 h) palmitate publicity will increase, through the up-regulation of UGCG, the degrees of GlcCer with no vital impact on SM and Cer accumulation, [42,73] thus recapitulating the modifications we have now detected in T2D human islets. Equally, stress-induced Cer improve in keratinocytes following publicity to exogenous sphingomyelinase resulted in elevated GlcCer synthase expression and GlcCer ranges [74]. We hypothesize that enhancing the conversion of Cer into GlcCer, through the up-regulation of UGCG, prevents the deleterious impact of extreme Cer quantities and will thus cut back ER stress markers and apoptosis [74,75].

Right here, we present that de novo manufacturing of sphingolipids is required for regular secretion of insulin by human islet cells in vitro, since software of sphingolipid synthesis inhibitor myriocin dampened the basal ranges of secreted insulin in each ND and T2D human islet cells (Fig 6A–6C). Information in mouse islets and in rodent β-cell line additional help an vital function of sphingolipid metabolism for insulin secretion, since inhibition of this pathway in rodent β-cells by myriocin or fumonisin B1 attenuates insulin secretion [63,64]. On the identical time, we confirmed that discount of Cer by shunting them towards HexCer is critical for correct basal and GSIS by human islet cells. Certainly, inhibition of GlcCer biosynthesis by PDMP considerably lowered basal insulin secretion and utterly abolished their response to excessive glucose problem or following KCL-triggered depolarization in vitro (Fig 6D and 6E). Along with glucosylceramide synthase inhibition, the attenuation of mTOR signaling pathway and lysosomal lipid accumulation reported following PDMP remedy [76] could partly account for its inhibitory impact on insulin secretion. Importantly, knockdown of UGCG by siRNA in mouse islets additionally resulted in main insulin secretion defects [77], additional suggesting that UGCG performs a key function within the noticed phenotype.

Current research confirmed that pharmacological inhibition of two different ceramide-shunting pathways (sphingomyelin biosynthesis by D609 and S1P biosynthesis by sphingosine-kinase inhibitor SKI), equally to described right here HexCer biosynthesis inhibition by PDMP, considerably reduces basal and glucose-induced insulin secretion in vitro in addition to in vivo in rodents [63,64]. In MIN6 cells, glucose stimulation enhanced conversion of Cer to GlcCer and to SM [78], in addition to accumulation of S1P however not Cer [79]. Collectively, these information recommend that correct Cer homeostasis is required for stimulus-secretion coupling in β-cells.

Noteworthy, a number of DHCer species have been elevated in T2D islets in comparison with ND islets, with a marked distinction 12 h after synchronization (Figs 2A, 2G, 2J, 3A, 3C, and 3F). The numerous improve of DHCer42:0(-H2O) (C24DHCer) noticed within the T2D islets could masks an up-regulation of C24DoxCer. We and others not too long ago reported that noncanonical 1-deoxyceramide (DoxCer) ranges have been elevated in serum and adipose tissue of T2D sufferers [35,80]. On condition that DoxCer has the very same m/z ratio as DHCer-H2O, these 2 lipid species could also be misidentified, thus requiring a separate evaluation utilizing liquid chromatography mass spectrometry to be correctly measured [35]. Deoxysphingolipids have been proven to compromise GSIS in rodent islets and Ins-1 cells [34] permitting to envisage a selected function of those poisonous sphingolipids within the failure of pancreatic β-cells. Additional lipidomic analyses in human islets must be carried out to conclude this hyperlink in people.

Importantly, we exhibit that the plasma membrane of T2D pancreatic islet cells is extra inflexible in comparison with ND counterparts (Fig 5A). Lowered membrane fluidity was reported in erythrocytes [81], leukocytes [82], and platelets [83,84] from T2D sufferers, suggesting a possible generality of membrane stiffness upon T2D. Strikingly, an analogous phenotype was noticed in clock-compromised islet cells from ND donors that exhibited stiffer plasma membrane than their counterparts bearing purposeful clocks (Fig 5B) and following direct sphingolipid perturbation by PDMP or myriocin (Fig 5C). Rheological properties of the membrane bilayer depend on lipid composition and ldl cholesterol content material [85,86]. Thus, saturated lipids improve membrane rigidity, whereas polyunsaturated phospholipids that bear extra versatile chains facilitate membrane conformational state modifications by rising membrane flexibility and fission [85,8790]. Consequently, membrane PUFAs may be notably crucial for cells that undergo a number of endocytic occasions corresponding to epithelial cells [89]. Our lipidomic evaluation revealed an general development for decreasing PE species, with the degrees of PE-PUFAs being considerably decreased in islets from T2D sufferers as in comparison with their ND counterparts (Figs 2P and 2Q and 3M and 3N). On the identical time, the degrees of PC lipids stayed comparatively secure, thus leading to elevated PC/PE ratio that reaches significance at 24 h after synchronization (Fig 3K). Membrane fluidity impacts on cell communication with the surroundings by affecting the receptor perform, sign transduction, endo-, and exocytosis. Certainly, decreased membrane fluidity reduces the insulin signaling in kidney mononuclear leukocytes and in diabetic kidney [82,91]. The precise mechanism of membrane fluidity modifications within the clock-compromised and T2D human islet cells and its function on insulin secretion and sign transduction in β-cells must be assessed in future research.

In abstract, our large-scale lipidomic analyses present the primary systematic characterization of the temporal group of lipid metabolite panorama in human pancreatic islets from ND donors. Our current research demonstrated that molecular clocks are compromised in pancreatic islets from T2D human donors, resulting in disrupted absolute and temporal profiles of insulin and glucagon secretion [15]. Right here, we report time-of-the-day-specific alterations of lipid metabolism in T2D human islets. The modifications in lipid composition and saturation diploma have been concomitant with noticed lower of membrane fluidity in T2D human islets. Strikingly, a drop-in membrane fluidity was recapitulated in ND islets bearing compromised clocks, according to an analogous parallel between disrupted islet hormone secretion between T2D and ND islets transfected with siClock in our earlier research [15]. Lastly, our information recommend a reciprocal connection between the islet circadian clocks and Cer metabolism. Perturbation of Cer turnover noticed in human pancreatic islets upon T2D could result in exacerbation of the islet clock disruption and thus to additional disturbance of lipid homeostasis in a feed-forward loop. Altogether, we offer a novel hyperlink between disruption of circadian clock, temporal coordination of lipid metabolism in human pancreatic islet, and islet dysfunction upon T2D in people, highlighting each molecular oscillator and sphingolipid metabolites as vital regulators of insulin secretion and membrane fluidity.

Materials and strategies

Pancreatic islet and islet cell tradition

Human pancreatic islets have been obtained from 4 totally different sources, summarized in Desk 1: (i) Prodo Laboratories firm (ND and T2D islets); (ii) Alberta Diabetes Institute islet core middle (UAL) (ND and T2D islets); and (iii) Islet Transplantation Middle of Geneva College Hospital (ND islets). T2D donors had a historical past of T2D and/or HbA1c better than 6.5%. Particulars of the islet donors are summarized in Desk 1. All procedures utilizing human islets have been authorized by the moral committee of Geneva College Hospital CCER 2017–00147. Human pancreatic islets have been cultured in CMRL 1066 medium, containing 5.5 mM glucose and supplemented with 10% fetal bovine serum (Gibco), 110 U/ml penicillin (Gibco), 110 μg/ml streptomycin (Gibco), 50 μg/ml gentamicin (Gibco), 2 mM L-glutamine (GlutaMax, Gibco), and 1 mM sodium pyruvate (Gibco). Islet cell mild dissociation was performed utilizing 0.05% Trypsin (Gibco) remedy. For lipidomic evaluation, roughly 600 islets have been plated to 35-mm dishes (Falcon). For bioluminescence recordings, 100 islets have been plated to multi-well plates (LifeSystemDesign). For the remainder of the experiments, roughly 50,000 dissociated islet cells have been connected to 35-mm dishes (Falcon). All dishes have been precoated with a do-it-yourself laminin-5-rich extracellular matrix derived from 804G cells as described in [92].

Viral transduction and small interfering RNA transfection

Human islet cells have been transduced with Per2-luc lentivectors as described in [14]. Dissociated adherent human islet cells have been transfected twice with 50 nM siClock or with the identical quantity of nontargeting siControl (Dharmacon, GE Healthcare, Little Chalfont, United Kingdom) [13,52].

Lipid extraction procedures

The lipidomic extractions have been carried out as described in [35]. A complete of 600 human islets have been harvested (roughly 6 × 105 cells) on the indicated time factors after 1-h pulse of forskolin synchronization (Fig 1A) or as indicated in any other case (Figs 2 and 3) and resuspended in 100 μL H2O. Lipid extracts have been ready utilizing a modified MTBE (methyl-tert-butyl ether) extraction protocol with addition of inner lipid requirements [94]. Briefly, 360 μL methanol and a mixture of inner requirements have been added (400 pmol PC 12:0/12:0, 1,000 pmol PE 17:0/14:1, 1,000 pmol PI 17:0/14:1, 3,300 pmol PS 17:0/14:1, 2,500 pmol SM d18:1/12:0, 500 pmol Cer d18:1/17:0, and 100 pmol GlcCer d18:1/8:0). After addition of 1.2 mL of MTBE, samples have been positioned for 10 min on a multitube vortexer at 4°C adopted by incubation for 1 h at room temperature (RT) on a shaker. Part separation was induced by addition of 200 μL MS-grade water. After 10 min at RT, samples have been centrifuged at 1,000g for 10 min. The higher (natural) section was transferred right into a 13-mm glass tube, and the decrease section was re-extracted with 400 μL synthetic higher section [MTBE/methanol/H2O (10:3:1.5, v/v/v)]. The mixed natural phases have been separated into 2 aliquots and dried in a vacuum concentrator (CentriVap, Labconco). Phospholipids have been eluted with methanol (3 × 500 μL) and divided into 2 aliquots. One aliquot was used for glycerophospholipid and phosphorus assay, respectively, whereas the opposite aliquot was handled by delicate alkaline hydrolysis to complement for sphingolipids, in accordance with the strategy by Clarke [95]. Briefly, 1 mL freshly ready monomethylamine reagent [methylamine/H2O/n-butanol/methanol (5:3:1:4, (v/v/v/v)] was added to the dried lipid extract after which incubated at 53°C for 1 h in a water tub. Lipids have been cooled to RT after which dried. For desalting, the dried lipid extract was resuspended in 300 μL water-saturated n-butanol after which extracted with 150 μL H2O. The natural section was collected, and the aqueous section was re-extracted twice with 300 μL water-saturated n-butanol. The natural phases have been pooled and dried in a vacuum concentrator.

Dedication of whole phosphorus

Complete phosphorus was decided as described in [35]. Briefly, 100 μL of the entire lipid extract, resuspended in chloroform/methanol (1:1), have been positioned into 13-mm disposable pyrex tubes and dried in a vacuum concentrator, and 0, 2, 5, 10, 20 μL of a 3 mmol/L KH2PO4 commonplace resolution have been positioned into separate tubes. To every tube, distilled water was added to achieve 20 μL of aqueous resolution. After addition of 140 μL 70% perchloric acid, samples have been heated at 180°C for 1 h in a chemical hood. Then, 800 μL of a freshly ready resolution of water, ammonium molybdate (100 mg/8 mL H2O), and ascorbic acid (100 mg/6 mL H2O) in a ratio of 5:2:1 (v/v/v) have been added. Tubes have been heated at 100°C for five min and cooled at RT for five min. Roughly 100 μL of every pattern was then transferred right into a 96-well microplate, and the absorbance at 820 nm was measured.

Phospho- and sphingolipid evaluation by mass spectrometry

Mass spectrometry evaluation was carried out utilizing a number of response monitoring on a TSQ Vantage Prolonged Mass Vary Mass Spectrometer (Thermo Fisher Scientific), outfitted with a robotic nanoflow ion supply (Triversa Nanomate, Advion Biosciences) as beforehand described [35]. Optimized fragmentation was generated utilizing applicable collision energies and s-lens values for every lipid class. Mass spectrometry information have been acquired with TSQ Tune 2.6 SP1 and handled with Xcalibur 4.0 QF2 software program (Thermo Fisher Scientific). Lipid quantification was carried out utilizing an evaluation platform for lipidomics information hosted at EPFL Lausanne Switzerland ( Quantification process was described in [96]. Dried lipid extracts have been resuspended in 250 μL MS-grade chloroform/methanol (1:1) and additional diluted in both chloroform/methanol (1:2) plus 5 mmol/L ammonium acetate (detrimental ion mode) or in chloroform/methanol/H2O (2:7:1) plus 5 mmol/L ammonium acetate (optimistic ion mode).

Membrane fluidity experiments

For evaluation of membrane fluidity, the islets cells have been seeded onto a glass-bottom dishes (Willco) at a density of 30,000 cells/dish. For microscopy imaging, the connected cells have been washed as soon as with heat CMRL 1066 medium with no phenol crimson (Gibco-Invitrogen), supplemented with 2 mM L-glutamine (GlutaMax, Gibco), 1 mM sodium pyruvate (Gibco), and 15 mM HEPES to take care of pH. After that, 200 μL of a 2 μM NS12R dye resolution (Klymchenko Laboratory [50]) diluted in the identical medium was added, and the cells have been incubated for five min at RT. Cells have been washed 3 instances with the nice and cozy medium and instantly subjected to fluorescence microscopy utilizing a Nikon A1r microscope, outfitted with CFI Plan Apo ×60 oil (NA = 1.4) goal. The excitation in confocal mode was offered by a 488-nm laser, whereas the fluorescence was detected at 2 spectral ranges: 550 to 600 (I550-600) and 600 to 650 (I600-650) nm in sequential mode by speedy switching to attenuate drift. All of the parameters at every channel have been left fixed. The laser energy was set at 1% of most depth to realize sign. A minimum of 10 confocal photographs have been recorded utilizing NIS Parts per 1 dish. The fluorescence shift radiometry was assessed utilizing Fiji after outlaying membrane space. GP was calculated as follows: GP = (I550-600 − gI600-650)/(I550-600 + gI600-650). The place coefficient g was beforehand calculated for the NR12S resolution in CMRL.

Information quantification and analyses

Lipid concentrations have been calculated relative to the related inner requirements and normalized to the entire phosphate content material of every whole lipid extract (S1S3 Information). Then, for comparability between totally different lipids samples, relative lipid concentrations have been normalized to the entire lipid content material of every lipid extract (mol%). For temporal evaluation, normalized lipid values have been z-scored inside sufferers. To determine circadian variations throughout the lipidomic information set, normalized lipid values have been additional analyzed utilizing the METACYCLE v1.2.0 algorithm in R Bioconductor v3.11 [97]. The interval width was set to suit a timeframe of 20 to twenty-eight h and a p worth of ≤ 0.05 was thought of statistically vital.

Lipid concentrations have been corrected for sophistication II isotopic overlaps for the evaluation of lipid diploma of saturation as described in [98]. Briefly, correction elements for deisotoping have been derived utilizing theoretical M+2 abundances calculated utilizing the Envipat Internet 2.4 instrument ( making use of a mass decision of 5,000. These theoretical M+2 abundances have been multiplied by a correction issue accounting for the chance at random distribution of two 13C isotopes throughout the remaining heavy fragment generated in the course of the fragmentation within the collision chamber (Q2) however not detected within the Q3. The ensuing method for correction is: M + 2correction  =  (M + 2theoretical)×((nheavy)/(mwhole))2 with nheavy being the variety of carbons within the heavy fragment, and mwhole, the variety of carbons in all the lipid molecule. For every lipid species, the corrected M + 2 sign was calculated and subtracted from the acquired sign for the lipid species with m/z + 2 inside a collection of lipid species from the identical lipid class, starting with probably the most desaturated species, stepwise till reaching the totally saturated kind.

Further information processing (filtering, normalization, transformation, scaling), statistical analyses, and information plotting have been carried out utilizing MetaboAnalyst 5.0 [97] and Prism Graph Pad 8.0. Statistical checks used for comparability between teams are indicated within the determine legends. Variations have been thought of vital for p ≤ 0.05 (*), p ≤ 0.01 (**), and p ≤ 0.001 (***).

To find out the clustering, k-NN (nearest neighbors with ok clusters) was utilized to the phases and amplitudes in polar coordinates of all circadian indicators for ok = 1, 2, and three clusters.


  1. 1.
    Dibner C. The significance of being rhythmic: Residing in concord together with your physique clocks. Acta Physiol (Oxf). 2020;228(1):e13281. Epub 2019/04/14. pmid:30980501.
  2. 2.
    Dibner C, Schibler U. Circadian timing of metabolism in animal fashions and people. J Intern Med. 2015. Epub 2015/01/21. pmid:25599827.
  3. 3.
    Sinturel F, Petrenko V, Dibner C. Circadian Clocks Make Metabolism Run. J Mol Biol. 2020;432(12):3680–99. Epub 2020/01/31. pmid:31996313.
  4. 4.
    Finger AM, Dibner C, Kramer A. Coupled community of the circadian clocks: a driving power of rhythmic physiology. FEBS Lett. 2020;594(17):2734–69. Epub 2020/08/05. pmid:32750151.
  5. 5.
    Allada R, Bass J. Circadian Mechanisms in Medication. N Engl J Med. 2021;384(6):550–61. Epub 2021/02/11. pmid:33567194; PubMed Central PMCID: PMC8108270.
  6. 6.
    Rijo-Ferreira F, Takahashi JS. Genomics of circadian rhythms in well being and illness. Genome Med. 2019;11(1):82. Epub 2019/12/19. pmid:31847894; PubMed Central PMCID: PMC6916512.
  7. 7.
    Perelis M, Marcheva B, Ramsey KM, Schipma MJ, Hutchison AL, Taguchi A, et al. Pancreatic beta cell enhancers regulate rhythmic transcription of genes controlling insulin secretion. Science. 2015;350(6261):aac4250. pmid:26542580; PubMed Central PMCID: PMC4669216.
  8. 8.
    Petrenko V, Saini C, Giovannoni L, Gobet C, Sage D, Unser M, et al. Pancreatic alpha- and beta-cellular clocks have distinct molecular properties and influence on islet hormone secretion and gene expression. Genes Dev. 2017;31(4):383–398. pmid:28275001; PubMed Central PMCID: PMC5358758.
  9. 9.
    Petrenko V, Dibner C. Circadian orchestration of insulin and glucagon launch. Cell Cycle. 2017;1–2. pmid:28537528.
  10. 10.
    Petrenko V, Stolovich-Rain M, Vandereycken B, Giovannoni L, Storch KF, Dor Y, et al. The core clock transcription issue BMAL1 drives circadian beta-cell proliferation throughout compensatory regeneration of the endocrine pancreas. Genes Dev. 2020;34(23–24):1650–65. Epub 2020/11/14. pmid:33184223; PubMed Central PMCID: PMC7706703.
  11. 11.
    Petrenko V, Dibner C. Cell-specific resetting of mouse islet mobile clocks by glucagon, glucagon-like peptide 1 and somatostatin. Acta Physiol (Oxf). 2017. pmid:29271578.
  12. 12.
    Marcheva B, Ramsey KM, Buhr ED, Kobayashi Y, Su H, Ko CH, et al. Disruption of the clock parts CLOCK and BMAL1 results in hypoinsulinaemia and diabetes. Nature. 2010;466(7306):627–31. Epub 2010/06/22. [pii] pmid:20562852; PubMed Central PMCID: PMC2920067.
  13. 13.
    Saini C, Petrenko V, Pulimeno P, Giovannoni L, Berney T, Hebrok M, et al. A purposeful circadian clock is required for correct insulin secretion by human pancreatic islet cells. Diabetes Obes Metab. 2016;18(4):355–365. pmid:26662378.
  14. 14.
    Pulimeno P, Mannic T, Sage D, Giovannoni L, Salmon P, Lemeille S, et al. Autonomous and self-sustained circadian oscillators displayed in human islet cells. Diabetologia. 2013;56(3):497–507. Epub 2012/12/18. pmid:23242133; PubMed Central PMCID: PMC3563957.
  15. 15.
    Petrenko V, Gandasi NR, Sage D, Tengholm A, Barg S, Dibner C. In pancreatic islets from sort 2 diabetes sufferers, the dampened circadian oscillators result in lowered insulin and glucagon exocytosis. Proc Natl Acad Sci U S A. 2020;117(5):2484–95. Epub 2020/01/23. pmid:31964806; PubMed Central PMCID: PMC7007532.
  16. 16.
    Chaurasia B, Summers SA. Ceramides in Metabolism: Key Lipotoxic Gamers. Annu Rev Physiol. 2021;83:303–30. Epub 2020/11/08. pmid:33158378; PubMed Central PMCID: PMC7905841.
  17. 17.
    Meikle PJ, Summers SA. Sphingolipids and phospholipids in insulin resistance and associated metabolic issues. Nat Rev Endocrinol. 2017;13(2):79–91. pmid:27767036.
  18. 18.
    Harayama T, Riezman H. Understanding the range of membrane lipid composition. Nat Rev Mol Cell Biol. 2018. pmid:29410529
  19. 19.
    Jimenez-Rojo N, Leonetti MD, Zoni V, Colom A, Feng S, Iyengar NR, et al. Conserved Capabilities of Ether Lipids and Sphingolipids within the Early Secretory Pathway. Curr Biol. 2020;30(19):3775–87 e7. Epub 2020/08/29. pmid:32857977.
  20. 20.
    Loewith R, Riezman H, Winssinger N. Sphingolipids and membrane targets for therapeutics. Curr Opin Chem Biol. 2019;50:19–28. Epub 2019/03/22. pmid:30897494.
  21. 21.
    Shevchenko A, Simons Ok. Lipidomics: coming to grips with lipid range. Nat Rev Mol Cell Biol. 2010;11(8):593–8. Epub 2010/07/08. pmid:20606693.
  22. 22.
    Eggers LF, Schwudke D. Shotgun Lipidomics Strategy for Medical Samples. Strategies Mol Biol. 2018;1730:163–74. Epub 2018/01/25. pmid:29363073.
  23. 23.
    Adamovich Y, Rousso-Noori L, Zwighaft Z, Neufeld-Cohen A, Golik M, Kraut-Cohen J, et al. Circadian clocks and feeding time regulate the oscillations and ranges of hepatic triglycerides. Cell Metab. 2014;19(2):319–330. pmid:24506873; PubMed Central PMCID: PMC4261230.
  24. 24.
    Dallmann R, Viola AU, Tarokh L, Cajochen C, Brown SA. The human circadian metabolome. Proc Natl Acad Sci U S A. 2012;109(7):2625–9. Epub 2012/02/07. pmid:22308371; PubMed Central PMCID: PMC3289302.
  25. 25.
    Chua EC, Shui G, Lee IT, Lau P, Tan LC, Yeo SC, et al. Intensive range in circadian regulation of plasma lipids and proof for various circadian metabolic phenotypes in people. Proc Natl Acad Sci U S A. 2013;110(35):14468–73. Epub 2013/08/16. pmid:23946426; PubMed Central PMCID: PMC3761633.
  26. 26.
    Sinturel F, Spaleniak W, Dibner C. Circadian rhythm of lipid metabolism. Biochem Soc Trans. 2022. Epub 2022/05/24. pmid:35604112.
  27. 27.
    Loizides-Mangold U, Petrenko V, Dibner C. Circadian Lipidomics: Evaluation of Lipid Metabolites Across the Clock. Strategies Mol Biol. 2021;2130:169–83. Epub 2020/12/08. pmid:33284444.
  28. 28.
    Held NM, Wefers J, van Weeghel M, Daemen S, Hansen J, Vaz FM, et al. Skeletal muscle in wholesome people reveals a day-night rhythm in lipid metabolism. Mol Metab. 2020;37:100989. Epub 2020/04/10. pmid:32272236; PubMed Central PMCID: PMC7217992.
  29. 29.
    Loizides-Mangold U, Perrin L, Vandereycken B, Betts JA, Walhin JP, Templeman I, et al. Lipidomics reveals diurnal lipid oscillations in human skeletal muscle persisting in mobile myotubes cultured in vitro. Proc Natl Acad Sci U S A. 2017. pmid:28973848.
  30. 30.
    Perrin L, Loizides-Mangold U, Chanon S, Gobet C, Hulo N, Isenegger L, et al. Transcriptomic analyses reveal rhythmic and CLOCK-driven pathways in human skeletal muscle. Elife. 2018;7. pmid:29658882
  31. 31.
    Chaurasia B, Tippetts TS, Mayoral Monibas R, Liu J, Li Y, Wang L, et al. Focusing on a ceramide double bond improves insulin resistance and hepatic steatosis. Science. 2019;365(6451):386–92. Epub 2019/07/06. pmid:31273070; PubMed Central PMCID: PMC6787918.
  32. 32.
    Chaurasia B, Summers SA. Ceramides—Lipotoxic Inducers of Metabolic Problems. Traits Endocrinol Metab. 2015;26(10):538–550. pmid:26412155.
  33. 33.
    Othman A, Saely CH, Muendlein A, Vonbank A, Drexel H, von Eckardstein A, et al. Plasma 1-deoxysphingolipids are predictive biomarkers for sort 2 diabetes mellitus. BMJ Open Diabetes Res Care. 2015;3(1):e000073. pmid:25815206; PubMed Central PMCID: PMC4368929.
  34. 34.
    Zuellig RA, Hornemann T, Othman A, Hehl AB, Bode H, Guntert T, et al. Deoxysphingolipids, novel biomarkers for sort 2 diabetes, are cytotoxic for insulin-producing cells. Diabetes. 2014;63(4):1326–1339. pmid:24379346.
  35. 35.
    Hannich JT, Loizides-Mangold U, Sinturel F, Harayama T, Vandereycken B, Saini C, et al. Ether lipids, sphingolipids and poisonous 1-deoxyceramides as hallmarks for lean and overweight sort 2 diabetic sufferers. Acta Physiol (Oxf). 2020:e13610. Epub 2020/12/23. pmid:33351229.
  36. 36.
    Hilvo M, Salonurmi T, Havulinna AS, Kauhanen D, Pedersen ER, Inform GS, et al. Ceramide stearic to palmitic acid ratio predicts incident diabetes. Diabetologia. 2018;61(6):1424–1434. pmid:29546476.
  37. 37.
    Hla T, Kolesnick R. C16:0-ceramide indicators insulin resistance. Cell Metab. 2014;20(5):703–705. pmid:25440051; PubMed Central PMCID: PMC4393079.
  38. 38.
    Holland WL, Brozinick JT, Wang LP, Hawkins ED, Sargent KM, Liu Y, et al. Inhibition of ceramide synthesis ameliorates glucocorticoid-, saturated-fat-, and obesity-induced insulin resistance. Cell Metab. 2007;5(3):167–179. pmid:17339025.
  39. 39.
    Chew WS, Torta F, Ji S, Choi H, Begum H, Sim X, et al. Massive-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence. JCI Perception. 2019;5. Epub 2019/06/05. pmid:31162145; PubMed Central PMCID: PMC6629294.
  40. 40.
    Wigger L, Cruciani-Guglielmacci C, Nicolas A, Denom J, Fernandez N, Fumeron F, et al. Plasma Dihydroceramides Are Diabetes Susceptibility Biomarker Candidates in Mice and People. Cell Rep. 2017;18(9):2269–2279. pmid:28249170.
  41. 41.
    Othman A, Rutti MF, Ernst D, Saely CH, Rein P, Drexel H, et al. Plasma deoxysphingolipids: a novel class of biomarkers for the metabolic syndrome? Diabetologia. 2012;55(2):421–431. pmid:22124606.
  42. 42.
    Boslem E, MacIntosh G, Preston AM, Bartley C, Busch AK, Fuller M, et al. A lipidomic display screen of palmitate-treated MIN6 beta-cells hyperlinks sphingolipid metabolites with endoplasmic reticulum (ER) stress and impaired protein trafficking. Biochem J. 2011;435(1):267–76. Epub 2011/01/27. pmid:21265737.
  43. 43.
    MacDonald MJ, Ade L, Ntambi JM, Ansari IU, Stoker SW. Characterization of phospholipids in insulin secretory granules and mitochondria in pancreatic beta cells and their modifications with glucose stimulation. J Biol Chem. 2015;290(17):11075–92. Epub 2015/03/13. pmid:25762724; PubMed Central PMCID: PMC4409267.
  44. 44.
    Sanchez-Archidona AR, Cruciani-Guglielmacci C, Roujeau C, Wigger L, Lallement J, Denom J, et al. Plasma triacylglycerols are biomarkers of beta-cell perform in mice and people. Mol Metab. 2021;54:101355. Epub 2021/10/12. pmid:34634522; PubMed Central PMCID: PMC8602044.
  45. 45.
    van der Veen JN, Kennelly JP, Wan S, Vance JE, Vance DE, Jacobs RL. The crucial function of phosphatidylcholine and phosphatidylethanolamine metabolism in well being and illness. Biochim Biophys Acta Biomembr. 2017;1859(9 Pt B):1558–72. pmid:28411170.
  46. 46.
    Harayama T, Shimizu T. Roles of polyunsaturated fatty acids, from mediators to membranes. J Lipid Res. 2020;61(8):1150–60. Epub 2020/06/04. pmid:32487545; PubMed Central PMCID: PMC7397749.
  47. 47.
    Zitomer NC, Mitchell T, Voss KA, Bondy GS, Pruett ST, Garnier-Amblard EC, et al. Ceramide synthase inhibition by fumonisin B1 causes accumulation of 1-deoxysphinganine: a novel class of bioactive 1-deoxysphingoid bases and 1-deoxydihydroceramides biosynthesized by mammalian cell strains and animals. J Biol Chem. 2009;284(8):4786–4795. pmid:19095642; PubMed Central PMCID: PMC2643501.
  48. 48.
    Turpin SM, Nicholls HT, Willmes DM, Mourier A, Brodesser S, Wunderlich CM, et al. Weight problems-induced CerS6-dependent C16:0 ceramide manufacturing promotes weight achieve and glucose intolerance. Cell Metab. 2014;20(4):678–86. Epub 2014/10/09. pmid:25295788.
  49. 49.
    Mullen TD, Hannun YA, Obeid LM. Ceramide synthases on the centre of sphingolipid metabolism and biology. Biochem J. 2012;441(3):789–802. Epub 2012/01/18. pmid:22248339; PubMed Central PMCID: PMC3689921.
  50. 50.
    Kucherak OA, Oncul S, Darwich Z, Yushchenko DA, Arntz Y, Didier P, et al. Switchable nile red-based probe for ldl cholesterol and lipid order on the outer leaflet of biomembranes. J Am Chem Soc. 2010;132(13):4907–4916. pmid:20225874.
  51. 51.
    Owen DM, Rentero C, Magenau A, Abu-Siniyeh A, Gaus Ok. Quantitative imaging of membrane lipid order in cells and organisms. Nat Protoc. 2012;7(1):24–35. pmid:22157973.
  52. 52.
    Petrenko V, Saini C, Perrin L, Dibner C. Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Major Cell Cultures. J Vis Exp. 2016;(117). pmid:27911383.
  53. 53.
    Wuttke A. Lipid signalling dynamics on the beta-cell plasma membrane. Fundamental Clin Pharmacol Toxicol. 2015;116(4):281–90. Epub 2014/12/23. pmid:25529872.
  54. 54.
    Hagren OI, Tengholm A. Glucose and insulin synergistically activate phosphatidylinositol 3-kinase to set off oscillations of phosphatidylinositol 3,4,5-trisphosphate in beta-cells. J Biol Chem. 2006;281(51):39121–7. Epub 2006/11/01. pmid:17074763.
  55. 55.
    Wuttke A, Idevall-Hagren O, Tengholm A. Imaging phosphoinositide dynamics in residing cells. Strategies Mol Biol. 2010;645:219–35. Epub 2010/07/21. pmid:20645191.
  56. 56.
    Zheng B, Larkin DW, Albrecht U, Solar ZS, Sage M, Eichele G, et al. The mPer2 gene encodes a purposeful part of the mammalian circadian clock. Nature. 1999;400(6740):169–73. Epub 1999/07/17. pmid:10408444.
  57. 57.
    Bae Ok, Jin X, Maywood ES, Hastings MH, Reppert SM, Weaver DR. Differential features of mPer1, mPer2, and mPer3 within the SCN circadian clock. Neuron. 2001;30(2):525–36. Epub 2001/06/08. pmid:11395012.
  58. 58.
    Brenna A, Albrecht U. Phosphorylation and Circadian Molecular Timing. Entrance Physiol. 2020;11:612510. Epub 2020/12/17. pmid:33324245; PubMed Central PMCID: PMC7726318.
  59. 59.
    Vanselow Ok, Vanselow JT, Westermark PO, Reischl S, Maier B, Korte T, et al. Differential results of PER2 phosphorylation: molecular foundation for the human familial superior sleep section syndrome (FASPS). Genes Dev. 2006;20(19):2660–72. Epub 2006/09/20. pmid:16983144; PubMed Central PMCID: PMC1578693.
  60. 60.
    Bartke N, Hannun YA. Bioactive sphingolipids: metabolism and performance. J Lipid Res. 2009;50(Suppl:S91-6). Epub 2008/11/20. pmid:19017611; PubMed Central PMCID: PMC2674734.
  61. 61.
    Hannun YA, Obeid LM. Ideas of bioactive lipid signalling: classes from sphingolipids. Nat Rev Mol Cell Biol. 2008;9(2):139–50. Epub 2008/01/25. pmid:18216770.
  62. 62.
    Russo D, Parashuraman S, D’Angelo G. Glycosphingolipid-Protein Interplay in Sign Transduction. Int J Mol Sci. 2016;17(10). Epub 2016/10/19. pmid:27754465; PubMed Central PMCID: PMC5085762.
  63. 63.
    Khan SR, Manialawy Y, Obersterescu A, Cox BJ, Gunderson EP, Wheeler MB. Diminished Sphingolipid Metabolism, a Hallmark of Future Sort 2 Diabetes Pathogenesis, Is Linked to Pancreatic beta Cell Dysfunction. iScience. 2020;23(10):101566. Epub 2020/10/27. pmid:33103069; PubMed Central PMCID: PMC7578680.
  64. 64.
    Khan SR, Mohan H, Liu Y, Batchuluun B, Gohil H, Al Rijjal D, et al. The invention of novel predictive biomarkers and early-stage pathophysiology for the transition from gestational diabetes to sort 2 diabetes. Diabetologia. 2019;62(4):687–703. Epub 2019/01/16. pmid:30645667; PubMed Central PMCID: PMC7237273.
  65. 65.
    Holm LJ, Krogvold L, Hasselby JP, Kaur S, Claessens LA, Russell MA, et al. Irregular islet sphingolipid metabolism in sort 1 diabetes. Diabetologia. 2018;61(7):1650–61. Epub 2018/04/20. pmid:29671030; PubMed Central PMCID: PMC6445476.
  66. 66.
    Turpin SM, Lancaster GI, Darby I, Febbraio MA, Watt MJ. Apoptosis in skeletal muscle myotubes is induced by ceramides and is positively associated to insulin resistance. Am J Physiol Endocrinol Metab. 2006;291(6):E1341–50. Epub 2006/07/20. pmid:16849630.
  67. 67.
    Ichikawa S, Sakiyama H, Suzuki G, Hidari KI, Hirabayashi Y. Expression cloning of a cDNA for human ceramide glucosyltransferase that catalyzes the primary glycosylation step of glycosphingolipid synthesis. Proc Natl Acad Sci U S A. 1996;93(10):4638–43. Epub 1996/05/14. pmid:8643456; PubMed Central PMCID: PMC39331.
  68. 68.
    Lloyd-Evans E, Pelled D, Riebeling C, Bodennec J, de-Morgan A, Waller H, et al. Glucosylceramide and glucosylsphingosine modulate calcium mobilization from mind microsomes through totally different mechanisms. J Biol Chem. 2003;278(26):23594–9. Epub 2003/04/24. pmid:12709427.
  69. 69.
    Westerlund B, Slotte JP. How the molecular options of glycosphingolipids have an effect on area formation in fluid membranes. Biochim Biophys Acta. 2009;1788(1):194–201. Epub 2008/12/17. pmid:19073136.
  70. 70.
    Sillence DJ, Puri V, Marks DL, Butters TD, Dwek RA, Pagano RE, et al. Glucosylceramide modulates membrane visitors alongside the endocytic pathway. J Lipid Res. 2002;43(11):1837–45. Epub 2002/10/29. pmid:12401882.
  71. 71.
    Inokuchi J. Membrane microdomains and insulin resistance. FEBS Lett. 2010;584(9):1864–71. Epub 2009/10/14. pmid:19822143.
  72. 72.
    Kabayama Ok, Sato T, Saito Ok, Loberto N, Prinetti A, Sonnino S, et al. Dissociation of the insulin receptor and caveolin-1 advanced by ganglioside GM3 within the state of insulin resistance. Proc Natl Acad Sci U S A. 2007;104(34):13678–83. Epub 2007/08/19. pmid:17699617; PubMed Central PMCID: PMC1949342.
  73. 73.
    Veret J, Coant N, Berdyshev EV, Skobeleva A, Therville N, Bailbe D, et al. Ceramide synthase 4 and de novo manufacturing of ceramides with particular N-acyl chain lengths are concerned in glucolipotoxicity-induced apoptosis of INS-1 beta-cells. Biochem J. 2011;438(1):177–89. Epub 2011/05/20. pmid:21592087.
  74. 74.
    Uchida Y, Murata S, Schmuth M, Behne MJ, Lee JD, Ichikawa S, et al. Glucosylceramide synthesis and synthase expression defend in opposition to ceramide-induced stress. J Lipid Res. 2002;43(8):1293–302. Epub 2002/08/15. pmid:12177173.
  75. 75.
    Turpin-Nolan SM, Bruning JC. The function of ceramides in metabolic issues: when measurement and localization issues. Nat Rev Endocrinol. 2020;16(4):224–33. Epub 2020/02/16. pmid:32060415.
  76. 76.
    Hartwig P, Hoglinger D. The Glucosylceramide Synthase Inhibitor PDMP Causes Lysosomal Lipid Accumulation and mTOR Inactivation. Int J Mol Sci. 2021;22(13). Epub 2021/07/03. pmid:34209164; PubMed Central PMCID: PMC8268262.
  77. 77.
    Jennemann R, Kaden S, Volz M, Nordstrom V, Herzer S, Sandhoff R, et al. Gangliosides modulate insulin secretion by pancreatic beta cells beneath glucose stress. Glycobiology. 2020;30(9):722–34. Epub 2020/03/10. pmid:32149357.
  78. 78.
    Pearson GL, Mellett N, Chu KY, Boslem E, Meikle PJ, Biden TJ. A complete lipidomic display screen of pancreatic beta-cells utilizing mass spectroscopy defines novel options of glucose-stimulated turnover of impartial lipids, sphingolipids and plasmalogens. Mol Metab. 2016;5(6):404–14. Epub 2016/06/04. pmid:27257600; PubMed Central PMCID: PMC4877660.
  79. 79.
    Cantrell Stanford J, Morris AJ, Sunkara M, Popa GJ, Larson KL, Ozcan S. Sphingosine 1-phosphate (S1P) regulates glucose-stimulated insulin secretion in pancreatic beta cells. J Biol Chem. 2012;287(16):13457–64. Epub 2012/03/06. pmid:22389505; PubMed Central PMCID: PMC3339968.
  80. 80.
    Bertea M, Rutti MF, Othman A, Marti-Jaun J, Hersberger M, von Eckardstein A, et al. Deoxysphingoid bases as plasma markers in diabetes mellitus. Lipids Well being Dis. 2010;9:84. Epub 2010/08/18. pmid:20712864; PubMed Central PMCID: PMC2931514.
  81. 81.
    Kamada T, McMillan DE, Yamashita T, Otsuji S. Lowered membrane fluidity of youthful erythrocytes in diabetes. Diabetes Res Clin Pract. 1992;16(1):1–6. Epub 1992/04/01. pmid:1576926.
  82. 82.
    Tong P, Thomas T, Berrish T, Humphriss D, Barriocanal L, Stewart M, et al. Cell membrane dynamics and insulin resistance in non-insulin-dependent diabetes mellitus. Lancet. 1995;345(8946):357–8. Epub 1995/02/11. pmid:7845118.
  83. 83.
    Watala C, Boncler M, Golanski J, Koziolkiewcz W, Trojanowski Z, Walkowiak B. Platelet membrane lipid fluidity and intraplatelet calcium mobilization in sort 2 diabetes mellitus. Eur J Haematol. 1998;61(5):319–26. Epub 1998/12/17. pmid:9855247.
  84. 84.
    Winocour PD, Bryszewska M, Watala C, Rand ML, Epand RM, Kinlough-Rathbone RL, et al. Lowered membrane fluidity in platelets from diabetic sufferers. Diabetes. 1990;39(2):241–4. Epub 1990/02/01. pmid:2227132.
  85. 85.
    Rawicz W, Olbrich KC, McIntosh T, Needham D, Evans E. Impact of chain size and unsaturation on elasticity of lipid bilayers. Biophys J. 2000;79(1):328–39. Epub 2000/06/27. pmid:10866959; PubMed Central PMCID: PMC1300937.
  86. 86.
    Chakraborty S, Doktorova M, Molugu TR, Heberle FA, Scott HL, Dzikovski B, et al. How ldl cholesterol stiffens unsaturated lipid membranes. Proc Natl Acad Sci U S A. 2020;117(36):21896–905. Epub 2020/08/28. pmid:32843347; PubMed Central PMCID: PMC7486787.
  87. 87.
    Pinot M, Vanni S, Pagnotta S, Lacas-Gervais S, Payet LA, Ferreira T, et al. Lipid cell biology. Polyunsaturated phospholipids facilitate membrane deformation and fission by endocytic proteins. Science. 2014;345(6197):693–7. Epub 2014/08/12. pmid:25104391.
  88. 88.
    Manni MM, Tiberti ML, Pagnotta S, Barelli H, Gautier R, Antonny B. Acyl chain asymmetry and polyunsaturation of mind phospholipids facilitate membrane vesiculation with out leakage. Elife. 2018;7. Epub 2018/03/16. pmid:29543154; PubMed Central PMCID: PMC5903860.
  89. 89.
    Tiberti ML, Antonny B, Gautier R. The transbilayer distribution of polyunsaturated phospholipids determines their facilitating impact on membrane deformation. Tender Matter. 2020;16(7):1722–30. Epub 2020/01/10. pmid:31916552.
  90. 90.
    Maulucci G, Cohen O, Daniel B, Sansone A, Petropoulou PI, Filou S, et al. Fatty acid-related modulations of membrane fluidity in cells: detection and implications. Free Radic Res. 2016;50(sup1):S40–S50. Epub 2016/09/07. pmid:27593084.
  91. 91.
    Mitrofanova A, Mallela SK, Ducasa GM, Yoo TH, Rosenfeld-Gur E, Zelnik ID, et al. SMPDL3b modulates insulin receptor signaling in diabetic kidney illness. Nat Commun. 2019;10(1):2692. Epub 2019/06/21. pmid:31217420; PubMed Central PMCID: PMC6584700.
  92. 92.
    Parnaud G, Bosco D, Berney T, Pattou F, Kerr-Conte J, Donath MY, et al. Proliferation of sorted human and rat beta cells. Diabetologia. 2008;51(1):91–100. pmid:17994216.
  93. 93.
    Gerber A, Esnault C, Aubert G, Treisman R, Pralong F, Schibler U. Blood-borne circadian sign stimulates day by day oscillations in actin dynamics and SRF exercise. Cell. 2013;152(3):492–503. Epub 2013/02/05. S0092-8674(12)01549-8 [pii] pmid:23374345.
  94. 94.
    Matyash V, Liebisch G, Kurzchalia TV, Shevchenko A, Schwudke D. Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. J Lipid Res. 2008;49(5):1137–46. Epub 2008/02/19. pmid:18281723; PubMed Central PMCID: PMC2311442.
  95. 95.
    Clarke NG, Dawson RM. Alkaline O results in N-transacylation. A brand new technique for the quantitative deacylation of phospholipids. Biochem J. 1981;195(1):301–6. Epub 1981/04/01. pmid:7306057; PubMed Central PMCID: PMC1162886.
  96. 96.
    Pietilainen KH, Sysi-Aho M, Rissanen A, Seppanen-Laakso T, Yki-Jarvinen H, Kaprio J, et al. Acquired weight problems is related to modifications within the serum lipidomic profile unbiased of genetic results—a monozygotic twin research. PLoS ONE. 2007;2(2):e218. Epub 2007/02/15. pmid:17299598; PubMed Central PMCID: PMC1789242.
  97. 97.
    Pang Z, Chong J, Zhou G, de Lima Morais DA, Chang L, Barrette M, et al. MetaboAnalyst 5.0: narrowing the hole between uncooked spectra and purposeful insights. Nucleic Acids Res. 2021;49(W1):W388–W96. Epub 2021/05/22. pmid:34019663; PubMed Central PMCID: PMC8265181.
  98. 98.
    Cadena Del Castillo CE, Hannich JT, Kaech A, Chiyoda H, Brewer J, Fukuyama M, et al. Patched regulates lipid homeostasis by controlling mobile levels of cholesterol. Nat Commun. 2021;12(1):4898. Epub 2021/08/14. pmid:34385431; PubMed Central PMCID: PMC8361143.


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