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Volume 1, December
 
 

Lipidology, Volume 1, Issue 1 (September 2024) – 6 articles

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17 pages, 2941 KiB  
Article
Exploration of High-Nutritional-Quality Vegetable Oil Blend with Enhanced Oxidative Stability as a Frying Medium Substitute for Palm Oil
by Vassilis Athanasiadis, Theodoros Chatzimitakos, Dimitrios Kalompatsios, Eleni Bozinou and Stavros I. Lalas
Lipidology 2024, 1(1), 75-91; https://doi.org/10.3390/lipidology1010006 - 1 Aug 2024
Viewed by 869
Abstract
Blending is a commonly utilized technique for enhancing the oxidative stability, nutritional quality, and physicochemical properties of vegetable oils. This study explored the potential of a vegetable oil blend consisting of common seed oils (sunflower, soybean, rapeseed, cottonseed, and corn oils), through partial [...] Read more.
Blending is a commonly utilized technique for enhancing the oxidative stability, nutritional quality, and physicochemical properties of vegetable oils. This study explored the potential of a vegetable oil blend consisting of common seed oils (sunflower, soybean, rapeseed, cottonseed, and corn oils), through partial least squares analysis, as a substitute for palm oil in the food preparation sector. Oxidative stability assays were conducted initially and after 14 and 28 days of incubation at 60 °C. These assays included radical inhibition activities between the optimal blended oil and palm oil through DPPH inhibition activity and thermal stability via accelerated oxidation conditions with Rancimat (110 °C, 15 L/h) and conjugated diene and triene formation. The impact of each oil was assessed through correlation analyses and Pareto plots. The optimal blended oil consisted of soybean/sunflower/cottonseed/corn oils at a ratio of 2:1:4:4. It had an induction period (i.e., full rancidity) vastly enhanced to 5.38 h but was statistically significantly lower than the stable palm oil by ~50%. Prior to thermal incubation, the blended oil was more potent in inhibiting DPPH, as it recorded 139.83 μmol of Trolox equivalents per kg of oil, ~53% more than palm oil. The conjugated diene and triene concentrations were similar for both oils at ~15 and ~7 mmol/kg oil, respectively. The Fourier-Transform Infrared spectra revealed the prevalence of cis fatty acids in the optimal oil blend and trans fatty acids in palm oil, indicating an enhancement in the nutritional quality of the vegetable oil blend. The results of the study could provide a nutritional oil blend that could be used as a substitute for palm oil in the food industry. Full article
(This article belongs to the Special Issue Technologies and Quality Control of Lipid-Based Foods)
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<p>Pareto plots of transformed estimates for oxidative stability (%OS) and oxidative power (%OP) in various assays. Plot (<b>A</b>) is Rancimat, and plot (<b>B</b>) is DPPH assays, which measure %OS; plot (<b>C</b>) is the CD assay, and plot (<b>D</b>) is the CT assay, which assess %OP. A gold reference rectangle is drawn on the plot to indicate the significance level (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Multiple factor analysis for the measured variables; the plot displays the factor scores of each variable. Inset tables include variable loadings and colors representing the variables’ block parameters.</p>
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<p>Multiple factor analysis for the measured variables; the plot displays the factor scores of each variable and shows the block partial inertias. The inset table includes block partial inertias and colors representing the variables’ block parameters.</p>
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<p>Multivariate correlation analysis of measured variable parameters.</p>
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<p>The PLS prediction profiler of each variable and the desirability function for optimizing blended vegetable oils are shown in plot (<b>A</b>), while the Variable Importance Plot (VIP) option graph with the VIP values for each predictor variable is shown in the plot (<b>B</b>) table. A blue dashed line in the VIT at 0.8 indicates the significance level of each variable.</p>
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<p>The relationship between the induction period and temperature through a polynomial regression fit.</p>
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<p>Stacked ATR–FTIR spectra of palm oil (orange line) and the optimal sample (green line). Blue values indicate the major wavenumbers in specific functional groups.</p>
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23 pages, 4540 KiB  
Article
Identification of Lipid Droplet-Associated Genes in Breast Cancer Patients
by Senol Dogan, Jenny Leopold, Daniel T. Hoffmann, Hans Kubitschke, Eliane Blauth, Carlotta Ficorella, Amelie Zschau, Jürgen Schiller and Josef A. Käs
Lipidology 2024, 1(1), 52-74; https://doi.org/10.3390/lipidology1010005 - 11 Jul 2024
Viewed by 842
Abstract
Lipid droplets (LDs) are known to be involved in the invasion and migration of breast cancer (BC) cells. This study aimed to identify LD-associated genes as prognostic markers in BC through comprehensive literature research and integration with lipid composition studies in BC cell [...] Read more.
Lipid droplets (LDs) are known to be involved in the invasion and migration of breast cancer (BC) cells. This study aimed to identify LD-associated genes as prognostic markers in BC through comprehensive literature research and integration with lipid composition studies in BC cell lines. The GEPIA platform was used to analyze the differential expression of LD-associated genes in BC. The lipid composition of cell lines (MCF-10A, MDA-MB 436 and 231) was obtained by extraction and thin-layer chromatography coupled with mass spectrometry (MS). Additionally, cell lines were co-cultured with fatty tissue and analyzed by confocal fluorescence microscopy. A total of 143 genes were identified as LD-associated genes through literature research and were subsequently analyzed using GEPIA. Among these, three genes were found to be over-expressed and 45 under-expressed in BC. Notably, FABP7 showed a statistically significant rank for all bioinformatics criteria as a prognostic factor. Experimental results showed only minor changes from MCF-10A to both MDA-MB cell lines for apolar lipids (triacylglycerols and cholesteryl esters) compared to phospholipids (PLs). Microscopic analyses showed that MDA-MB-231 had larger LDs compared to MCF-10A after 10 days of cultivation. Our bioinformatics analysis identified 26 genes that play important roles in metastatic transition in BC via LD-related mechanisms, though these findings could be only partially confirmed by experimental lipid compositional analyses, so far. Full article
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<p><b>Overview of three different research aspects included in this study</b>. The database search was first carried out by supervised searching using the PubMed platform to find all genes associated with breast cancer. Afterwards, different unsupervised research tools were used to define the characteristics of the genes found. The gene-expression-profiling interactive analysis (GEPIA, <a href="http://www.gepia.cancer-pku.cn" target="_blank">www.gepia.cancer-pku.cn</a>) was used for gene expression levels and the overall survival (OS) analysis, and for differences in metastatic transitions and differential gene expression. The experimental part of this study included the cultivation of three different cell lines (MCF-10A, MDA-MB-436 and MDA-MB-231). The lipid extraction (according to the Folch extraction protocol [<a href="#B24-lipidology-01-00005" class="html-bibr">24</a>] and analysis by TLC-ESI MS from the cell lines were used to create lipid fingerprints. At the end, similarities or differences between experimental and statistically gained results were identified and interpreted. In a third experiment, cell lines were co-cultivated with human fatty tissue (natural lipid source) in order to detect the amount of lipid droplets inside the different cell lines.</p>
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<p>Expression Analysis of <span class="html-italic">FABP7</span>. Differential expression (<b>left</b>), metastatic transition stages (<b>middle</b>) and overall survival (OS, <b>right</b>) images of <span class="html-italic">FABP7</span>. (<b>Left</b>): the gene is drastically under-expressed in tumor samples (red box) compared to normal tissue (gray box), red star shows the differences is statistically significant. (<b>Middle</b>): there are significant alterations between the metastatic stages (Stage I–IV, Stage X means unknown) [<a href="#B30-lipidology-01-00005" class="html-bibr">30</a>], which leads to the high F-value. (<b>Right</b>): the OS analysis indicates <span class="html-italic">FABP7</span> as a prognostic factor for breast cancer. The Y axis of BRCA and metastatic stages shows expression value which is calculated as log2(TPM + 1) for log-scale.</p>
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<p><b>The other significantly-changed genes.</b> Next to <span class="html-italic">FABP7</span>, three more genes are commonly significant in OS, HR, and F-value: <span class="html-italic">DGAT1</span> (first row), <span class="html-italic">OSBPL2</span> (second row) and <span class="html-italic">CPA4</span> (third row). The left figure compares the expression of genes between tumor (red box) and healthy (gray box) tissue. The middle figure shows the genes’ effectiveness during metastatic transitions. The right figure is an OS analysis of the same genes and shows how they play a role in the long term. The Y axis of BRCA and metastatic stages shows expression value which is calculated as log2(TPM + 1) for log-scale.</p>
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<p><b>OS survival of nine genes with lowest OS <span class="html-italic">p</span>-values</b>. Since each of these figures shows the overall survival analysis together with, in detail, Log-rank, HR (hazard ratio) and <span class="html-italic">p</span> (HR), the comparison of the data is straightforward.</p>
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<p><b>Nine genes with the highest F-values</b>. These figures show differentially expressed genes (DEGs) between metastatic stages. The differences are calculated as F Statistics and presented by F-value and <span class="html-italic">p</span>-value of F-value. Combining these images enables the visualization of how the genes’ expression changes between different stages.</p>
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<p><b>Lipid separation and lipid fingerprint</b>. (<b>A</b>) Separation of polar lipids by high-performance thin-layer chromatography (HPTLC) and visualization under UV light (366 nm) after primuline staining. (<b>B</b>) Relative lipid distribution of different cell lines using densitometry. Independent of the cell line, the overall lipid composition is very similar. Abbreviations: phosphatidylcholine (PC)—ethanolamine (PE)—inositol (PI)—glycerol (PG), lyso-PC (LPC), sphingomyelin (SM), free fatty acids (FFAs), cholesteryl ester (CE), free cholesterol (FC) and triacylglycerols (TAGs).</p>
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<p><b>Relative intensities of identified PC species after HPTLC-ESI IT MS from different cell lines (n = 3)</b>. Spots of interest were released by direct elution using the Plate Express<sup>TM</sup> TLC plate reader with methanol as the solvent. Most significant differences could be found between the control cell line (MCF-10A, yellow) and both tumorigenic cell lines MDA-MB-231 (gray) and MDA-MB-436 (black). Significances were classified using two-way ANOVA with Tukey’s multiple comparisons test as follows: * <span class="html-italic">p</span> value &lt; 0.05; ** <span class="html-italic">p</span>-value &lt; 0.01; *** <span class="html-italic">p</span>-value &lt; 0.001; **** <span class="html-italic">p</span>-value &lt; 0.0001.</p>
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<p><b>TLC image of separated apolar lipids of standard mixture and cellular extracts</b>. MCF-10A as reference cell line and MDA-MB-231 and MDA-MB-436 as cancerous cell lines. Spot intensities of both cancer cell lines lead to the assumption of higher amounts of apolar lipids and thus to higher lipid droplet concentration. Although the spots could be clearly identified using the video densitometric device in all cell lines, the extraction process during the direct infusion ESI-IT MS leads to the loss of lipids, which makes the measurements difficult for low-abundance lipids. Thus, only cholesterol ester (CE) species in both MDA-MB cell lines could be identified, but not in the MCF-10A. Triacylglycerol (TAG) concentrations were under the detection limit as well. Background signals in the ESI-IT mass spectrum are marked with an asterisk (*). Abbreviations: monoacylglycerol (MAG), diacylglycerol (DAG), free cholesterol (FC), free fatty acid (FFA), triacylglycerol (TAG), cholesterol ester (CE).</p>
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<p><b>Microscopic images of breast cancer cell lines.</b> (<b>Left</b>): MCF-10A (upper images) and MDA-MB 231 (lower images) cells grown without fatty tissue (left images) and after 10 days of co-culture with primary fatty tissue (right images). The scale bar is 10 µm. The amount of lipid droplets (yellow) does not change significantly for the MCF-10A cells. For the MDA-MB-231 cell, on the other hand, the amount and the size of lipid droplets increases after 10 days of co-culture. Yellow: the lipid stain LipidTox Green predominantly stains the endoplasmic reticulum. Blue: cell nuclei stained with SPY-DNA 555. Pink: actin stained with SiR-Actin. (<b>Right</b>): lipid droplet accumulation over time in MCF-10A cells (upper image) when exposed to co-cultured fatty tissue. The lipid droplet size is normalized to the smallest lipid droplets of the cell cohort.</p>
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22 pages, 2578 KiB  
Article
Impact of Endogenous Lipids on Mechanical Properties of Wheat Gluten Fractions, Gliadin and Glutenin, under Small, Medium, and Large Deformations
by Gamze Yazar, Jozef L. Kokini and Brennan Smith
Lipidology 2024, 1(1), 30-51; https://doi.org/10.3390/lipidology1010004 - 16 Apr 2024
Cited by 1 | Viewed by 811
Abstract
The individual viscoelastic responses of gluten proteins and their lipid-removed counterparts were studied under mixing deformations and small, medium, and large deformations selected in the Large Amplitude Oscillatory Shear (LAOS) sweeps. During Farinograph mixing, gliadin reached the 500 BU consistency line after 3.6 [...] Read more.
The individual viscoelastic responses of gluten proteins and their lipid-removed counterparts were studied under mixing deformations and small, medium, and large deformations selected in the Large Amplitude Oscillatory Shear (LAOS) sweeps. During Farinograph mixing, gliadin reached the 500 BU consistency line after 3.6 ± 0.4 min, while the highest consistency recorded for lipid-removed gliadin was 268 ± 8.4 BU, suggesting a reduction in the water absorption of gliadin in the absence of lipids. The affinity of glutenin to water increased in the absence of lipids, as development time was reached 11 min earlier for lipid-removed glutenin. Under small LAOS strains, tanδ of gliadin remained constant with the removal of lipids, while glutenin’s elasticity decreased (tanδ increased) in the absence of lipids at high frequencies. Intracycle strain-stiffening behavior (e3/e1 > 0) of gliadin increased under medium deformations with high frequency and decreased under low-frequency large deformations as lipids were removed, while this response decreased for glutenin with the removal of lipids only under high-frequency medium and large deformations. Under large LAOS strains, the clockwise rotation of the Lissajous–Bowditch curves for gliadin in the absence of lipids suggested higher intercycle strain-softening and shear-thinning, while the counter-clockwise rotation of the curves for glutenin in the absence of lipids suggested lower intercycle strain-softening and shear-thinning. These results revealed the influence of endogenous lipids on the viscous-dominated response of gliadin and to the elastic-dominated response of glutenin, while balancing the intracycle strain-stiffening behaviors of these gluten proteins especially under large deformations. Full article
(This article belongs to the Special Issue Technologies and Quality Control of Lipid-Based Foods)
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<p>SDS-PAGE gels for ladder (M<sub>w</sub> standards) and wheat gluten fractions with and without endogenous lipids. Samples were reduced prior to analysis.</p>
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<p>Farinograms for gluten fractions with and without endogenous lipids: (<b>a</b>) gliadin, (<b>b</b>) lipid-removed gliadin, (<b>c</b>) glutenin, (<b>d</b>) lipid-removed glutenin.</p>
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<p>Strain sweep data (γ: 0.01–200%; ω: 1, 10, 20 rad/s) for hydrated gliadin and glutenin with (full symbol) and without (empty symbol) endogenous lipids: (<b>a</b>) gliadin, (<b>b</b>) lipid-removed gliadin, (<b>c</b>) glutenin, (<b>d</b>) lipid-removed glutenin.</p>
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<p>MAOS behaviors of gliadin with (full symbol) and without (empty symbol) endogenous lipids: harmonic intensity maps of gliadin (<b>a</b>) and lipid-removed gliadin (<b>d</b>), reduced moduli of gliadin (<b>b</b>) and lipid-removed gliadin (<b>e</b>), scaled third-order elastic and viscous Chebyshev coefficients for gliadin (<b>c</b>) and lipid-removed gliadin (<b>f</b>). MAOS region limits are shown with the dash dots.</p>
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<p>MAOS behaviors of glutenin with (full symbol) and without (empty symbol) endogenous lipids: harmonic intensity maps of glutenin (<b>a</b>) and lipid-removed glutenin (<b>d</b>), reduced moduli of glutenin (<b>b</b>) and lipid-removed glutenin (<b>e</b>), scaled third-order elastic and viscous Chebyshev coefficients for glutenin (<b>c</b>) and lipid-removed glutenin (<b>f</b>). MAOS region limits are shown with the dash dots.</p>
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<p>Elastic Lissajous–Bowditch curves for gluten fractions with (straight line) and without (dotted line) endogenous lipids. Absolute stress values were plotted versus strain (elastic trajectories) at selected strain values including 0.1%, 0.25%, 10%, 25%, 110%, and 200%. Light color indicates low frequency [(<b>a</b>): 1 rad/s] and dark color indicates high frequency [(<b>b</b>): 20 rad/s]. The arrows indicate the direction of the rotation in the Lissajous-Bowditch curves of gluten fractions in the absence of endogenous lipids.</p>
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<p>Viscous Lissajous–Bowditch curves for gluten fractions with (straight line) and without (dotted line) endogenous lipids. Absolute stress values were plotted versus strain rate (viscous trajectories) at selected strain values including 0.1%, 0.25%, 10%, 25%, 110%, and 200%. Light color indicates low frequency [(<b>a</b>): 1 rad/s] and dark color indicates high frequency [(<b>b</b>): 20 rad/s]. The arrows indicate the direction of the rotation in the Lissajous-Bowditch curves of gluten fractions in the absence of endogenous lipids.</p>
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<p>e<sub>3</sub>/e<sub>1</sub> values of gliadin, glutenin, and their lipid-removed counterparts throughout the LAOS sweeps at different frequencies [ω: 20 rad/s (<b>a</b>,<b>d</b>), 10 rad/s (<b>b</b>,<b>e</b>), 1 rad/s (<b>c</b>,<b>f</b>)]. Frequencies from high to low are indicated by the colors changing from dark to light. The data for gliadin (full symbol) and lipid-removed gliadin (empty symbol) are given in blue shades, while those for glutenin (full symbol) and lipid-removed glutenin (empty symbol) are given in red shades.</p>
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<p>v<sub>3</sub>/v<sub>1</sub> values of gliadin, glutenin, and their lipid-removed counterparts throughout the LAOS sweeps at different frequencies [ω: 20 rad/s (<b>a</b>,<b>d</b>), 10 rad/s (<b>b</b>,<b>e</b>), 1 rad/s (<b>c</b>,<b>f</b>)]. Frequencies from high to low are indicated by the colors changing from dark to light. The data for gliadin (full symbol) and lipid-removed gliadin (empty symbol) are given in blue shades, while those for glutenin (full symbol) and lipid-removed glutenin (empty symbol) are given in red shades.</p>
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12 pages, 1746 KiB  
Article
1H Nuclear Magnetic Resonance, Infrared, and Chemometrics in Lipid Analysis of Brazilian Edible-Oil-Based Nutraceuticals
by Igor S. Flores, Daniel L. R. Annunciação, Vinícius S. Pinto and Luciano M. Lião
Lipidology 2024, 1(1), 18-29; https://doi.org/10.3390/lipidology1010003 - 2 Apr 2024
Cited by 1 | Viewed by 1141
Abstract
Edible oils have commercial and nutritional value due to the presence of essential fatty acids. They can be consumed fresh in the form of capsules known as nutraceuticals. The quality of such products is of interest to the consumer. In this context, this [...] Read more.
Edible oils have commercial and nutritional value due to the presence of essential fatty acids. They can be consumed fresh in the form of capsules known as nutraceuticals. The quality of such products is of interest to the consumer. In this context, this study describes a method based on high-resolution nuclear magnetic resonance (NMR) and Fourier-transform mid-infrared spectroscopic analysis (FTIR), combined with statistical analyses, to differentiate different edible oils used as nutraceuticals in Brazil by fatty acid content. Through the analysis of 1H NMR spectra, the levels of saturated and unsaturated fatty acids in edible oils were characterized and quantified. Statistical analysis of the data confirmed the real distinctions between nutraceutical raw materials, with emphasis on ω-9, ω-6, and ω-3 fatty acids. The analytical approach presented also demonstrates the potential to identify the origin (animal or vegetable) of edible oils used as nutraceuticals. Full article
(This article belongs to the Special Issue Technologies and Quality Control of Lipid-Based Foods)
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<p><sup>1</sup>H NMR spectrum of a linseed oil sample (CDCl<sub>3</sub>, 500 MHz). Highlighted expansions of spectral regions useful in the characterization of lipid profiles are presented.</p>
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<p>Score plot (<b>A</b>) and loadings (<b>B</b>) of PC1 versus PC2 obtained from the <sup>1</sup>H NMR data of Brazilian edible-oil-based nutraceuticals.</p>
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<p><sup>1</sup>H NMR spectrum of soy-oil-based nutraceutical. The integrations of the signals of the chemical groups are presented concerning the ERETIC signal, positioned at δ 5.00 ± 0.15 of precision related to the signal’s center. Also highlighted are the expansions of the regions of interest for calculating the percentages of SFA, ω-9, ω-6, and ω-3, calculated from Equations (1)–(4), positioned in the upper left portion.</p>
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<p>Score plot of PC1 versus PC2 obtained from the FTIR data of Brazilian edible-oil-based nutraceuticals. The main numbers of waves and chemical groups responsible for the observed discrimination are highlighted.</p>
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<p>Resulting dendrogram from the hierarchical classes analysis of FTIR analysis of oil-based nutraceuticals.</p>
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15 pages, 1877 KiB  
Article
Comparison of In Silico Signal Sequence-Phospholipid Results with Described In Vitro and In Vivo Protein Translocation Studies Seems to Underscore the Significance of Phospholipids
by Rob C. A. Keller
Lipidology 2024, 1(1), 3-17; https://doi.org/10.3390/lipidology1010002 - 25 Mar 2024
Viewed by 967
Abstract
The precise role of protein–lipid interactions in protein translocation is, after almost four decades of research, still a matter of debate. The experimental evidence, as described in the literature, indicates that (anionic) phospholipids play a role in numerous events in protein translocation; however, [...] Read more.
The precise role of protein–lipid interactions in protein translocation is, after almost four decades of research, still a matter of debate. The experimental evidence, as described in the literature, indicates that (anionic) phospholipids play a role in numerous events in protein translocation; however, its meaning and relevance are still a matter of debate. This study tries to fill some missing links in the experimental evidence by means of in silico experiments. The study presented here indicates not only that there is a direct signal sequence–phospholipid interaction but also that the corresponding signal peptides can translocate additional amino acids across a pure lipid membrane. Furthermore, results are presented when it comes to the extent of anionic phospholipids’ dependence on this process. The correlations between the in silico results of pure signal peptide–phospholipid interactions and the observed experimental trends in the overall protein translocation effects are at least remarkable. The results emphasize that new models for protein translocation will have to be developed to take all these and previous experimental data into account. Full article
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<p>Comparison of protein translocation efficiency of in vitro [<a href="#B24-lipidology-01-00002" class="html-bibr">24</a>] and in silico experiments (this study). Two sets of peptides where compared, one with 8 or 9 leucines (L) and one with 9 or 10 valines (V). The anionic phospholipid content used is 5% (blue) and 20% (red), respectively.</p>
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<p>The model representations of the Monte Carlo results as obtained by MCPep [<a href="#B46-lipidology-01-00002" class="html-bibr">46</a>] depict from left to right the PhoE SP with 10 extra amino acids (AA) interaction with the membrane in the surface and TM orientation, respectively. On the right, a transmembrane (TM) orientation of the PhoE SP with 16 additional AA is depicted. The signal sequence is indicated in blue/green, and the white/yellow color resembles the additional AA attached.</p>
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<p>A schematic representation of the various (initial) steps in protein translocation. Step 1 is the binding and partial insertion of the SP (in purple). In Step 2, the SP adopts a close to transmembrane orientation and subsequently translocates additional amino acids (colored in blue) across the membrane. In Step 3, additional parts of the mature protein translocate either purely through the lipid phase of the membrane or ‘slide’ along the surface of the Sec machinery (dark blue) with the possible aid of SecA (green) that provides a ‘pushing’ movement. Created using <a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a> (accessed 10 January 2023).</p>
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2 pages, 648 KiB  
Editorial
Lipidology: A New Open Access Journal
by Nicola Ferri
Lipidology 2024, 1(1), 1-2; https://doi.org/10.3390/lipidology1010001 - 1 Mar 2024
Viewed by 811
Abstract
On behalf of all the Editorial Board members and MDPI staff, I am pleased to announce the publication of the inaugural issue of the Lipidology journal [...] Full article
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<p>Lipids and their relevance in preclinical and clinical sciences.</p>
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