Sodium-Permeable Ion Channels TRPM4 and TRPM5 are Functional in Human Gastric Parietal Cells in Culture and Modulate the Cellular Response to Bitter-Tasting Food Constituents

Biomolecular and biophysical AFM probing reveals distinct binding of bitter peptide VAPFPEVF to TAS2R16 without inducing an intracellular calcium response

The casein-derived bitter peptide VAPFPEVF has been shown to stimulate proton secretion in human parietal cells (HGT-1) via bitter taste receptor TAS2R16, confirmed by siRNA knockdown. Since literature evidence is inconclusive, we hypothized that VAPFPEVF binds to TAS2R16, and investigated its effects on G protein-coupled signaling pathways. Exposure of HGT-1 cells to VAPFPEVF altered cAMP signaling without inducing a calcium response. An atomic force microscopy (AFM)-based approach was employed to demonstrate peptide binding to TAS2R16 in cellular and cell-free environments using TAS2R16-reconstituted proteoliposomes. Increased binding events were observed, reduced by the addition of salicin and TAS2R16 antagonist probenecid. AlphaFold multimer and molecular dynamics simulations suggest VAPFPEVF binds the orthosteric site of TAS2R16. These findings reveal (i) VAPFPEVF interacts with TAS2R16 to modulate cAMP levels without triggering calcium mobilization and (ii) the AFM approach as a valuable tool for studying peptide binding to TAS2R16 and possibly other G-protein coupled transmembrane receptors.

AFM-optimized single-cell level LA-ICP-MS imaging for quantitative mapping of intracellular zinc concentration in immobilized human parietal cells using gelatin droplet-based calibration

BACKGROUND

Quantitative bioimaging of trace elements at the single-cell level is crucial for understanding cellular processes, including metal uptake and distribution. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has emerged as a gold standard for elemental bioimaging due to its high sensitivity and spatial resolution. However, calibration remains challenging due to the lack of homogeneous biological standards. This study addresses these challenges by introducing a gelatin-based calibration strategy optimized for Zn mapping in human parietal cells. By minimizing heterogeneity in gelatin standards and optimizing laser ablation conditions, the approach ensures accurate and reproducible results for cellular bioimaging.

RESULTS

A gelatin-based calibration strategy for LA-ICP-MS was developed to quantify intracellular Zn at a single-cell level in human parietal cells. Preparation conditions for gelatin standards were optimized to minimize heterogeneity, eliminating the need for entire droplet ablation and significantly reducing analysis time. Atomic force microscopy (AFM) was employed to optimize laser ablation conditions and determine ablated volumes, ensuring quantitative Zn detection. The method demonstrated high linearity (R2 > 0.99) and reproducibility. Application of the calibration strategy to ZnCl2-treated parietal cells revealed Zn distribution at a cellular level, visualized using a 5 μm laser beam. Integration with bright field imaging enabled the exclusion of apoptotic cells and debris, ensuring robust analysis. Validation with bulk ICP-MS showed excellent agreement, confirming the method's reliability and potential for high-resolution bioimaging.

SIGNIFICANCE

This work introduces a robust and reproducible calibration strategy for quantitative elemental bioimaging using LA-ICP-MS. It details the preparation of a gelatin matrix with a homogeneous element distribution, serving as an alternative to using biological material and significantly reducing analysis time. Laser ablation parameters were optimized using AFM to ensure quantitative ablation, which is necessary for calibration through LA-ICP-MS imaging. This approach provides a powerful tool for studying trace element dynamics in single cells and holds potential for diverse biological and biomedical applications.

Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development

The food flavor science, traditionally reliant on experimental methods, is now entering a promising era with the help of artificial intelligence (AI). By integrating existing technologies with AI, researchers can explore and develop new flavor substances in a digital environment, saving time and resources. More and more research will use AI and big data to enhance product flavor, improve product quality, meet consumer needs, and drive the industry toward a smarter and more sustainable future. In this review, we elaborate on the mechanisms of flavor recognition and their potential impact on nutritional regulation. With the increase of data accumulation and the development of internet information technology, food flavor databases and food ingredient databases have made great progress. These databases provide detailed information on the nutritional content, flavor molecules, and chemical properties of various food compounds, providing valuable data support for the rapid evaluation of flavor components and the construction of screening technology. With the popularization of AI in various fields, the field of food flavor has also ushered in new development opportunities. This review explores the mechanisms of flavor recognition and the role of AI in enhancing food flavor analysis through high-throughput omics data and screening technologies. AI algorithms offer a pathway to scientifically improve product formulations, thereby enhancing flavor and customized meals. Furthermore, it discusses the safety challenges of integrating AI into the food flavor industry.

Activation of the TRPML1 Ion Channel Induces Proton Secretion in the Human Gastric Parietal Cell Line HGT-1

The lysosomal Ca2+ channel TRPML1 was found to be responsible for gastric acid secretion in murine gastric parietal cells by inducing the trafficking of H+/K+-ATPase containing tubulovesicles to the apical membrane. Therefore, we hypothesized a similar role of TRPML1 in regulating proton secretion in the immortalized human parietal cell line HGT-1. The primary focus was to investigate the involvement of TRPML1 in proton secretion using the known synthetic agonists ML-SA1 and ML-SA5 and the antagonist ML-SI3 and, furthermore, to identify food-derived compounds that target the channel. Proton secretion stimulated by ML-SA1 was reduced by 122.2 ± 22.7% by the antagonist ML-SI3. The steroid hormone 17β-estradiol, present in animal-derived foods, diminished the proton secretory effect of ML-SA1 by 63.4 ± 14.5%. We also demonstrated a reduction in the proton secretory effects of ML-SA1 and ML-SA5 on TRPML1 knock-down cells. The food-derived compounds sulforaphane and trehalose promoted proton secretion in HGT-1 cells but may act independently of TRPML1. Also, histamine- and caffeine-induced proton secretion were affected by neither the TRPML1 antagonist ML-SI3 nor the TRPML1 knock-down. In summary, the results obtained suggest that the activation of TRPML1 promotes proton secretion in HGT-1 cells, but the channel may not participate in canonical signaling pathways.

Insights into the identification of bitter peptides from Jinhua ham and its taste mechanism by molecular docking and transcriptomics analysis

In order to identify the peptides responsible for bitter defects and to understand the mechanism of bitterness in dry-cured ham, the peptides were identified by LC-MS/MS, and the interaction between bitter peptides and receptor proteins were evaluated by molecular docking and molecular dynamics simulation; the signal transduction mechanism of bitter peptides was investigated using the model of HEK-293T cells by calcium imaging and transcriptomics analysis. The results of LC-MS/MS showed that 11 peptides were identified from the high bitterness fraction of defective ham; peptides PKAPPAK, VTDTTR and YIIEK derived from titin showed the highest bitterness values compared with other peptides. The results of molecular docking showed that lower CDOCKER energy was observed in the interaction between these peptides and hT2R16 in comparison with these receptors of hT2R1, hT2R4, hT2R5, hT2R8 and hT2R14, and the interaction of hT2R16 and peptides was stabilized by hydrophobic interaction and hydrogen bond. The average RMSF values of VTDTTR were higher than that of YIIEK and PKAPPAK, while EC50 values of VTDTTR were lower compared with PKAPPAK and YIIEK. Transcriptomics analysis showed that 529 differentially expressed genes were identified in HEK-293T cells during the stimulating by VTDTTR and were mainly enriched into neuroactive ligand-receptor interaction, MAPK pathway, cAMP pathway and calcium signaling pathway, which were mainly responsible for the bitter signal transduction of VTDTTR. These results could provide evidence for understanding the bitter defects of dry-cured ham and the taste mechanism of bitter peptide.

Gastric digestion of the sweet-tasting plant protein thaumatin releases bitter peptides that reduce H. pylori induced pro-inflammatory IL-17A release via the TAS2R16 bitter taste receptor

About half of the world's population is infected with the bacterium Helicobacter pylori. For colonization, the bacterium neutralizes the low gastric pH and recruits immune cells to the stomach. The immune cells secrete cytokines, i.e., the pro-inflammatory IL-17A, which directly or indirectly damage surface epithelial cells. Since (I) dietary proteins are known to be digested into bitter tasting peptides in the gastric lumen, and (II) bitter tasting compounds have been demonstrated to reduce the release of pro-inflammatory cytokines through functional involvement of bitter taste receptors (TAS2Rs), we hypothesized that the sweet-tasting plant protein thaumatin would be cleaved into anti-inflammatory bitter peptides during gastric digestion. Using immortalized human parietal cells (HGT-1 cells), we demonstrated a bitter taste receptor TAS2R16-dependent reduction of a H. pylori-evoked IL-17A release by up to 89.7 ± 21.9% (p ≤ 0.01). Functional involvement of TAS2R16 was demonstrated by the study of specific antagonists and siRNA knock-down experiments.