Using genetic variants to evaluate the causal effect of serum vitamin D concentration on COVID-19 susceptibility, severity and hospitalization traits: a Mendelian randomization study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has struck globally and is exerting a devastating toll on humans. The pandemic has led to calls for widespread vitamin D supplementation in public. However, evidence supporting the role of vitamin D in the COVID-19 pandemic remains controversial. METHODS: We performed a two-sample Mendelian randomization (MR) analysis to analyze the causal effect of the 25-hydroxyvitamin D [25(OH)D] concentration on COVID-19 susceptibility, severity and hospitalization traits by using summary-level GWAS data. The causal associations were estimated with inverse variance weighted (IVW) with fixed effects (IVW-fixed) and random effects (IVW-random), MR-Egger, weighted edian and MR Robust Adjusted Profile Score (MR.RAPS) methods. We further applied the MR Steiger filtering method, MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global test and PhenoScanner tool to check and remove single nucleotide polymorphisms (SNPs) that were horizontally pleiotropic. RESULTS: We found no evidence to support the causal associations between the serum 25(OH)D concentration and the risk of COVID-19 susceptibility [IVW-fixed: odds ratio (OR) = 0.9049, 95% confidence interval (CI) 0.8197-0.9988, p = 0.0473], severity (IVW-fixed: OR = 1.0298, 95% CI 0.7699-1.3775, p = 0.8432) and hospitalized traits (IVW-fixed: OR = 1.0713, 95% CI 0.8819-1.3013, p = 0.4878) using outlier removed sets at a Bonferroni-corrected p threshold of 0.0167. Sensitivity analyses did not reveal any sign of horizontal pleiotropy. CONCLUSIONS: Our MR analysis provided precise evidence that genetically lowered serum 25(OH)D concentrations were not causally associated with COVID-19 susceptibility, severity or hospitalized traits. Our study did not provide evidence assessing the role of vitamin D supplementation during the COVID-19 pandemic. High-quality randomized controlled trials are necessary to explore and define the role of vitamin D supplementation in the prevention and treatment of COVID-19.

A CRISPR/Cas9-Mediated, Homology-Independent Tool Developed for Targeted Genome Integration in Yarrowia lipolytica.

Yarrowia lipolytica has been extensively used to produce essential chemicals and enzymes. As in most other eukaryotes, nonhomologous end joining (NHEJ) is the major repair pathway for DNA double-strand breaks in Y. lipolytica Although numerous studies have attempted to achieve targeted genome integration through homologous recombination (HR), this process requires the construction of homologous arms, which is time-consuming. This study aimed to develop a homology-independent and CRISPR/Cas9-mediated targeted genome integration tool in Y. lipolytica Through optimization of the cleavage efficiency of Cas9, targeted integration of a hyg fragment was achieved with 12.9% efficiency, which was further improved by manipulation of the fidelity of NHEJ repair, the cell cycle, and the integration sites. Thus, the targeted integration rate reached 55% through G1 phase synchronization. This tool was successfully applied for the rapid verification of intronic promoters and iterative integration of four genes in the pathway for canthaxanthin biosynthesis. This homology-independent integration tool does not require homologous templates and selection markers and achieves one-step targeted genome integration of the 8,417-bp DNA fragment, potentially replacing current HR-dependent genome-editing methods for Y. lipolyticaIMPORTANCE This study describes the development and optimization of a homology-independent targeted genome integration tool mediated by CRISPR/Cas9 in Yarrowia lipolytica This tool does not require the construction of homologous templates and can be used to rapidly verify genetic elements and to iteratively integrate multiple-gene pathways in Y. lipolytica This tool may serve as a potential supplement to current HR-dependent genome-editing methods for eukaryotes.

Schizophrenia, Bipolar Disorder, and Alzheimer's Disease are not Causal Factors of Bone Mineral Density: A Mendelian Randomization Analysis.

Until recently, it remains unclear whether schizophrenia, bipolar disorder (BD), and Alzheimer's disease (AD) is associated with bone mineral density (BMD). We aimed to investigate the causal effects of schizophrenia, BD and AD on BMD with Mendelian randomization (MR) analysis. Single-nucleotide polymorphisms (SNPs) strongly associated with these three neuropsychiatric diseases as instrumental variables were selected from genome-wide association studies in the MR Base database. We analyzed the effects of these SNPs on the femoral neck BMD (FN-BMD), lumbar spine BMD (LS-BMD) and forearm BMD (FA-BMD), and evaluated the heterogeneities and pleiotropy of these genetic variants. We also evaluated the potential confounding factors in the association between these three neuropsychiatric diseases and the BMD level. It was found that none of these genetic variants were significantly associated with BMD or confounding factors. Using these genetic variants, we did not find statistically significant causal effects of per unit increase in the log-odds of having schizophrenia, BD or AD with FN-BMD, LS-BMD and FA-BMD changes (e.g. schizophrenia and FN-BMD, MR-Egger OR 0.9673, 95% CI 0.8382 to 1.1163, p = 0.6519). The MR results also revealed that directional pleiotropy was unlikely to bias the causality (e.g., schizophrenia and FN-BMD, intercept = 0.0023, p = 0.6887), and no evidence of heterogeneity was found between the genetic variants (e.g., schizophrenia and FN-BMD, MR-Egger Q = 46.1502, I2 = 0.0899, p = 0.3047). Our MR study did not support causal effects of increased risk of schizophrenia, BD and AD status with BMD level.

Homology-independent genome integration enables rapid library construction for enzyme expression and pathway optimization in Yarrowia lipolytica.

Yarrowia lipolytica is an important oleaginous industrial microorganism used to produce biofuels and other value-added compounds. Although several genetic engineering tools have been developed for Y. lipolytica, there is no efficient method for genomic integration of large DNA fragments. In addition, methods for constructing multigene expression libraries for biosynthetic pathway optimization are still lacking in Y. lipolytica. In this study, we demonstrate that multiple and large DNA fragments can be randomly and efficiently integrated into the genome of Y. lipolytica in a homology-independent manner. This homology-independent integration generates variation in the chromosomal locations of the inserted fragments and in gene copy numbers, resulting in the expression differences in the integrated genes or pathways. Because of these variations, gene expression libraries can be easily created through one-step integration. As a proof of concept, a LIP2 (producing lipase) expression library and a library of multiple genes in the ß-carotene biosynthetic pathway were constructed, and high-production strains were obtained through library screening. Our work demonstrates the potential of homology-independent genome integration for library construction, especially for multivariate modular libraries for metabolic pathways in Y. lipolytica, and will facilitate pathway optimization in metabolic engineering applications.

Enhanced itaconic acid production in Yarrowia lipolytica via heterologous expression of a mitochondrial transporter MTT.

Itaconic acid, a promising platform chemical, has been applied in many fields of industrial production. As a potential candidate for itaconic acid production, Yarrowia lipolytica possesses several innate abilities such as the tolerance of low-pH and high-shear stress, fast growth rate, cultivation flexibility, and easy for genetic manipulation. Here, Y. lipolytica Po1f which was tested to show high tolerance to itaconic acid could accumulate itaconic acid (0.363 g/L) by expressing the Aspergillus terreus cis-aconitic acid decarboxylase (CAD). Then, we tried to improve the supply and transport of the immediate precursor cis-aconitic acid by overexpressing a series of genes; these results indicate that overexpression of mitochondrial cis-aconitate transporter MTT is beneficial to the itaconic acid biosynthesis in Y. lipolytica. Further culture optimization enabled 22.03 g/L of itaconic acid to be produced in bioreactors, about 60-fold improvement over the initial titer, which is the highest itaconic acid production achieved at low pH by yeast reported worldwide, to data. This study demonstrates the great potential of Y. lipolytica as an industrial platform for itaconic acid production.

Engineering of unconventional yeast Yarrowia lipolytica for efficient succinic acid production from glycerol at low pH.

Yarrowia lipolytica is considered as a potential candidate for succinic acid production because of its innate ability to accumulate citric acid cycle intermediates and its tolerance to acidic pH. Previously, a succinate-production strain was obtained through the deletion of succinate dehydrogenase subunit encoding gene Ylsdh5. However, the accumulation of by-product acetate limited further improvement of succinate production. Meanwhile, additional pH adjustment procedure increased the downstream cost in industrial application. In this study, we identified for the first time that acetic acid overflow is caused by CoA-transfer reaction from acetyl-CoA to succinate in mitochondria rather than pyruvate decarboxylation reaction in SDH negative Y. lipolytica. The deletion of CoA-transferase gene Ylach eliminated acetic acid formation and improved succinic acid production and the cell growth. We then analyzed the effect of overexpressing the key enzymes of oxidative TCA, reductive carboxylation and glyoxylate bypass on succinic acid yield and by-products formation. The best strain with phosphoenolpyruvate carboxykinase (ScPCK) from Saccharomyces cerevisiae and endogenous succinyl-CoA synthase beta subunit (YlSCS2) overexpression improved succinic acid titer by 4.3-fold. In fed-batch fermentation, this strain produced 110.7g/L succinic acid with a yield of 0.53g/g glycerol without pH control. This is the highest succinic acid titer achieved at low pH by yeast reported worldwide, to date, using defined media. This study not only revealed the mechanism of acetic acid overflow in SDH negative Y. lipolytica, but it also reported the development of an efficient succinic acid production strain with great industrial prospects.

Enhancement of succinate yield by manipulating NADH/NAD+ ratio and ATP generation.

We previously engineered Escherichia coli YL104 to efficiently produce succinate from glucose. In this study, we investigated the relationships between the NADH/NAD+ ratio, ATP level, and overall yield of succinate production by using glucose as the carbon source in YL104. First, the use of sole NADH dehydrogenases increased the overall yield of succinate by 7% and substantially decreased the NADH/NAD+ ratio. Second, the soluble fumarate reductase from Saccharomyces cerevisiae was overexpressed to manipulate the anaerobic NADH/NAD+ ratio and ATP level. Third, another strategy for reducing the ATP level was applied by introducing ATP futile cycling for improving succinate production. Finally, a combination of these methods exerted a synergistic effect on improving the overall yield of succinate, which was 39% higher than that of the previously engineered strain YL104. The study results indicated that regulation of the NADH/NAD+ ratio and ATP level is an efficient strategy for succinate production.

A ß-Primeverosidase-like Enzyme in Soybean [Glycine max (L.) Merr] Hypocotyls: Specificity toward 1-Octen-3-yl and 3-Octanyl ß-Primeverosides.

A novel ß-primeverosidase-like enzyme, originating from the hypocotyl of soybeans, was isolated and characterized. This enzyme, with an estimated molecular weight of 44 kDa, was identified as a monomer and exhibited peak activity at 55 °C and pH 5.5. It demonstrated a specific and efficient hydrolysis of 1-octen-3-yl ß-primeveroside (1-octen-3-yl prim) and 3-octanyl ß-primeveroside (3-octanyl prim) but did not act on glucopyranosides. Mn2+ significantly enhanced its activity, while Zn2+, Cu2+, and Hg2+ exerted inhibitory effects. Kinetic analysis revealed a higher hydrolytic capacity toward 1-octen-3-yl prim. Partial amino acid sequences were determined and the N-terminal amino acid sequence was determined to be AIVAYAL ALSKRAIAAQ. The binding energy and binding free energy between the ß-primeverosidase enzyme and its substrates were observed to be higher than that of ß-glucosidase, thus validating its superior hydrolysis efficiency. Hydrogen bonds and hydrophobic interactions were the main types of interactions between ß-primeverosidase enzyme and 1-octen-3-yl prim and 3-octanyl prim, involving amino acid residues such as GLU-470, TRP-463, GLU-416, TRP-471, GLN-53, and GLN-477 (hydrogen bonds) and PHE-389, TYR-345, LEU-216, and TYR-275 (hydrophobic interactions). This study contributes to the application of a ß-primeverosidase-like enzyme in improving the release efficiency of glycosidically conjugated flavor substances.

From Molecular Dynamics to Taste Sensory Perception: A Comprehensive Study on the Interaction of Umami Peptides with the T1R1/T1R3-VFT Receptor.

The research on the umami receptor-ligand interaction is crucial for understanding umami perception. This study integrated molecular simulations, sensory evaluation, and biosensor technology to analyze the interaction between umami peptides and the umami receptor T1R1/T1R3-VFT. Molecular dynamics simulations were used to investigate the dissociation process of seven umami peptides with the umami receptor T1R1/T1R3-VFT, and by calculating the potential mean force curve using the Jarzynski equation, it was found that the binding free energy of umami peptide is between -58.80 and -12.17 kcal/mol, which had a strong correlation with the umami intensity obtained by time intensity sensory evaluation. Through correlation analysis, the dissociation rate constants (0.0126-0.394 1/s) of umami peptides were found to have a great impact on umami perception. The faster the dissociation rate of umami peptides from receptors, the stronger the perceived intensity of the umami taste. This research aims to elucidate the relationship between the umami peptide-receptor interaction and umami perception, providing theoretical support for the exploration of umami perception mechanisms.

Genome-scale transcriptional activation by non-homologous end joining-mediated integration in Yarrowia lipolytica.

BACKGROUND: Genome-scale screening can be applied to efficiently mine for unknown genes with phenotypes of interest or special functions. It is also useful to identify new targets for engineering desirable properties of cell factories. RESULTS: Here, we designed a new approach for genome-scale transcription activation using non-homologous end joining (NHEJ)-mediated integration in Yarrowia lipolytica. We utilized this approach to screen for genes that, upon activation, confer phenotypes including improved acetic acid tolerance and xylose metabolism. The candidates were validated using gene overexpression, and functional changes including improved growth performance under multiple stressors and activated pentose metabolism were identified. CONCLUSIONS: This study provides a simple and effective approach to randomly activate endogenous genes and mine for key targets associated with phenotypes of interest. The specific gene targets identified here will be useful for cell factory construction and biorefining lignocellulose.

Novel Umami Peptides from Mushroom (Agaricus bisporus) and Their Umami Enhancing Effect via Virtual Screening and Molecular Simulation.

This study aimed to identify novel umami peptides in Agaricus bisporus and investigate their umami enhancing effect. We virtually screened 155 potential umami peptides from the ultrasound-assisted A. bisporus hydrolysate according to Q values, iUmami-SCM, Umami_YYDS, and Tastepeptides_DM models, and molecular docking. Five peptides (AGKNTNGSQF, DEAVARGATF, REESDFQSSF, SEETTTGVHH, and WNNDAFQSSTN) were synthesized for sensory evaluation and kinetic analysis. The result showed that the umami thresholds of the five peptides were in the range of 0.21-0.40 mmol/L. Notably, REESDFQSSF, SEETTTGVHH, and WNNDAFQSSTN had low dissociation constant (KD) values and high affinity for the T1R1-VFT receptor. The enhancing effect of the three peptides with MSG or IMP was investigated by sensory evaluation, kinetic analysis, and molecular dynamics simulations. In stable complexes, ARG_277 in T1R1 played a major role in umami peptide binding to T1R1-VFT. These results provide a theoretical basis for future screening of umami peptides and improving the umami taste of food containing mushrooms.

Noteworthy Consensus Effects of D/E Residues in Umami Peptides Used for Designing the Novel Umami Peptides.

Aspartic acid (D) and glutamic acid (E) play vital roles in the umami peptides. To understand their exact mechanism of action, umami peptides were collected and cut into 1/2/3/4 fragments. Connecting D/E to the N/C-termini of the fragments formed D/E consensus effect groups (DEEGs), and all fragments containing DEEG were summarized according to the ratio and ranking obtained in the above four situations. The interaction patterns between peptides in DEEG and T1R1/T1R3-VFD were compared by statistical analysis and molecular docking, and the most conservative contacts were found to be HdB_277_ARG and HdB_148_SER. The molecular docking score of the effector peptides significantly dropped compared to that of their original peptides (-1.076 ± 0.658 kcal/mol, p value < 0.05). Six types of consensus fingerprints were set according to the Top7 contacts. The exponential of relative umami was linearly correlated with ΔGbind (R2 = 0.961). Under the D/E consensus effect, the electrostatic effect of the umami peptide was improved, and the energy gap between the highest occupied molecular orbital-the least unoccupied molecular orbital (HOMO-LUMO) was decreased. The shortest path map showed that the peptides had similar T1R1-T1R3 recognition pathways. This study helps to reveal umami perception rules and provides support for the efficient screening of umami peptides based on the material richness in D/E sequences.

FAPD: An Astringency Threshold and Astringency Type Prediction Database for Flavonoid Compounds Based on Machine Learning.

Astringency is a puckering or velvety sensation mainly derived from flavonoid compounds in food. The traditional experimental approach for astringent compound discovery was labor-intensive and cost-consuming, while machine learning (ML) can greatly accelerate this procedure. Herein, we propose the Flavonoid Astringency Prediction Database (FAPD) based on ML. First, the Molecular Fingerprint Similarities (MFSs) and thresholds of flavonoid compounds were hierarchically clustering analyzed. For the astringency threshold prediction, four regressions models (i.e., Gaussian Process Regression (GPR), Support Vector Regression (SVR), Random Forest (RF), and Gradient Boosted Decision Tree (GBDT)) were established, and the best model was RF which was interpreted by the SHapley Additive exPlanations (SHAP) approach. For the astringency type prediction, six classification models (i.e., RF, GBDT, Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), k-Nearest Neighbor (kNN), and Stochastic Gradient Descent (SGD)) were established, and the best model was SGD. Furthermore, over 1200 natural flavonoid compounds were discovered and built into the customized FAPD. In FAPD, the astringency thresholds were achieved by RF; the astringency types were distinguished by SGD, and the real and predicted astringency types were verified by t-Distributed Stochastic Neighbor Embedding (t-SNE). Therefore, ML models can be used to predict the astringency threshold and astringency type of flavonoid compounds, which provides a new paradigm to research the molecular structure-flavor property relationship of food components.

A TastePeptides-Meta system including an umami/bitter classification model Umami_YYDS, a TastePeptidesDB database and an open-source package Auto_Taste_ML.

Taste peptides with umami/bitterness play a role in food attributes. However, the taste mechanisms of peptides are not fully understood, and the identification of these peptides is time-consuming. Here, we created a taste peptide database by collecting the reported taste peptide information. Eight key molecular descriptors from di/tri-peptides were selected and obtained by modeling screening. A gradient boosting decision tree model named Umami_YYDS (89.6% accuracy) was established by data enhancement, comparison algorithm and model optimization. Our model showed a great prediction performance compared to other models, and its outstanding ability was verified by sensory experiments. To provide a convenient approach, we deployed a prediction website based on Umami_YYDS and uploaded the Auto_Taste_ML machine learning package. In summary, we established the system TastePeptides-Meta, containing a taste peptide database TastePeptidesDB an umami/bitter taste prediction model Umami_YYDS and an open-source machine learning package Auto_Taste_ML, which were helpful for rapid screening of umami peptides.

TastePeptides-EEG: An Ensemble Model for Umami Taste Evaluation Based on Electroencephalogram and Machine Learning.

In the field of food, the sensory evaluation of food still relies on the results of manual sensory evaluation, but the results of human sensory evaluation are not universal, and there is a problem of speech fraud. This work proposed an electroencephalography (EEG)-based analysis method that effectively enables the identification of umami/non-umami substances. First, the key features were extracted using percentage conversion, standardization, and significance screening, and based on these features, the top four models were selected from 19 common binary classification algorithms as submodels. Then, the support vector machine (SVM) algorithm was used to fit the outputs of these four submodels to establish TastePeptides-EEG. The validation set of the model achieved a judgment accuracy of 90.2%, and the test set achieved a judgment accuracy of 77.8%. This study discovered the frequency change of α wave in umami taste perception and found the frequency response delay phenomenon of the F/RT/C area under umami taste stimulation for the first time. The model is published at www.tastepeptides-meta.com/TastePeptides-EEG, which is convenient for relevant researchers to speed up the analysis of umami perception and provide help for the development of the next generation of brain-computer interfaces for flavor perception.

Conserved Sites and Recognition Mechanisms of T1R1 and T2R14 Receptors Revealed by Ensemble Docking and Molecular Descriptors and Fingerprints Combined with Machine Learning.

Taste peptides, as an important component of protein-rich foodstuffs, potentiate the nutrition and taste of food. Thereinto, umami- and bitter-taste peptides have been ex tensively reported, while their taste mechanisms remain unclear. Meanwhile, the identification of taste peptides is still a time-consuming and costly task. In this study, 489 peptides with umami/bitter taste from TPDB (http://tastepeptides-meta.com/) were collected and used to train the classification models based on docking analysis, molecular descriptors (MDs), and molecular fingerprints (FPs). A consensus model, taste peptide docking machine (TPDM), was generated based on five learning algorithms (linear regression, random forest, gaussian naive bayes, gradient boosting tree, and stochastic gradient descent) and four molecular representation schemes. Model interpretive analysis showed that MDs (VSA_EState, MinEstateIndex, MolLogP) and FPs (598, 322, 952) had the greatest impact on the umami/bitter prediction of peptides. Based on the consensus docking results, we obtained the key recognition modes of umami/bitter receptors (T1Rs/T2Rs): (1) residues 107S-109S, 148S-154T, 247F-249A mainly form hydrogen bonding contacts and (2) residues 153A-158L, 163L, 181Q, 218D, 247F-249A in T1R1 and 56D, 106P, 107V, 152V-156F, 173K-180F in T2R14 constituted their hydrogen bond pockets. The model is available at http://www.tastepeptides-meta.com/yyds.

[Clinical Features and Prognostic Factors of Patients with Primary Cutaneous Lymphoma].

OBJECTIVE: To retrospectively analyze the clinical characteristics and prognostic factors of patients with primary cutaneous lymphoma. METHODS: The clinical data of 22 patients with primary cutaneous lymphoma admitted to Xinjiang Hotan District People's Hospital, Heji Hospital affiliated to Changzhi Medical College and the Fifth Medical Center of PLA General Hospital from January 2013 to June 2021 were retrospectively analyzed. RESULTS: The incidence of primary cutaneous T cell and NK/T cell lymphoma was about 91.9/100 000, and the incidence of primary cutaneous B cell lymphoma was about 14.5/100 000. The overall survival (OS) of patients aged ≥65 years was significantly shorter than that of patients younger than 65 years (P <0.05). Patients with elevated ß2-microglobulin (ß2-MG) had shorter OS and progression-free survival (PFS) (both P <0.05). Patients who achieved complete/partial response after initial treatment had longer OS than those with stable or progressive disease (P <0.05). There were significant differences in OS and PFS among patients with different pathological types of primary cutaneous lymphoma that originated from T and NK/T cells, the OS and PFS of patients with mycosis fungoides were longer than those of patients with other pathological types (both P <0.05). In addition, disease stage might also affect the PFS of the patients (P =0.056). CONCLUSION: The age, disease stage, ß2-MG level, pathological type and remission state after treatment of the patients were related to the clinical prognosis.

Reconfiguration of the reductive TCA cycle enables high-level succinic acid production by Yarrowia lipolytica.

Succinic acid (SA) is an important C4-dicarboxylic acid. Microbial production of SA at low pH results in low purification costs and hence good overall process economics. However, redox imbalances limited SA biosynthesis from glucose via the reductive tricarboxylic acid (TCA) cycle in yeast. Here, we engineer the strictly aerobic yeast Yarrowia lipolytica for efficient SA production without pH control. Introduction of the reductive TCA cycle into the cytosol of a succinate dehydrogenase-disrupted yeast strain causes arrested cell growth. Although adaptive laboratory evolution restores cell growth, limited NADH supply restricts SA production. Reconfiguration of the reductive SA biosynthesis pathway in the mitochondria through coupling the oxidative and reductive TCA cycle for NADH regeneration results in improved SA production. In pilot-scale fermentation, the engineered strain produces 111.9 g/L SA with a yield of 0.79 g/g glucose within 62 h. This study paves the way for industrial production of biobased SA.

Identifying Umami Peptides Specific to the T1R1/T1R3 Receptor via Phage Display.

Umami peptides are small molecular weight oligopeptides that play a role in umami taste attributes. However, the identification of umami peptides is easily limited by environmental conditions, and the abundant source and high chromatographic separation efficiency remain difficult. Herein, we report a robust strategy based on a phage random linear heptapeptide library that targets the T1R1-Venus flytrap domain (T1R1-VFT). Two candidate peptides (MTLERPW and MNLHLSF) were readily identified with high affinity for T1R1-VFT binding (KD of MW-7 and MF-7 were 790 and 630 nM, respectively). The two peptides exhibited umami taste and significantly enhanced the umami intensity when added to the monosodium glutamate solution. Overall, this strategy shows that umami peptides could be developed via phage display technology for the first time. The phage display platform has a promising application to discover other taste peptides with affinity for taste receptors of interest and has more room for improvement in the future.

Bimetallic bionic taste sensor for perception of the synergistic effect of umami substances.

Synergistic effect is one of the main properties of umami substances, elucidating the synergistic effect of umami is of great significance in the food industry. In this study, a bimetallic bionic taste sensor was developed to evaluate the synergistic effect of umami substances based on the perceptual mechanism of the human taste system. The Venus flytrap domain of T1R1 which is in charge of recognizing umami ligands was employed as the sensing element and self-assembled on the bimetallic nanomaterial (MoS2-PtPd) by Au-S bonding, the binding of receptors and ligands is characterized by changes of electrical signals. The sensor had good linearity (R2 > 0.99) and wide detection range in the detection of different kinds of umami substances (amino acids, nucleotides, organic acids, umami peptides) with detection limits as low as 0.03 pM. Comparing with electronic tongues, the sensor owned multiple characteristics of human taste system and could recognize the presence of synergistic effect of umami substances in a variety of real samples. Moreover, the differences in synergistic effect at different concentrations and ratios were also explored, the findings showed that the synergistic effect was more obvious at lower concentrations and balanced ratios of multiple umami substances added. The strategy would afford a promising platform for in-depth research on the mechanism of synergistic effect and multifunctional industrial applications.