Effect of high-intensity ultrasonic time on structural, mechanical, and physicochemical properties of ß-conglycinin (7S)- Transglutaminase (TGase) composite edible films.

The ß-conglycinin (7S) was pre-treated with high-intensity ultrasonic (HIU) and subsequently formed into composite edible films with the transglutaminase (TGase) method. Effects of HIU pretreatment time (0, 5, 10, 15, and 20 min) on the conformation of 7S and structural and application properties of 7S-TGase films were evaluated. The analysis of 7S conformation results revealed that HIU pretreatment for 0-10 min significantly dissociated the 7S, exposed internal hydrophobic groups of protein, increased its intermolecular hydrogen bonds, and altered the protein secondary and tertiary structure. The structural properties of films were evaluated by SEM, XRD, and ATR-FTIR. SEM showed that HIU reduced film wrinkles and cracks and improved unevenness. XRD and ATR-FTIR indicated that the film obtained an enlarged crystallinity, and the amide I and amide II regions of films were peak-shifted which is usually associated with the formation of covalent bonds. Notably, analysis of intermolecular force showed that HIU facilitated the formation of hydrogen bonds, hydrophobic interactions, and ε-(γ-glutamyl) lysine bonds in 7S-TGase films. The above structural changes in 7S and films were beneficial for the application properties of films. Results indicated that 10 min HIU pretreatment effectively improved the mechanical properties and water resistance, reduced water vapor permeability and oxygen permeability, and decreased the opacity of 7S-TGase films. However, the color of the film was not affected by the HIU, with an overall bright and yellowish color.

Effect of High-Intensity Ultrasound Pretreatment on the Properties of the Transglutaminase (TGase)-Induced ß-Conglycinin (7S) Gel.

In this study, we investigated the effects of different high-intensity ultrasound (HIU) pretreatment times (0-60 min) on the structure of ß-conglycinin (7S) and the structural and functional properties of 7S gels induced by transglutaminase (TGase). Analysis of 7S conformation revealed that 30 min HIU pretreatment significantly induced the unfolding of the 7S structure, with the smallest particle size (97.59 nm), the highest surface hydrophobicity (51.42), and the lowering and raising of the content of the α-helix and ß-sheet, respectively. Gel solubility showed that HIU facilitated the formation of ε-(γ-glutamyl)lysine isopeptide bonds, which maintain the stability and integrity of the gel network. The SEM revealed that the three-dimensional network structure of the gel at 30 min exhibited filamentous and homogeneous properties. Among them, the gel strength and water-holding capacity were approximately 1.54 and 1.23 times higher than those of the untreated 7S gels, respectively. The 7S gel obtained the highest thermal denaturation temperature (89.39 °C), G', and G″, and the lowest tan δ. Correlation analysis demonstrated that the gel functional properties were negatively correlated with particle size and the α-helix, while positively with Ho and ß-sheet. By contrast, gels without sonication or with excessive pretreatment showed a large pore size and inhomogeneous gel network, and poor properties. These results will provide a theoretical basis for the optimization of HIU pretreatment conditions during TGase-induced 7S gel formation, to improve gelling properties.

Effects of different dry heating temperatures on the spatial structure and amino acid residue side-chain oxidative modification of soybean isolated proteins.

Spatial structure and amino acid residue side-chain oxidative modification of soybean isolated protein (SPI) at different dry heating temperatures (70, 100, 130, 160 and 190 °C) were investigated, respectively in this study. The results showed that the dry heating promoted the formation of disulfide bonds and oxidative modification of SPI, such as carboxylation and hydroxylation under the below 160 °C. With increasing temperature, ß-sheet and α-helix shifted to random coil and ß-turn. The conformation of SPI changed, the solubility decreased and the particle size became smaller resulting from the combination of protein oxidation and chemical bond redistribution, but the structural integrity of SPI was better ensured below 130 °C. SPI was severely hydrolyzed at 190 °C. These results provide a theoretical basis for the study of protein modification by dry heating, which is a guideline for controlling the degree of protein denaturation in the food industry.

Effect of Baking Temperature and Time on Advanced Glycation End Products and Polycyclic Aromatic Hydrocarbons in Beef.

ABSTRACT: Beef is an important red meat that contains essential nutrients for human growth and development. Baking is a popular beef cooking method. Temperature and time play key roles in the final quality of beef. How temperature and time affect the changes of nutrients and the formation of harmful products in beef is not clear. The purpose of this study was to measure the content of water, fat, protein, ash, nitrite, total volatile base nitrogen, advanced glycation end products (AGEs) and their precursors, and polycyclic aromatic hydrocarbons (PAHs) at different temperatures (150, 190, 230, 270, and 310°C) for 20 min and at 190°C for different times (10, 20, and 30 min), so as to discuss the effect of different temperatures and times on beef nutrients and harmful products. The results showed that the moisture content of beef decreased with increased baking temperature and time, resulting in the increase of the relative content of fat, protein, and ash. The content of total volatile base nitrogen increased continuously. Compared with the control group, the content of glyoxal in beef decreased, whereas the content of methylglyoxal, pentosidine, and fluorescent AGEs increased, indicating the continuous accumulation of AGEs in beef. A total of 13 PAHs were identified by gas chromatography-mass spectrometry. The concentrations of 13 PAHs in beef increased with increases in baking temperature and time. The concentrations of BkP and BaP, which are the most carcinogenic to humans, were 0.36 and 0.35 µg/kg in raw meat, respectively; these were increased by high temperature and long baking times. After beef was baked at 270 and 310°C for 20 min, the concentration of BkP increased to 9.49 and 5.66 µg/kg, respectively, and the concentration of BaP increased to 5.45 and 4.42 µg/kg, respectively. After baking at 190°C for 30 and 40 min, the concentration of BkP increased to 4.81 and 24.20 µg/kg, respectively, and the concentration of BaP increased to 3.85 and 17.79 µg/kg, respectively.

Exposure to Sri Lanka's local groundwater in a CKDu prevalent area causes kidney damage in zebrafish.

How local groundwater induces chronic kidney disease of unknown etiology (CKDu) in Sri Lanka is still elusive. This study aims to elucidate the impacts of Sri Lanka's local groundwater in a CKDu prevalent area and reveal the possible pathogenic mechanism of CKDu using zebrafish models. The drinking water from the local underground well in Vavuniya was sampled and the water quality parameters including Na+, Mg2+, K+, Ca2+, Cl-, NO3-, SO42-, and F- were analyzed. Then, local groundwater exposure to zebrafish larvae and 293T cells was performed, and water with high hardness and fluoride was prepared as parallel groups. Our result showed that exposure to Sri Lanka's local groundwater caused developmental toxicity, kidney damage, and pronephric duct obstruction as well as abnormal behavior in zebrafish. Similar results were also found after exposure to water with high hardness and fluoride in zebrafish. Further, the expression levels of marker genes related to renal development and functions (foxj1a, dync2h1, pkd2, gata3, and slc20a1) were significantly altered, which is also confirmed in the 293T cells. Taken together, those results indicated that Sri Lanka's local groundwater in a CKDu prevalent area could cause kidney damage, implying that high water hardness and fluorine might be the inducible environmental factors for the etiological cause of CKDu.

Drug Repurposing: An Alternative Strategy to Treat COVID-19.

In order to curve the ongoing trend of the COVID-19 pandemic and save more lives, effective treatments against COVID-19 are urgently needed. Compared to developing new drugs, which may take too much time, it's more efficient and cost-effective to repurpose existing drugs in the treatment of COVID-19. Fortunately, some of the shared features of COVID-19 and other wellknown diseases make it possible to use old strategies to combat this new challenge. In this paper, we reviewed various possible strategies of drug repurposing in the treatment of COVID-19 and explored the possible scientific mechanisms behind each strategy.

Plastic biodegradation by in vitro environmental microorganisms and in vivo gut microorganisms of insects.

Traditional plastics, such as polyethylene (PE), polystyrene (PS), polypropylene (PP), polyvinyl chloride (PVC), polyethylene terephthalate (PET), polyurethane (PUR), and other plastic polymers, are difficult to degrade and are gradually accumulated in the environment to cause a serious environmental problem, which is urgently needed to develop novel treatments or control technology. The biodegradation of plastics has gained great attention due to the advantages of green and safe characteristics. Microorganisms play a vital role in the biodegradation of plastics, including environmental microbes (in vitro) and gut microbes of insects (in vivo). Microbial degradation in environmental conditions in vitro is extremely slow for major plastics at degradation rates on the basis of a month or even a year time, but recent discoveries show that the fast biodegradation of specific plastics, such as PS, PE, and PUR, in some invertebrates, especially insects, could be enhanced at rates on basis of hours; the biodegradation in insects is likely to be gut microbial-dependent or synergetic bioreactions in animal digestive systems. This review comprehensively summarizes the latest 7-year (2016-2022) publications on plastic biodegradation by insects and microorganisms, elucidates the mechanism of plastic degradation in insects and environmental microbes, and highlights the cutting-edge perspectives for the potential applications of plastic biodegradation.

Role of germ-free animal models in understanding interactions of gut microbiota to host and environmental health: A special reference to zebrafish.

Numerous pieces of evidence documented the importance of gut microbiota in regulating human health and evaluating the toxicity of environmental pollutants, which are closely related to the host health in various aspects, including nutrition, energy translation, metabolism, pathogen resistance, and immune function. A variety of environmental factors can disrupt gut microbiota and their functions, and inevitably cause immune diseases, obesity and diabetes. However, deciphering the inner mechanisms involved in the functional interaction of gut microbes with host health is still needed extensive investigations. This review focused on the essential roles of intestinal microbes in host-related diseases and highlighted the development and applications of germ-free (GF) animal models, mainly zebrafish. Moreover, the generation, immunity characters, advantages and challenges of GF zebrafish models were also summarized. Importantly, the composition and isolation of zebrafish gut bacteria for further application and toxicity evaluation of aquatic environmental pollutants were also discussed. In conclusion, GF zebrafish play irreplaceable roles in understanding the potential functions and responses of customized microbiota towards human and environmental health implications.

Effect of roasting temperature on lipid and protein oxidation and amino acid residue side chain modification of beef patties.

Beef is rich in nutrients and is one of the most important ingredients in the world. But in the process of cooking and heating, the nutrients of beef will change to varying degrees. How temperature affects the oxidation of lipids and proteins in beef, and the modification of amino acid residues is unclear. This study intended to heat beef at different roasting temperatures (150 °C, 190 °C, 230 °C, 270 °C, 310 °C), measure parameter including colour, peroxide value (PV), thiobarbituric acid-reactive substances (TBARS), thiol and carbonyl content, protein solubility, tryptophan and Schiff base content, protein molecular weight distribution and modification of amino acid residues to discussed the effects of different temperatures on the lipid and protein oxidation of beef patties, as well as the modification of amino acid residues. The results showed that the values of L* and b* increased with the temperature increased, and the values of a* decreased. With the increase of temperature, the lipid oxidation indexes PV and TBARS, Schiff base and carbonyl content also increased, and the thiol content and protein solubility decreased significantly (p < 0.001). SDS-PAGE showed that the band of myosin heavy chain (MHC, 220 kDa) was significantly degraded, while the band of actin (42 kDa) was still clearly visible. The analysis of UPLC-MS/MS results found that the aromatic amino acid residues in all samples were oxidized to a certain extent, especially tryptophan. Other oxidative modifications, including α-amiooadipic acid (AAA), hydroxyethyl lysine (CEL) and malondialdehyde (MDA), were only present in roasted samples and not in raw meat. The results suggested that lipid oxidation and protein oxidation were closely related to colour parameters. The oxidation of proteins and lipids was aggravated at higher temperature. Amino acid side chains were also modified at high temperature, and this change was particularly evident in aromatic amino acids. These results provided new insights for the oxidation of proteins and lipids of beef and the modification level of amino acid residues under high temperature conditions, which will help us to improve the cooking quality of meat foods.

ProAcePred: prokaryote lysine acetylation sites prediction based on elastic net feature optimization.

Motivation: Lysine acetylation exists extensively in prokaryotes, and plays a vital role in function adjustment. Recent progresses in the identification of prokaryote acetylation substrates and sites provide a great opportunity to explore the difference of substrate site specificity between prokaryotic and eukaryotic acetylation. Motif analysis suggests that prokaryotic and eukaryotic acetylation sites have distinct location-specific difference, and it is necessary to develop a prokaryote-specific acetylation sites prediction tool. Results: Therefore, we collected nine species of prokaryote lysine acetylation data from various databases and literature, and developed a novel online tool named ProAcePred for predicting prokaryote lysine acetylation sites. Optimization of feature vectors via elastic net could considerably improve the prediction performance. Feature analyses demonstrated that evolutionary information played significant roles in prediction model for prokaryote acetylation. Comparison between our method and other tools suggested that our species-specific prediction outperformed other existing works. We expect that the ProAcePred could provide more instructive help for further experimental investigation of prokaryotes acetylation. Availability and implementation: http://computbiol.ncu.edu.cn/ProAcePred. Supplementary information: Supplementary data are available at Bioinformatics online.

Computational Prediction and Analysis for Tyrosine Post-Translational Modifications via Elastic Net.

The tyrosine residue has been identified as suffering three major post-translational modifications (PTMs) including nitration, sulfation, and phosphorylation, which could be involved in different physiological and pathological processes. Multiple tyrosine residues of the whole protein may be modified concurrently, where PTM of a single tyrosine may affect modification of other neighboring tyrosine residues. Hence, it is significant and beneficial to predict nitration, sulfation, and phosphorylation of tyrosine residues in the whole protein sequence. Here, we introduce elastic net to perform feature selection and develop a predictor named TyrPred for predicting nitrotyrosine, sulfotyrosine, and kinase-specific tyrosine phosphorylation sites on the basis of support vector machine. We critically evaluate the performance of TyrPred and compare it with other existing tools. The satisfying results show that using elastic net to mine important features for training can considerably improve the prediction performance. Feature optimization indicates that evolutionary information is significant and contributes to the prediction model. The online tool is established at http://computbiol.ncu.edu.cn/TyrPred . We anticipate that TyrPred can provide useful complements to the existing approaches in this field.

Site-Specific Systematic Analysis of Lysine Modification Crosstalk.

Research has revealed that post-translational modifications (PTMs) that occur at lysine (PLMs) can cooperatively regulate various biological processes by crosstalk. However, the trend of the crosstalk between multiple PLMs and the properties of PLM crosstalk require additional investigation. Here, the crosstalk among acetylation, succinylation, and SUMOylation is systematically studied in a site-specific waz. First, crosstalk between SUMOylation is detected and succinylation is found to be underexpressed, whereas succinylation tends to crosstalk with acetylation and SUMOylation on the same lysine residue while PLM crosstalk is tissue-specific across different species. Further analysis reveals that different PLMs tend to occur crosstalk at diverse subcellular compartments and structural regions, and they participate in distinct biological processes and functions. Additionally, short-term evolutionary analysis shows that there is no additional evolutionary pressure on PLMs crosstalk sites, as found by comparison with singly modified sites. Finally, phylogenetic classification reveals that genes with co-occupied lysine crosstalk are more likely to have higher evolutionary similarity and possess a tendency to cluster in the specific branch. The integrated approach reported here has the potential for large-scale prioritization of in situ crosstalk of PLM candidates and provides a profound understanding of the underlying relationship between different lysine modifications.

Computing Prediction and Functional Analysis of Prokaryotic Propionylation.

Identification and systematic analysis of candidates for protein propionylation are crucial steps for understanding its molecular mechanisms and biological functions. Although several proteome-scale methods have been performed to delineate potential propionylated proteins, the majority of lysine-propionylated substrates and their role in pathological physiology still remain largely unknown. By gathering various databases and literatures, experimental prokaryotic propionylation data were collated to be trained in a support vector machine with various features via a three-step feature selection method. A novel online tool for seeking potential lysine-propionylated sites (PropSeek) ( http://bioinfo.ncu.edu.cn/PropSeek.aspx ) was built. Independent test results of leave-one-out and n-fold cross-validation were similar to each other, showing that PropSeek is a stable and robust predictor with satisfying performance. Meanwhile, analyses of Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathways, and protein-protein interactions implied a potential role of prokaryotic propionylation in protein synthesis and metabolism.

Computational prediction of species-specific malonylation sites via enhanced characteristic strategy.

MOTIVATION: Protein malonylation is a novel post-translational modification (PTM) which orchestrates a variety of biological processes. Annotation of malonylation in proteomics is the first-crucial step to decipher its physiological roles which are implicated in the pathological processes. Comparing with the expensive and laborious experimental research, computational prediction can provide an accurate and effective approach to the identification of many types of PTMs sites. However, there is still no online predictor for lysine malonylation. RESULTS: By searching from literature and database, a well-prepared up-to-data benchmark datasets were collected in multiple organisms. Data analyses demonstrated that different organisms were preferentially involved in different biological processes and pathways. Meanwhile, unique sequence preferences were observed for each organism. Thus, a novel malonylation site online prediction tool, called MaloPred, which can predict malonylation for three species, was developed by integrating various informative features and via an enhanced feature strategy. On the independent test datasets, AUC (area under the receiver operating characteristic curves) scores are obtained as 0.755, 0.827 and 0.871 for Escherichia coli ( E.coli ), Mus musculus ( M.musculus ) and Homo sapiens ( H.sapiens ), respectively. The satisfying results suggest that MaloPred can provide more instructive guidance for further experimental investigation of protein malonylation. AVAILABILITY AND IMPLEMENTATION: http://bioinfo.ncu.edu.cn/MaloPred.aspx . CONTACT: jdqiu@ncu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Accurate in silico prediction of species-specific methylation sites based on information gain feature optimization.

As one of the most important reversible types of post-translational modification, protein methylation catalyzed by methyltransferases carries many pivotal biological functions as well as many essential biological processes. Identification of methylation sites is prerequisite for decoding methylation regulatory networks in living cells and understanding their physiological roles. Experimental methods are limitations of labor-intensive and time-consuming. While in silicon approaches are cost-effective and high-throughput manner to predict potential methylation sites, but those previous predictors only have a mixed model and their prediction performances are not fully satisfactory now. Recently, with increasing availability of quantitative methylation datasets in diverse species (especially in eukaryotes), there is a growing need to develop a species-specific predictor. Here, we designed a tool named PSSMe based on information gain (IG) feature optimization method for species-specific methylation site prediction. The IG method was adopted to analyze the importance and contribution of each feature, then select the valuable dimension feature vectors to reconstitute a new orderly feature, which was applied to build the finally prediction model. Finally, our method improves prediction performance of accuracy about 15% comparing with single features. Furthermore, our species-specific model significantly improves the predictive performance compare with other general methylation prediction tools. Hence, our prediction results serve as useful resources to elucidate the mechanism of arginine or lysine methylation and facilitate hypothesis-driven experimental design and validation. AVAILABILITY AND IMPLEMENTATION: The tool online service is implemented by C# language and freely available at http://bioinfo.ncu.edu.cn/PSSMe.aspx CONTACT: jdqiu@ncu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.

SuccFind: a novel succinylation sites online prediction tool via enhanced characteristic strategy.

UNLABELLED: Lysine succinylation orchestrates a variety of biological processes. Annotation of succinylation in proteomes is the first-crucial step to decipher physiological roles of succinylation implicated in the pathological processes. In this work, we developed a novel succinylation site online prediction tool, called SuccFind, which is constructed to predict the lysine succinylation sites based on two major categories of characteristics: sequence-derived features and evolutionary-derived information of sequence and via an enhanced feature strategy for further optimizations. The assessment results obtained from cross-validation suggest that SuccFind can provide more instructive guidance for further experimental investigation of protein succinylation. AVAILABILITY AND IMPLEMENTATION: A user-friendly server is freely available on the web at: http://bioinfo.ncu.edu.cn/SuccFind.aspx. CONTACT: jdqiu@ncu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Progress and challenges in predicting protein methylation sites.

Protein methylation catalyzed by methyltransferases carries many important biological functions. Methylation and their regulatory enzymes are involved in a variety of human disease states, raising the possibility that abnormally methylated proteins can be disease markers and methyltransferases are potential therapeutic targets. Identification of methylation sites is a prerequisite for decoding methylation regulatory networks in living cells and understanding their physiological roles that have been implicated in the pathological processes. Due to various limitations of experimental methods, in silico approaches for identifying novel methylation sites have become increasingly popular. In this review, we summarize the progress in the prediction of protein methylation sites from the dataset, feature representation, prediction algorithm and online resources in the past ten years. We also discuss the challenges that are faced while developing novel predictors in the future. The development and application of methylation site prediction is a promising field of systematic biology, provided that protein methyltransferases, species and functional information will be taken into account.

Flux of granular particles through a shaken sieve plate.

We experimentally investigate a discharging flux of granular particles through a sieve plate subject to vertical vibrations. The mean mass flux shows a non-monotonic relation with the vibration strength. High-speed photography reveals that two stages, the free flight of the particles' bulk over the plate and the adhesion of the particles' bulk with the plate, alternately appear, where only the adhesion stage contributes to the flow. With two independent methods, we then measure the adhesion time under different vibration conditions, and define an adhesion flux. The adhesion flux monotonically increases with increasing vibration strength. By rescaling the adhesion flux, we find that the adhesion flux is approximately determined by the peak vibration velocity of the shaker. The conclusion is examined with other sieve geometries.

Symmetrically periodic segregation in a vertically vibrated binary granular bed.

Periodic segregation behaviors in fine mixtures of copper and alumina particles, including both percolation and eruption stages, are experimentally investigated by varying the ambient air pressure and vibrational acceleration. For the cases with moderate air pressure, the heaping profile of the granular bed keeps symmetrical in the whole periodic segregation. The symmetrical shape of the upper surface of the granular bed in the eruption stage, which resembles a miniature volcanic eruption, could be described by the Mogi model that illuminates the genuine volcanic eruption in the geography. When the air pressure increases, an asymmetrical heaping profile is observed in the eruption stage of periodic segregation. With using the image processing technique, we estimate a relative height difference between the copper and the alumina particles as the order parameter to quantitatively characterize the evolution of periodic segregation. Both eruption and percolation time, extracted from the order parameter, are plotted as a function of the vibration strength. Finally, we briefly discuss the air effect on the granular segregation behaviors.

Polymerlike statistical characterization of two-dimensional granular chains.

Statistical behaviors of packing collections of granular chains in a two-dimensional container have been investigated experimentally. On compaction from their own gravity, the longer chains pack into a structure with lower packing density due to the prevalence of backbone loops. The packing of chains can be considered as the jamming of the granular system. The structure factor of packing chains shows scaling behavior g(q)∼q(-2) in good agreement with dense polymer solutions. In addition, we compute various probability distributions of distances and estimate three crucial contact exponents, finding that the scaling behavior from granular chains is in accord with the theoretical expectation of polymers. Finally, an orientational anticorrelation of granular chains is observed by bond-bond correlation function, which agrees with the results in the two-dimensional model of compact polymers.