Mechanism and Application of Enzyme Treatment on Wool

Protease treatments on wool have its inherent defect in shrink-proofing because protease will decompose wool through cell membrane complex （CMC）. In order to solve this problem, mechanism of enzyme treatments on wool was adequately analyzed and possible enzyme applications were discussed. The mechanism of enzyme treatment on wool was analyzed through weight loss, strength, scanning electron microscopy （SEM）, electrophoresis, sodium dodecyl sulfate polyacrylamide gel electrophoresis （ SDS- PAGE）, and amino acids composition. Based on the results, a possible novel multifunetional enzyme treatment on wool to achieve shrink-resistance was proposed. In order to shorten enzyme treatment time, the rate of proteolysis of wool was investigated. Considering the specificity of proteases, wool composition, and structure of dyes, a better enzyme pretreatment before dyeing to get better dyeabflity and lower dyeing temperature was discussed.

Safety assessment of a novel marine multi-stress-tolerant yeast Meyerozyma guilliermondii GXDK6 according to phenotype and whole genome-sequencing analysis

The application of microorganisms as probiotics is limited due to lack of safety evaluation.Here,a novel multi-stress-tolerant yeast Meyerozyma guilliermondii GXDK6 with aroma-producing properties was identified from marine mangrove microorganisms.Its safety and probiotic properties were assessed in accordance with phenotype and whole-genome sequencing analysis.Results showed that the genes and phenotypic expression of related virulence,antibiotic resistance and retroelement were rarely found.Hyphal morphogenesis genes(SIT4,HOG1,SPA2,ERK1,ICL1,CST20,HSP104,TPS1,and RHO1)and phospholipase secretion gene(VPS4)were annotated.True hyphae and phospholipase were absent.Only one retroelement(Tad1-65_BG)was found.Major biogenic amines(BAs)encoding genes were absent,except for spermidine synthase(JA9_002594),spermine synthase(JA9_004690),and tyrosine decarboxylase(inx).The production of single BAs and total BAs was far below the food-defined thresholds.GXDK6 had no resistance to common antifungal drugs.Virulence enzymes,such as gelatinase,DNase,hemolytic,lecithinase,and thrombin were absent.Acute toxicity test with mice demonstrated that GXDK6 is safe.GXDK6 has a good reproduction ability in the simulation gastrointestinal tract.GXDK6 also has a strong antioxidant ability,β-glucosidase,and inulinase activity.To sum up,GXDK6 is considered as a safe probiotic for human consumption and food fermentation.

Uptake of Polycyclic Aromatic Hydrocarbons across Bacterial Membrane

Polycyclic aromatic hydrocarbons (PAHs) are important pollutants, whose biodegradation and bioremediation with microorganisms are the promising ways to clean environments and reduce their exposure to humans. Although the transportation of PAHs across bacterial membrane is the first step forwards their biodegradation, it receives less attention. In this mini-review, we explore which transport system for uptake of carbon sources can serve for uptake of PAHs in bacteria, and try to uncover some patterns in their transport mechanisms. Collectively, 1) the major carbohydrate transport system, PTS, is unlikely to take PAHs because PAHs lack a hydroxy group for phosphorylation but aromatic acids are good candidates;2) PAHs could probably go through H+ symporters, especially the low-molecular-weight PAHs, which are partially dissolvable in water;3) it is unlikely that PAHs can produce chemiosmotic ion gradients to go through uniporters;and 4) antiporters could serve as transporters to transport PAHs across bacterial membrane only after the metabolism of PAHs generates extra H+ inside cell. Accordingly, the basic mechanism for uptake of PAHs is whether they can donate H+ in order to generate an electrochemical proton gradient to go through symporters.

Impact of Temperature on Influenza A Status during Global Warming Hiatus

Temperature is a crucial factor that affects in flue nza tran smissi on. Therefore, several studies have correlated various aspects of in flue nza with temperature from the global warming period during which temperature exhibits a clear trend. The global warming hiatus has been existing since the year 1998. This provides an opportunity to investigate the effect of temperature on the transmission of influenza from the viewpoint that temperature is trendless.

Adaptation in polymerase basic protein 1 family from influenza A virus to climate change

Global climate changes affect the functioning of ecosystems, in particular host-pathogen interactions, with major consequences in health ecology, however, it is less addressed how the change in global temperature affects the protein family of influenza virus. In this study, we studied the adaptation of polymerase basic protein 1 (PB1) family from influenza A virus to temperature change. 3841 PB1 proteins sampled from 1956-2011 were quantified by the amino-acid pair predictability and then compared their general changes with the temperature changes (Had-CRUT3v and CRUTEM4v data sets) of corresponding years on a 5? by 5? grid-box basis. Also, point-to-point comparisons were conducted from 1956 to 1998 in all and different species. The results showed that both changes in the temperature and unpredictable portion of PB1 proteins had similar trends from 1956 to 2011, which provides the evidence of virus adaptation at protein level to climate change.

Elaboration of Simplest Folding Structures in 2-Dimensional Lattice with Delta-Hemolysin and Its Variants in HP Model

Although the advanced 3-dimensional structure measurements provide more and more detailed structures in Protein Data Bank, the simplest 2-dimensional lattice model still looks meaningful because 2-dimensional structures play a complementary role with respect to 3-dimensional structures. In this study, the folding structures of delta-hemolysin and its six variants were studied at 2-dimensional lattice, and their amino acid contacts in folding structures were considered according to HP model with the aid of normalized amino acid hydrophobicity index. The results showed that: 1) either delta-hemolysin or each of its variants could find any of its folding structure in one eighth of 1,129,718,145,924 folding structures because of symmetry, which reduces the time required for folding, 2) the impact of pH on folding structures is varying and associated directly with the amino acid sequence itself, 3) the changes in folding structures of variants appeared different case by case, and 4) the assigning of hydrophobicity index to each amino acid was a way to distinguish folding structures at the same native state. This study can help to understand the structure of delta-hemolysin, and such an analysis can shed lights on NP-problem listed in millennium prize because the HP folding in lattice belongs to a sub-problem of NP-problem.

Correlation of Combined Characters of Amino Acid and Whole Protein with Success Rate of Crystallization of <i>Lactobacillus</i>Proteins

Crystallization of proteins is a very delicate process, which is influenced by many known and unknown factors. Of tested factors, many factors are exclusively related to individual amino-acid characters such as molecular weight or protein characters such as protein length. It is considered necessary to test factors that combine both individual amino-acid characters and protein characters with respect to success rate of crystallization. In this study, two combined characters characterizing individual amino-acid character and protein character, amino acid distribution probability and future composition, were used to correlate the success rate of crystallization of proteins from Lactobacillus via modeling. The results obtained from logistic regression and neural network were compared against the results obtained from each of 533 individual amino-acid characters. This study demonstrated that the combined characters are involved in crystallization process and should be taken into account for predicting the success rate of crystallization process.

Building Quantitative Gene Regulatory Mechanism in Quorum Sensing in <i>Pseudomonas aeruginosa</i>Using Transcriptomic Data

A large amount of transcriptomic data provides opportunities 1) to verify the gene regulatory mechanism, which is usually obtained from a single experiment, at population level;2) to uncover the gene regulatory mechanism at population level;and 3) to build a quantitatively gene regulatory mechanism. One of the best studied regulatory mechanisms in bacteria is the quorum sensing (QS), which plays an important role in regulation of bacteria population behaviors such as antibiotic production, biofilm formation, bioluminescence, competence, conjugation, motility and sporulation. Pseudomonas aeruginosa is a Gram-negative bacterium causing diseases in plants, animals, humans, and its biofilm and drug-resistance become great concerns in clinics. P. aeruginosa has three QS systems including a specific one for Pseudomonas. In this study, the transcriptomic data of P. aeruginosa were combined from 104 publications and QS gene expressions were analyzed under different experimental conditions. The results demonstrate the quantitatively regulatory mechanisms of QS genes at population level including 1) to rank and group QS-related genes according to their activity;2) to quantitatively define the role of a single global regulator;3) to find out the probability that a global regulator impacts QS genes and the probability that a QS gene responds to global regulators;and 4) to search for overlapped genes under four types of experimental conditions. These results provide integrative information on understanding the regulation of QS genes at population level.

Mutation Patterns in Lysostaphin

Lysostaphin is widely used in clinical settings against Staphylococcus aureus, but its mutants can abolish its killing activity. The difficulty in studies of mutations in lysostaphin is the shortage of data, which may need many decades to collect, although lysostaphin is so important for clinical therapeutics and drug development. In order not to passively wait for the accumulation of new data, in this study 1) the 23,442 mutations in 1408 proteins from databank were used to determine whether the mutations in lysostaphin follow the general mutation trend obtained from the databank, 2) the amino-acid pair predictability was used to explore the underlined mechanism for lysostaphin mutations, and 3) the amino-acid distribution probability was used to associate the mutation with dysfunction of lysostaphin. The results show that the mutations in lysostaphin follow the general trend of mutations in proteins;the underlined mechanism for mutations in lysostaphin is explainable from a viewpoint of randomness, and a mutation with increased distribution probability would have a larger chance to dysfunction lysostaphin. This study provides useful information for future design of anti-S. aureus drug and enzyme engineering.

Spontaneous Unfolding and Refolding of Plantaricin α-Helix in Molecular Dynamics Simulation

Antimicrobial peptides are promising therapeutic agents in view of increasing resistance to conventional antibiotics. Antimicrobial peptides usually fold in α-helical, β-sheet, and extended/random-coil structures. The α-helical antimicrobial peptides are often unstructured in aqueous solution but become structured on bacterial membrane. The α-helical structure allows the partitioning into bacterial membrane. Therefore it is important to understand the mechanism of unfolding and refolding of α-helical structure in antimicrobial peptides. It is not very easy to obverse and study the process of unfolding and refolding of α-helical antimicrobial peptides because of their rapidity. Therefore, molecular simulation provides a way to observe and explain this phenomenon. Plantaricin A is a 26 amino-acid antimicrobial pheromone peptide and can spontaneously unfold and refold under physiological condition. This study demonstrated the unfolding and refolding of plantaricin A by means of molecular simulation, and its mechanism was discussed with its implication to the Levinthal paradox.

Do We Ignore Tobacco’s Positive Ecological Role Too Long?

Definitely, tobacco is one of the most troubling plants in this planet because of its harmful effects on humans. Therefore, tobacco plantation declines continuously in the world. For such a plant, do we need to eliminate tobacco entirely from the surface of the earth? Perhaps, humans might have ignored the tobacco’s positive role in environment and ecology, especially in the heavily industrialized environments, for too long. Because the human activity generates more and more nitrogen oxides (NOx) in atmosphere, which not only cause imbalance in the global nitrogen cycle but also lead to haze, smog, acid rain, PM2.5, and eventually impact on environment and human health. Unfortunately the current technologies do not provide an efficient way to remove NOx from atmosphere. However, it is only tobacco can remove NOx from atmosphere. Perhaps, we should blame us, humans who use tobacco unwisely, rather than blame tobacco in nature. Anyways, the ability of tobacco to remove NO2 from atmosphere should not be ignored.

The Streptococcus agalactiae Ribose Binding Protein B (RbsB) Mediates Quorum Sensing Signal Uptake via Interaction with Autoinducer-2 Signals

Understanding aquatic pathogen in sediments or aquacultural water is crucial to protect public health from soilborne and waterborne diseases.Quorum sensing(QS)was increasingly reported in biological wastewater treatment processes because of their inherent roles in biofilm development,bacterial aggregation and so on.The widely QS signals was Antoinducer-2(AI-2),primarily involved to allow the possibility of interspecies communication.However,the cellular components that mediate the response of Streptococcus agalactiae to AI-2 have not been fully characterized.Analysis of the complete genome sequence of S.agalactiae indi-cated that its RbsB protein has similarity to Escherichia coli LsrB and Aggregatibacter actinomycetemcomitans RbsB proteins that bind AI-2.We hypothesized that RbsB protein mediates quorum sensing signal uptake via interaction with AI-2.To evaluate the regulatory effect of RbsB on QS system,the recombinant plasmid pGEX-6p-1-RbsB was constructed and RbsB protein was purified with GST-tag.To further elucidate the role of RbsB protein binding to DPD(AI-2 precursor dihydroxypentanedione),the systemati-cally throughput circular dichroism(CD)spectroscopy,isothermal titration calorimetry200(ITC200)and molecular docking methods were employed.The high expression of soluble RbsB protein with molecular weight of 33 kDa was obtained.The thermodynamics results(ΔH<0,ΔS<0,ΔG<0)with ITC determination indicated that the binding process between DPD and RbsB was exothermic and spontaneous,with hydrogen bonds and van der Waals forces as the main binding forces.Obviously,DPD can be more easily combined with RbsB in a dose-dependent manner,suggesting that RbsB was changed in the microenvironment of DPD when the DPD concentration was between 0.8-1.0mmolL−1 and reaching the maximum binding amount.According to molecular docking,3 hydrophobic residues involved in DPD and RbsB protein stable binding were be found,and also hydrogen bonding plays a key role in the formation of the new complex.RbsB efficiently inhibited V.harveyi bioluminescence induced by both S.agalactiae AI-2 and V.harveyi AI-2 in a dose-dependent manner.However,our results suggest that RbsB may play a role in the response of S.agalactiace to AI-2.

Prediction of Mutations in H7 Hemagglutinins from Influenza A Virus

Influenza A viruses have led several pandemics and epidemics in human history. H7 subtype influenza mainly infects avian but also humans occasionally. Since the outbreak of H7N9 subtype influenza occurred in China in 2013, this virus is still circulating in domestic poultry and leading several waves of influenza. To prevent influenza, vaccination is an important strategy. However, influenza virus evolves constantly, but unpredictably. If we would have a one-to-one cause-mutation relationship, the mutation prediction would be possible. However, many external causes, which led to the mutations in the past, might not leave any trace due to the change in environments, whereas the current virus might not be subject to the historically external causes because of evolution. Furthermore, the protein should have the internal causes, which might be quite unclear and difficult to quantify, to engineer mutations. Indeed, various forces twist proteins into 3-demensional structures, whereas any perturbation could lead to a mutation. Of various internal causes for mutation, randomness in protein primary structure should play an important role in mutation. Over years, we have developed three methods to quantify the randomness within a protein primary structure;thus we build a relationship between cause, which is randomness in primary structure, and mutations, which are occurrence and non-occurrence of mutation. In this way, the cause-mutation relationship becomes the problem of classification, which can be solved using logistic regression and neural network. In this study, we apply this model to predict 1) the mutation positions in H7 hemagglutinins from influenza A virus and 2) the would-be-mutated amino-acids at predicted positions with the amino-acid mutating probability. The results show suitability and predictability in such modelling, and pave the way for further development.

Correlating Combined Features of Amino Acid and Protein with Crystallization Propensity of Proteins from <i>Mycobacterium tuberculosis</i>

Since a decade ago, both protein and amino acid features have been correlated with crystallization propensity of proteins in order to develop methods to predict whether a protein can be crystallized. In this continuing study, each of three features combining features of amino acid and protein, was correlated with the crystallization propensity of proteins from Mycobacterium tuberculosis using logistic and neural network models. The results showed that two combined features, amino acid distribution probability and future composition, had good predictions on whether a protein would be crystallized in comparison with the predictions obtained from each of 531 amino acid features. The results obtained from the third combined feature, amino acid pair predictability, demonstrated the trend of crystallization propensity in proteins from Mycobacterium tuberculosis.

Predicting pH Optimum for Activity of Beta-Glucosidases

The working conditions for enzymatic reaction are elegant, but not many optimal conditions are documented in literatures. For newly mutated and newly found enzymes, the optimal working conditions can only be extrapolated from our previous experience. Therefore a question raised here is whether we can use the knowledge on enzyme structure to predict the optimal working conditions. Although working conditions for enzymes can be easily measured in experiments, the predictions of working conditions for enzymes are still important because they can minimize the experimental cost and time. In this study, we develop a 20-1 feedforward backpropagation neural network with information on amino acid sequence to predict the pH optimum for the activity of beta-glucosidase, because this enzyme has drawn much attention for its role in bio-fuel industries. Among 25 features of amino acids being screened, the results show that 11 features can be used as predictors in this model and the amino-acid distribution probability is the best in predicting the pH optimum for the activity of beta-glucosidases. Our study paves the way for predicting the optimal working conditions of enzymes based on the amino-acid features.

Prediction of Crystallization Propensity of Proteins from <i>Bacillus haloduran</i>Using Various Amino Acid and Protein Features

Correct prediction of propensity of crystallization of proteins is important for cost- and time-saving in determination of 3-demensional structures because one can focus to crystallize the proteins whose propensity is high through predictions instead of choosing proteins randomly. However, so far this job has yet to accomplish although huge efforts have been made over years, because it is still extremely hard to find an intrinsic feature in a protein to directly relate to the propensity of crystallization of the given protein. Despite of this difficulty, efforts are never stopped in testing of known features in amino acids and proteins versus the propensity of crystallization of proteins from various sources. In this study, the comparison of the features, which were developed by us, with the features from well-known resource for the prediction of propensity of crystallization of proteins from Bacillus haloduran was conducted. In particular, the propensity of crystallization of proteins is considered as a yes-no event, so 185 crystallized proteins and 270 uncrystallized proteins from B. haloduran were classified as yes-no events. Each of 540 amino-acid features including the features developed by us was coupled with these yes-no events using logistic regression and neural network. The results once again demonstrated that the predictions using the features developed by us are relatively better than the predictions using any of 540 amino-acid features.

Predictors for Predicting Temperature Optimum in Beta-Glucosidases

This is the continuation of our studies on beta-glucosidase, which plays an important role in biological processes and recently strong interests focus on their potential role in biofeul production. In order to develop simple methods to predict the optimal working condition for beta-glucosidase, we used a 20-1 feedforward backpropagation neural network to screen possible predictors to predict the temperature optimum of beta-glucosidase from 25 amino-acid properties related to the primary structure of beta-glucosidases. The results show that the normalized polarizability index and amino-acid distribution probability can predict the temperature optimum of beta-glucosidase, which highlights a cost-effective way to predict various enzymatic parameters of beta-glucosidase.

2-Dimensional HP Foldings of Dermaseptin-J2

Although the hydrophobic-polar (HP) model is a simple model to study protein folding, it is an approximation to the real-life case. Dermaseptin is a subfamily of frog skin active peptide family, which has various antimicrobial activities, and dermaseptin-J2 is a newly found peptide composed of 26 amino acids. In this study, the 2-dimensional HP model was used to analyze the foldings of dermaseptin-J2 and its nine mutants, which were converted to different HP sequences according to the normalized amino acid hydrophobicity index with respect to pH levels and the conversion of glycine as hydrophobic or polar, and each has 847,288,609,443 possible foldings. The results show that the foldings with minimal energy have different native states, which are chiral and can be numerically distinguished and ranked according to the normalized amino acid hydrophobicity index. The nine mutants of dermaseptin-J2 do not affect the minimal energy but affect their native states at pH 7. The results demonstrate that two pH levels and conversion of glycine as hydrophobic or polar affect the native state and minimal energy, suggesting these are two ways to modify dermaseptin-J2.

Potentials of marine natural products against malaria, leishmaniasis, and trypanosomiasis parasites: a review of recent articles

Background:Malaria and neglected communicable protozoa parasitic diseases,such as leishmaniasis,and trypanosomiasis,are among the otherwise called diseases for neglected communities,which are habitual in underprivileged populations in developing tropical and subtropical regions of Africa,Asia,and the Americas.Some of the currently available therapeutic drugs have some limitations such as toxicity and questionable efficacy and long treatment period,which have encouraged resistance.These have prompted many researchers to focus on fin ding new drugs that are safe,effective,and affordable from marine environ merits.The aim of this review was to show the diversity,structural scaffolds,in-vitro or in-vivo efficacy,and recent progress made in the discovery/isolation of marine natural products(MNPs)with potent bioactivity against malaria,leishmaniasis,and trypanosomiasis.Main text:We searched PubMed and Google scholar using Boolean Operators(AND,OR,and NOT)and the combination of related terms for articles on marine natural products(MNPs)discovery published only in English language from January 2016 to June 2020.Twenty nine articles reported the isolation,identification and antiparasitic activity of the isolated compounds from marine environment.A total of 125 compounds were reported to have been isolated,out of which 45 were newly isolated compounds.These compounds were all isolated from bacteria,a fungus,sponges,algae,a bryozoan,cnidarians and soft corals.In recent years,great progress is being made on anti-malarial drug discovery from marine organisms with the isolation of these potent compounds.Comparably,some of these promising antikinetoplastid MNPs have potency better or similar to conventional drugs and could be developed as both antileishmanial and antitrypanosomal drugs.However,very few of these MNPs have a pharmaceutical destiny due to lack of the following:sustainable production of the bioactive compounds,stan da rd efficient screening methods,knowledge of the mechanism of action,partnerships between researchers and pharmaceutical industries.Conclusions:It is crystal clear that marine organisms are a rich source of antiparasitic compounds,such as alkaloids,terpenoids,peptides,polyketides,terpene,coumarins,steroids,fatty acid derivatives,and lactones.The current and future technological innovation in natural products drug discovery will bolster the drug armamentarium for malaria and neglected tropical diseases.

The biosynthesis of asiaticoside and madecassoside reveals tandem duplication-directed evolution of glycoside glycosyltransferases in the Apiales

Certain plant species within the Apiales order accumulate triterpenoid saponins that feature a distinctive glucose-glucose-rhamnose(G-G-R)sugar chain attached at the C-28 position of the pentacyclic triterpene skeleton.Until recently,the genomic basis underlying the biosynthesis and evolution of this sugar chain has remained elusive.In this study,we identified two novel glycoside glycosyltransferases(GGTs)that can sequentially install the sugar chain’s second D-glucose and third L-rhamnose during the biosynthesis of asiaticoside and madecassoside,two representative G-G-R sugar chain-containing triterpenoid saponins produced by Centella asiatica.Enzymatic assays revealed the remarkable substrate promiscuity of the two GGTs and the key residues crucial for sugar-donor selectivity of the glucosyltransferase and rhamnosyltransferase.We further identified syntenic tandem gene duplicates of the two GGTs in the Apiaceae and Araliaceae families,suggesting a well-conserved genomic basis underlying sugar chain assembly that likely has evolved in the early ancestors of the Apiales order.Moreover,expression patterns of the two GGTs in pierced leaves of C.asiatica were found to be correlated with the production of asiaticoside and madecassoside,implying their involvement in host defense against herbivores and pathogens.Our work sheds light on the biosynthesis and evolution of complex saponin sugars,paving the way for future engineering of diverse bioactive triterpenoids with unique glycoforms.