A polystyrene binding target-unrelated peptide isolated in the screening of phage display library

Targeted inhibition of oral biofilm formation using phage-derived high-affinity peptides

Dental caries, commonly known as tooth decay, poses a significant oral health challenge affecting individuals of all age groups. While dietary factors play a role, tooth decay primarily results from the activity of various oral bacteria that form biofilms in the oral cavity. In this study, we employed the phage display technique to identify high-affinity peptides capable of binding specifically to three oral bacteria strains: Streptococcus mutans, Streptococcus oralis, and Lactobacillus casei. Four selected peptides underwent binding affinity testing for each target bacterium, revealing that three of them exhibited specific binding capabilities, effectively inhibiting biofilm formation. This study demonstrates the efficacy of engineered phages in identifying high-affinity peptides that selectively target oral bacteria. These peptides hold promise for preventing oral biofilm formation, a significant contributor to oral diseases and dental caries. This innovative approach opens doors to novel therapeutic strategies for addressing oral health issues. The findings may spur further research into the utilization of phages and peptides as potential anti-biofilm agents, potentially revolutionizing the field of oral health.

Integrating biophysical modeling, quantum computing, and AI to discover plastic-binding peptides that combat microplastic pollution

Methods are needed to mitigate microplastic (MP) pollution to minimize their harm to the environment and human health. Given the ability of polypeptides to adsorb strongly to materials of micro- or nanometer size, plastic-binding peptides (PBPs) could help create bio-based tools for detecting, filtering, or degrading MNP pollution. However, the development of such tools is prevented by the lack of PBPs. In this work, we discover and evaluate PBPs for several common plastics by combining biophysical modeling, molecular dynamics (MD), quantum computing, and reinforcement learning. We frame peptide affinity for a given plastic through a Potts model that is a function of the amino acid sequence and then search for the amino acid sequences with the greatest predicted affinity using quantum annealing. We also use proximal policy optimization to find PBPs with a broader range of physicochemical properties, such as isoelectric point or solubility. Evaluation of the discovered PBPs in MD simulations demonstrates that the peptides have high affinity for two of the plastics: polyethylene and polypropylene. We conclude by describing how our computational approach could be paired with experimental approaches to create a nexus for designing and optimizing peptide-based tools that aid the detection, capture, or biodegradation of MPs. We thus hope that this study will aid in the fight against MP pollution.

Nature-Inspired Strategies for Sustainable Degradation of Synthetic Plastics

Synthetic plastics have become integral to our daily lives, yet their escalating production, limited biodegradability, and inadequate waste management contribute to environmental contamination. Biological plastic degradation is one promising strategy to address this pollution. The inherent chemical and physical properties of synthetic plastics, however, pose challenges for microbial enzymes, hindering the effective degradation and the development of a sustainable biological recycling process. This Perspective explores alternative, nature-inspired strategies designed to overcome some key limitations in currently available plastic-degrading enzymes. Nature's refined degradation pathways for natural polymers, such as cellulose, present a compelling framework for the development of efficient technologies for enzymatic plastic degradation. By drawing insights from nature, we propose a general strategy of employing substrate binding domains to improve targeting and multienzyme scaffolds to overcome enzymatic efficiency limitations. As one potential application, we outline a multienzyme pathway to upcycle polyethylene into alkenes. Employing nature-inspired strategies can present a path toward sustainable solution to the environmental impact of synthetic plastics.

Selection for antimicrobial resistance in the plastisphere

Microplastics and antimicrobials are widespread contaminants that threaten global systems and frequently co-exist in the presence of human or animal pathogens. Whilst the impact of each of these contaminants has been studied in isolation, the influence of this co-occurrence in driving antimicrobial resistance (AMR)1 in microplastic-adhered microbial communities, known as 'the Plastisphere', is not well understood. This review proposes the mechanisms by which interactions between antimicrobials and microplastics may drive selection for AMR in the Plastisphere. These include: 1) increased rates of horizontal gene transfer in the Plastisphere compared with free-living counterparts and natural substrate controls due to the proximity of cells, co-occurrence of environmental microplastics with AMR selective compounds and the sequestering of extracellular antibiotic resistance genes in the biofilm matrix. 2) An elevated AMR selection pressure in the Plastisphere due to the adsorbing of AMR selective or co-selective compounds to microplastics at concentrations greater than those found in surrounding mediums and potentially those adsorbed to comparator particles. 3) AMR selection pressure may be further elevated in the Plastisphere due to the incorporation of antimicrobial or AMR co-selective chemicals in the plastic matrix during manufacture. Implications for both ecological functioning and environmental risk assessments are discussed, alongside recommendations for further research.

IIFS: An improved incremental feature selection method for protein sequence processing

MOTIVATION

Discrete features can be obtained from protein sequences using a feature extraction method. These features are the basis of downstream processing of protein data, but it is necessary to screen and select some important features from them as they generally have data redundancy.

RESULT

Here, we report IIFS, an improved incremental feature selection method that exploits a new subset search strategy to find the optimal feature set. IIFS combines nonadjacent sorting features to prevent the drawbacks of data explosion and excessive reliance on feature sorting results. The comparative experimental results on 27 feature sorting data show that IIFS can find more accurate and important features compared to existing methods.The IIFS approach also handles data redundancy more efficiently and finds more representative and discriminatory features while ensuring minimal feature dimensionality and good evaluation metrics. Moreover, we wrap this method and deploy it on a web server for access at http://112.124.26.17:8005/.

Recent Advances on Peptide-Based Biosensors and Electronic Noses for Foodborne Pathogen Detection

Foodborne pathogens present a serious issue around the world due to the remarkably high number of illnesses they cause every year. In an effort to narrow the gap between monitoring needs and currently implemented classical detection methodologies, the last decades have seen an increased development of highly accurate and reliable biosensors. Peptides as recognition biomolecules have been explored to develop biosensors that combine simple sample preparation and enhanced detection of bacterial pathogens in food. This review first focuses on the selection strategies for the design and screening of sensitive peptide bioreceptors, such as the isolation of natural antimicrobial peptides (AMPs) from living organisms, the screening of peptides by phage display and the use of in silico tools. Subsequently, an overview on the state-of-the-art techniques in the development of peptide-based biosensors for foodborne pathogen detection based on various transduction systems was given. Additionally, limitations in classical detection strategies have led to the development of innovative approaches for food monitoring, such as electronic noses, as promising alternatives. The use of peptide receptors in electronic noses is a growing field and the recent advances of such systems for foodborne pathogen detection are presented. All these biosensors and electronic noses are promising alternatives for the pathogen detection with high sensitivity, low cost and rapid response, and some of them are potential portable devices for on-site analyses.

Sensitive and specific capture of polystyrene and polypropylene microplastics using engineered peptide biosensors

Owing to increased environmental pollution, active research regarding microplastics circulating in the ocean has attracted significant interest in recent times. Microplastics accumulate in the bodies of living organisms and adversely affect them. In this study, a new method for the rapid detection of microplastics using peptides was proposed. Among the various types of plastics distributed in the ocean, polystyrene and polypropylene were selected. The binding affinity of the hydrophobic peptides suitable for each type of plastic was evaluated. The binding affinities of peptides were confirmed in unoxidized plastics and plasma-oxidized plastics in deionised or 3.5% saline water. Also, the detection of microplastics in small animals' intestine extracts were possible with the reported peptide biosensors. We expect plastic-binding peptides to be used in sensors to increase the detection efficiency of microplastics and potentially help separate microplastics from seawater.

The emerging role of selenium metabolic pathways in cancer: New therapeutic targets for cancer

Selenium (Se) is incorporated into the body via the selenocysteine (Sec) biosynthesis pathway, which is critical in the synthesis of selenoproteins, such as glutathione peroxidases and thioredoxin reductases. Selenoproteins, which play a key role in several biological processes, including ferroptosis, drug resistance, endoplasmic reticulum stress, and epigenetic processes, are guided by Se uptake. In this review, we critically analyze the molecular mechanisms of Se metabolism and its potential as a therapeutic target for cancer. Sec insertion sequence binding protein 2 (SECISBP2), which is a positive regulator for the expression of selenoproteins, would be a novel prognostic predictor and an alternate target for cancer. We highlight strategies that attempt to develop a novel Se metabolism-based approach to uncover a new metabolic drug target for cancer therapy. Moreover, we expect extensive clinical use of SECISBP2 as a specific biomarker in cancer therapy in the near future. Of note, scientists face additional challenges in conducting successful research, including investigations on anticancer peptides to target SECISBP2 intracellular protein.

Identification of novel paraben-binding peptides using phage display

Parabens are alkyl esters of 4-hydroxybenzoic acid, which is derived from a family of synthetic esters of p-hydroxybenzoic acid. Among all the kinds of paraben, two parabens (methyl paraben, MP; and n-propyl paraben, PP) are the most generally used as preservatives in personal care products, such as cosmetics, pharmaceuticals, and food also, and are often presented together. However, a number of studies have reported that the toxicity of parabens affects the water environment, and human as well. This study utilized M13 phage display technology to provide easy, efficient, and relatively inexpensive methods to identify peptides that bind to MP and PP, respectively, to remove in wastewater. At first, biopanning was performed, to sort MP and PP specific binding phages, and three cases of experiment, including negative control (NC), which could sort unspecific binding phage, were conducted at the same time. Phage binding affinity tests were substituted by concentration reduction using antibody conjugated magnetic beads, and paraben concentration was measured by HPLC. Analysis showed that the MP concentration reduction of 38% was the highest in M4 phage, while the PP concentration reduction of 44% was the highest in P3 phage. We successfully screened two peptides specific to MP and PP, namely, MP4 and PP3, respectively; the results showed that the MP concentration reduction in MP4 was the highest at 44%, and the PP concentration reduction in PP3 was the highest at 39%, and their specificity was measured by the capture rate between target and control. In conclusion, the phage display technique shows applicability to the removal of parabens in water; furthermore, it also shows the possibility of the detection or removal of other chemicals.

Efficient and robust isolation of rabbit scFv antibodies using antigen-coupled multilamellar vesicles

We demonstrated an efficient screening method for rabbit scFv antibodies using antigen-coupled multi-lamellar vesicles (Ag-MLVs) as solid supports. Model phages displaying mouse anti-human IgG scFv at a probability of 10^-4-10^-5% were successfully isolated by Ag-MLVs after 3 or less rounds of biopanning, whereas they could not be isolated using conventional antigen-coated immunotubes. This screening method was applied to isolate rabbit antigen-specific scFvs from 4 different phage libraries. Biopanning procedures employing Ag-MLVs yielded positive phages in the 3rd round or earlier, and specific antigen-binding of scFvs was observed after the 1st round in two biopanning selections. The dissociation rate constants (k_off) of isolated scFv clones tended to decrease with progressing biopanning rounds. The average dissociation constants (K_D) of the isolated scFvs ranged between 1.7 and 87 nM, whereas the lowest K_D of 12 pM was recorded for anti-CRP scFv. Comprehensive characterization of 355 different clones of the isolated rabbit scFvs presented a relatively low isoelectric point, and most of these were more thermo-stable than the conventional mouse scFvs, based on their instability and aliphatic indices. These results clearly indicate the advantages and potential of a combination of rabbit scFv-displaying phage library and biopanning using Ag-MLVs for antibody discovery. In addition, the results obtained in this study support the suitability of rabbit scFvs for several applications, including the development of diagnostic agents and affinity ligands for molecular diagnosis and bioseparation.

PSBP-SVM: A Machine Learning-Based Computational Identifier for Predicting Polystyrene Binding Peptides

Polystyrene binding peptides (PSBPs) play a key role in the immobilization process. The correct identification of PSBPs is the first step of all related works. In this paper, we proposed a novel support vector machine-based bioinformatic identification model. This model contains four machine learning steps, including feature extraction, feature selection, model training and optimization. In a five-fold cross validation test, this model achieves 90.38, 84.62, 87.50, and 0.90% SN, SP, ACC, and AUC, respectively. The performance of this model outperforms the state-of-the-art identifier in terms of the SN and ACC with a smaller feature set. Furthermore, we constructed a web server that includes the proposed model, which is freely accessible at http://server.malab.cn/PSBP-SVM/index.jsp.

A Specific Nonenal-Binding Peptide, P4 Screened by Phage Display can Remove Trans-2-Nonenal

Trans-2-nonenal is a fatty aldehyde with a long-chain, containing nine carbons. It was known that trans-2-nonenal is a cause of the odor associated with aging, and mainly found from the ages of 40 years. Phage display was a famous laboratory technique for proteins, peptides, and DNA interaction using bacteriophages to connect proteins with the genetic information. In this study, we have carried out random phage display screening to identify specific binding peptides for trans-2-nonenal. Trans-2-nonenal was directly coated on the plate. To select the phages against trans-2-nonenal, the random phages were attached to trans-2-nonenal and selected by 1-5 panning steps. Individual DNA of phage after 5 panning was analyzed to find the specific peptide sequence against trans-2-nonenal. The affinity of positive and negative binding phages was verified by ELISA assay using M13 phage-specific antibody. Among the phages, the phage with sequence of AHKSKLHQHVMFGGG (called as P4) in the end of tail, has shown the highest response. To explore a role of the peptide selected in sequence analysis and ELISA assay, the peptide was connected to magnetic beads. The peptide-coated beads were treated within trans-2-nonenal: treatment of P4 peptide shows significant decrease of trans-2-nonenal compared to negative peptide. Based on our results, it is suggested that the peptide, which is selected by phage display, could be used for the removal of trans-2-nonenal and odor associated with aging.

KnowVolution of the Polymer-Binding Peptide LCI for Improved Polypropylene Binding

The functionalization of polymer surfaces by polymer-binding peptides offers tremendous opportunities for directed immobilization of enzymes, bioactive peptides, and antigens. The application of polymer-binding peptides as adhesion promoters requires reliable and stable binding under process conditions. Molecular modes of interactions between material surfaces, peptides, and solvent are often not understood to an extent that enables (semi-) rational design of polymer-binding peptides, hindering the full exploitation of their potential. Knowledge-gaining directed evolution (KnowVolution) is an efficient protein engineering strategy that facilitates tailoring protein properties to application demands through a combination of directed evolution and computational guided protein design. A single round of KnowVolution was performed to gain molecular insights into liquid chromatography peak I peptide, 47 aa (LCI)-binding to polypropylene (PP) in the presence of the competing surfactant Triton X-100. KnowVolution yielded a total of 8 key positions (D19, S27, Y29, D31, G35, I40, E42, and D45), which govern PP-binding in the presence of Triton X-100. The recombination of two of the identified amino acid substitutions (Y29R and G35R; variant KR-2) yielded a 5.4 ± 0.5-fold stronger PP-binding peptide compared to LCI WT in the presence of Triton X-100 (1 mM). The LCI variant KR-2 shows a maximum binding capacity of 8.8 ± 0.1 pmol/cm² on PP in the presence of Triton X-100 (up to 1 mM). The KnowVolution approach enables the development of polymer-binding peptides, which efficiently coat and functionalize PP surfaces and withstand surfactant concentrations that are commonly used, such as in household detergents.

[Construction and characterization of a recombinant mutant homolog of the CheW protein from Thermotoga petrophila RKU-1]

In the work a recombinant chemotaxis protein CheW from Thermotoga petrophila RKU-1 (TpeCheW) and its mutant homolog (TpeCheW-mut) were created. It was shown that, despite the low homology with CheW prototypes from intestinal bacteria, these proteins didn't cause metabolic overload and were well expressed by cells of E. coli laboratory strains. We have discovered a broad spectrum of industrial valuable properties of the TpeCheW-mut protein such as stability in a wide range of temperatures and pH, high expression level, solubility and possibility of the application of a simple low-stage purification methodology with the use of preliminary heat treatment. Possible directions of the scientific and industrial application of this protein were claimed.

PSBinder: A Web Service for Predicting Polystyrene Surface-Binding Peptides

Polystyrene surface-binding peptides (PSBPs) are useful as affinity tags to build a highly effective ELISA system. However, they are also a quite common type of target-unrelated peptides (TUPs) in the panning of phage-displayed random peptide library. As TUP, PSBP will mislead the analysis of panning results if not identified. Therefore, it is necessary to find a way to quickly and easily foretell if a peptide is likely to be a PSBP or not. In this paper, we describe PSBinder, a predictor based on SVM. To our knowledge, it is the first web server for predicting PSBP. The SVM model was built with the feature of optimized dipeptide composition and 87.02% (MCC = 0.74; AUC = 0.91) of peptides were correctly classified by fivefold cross-validation. PSBinder can be used to exclude highly possible PSBP from biopanning results or to find novel candidates for polystyrene affinity tags. Either way, it is valuable for biotechnology community.

Discovery of a polystyrene binding peptide isolated from phage display library and its application in peptide immobilization

Phage peptide display is a powerful technique for discovery of various target-specific ligands. However, target-unrelated peptides can often be obtained and cause ambiguous results. Peptide PB-TUP has been isolated repeatedly in our laboratory on different targets and we conducted a research on PB-TUP phage to investigate their binding properties and rate of propagation. ELISA and phage recovery assay demonstrated that PB-TUP phage had a significant superior affinity to polystyrene solid surface compared with control phage clones. In this study, some incidental bindings are excluded like blocking agents and non-specific binding of secondary antibodies. Propagation rate assays of the selected phage clones showed that the growth rate of PB-TUP phage was not superior to the control phages. Furthermore, the binding of PB-TUB to polystyrene was concentration dependent and varied with solution pH. Molecular modeling revealed that stable structures of α-helix and β-turn may contribute to the binding of PB-TUP to polystyrene plate. The PB-TUP sequence was fused to the N-terminus of peptide P2 and the fusion peptide significantly increased the binding affinity to polystyrene. The fusion peptide also enhanced the cell adhesion ability of peptide P2 with human umbilical vein endothelial cell (HUVEC). The addition of the polystyrene binding peptide provided a convenient method for peptide immobilization.