Peptide Patterns Research Articles

Seasonal variation in expression patterns of anti-microbial peptides and activity of anti-oxidant defence enzymes in muga silkworm larvae, Antheraea assamensis Helfer

Seasonal variation in expression patterns of anti-microbial peptides and activity of anti-oxidant defence enzymes in muga silkworm larvae, Antheraea assamensis Helfer

Multi-parameter tunable synthetic matrix for engineering lymphatic vessels

Controlling the formation of new lymphatic vessels has been postulated as an innovative therapeutic strategy for various disease phenotypes, including neurodegenerative diseases, metabolic syndrome, cardiovascular disease, and lymphedema. Yet, compared to the blood vascular system, little is known about the molecular regulation that controls lymphatic tube formation in a synthetic matrix. In this study, we utilize hyaluronic acid (HA)-hydrogels to design a novel platform for decoupled investigation into how mechanical and biochemical cues regulate lymphatic vessel formation in a synthetic matrix. Using HA and controlling the degree of modification provides a method to preserve and modulate key lymphatic markers Prox1, LYVE-1, and Pdpn. The chemistry of the system allows for spatial and temporal patterning of specific peptides and substrate stiffnesses, and an MMP-sensitive crosslinker allowed cells to degrade and remodel their matrix. Through systematic optimization of multiple parameters, we have designed a system that allows human lymphatic endothelial cells (LECs) to self-assemble into vessels in vitro within 3 days. These engineered vessels can be cultured for up to 3 weeks and can be used for high-throughput mechanistic studies, or can be implanted into immunodeficient mice where they have demonstrated the ability to integrate and mature. Collectively, these studies report a novel, fully-defined 3D synthetic matrix system capable of generating lymphatic vessels in vitro that provide promise as an in vitro screening platform and as a therapeutic vessel transplant, which to our knowledge, is the first ever 3D lymphatic tissue engineering approach to not require the use of support cells.

Molecular recognition characteristics of co-assembled peptides on atomically flat graphite surfaces

Molecular recognition, involving the binding of two or more molecules, is widely found in multiple disciplines. It plays a crucial role in driving specific molecular functionalization or biological activities such as antigen–antibody interactions. Recently, the molecular recognition of single peptides self-assembly at interfaces has been widely investigated since their broad applications in biosensors and bioelectronics. However, the recognition characteristics of peptide-peptide co-assembly on solids has not been investigated yet, which provides a basis for potential multi-probes biosensing or structure-intermingled functionalized bioelectronic applications. Here, we explored the molecular recognition characteristics of co-assembled peptides on two-dimensional (2D) layered nanomaterials, specifically graphite. Our findings showed distinct surface characteristics of peptide co-assembly in comparison to the independent peptides self-assembly. Peptide co-assembly exhibited the nucleation and growth heterogeneities with reduced nucleation and growth rates, dominated by a diffusion-limited step as confirmed via carrying out the sequential-assembled experiments. Moreover, molecular dynamics simulation reveals a slowdown binding process of co-assembled peptides to graphite. Furthermore, the misattachment of one peptide to arrays of another types of peptide with distinct structural ordering orientations severely postponed peptide elongation. Therefore, our work provides valuable insight into the fundamental surface characteristics of two co-assembled peptides as they specifically recognize graphite surface via undergoing continuous surface behaviors from binding to diffusion until final ordering process. The formation of co-assembled peptide patterns on 2D layered nanomaterials incorporates multiple functions enabling to provide potential applications in intermingled peptide-based biosensing or bioelectronic nanodevices.

The MAMP Peptide Patterns of Bacterial Flagellins and Their Interaction with Plant Receptors: Bioinformatic and Coevolutionary Aspects

Conservative motifs (peptide patterns) determining the elicitor properties of plant-pathogenic bacteria were revealed in amino acid sequences of the flagellins of phytopathogenic, associated, and root nodule microflora. In plant growth-promoting rhizobacteria (PGPR), analogs of one (flg22) out of two (flg22 and flgII-28) specific peptides, characterizing pathogens were revealed. Instead of glycine G18, characteristic of an elicitor, tyrosine Y18 was identified in flg22 analogs of most PGPR, which prevents actuation of the phytoimmunity mechanism against PGPR. Molecular docking with the AlphaFold software complex demonstrated reliability of the interaction between the plant receptor FLS2 and the canonical peptide flg22 and its analogs from a plant pathogen and an Azospirillum. However, in the case of the FLS3 plant receptor only its interactions with the canonical peptide flgII-28 and its analog from the plant pathogen were reliable.

Reinvigoration of cytotoxic T lymphocytes in microsatellite instability-high colon adenocarcinoma through lysosomal degradation of PD-L1

Compensation and intracellular storage of PD-L1 may compromise the efficacy of antibody drugs targeting the conformational blockade of PD1/PD-L1 on the cell surface. Alternative therapies aiming to reduce the overall cellular abundance of PD-L1 thus might overcome resistance to conventional immune checkpoint blockade. Here we show by bioinformatics analysis that colon adenocarcinoma (COAD) with high microsatellite instability (MSI-H) presents the most promising potential for this therapeutic intervention, and that overall PD-L1 abundance could be controlled via HSC70-mediated lysosomal degradation. Proteomic and metabolomic analyses of mice COAD with MSI-H in situ unveil a prominent acidic tumor microenvironment. To harness these properties, an artificial protein, IgP β, is engineered using pH-responsive peptidic foldamers. This features customized peptide patterns and designed molecular function to facilitate interaction between neoplastic PD-L1 and HSC70. IgP β effectively reduces neoplastic PD-L1 levels via HSC70-mediated lysosomal degradation, thereby persistently revitalizing the action of tumor-infiltrating CD8 + T cells. Notably, the anti-tumor effect of lysosomal-degradation-based therapy surpasses that of antibody-based immune checkpoint blockade for MSI-H COAD in multiple mouse models. The presented strategy expands the use of peptidic foldamers in discovering artificial protein drugs for targeted cancer immunotherapy.

Prediction of leukemia peptides using convolutional neural network and protein compositions

Leukemia is a type of blood cell cancer that is in the bone marrow’s blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances fast and chronic growth gradually which are further classified into lymphocytic and myeloid leukemias. This work evaluates a unique deep convolutional neural network (CNN) classifier that improves identification precision by carefully examining concatenated peptide patterns. The study uses leukemia protein expression for experiments supporting two different techniques including independence and applied cross-validation. In addition to CNN, multilayer perceptron (MLP), gated recurrent unit (GRU), and recurrent neural network (RNN) are applied. The experimental results show that the CNN model surpasses competitors with its outstanding predictability in independent and cross-validation testing applied on different features extracted from protein expressions such as amino acid composition (AAC) with a group of AAC (GAAC), tripeptide composition (TPC) with a group of TPC (GTPC), and dipeptide composition (DPC) for calculating its accuracies with their receiver operating characteristic (ROC) curve. In independence testing, a feature expression of AAC and a group of GAAC are applied using MLP and CNN modules, and ROC curves are achieved with overall 100% accuracy for the detection of protein patterns. In cross-validation testing, a feature expression on a group of AAC and GAAC patterns achieved 98.33% accuracy which is the highest for the CNN module. Furthermore, ROC curves show a 0.965% extraordinary result for the GRU module. The findings show that the CNN model is excellent at figuring out leukemia illnesses from protein expressions with higher accuracy.

A Versatile Microfluidic Platform for Extravasation Studies Based on DNA Origami-Cell Interactions.

The adhesion of circulating tumor cells (CTCs) to the endothelial lumen and their extravasation to surrounding tissues are crucial in the seeding of metastases and remain the most complex events of the metastatic cascade to study. Integrins expressed on CTCs are major regulators of the extravasation process. This knowledge is primarily derived from animal models and biomimetic systems based on artificial endothelial layers, but these methods have ethical or technical limitations. We present a versatile microfluidic device to study cancer cell extravasation that mimics the endothelial barrier by using a porous membrane functionalized with DNA origami nanostructures (DONs) that display nanoscale patterns of adhesion peptides to circulating cancer cells. The device simulates physiological flow conditions and allows direct visualization of cell transmigration through microchannel pores using 3D confocal imaging. Using this system, we studied integrin-specific adhesion in the absence of other adhesive events. Specifically, we show that the transmigration ability of the metastatic cancer cell line MDA-MB-231 is influenced by the type, distance, and density of adhesion peptides present on the DONs. Furthermore, studies with mixed ligand systems indicate that integrins binding to RGD (arginine-glycine-aspartic acid) and IDS (isoleucine-aspartic acid-serine) did not synergistically enhance the extravasation process of MDA-MB-231 cells.

A Versatile Microfluidic Platform for Extravasation Studies Based on DNA Origami—Cell Interactions

AbstractThe adhesion of circulating tumor cells (CTCs) to the endothelial lumen and their extravasation to surrounding tissues are crucial in the seeding of metastases and remain the most complex events of the metastatic cascade to study. Integrins expressed on CTCs are major regulators of the extravasation process. This knowledge is primarily derived from animal models and biomimetic systems based on artificial endothelial layers, but these methods have ethical or technical limitations. We present a versatile microfluidic device to study cancer cell extravasation that mimics the endothelial barrier by using a porous membrane functionalized with DNA origami nanostructures (DONs) that display nanoscale patterns of adhesion peptides to circulating cancer cells. The device simulates physiological flow conditions and allows direct visualization of cell transmigration through microchannel pores using 3D confocal imaging. Using this system, we studied integrin‐specific adhesion in the absence of other adhesive events. Specifically, we show that the transmigration ability of the metastatic cancer cell line MDA‐MB‐231 is influenced by the type, distance, and density of adhesion peptides present on the DONs. Furthermore, studies with mixed ligand systems indicate that integrins binding to RGD (arginine‐glycine‐aspartic acid) and IDS (isoleucine‐aspartic acid‐serine) did not synergistically enhance the extravasation process of MDA‐MB‐231 cells.

Erratum to: The MAMP Peptide Patterns of Bacterial Flagellins and Their Interaction with Plant Receptors: Bioinformatic and Coevolutionary Aspects

Erratum to: The MAMP Peptide Patterns of Bacterial Flagellins and Their Interaction with Plant Receptors: Bioinformatic and Coevolutionary Aspects

Manipulating Stem Cell Fate with Disordered Bioactive Cues on Surfaces: The Role of Bioactive Ligand Selection.

The development of 2D or 3D bioactive platforms for rapidly isolating pure populations of cells from adult stem cells holds promise for advancing the understanding of cellular mechanisms, drug testing, and tissue engineering. Over the years, methods have emerged to synthesize bioactive micro- and nanostructured 2D materials capable of directing stem cell fate. We introduce a novel method for randomly micro- or nanopatterning any protein/peptide onto both 2D and 3D scaffolds via spray technology. Our goal is to investigate the impact of arranging bioactive micropatterns (ordered vs disordered) on surfaces to guide human mesenchymal stem cell (hMSC) differentiation. The spray technology efficiently coats materials with controlled, cost-effective bioactive micropatterns in various sizes and shapes. BMP-2 mimetic peptides were covalently grafted, individually or in combination with RGD peptides, onto activated polyethylene terephthalate (PET) surfaces through a spraying process, incorporating nano/microscale parameters like size, shape, and composition. The study explores different peptide distributions on surfaces and various peptide combinations. Four surfaces were homogeneously functionalized with these peptides (M1 to M4 with various densities of peptides), and six surfaces with disordered micro- and nanopatterns of peptides (S0 to S5 with different sizes of peptide patterns) were synthesized. Fluorescence microscopy assessed peptide distribution, followed by hMSC culture for 2 weeks, and evaluated osteogenic differentiation via immunocytochemistry and RT-qPCR for osteoblast and osteocyte markers. Cells on uniformly peptide-functionalized surfaces exhibited cuboidal forms, while those on surfaces with disordered patterns tended toward columnar or cuboidal shapes. Surfaces S4 and S5 showed dendrite-like formations resembling an osteocyte morphology. S5 showed significant overexpression of osteoblast (OPN) and osteocyte markers (E11, DMP1, and SOST) compared to control surfaces and other micropatterned surfaces. Notably, despite sharing an equivalent quantity of peptides with a homogeneous functionalized surface, S5 displayed a distinct distribution of peptides, resulting in enhanced osteogenic differentiation of hMSCs.

The MAMP Peptide Patterns of Bacterial Flagellins and Their Interaction with Plant Receptors: Bioinformatic and Coevolutionary Aspects

The MAMP Peptide Patterns of Bacterial Flagellins and Their Interaction with Plant Receptors: Bioinformatic and Coevolutionary Aspects

Changes in potato peptide bioactivity after gastrointestinal digestion. An in silico and in vitro study of different patatin-rich potato protein isolate matrices

Potato protein has gained attention as a promising protein source, because of its amino acid profile and technological functionality; however, little is reported about its nutritional properties as a function of processing history. In this work, the digesta of the four potato protein matrices (suspension, foam, gel, and heated foam) were analyzed by LC-MS/MS and their bioactivity evaluated in vitro and in silico.Different treatments significantly influenced digestion efficiency and peptide distribution. Heat treatment enhanced the hydrolysis, which led to distinct peptide patterns and distributions compared to unheated proteins. Heated foams showed smallest concentration of residual protein in the intestinal stage, and the highest resistance to digestion. Peptides obtained after digestion exhibited a range of potential health benefits in silico, namely, antimicrobial, antihypertensive, and antioxidant activities. All intestinal digesta showed in vitro DPPH radical scavenging and ACE-inhibitory activity.

Spatial neurolipidomics-MALDI mass spectrometry imaging of lipids in brain pathologies.

Given the complexity of nervous tissues, understanding neurochemical pathophysiology puts high demands on bioanalytical techniques with respect to specificity and sensitivity. Mass spectrometry imaging (MSI) has evolved to become an important, biochemical imaging technology for spatial biology in biological and translational research. The technique facilitates comprehensive, sensitive elucidation of the spatial distribution patterns of drugs, lipids, peptides, and small proteins in situ. Matrix-assisted laser desorption ionization (MALDI)-based MSI is the dominating modality due to its broad applicability and fair compromise of selectivity, sensitivity price, throughput, and ease of use. This is particularly relevant for the analysis of spatial lipid patterns, where no other comparable spatial profiling tools are available. Understanding spatial lipid biology in nervous tissue is therefore a key and emerging application area of MSI research. The aim of this review is to give a concise guide through the MSI workflow for lipid imaging in central nervous system (CNS) tissues and essential parameters to consider while developing and optimizing MSI assays. Further, this review provides a broad overview of key developments and applications of MALDI MSI-based spatial neurolipidomics to map lipid dynamics in neuronal structures, ultimately contributing to a better understanding of neurodegenerative disease pathology.

Mobilize a Proton to Transform the Collision-Induced Dissociation Spectral Pattern of a Cyclic Peptide.

The collision-induced dissociation (CID) behaviors of protonated molecules of anabaenopeptins, a group of cyanobacterial cyclic peptides, were investigated in detail using liquid chromatography-tandem mass spectrometry. Although anabaenopeptin A and B share a macrocyclic peptide structure, they give strikingly different fragmentation patterns; the former gives a variety of product ions including cleavages in the cyclic peptide structure, which is useful for structural analysis; whereas the latter gives far fewer product ions and no fragmentation in the cyclic moiety. Energy-resolved CID experiments clarified the mechanism behind the striking difference attributable to the difference in exocyclic amino acid residues, Tyr or Arg. The guanidino group in Arg-containing analogue, anabaenopeptin B, should be by far the most preferred protonation site; the proton would be sequestered at the guanidino group in the protonated molecule, with the lack of proton mobility prohibiting opening of the charge-directed fragmentation channels in the cyclic moiety. Enzymatic hydrolysis of the guanidino group to give citrullinated-anabaenopeptin B restored proton mobility. The fragmentation pattern of the citrullinated peptide became almost identical to that of anabaenopeptin A. The observed fragmentation behaviors of these cyclic peptides were consistent with those of linear peptides, which have been well understood based on the mobile proton model.

Automatic generation of functional peptides with desired bioactivity and membrane permeability using Bayesian optimization.

Peptides are potentially useful modalities of drugs; however, cell membrane permeability is an obstacle in peptide drug discovery. The identification of bioactive peptides for a therapeutic target is also challenging because of the huge amino acid sequence patterns of peptides. In this study, we propose a novel computational method, PEptide generation system using Neural network Trained on Amino acid sequence data and Gaussian process-based optimizatiON (PENTAGON), to automatically generate new peptides with desired bioactivity and cell membrane permeability. In the algorithm, we mapped peptide amino acid sequences onto the latent space constructed using a variational autoencoder and searched for peptides with desired bioactivity and cell membrane permeability using Bayesian optimization. We used our proposed method to generate peptides with cell membrane permeability and bioactivity for each of the nine therapeutic targets, such as the estrogen receptor (ER). Our proposed method outperformed a previously developed peptide generator in terms of similarity to known active peptide sequences and the length of generated peptide sequences.

Effect of C7-3-Peptide-Loaded Chitosan Nanoparticles Against Multi-Drug-Resistant Neisseria gonorrhoeae.

The emergence of Neisseria gonorrhoeae-resistant strains represents one of the most urgent global threats. In this regard, C7-3 peptide is one of the anti-virulence therapies that has demonstrated promising anti-gonococcal activity. Accordingly, this research aimed to formulate C7-3 peptide and its derivatives in chitosan nanoparticles. The peptide loaded chitosan nanoparticles were prepared using ion gelation method, and their physicochemical characteristics were investigated. The anti-gonococcal and antibiofilm activity of prepared NPs was assessed, and their cytotoxicity in human ovarian cells was evaluated. All prepared NPs were optimized for the smallest particle size of 136.9 to 168.3 nm. The EE% of C7-3, C7-3m1, and C7-3m2 CNPs reached 90.2, 92.5, and 91.8%, respectively. An in vitro release study demonstrated a continuous sustained-release pattern of C7-3 peptide from NPs. The SDS-PAGE assay confirmed the integrity of C7-3 peptide after the fabrication process. When comparing each peptide alone, the generated NPs demonstrated higher anti-gonococcal and anti-biofilm effectiveness against standard and resistant bacterial strains under anaerobic conditions. The cytotoxicity experiments revealed the cytocompatibility of NPs in HeLa cell lines. Given the advantages of enhanced anti-gonococcal activity of the C7-3 peptide and its derivatives when loaded with CNPs, as well as the antimicrobial properties of chitosan NPs, the reported NPs have great potential in the treatment of gonococcal infection.

Alpha-1-Antitrypsin (A1AT) Proteotyping by LC-MS/MS.

The diagnosis of alpha-1-antitrypsin (A1AT) deficiency is established by quantitation of protein concentration in serum (immunoassay) followed by determination of specific allelic variants by phenotyping (isoelectric focusing (IEF) gel electrophoresis) and/or allele-specific genotyping. Various phenotyping and genotyping methodologies are available, and each has their own advantages and disadvantages. As an alternative, mass spectrometry is emerging as a powerful tool in the identification and quantitation of proteins and peptides. The method described here, referred to as proteotyping, is a proteomic method using trypsin digestion and tandem mass spectrometry that detects the most common deficiency alleles, S and Z, associated with A1AT deficiency.This qualitative mass spectrometry method is based on the principle that the S and Z mutations lead to amino acid changes which result in a change in the mass of the A1AT protein. When the A1AT protein is proteolytically digested, multiple peptides are generated, two of which include the sites of the S and Z mutations, respectively. Peptides generated from wild-type A1AT (M alleles) differ in sequence and mass from peptides generated from the S and Z alleles at these two specific locations. The mass difference allows for differentiation of S and Z peptides, representing the deficiency alleles, from non-S and non-Z peptides, representing the wild-type alleles (M). Interpretation of the peptide patterns in conjunction with A1AT quantitation by immunoassay allows for an accurate assessment for the presence of deficiency alleles in the majority of patients.

Bioinformatics and functional selection of GH77 4-α-glucanotransferases for potato starch modification

4-α-glucanotransferases (4αGTs, EC 2.4.1.25) from glycoside hydrolase family 77 (GH77) catalyze chain elongation of starch amylopectin chains and can be utilized to structurally modify starch to tailor its gelation properties. The potential relationship between the structural design of 4αGTs and functional starch modification is unknown. Here, family GH77 was mined in silico for enzyme candidates based on sub-grouping guided by Conserved Unique Peptide Patterns (CUPP) bioinformatics categorization. From + 12,000 protein sequences a representative set of 27 4αGTs, representing four different domain architectures, different bacterial origins and diverse CUPP groups, was selected for heterologous expression and further study. Most of the enzymes catalyzed starch modification, but their efficacies varied substantially. Five of the 4αGTs were characterized in detail, and their action was compared to that of the industrial benchmark enzyme, Tt4αGT (CUPP 77_1.2), from Thermus thermophilus. Reaction optima of the five 4αGTs ranged from ∼40–60 °C and pH 7.3–9.0. Several were stable for a minimum 4 h at 70 °C. Domain architecture type A proteins, consisting only of a catalytic domain, had high thermal stability and high starch modification ability. All five novel 4αGTs (and Tt4αGT) induced enhanced gelling of potato starch. One, At4αGT from Azospirillum thermophilum (CUPP 77_2.4), displayed distinct starch modifying abilities, whereas T24αGT from Thermus sp. 2.9 (CUPP 77_1.2) modified the starch similarly to Tt4αGT, but slightly more effectively. T24αGT and At4αGT are thus interesting candidates for industrial starch modification. A model is proposed to explain the link between the 4αGT induced molecular modifications and macroscopic starch gelation.

IMBAS-MS Discovers Organ-Specific HLA Peptide Patterns in Plasma

Distinction of non-self from self is the major task of the immune system. Immunopeptidomics studies the peptide repertoire presented by the human leukocyte antigen (HLA) protein, usually on tissues. However, HLA peptides are also bound to plasma soluble HLA (sHLA), but little is known about their origin and potential for biomarker discovery in this readily available biofluid. Currently, immunopeptidomics is hampered by complex workflows and limited sensitivity, typically requiring several mL of plasma. Here, we take advantage of recent improvements in the throughput and sensitivity of mass spectrometry (MS)-based proteomics to develop a highly sensitive, automated, and economical workflow for HLA peptide analysis, termed Immunopeptidomics by Biotinylated Antibodies and Streptavidin (IMBAS). IMBAS-MS quantifies more than 5000 HLA class I peptides from only 200μl of plasma, in just 30min. Our technology revealed that the plasma immunopeptidome of healthy donors is remarkably stable throughout the year and strongly correlated between individuals with overlapping HLA types. Immunopeptides originating from diverse tissues, including the brain, are proportionately represented. We conclude that sHLAs are a promising avenue for immunology and potentially for precision oncology.

Novel synergistic cross-linking ameliorate ready-to-eat sea cucumber deterioration and its quantum chemical analysis

Synergistic cross-linkers could improve the taste acceptability of ready-to-eat sea cucumber (RSC). Besides, the hardness of RSC was increased by 331.00% and 266.87% after synergistic cross-linking. Synergistic cross-linking treatment could ameliorate the non-enzymatic degradation of RSC collagen and polysaccharides. Gaussian calculations results showed that dipeptides containing asparagine residues may have different reaction pathways. The main cleavage pathways of CH3CO-Asn-Gly-NHCH3 (NG) might be water-assisted side chain cyclization, stepwise cyclamide hydrolysis via a Gemdiol Intermediate, deamination, and peptide bond breakage. The relative free energy of cyclamide hydrolysis process of NG was increased by 8.2 kcal/mol after synergistic cross-linking. The mass spectrometry results showed that typical peptides could cleavage at NG, CH3CO-Asn-Lys-NHCH3 (NK) and CH3CO-Asn-Leu-NHCH3 (NL) sites after heating, which justified the breakage pattern of peptides in Gaussian calculations. It can offer a comprehensive theoretical basis for the processing of the ready-to-eat sea cucumber with storage stability.