Peptide Ions Research Articles

Evaluating the capability of soybean peptides as calcium ion carriers: a study through sequence analysis and molecular dynamics simulations.

Calcium homeostasis imbalance in the body can lead to a variety of chronic diseases. Supplement efficiency is essential. Peptide calcium chelate, a fourth-generation calcium supplement, offers easy absorption and minimal side effects. Its effectiveness relies on peptide's calcium binding capacity. However, research on amino acid sequences in peptides with high calcium binding capacity (HCBC) is limited, affecting the efficient identification of such peptides. This study used soybean peptides (SP), separated and purified by gel chromatography, to obtain HCBC peptide (137.45 μg mg-1) and normal peptide (≤95.78 μg mg-1). Mass spectrometry identified the sequences of these peptides, and an analysis of the positional distribution of characteristic amino acids followed. Two HCBC peptides with sequences GGDLVS (271.55 μg mg-1) and YEGVIL (272.54 μg mg-1) were discovered. Molecular dynamics showed that when either aspartic acid is located near the N-terminal's middle, or glutamic acid is near the end, or in cases of continuous Asp or Glu, the binding speed, probability, and strength between the peptide and calcium ions are superior compared to those at other locations. The study's goal was to clarify how the positions of characteristic amino acids in peptides affect calcium binding, aiding in developing peptide calcium chelates as a novel calcium supplement.

Prediction of Peptide Ion Distribution in Positive Electrospray Ionization

We have investigated the possibility of predicting the distribution of ions of different charge during electrospray ionization of peptides in mass spectrometric experiments using neural networks. Three independent data sets obtained on the same equipment and deposited in ProteomeXchange (PXD032141, PXD051750, PXD019263) were used as training and test samples. A set of fractional values for 1+ to 5+ ions was calculated as predicted values for each of the newly identified peptides. Four different sets of peptide descriptions were used as independent variables, including both the spectrum of amino acid residues and the physicochemical properties of the amino acid residues. Sixty-four variants of neural networks were analyzed, varying the input description, number and type of layers, activation and loss functions. The coefficient of determination and a set of Euclidean, Sørensen, Chebyshev, and Cosine metrics were considered as measures of prediction quality. For the best selected variants, the error did not exceed 10% in 80% of the cases. This accuracy may be sufficient for a preliminary estimation of the probability of detecting a peptide ion of a given charge.

Characterization of the Oxazolone and Macrocyclic Motifs in the bn (n = 2-5) Product Ions from Collision-Induced Dissociation of Protonated Oligoglycine Peptides with Isomer-Selective, Cryogenic Vibrational Spectroscopy.

Collision-induced dissociation (CID) of small, protonated peptides leads to the formation of b-type fragment ions that can occur with several structural motifs driven by different covalent intramolecular bonding arrangements. Here, we characterize the so-called "oxazolone" and "macrocycle" bn ion structures that occur upon CID of oligoglycine peptides (Gn) ions (n = 2-6). This is determined by acquiring the vibrational band patterns of the cryogenically cooled, D2-tagged bn ions obtained using isomer-selective, two-color IR-IR photobleaching and analyzing them with predicted (DFT) harmonic spectra for the candidate structures. Both oxazolone and macrocyclic isomers are formed by b4, whereas only oxazolone species are created for b2 and b3 and the macrocycle is created for b5. As such, n = 4 corresponds to the minimum size where both Oxa and MC forms are present.

Peptide collision cross sections of 22 post-translational modifications

Recent advances have rekindled the interest in ion mobility as an additional dimension of separation in mass spectrometry (MS)-based proteomics. Ion mobility separates ions according to their size and shape in the gas phase. Here, we set out to investigate the effect of 22 different post-translational modifications (PTMs) on the collision cross section (CCS) of peptides. In total, we analyzed ~4300 pairs of matching modified and unmodified peptide ion species by trapped ion mobility spectrometry (TIMS). Linear alignment based on spike-in reference peptides resulted in highly reproducible CCS values with a median coefficient of variation of 0.26%. On a global level, we observed a redistribution in the m/z vs. ion mobility space for modified peptides upon changes in their charge state. Pairwise comparison between modified and unmodified peptides of the same charge state revealed median shifts in CCS between −1.4% (arginine citrullination) and +4.5% (O-GlcNAcylation). In general, increasing modified peptide masses were correlated with higher CCS values, in particular within homologous PTM series. However, investigating the ion populations in more detail, we found that the change in CCS can vary substantially for a given PTM and is partially correlated with the gas phase structure of its unmodified counterpart. In conclusion, our study shows PTM- and sequence-specific effects on the cross section of peptides, which could be further leveraged for proteome-wide PTM analysis.Graphical

Ionmob: a Python package for prediction of peptide collisional cross-section values.

Including ion mobility separation (IMS) into mass spectrometry proteomics experiments is useful to improve coverage and throughput. Many IMS devices enable linking experimentally derived mobility of an ion to its collisional cross-section (CCS), a highly reproducible physicochemical property dependent on the ion's mass, charge and conformation in the gas phase. Thus, known peptide ion mobilities can be used to tailor acquisition methods or to refine database search results. The large space of potential peptide sequences, driven also by posttranslational modifications of amino acids, motivates an in silico predictor for peptide CCS. Recent studies explored the general performance of varying machine-learning techniques, however, the workflow engineering part was of secondary importance. For the sake of applicability, such a tool should be generic, data driven, and offer the possibility to be easily adapted to individual workflows for experimental design and data processing. We created ionmob, a Python-based framework for data preparation, training, and prediction of collisional cross-section values of peptides. It is easily customizable and includes a set of pretrained, ready-to-use models and preprocessing routines for training and inference. Using a set of ≈21 000 unique phosphorylated peptides and ≈17 000 MHC ligand sequences and charge state pairs, we expand upon the space of peptides that can be integrated into CCS prediction. Lastly, we investigate the applicability of in silico predicted CCS to increase confidence in identified peptides by applying methods of re-scoring and demonstrate that predicted CCS values complement existing predictors for that task. The Python package is available at github: https://github.com/theGreatHerrLebert/ionmob.

Efficient Synergistic Cooperation of an Arginine-Rich Peptide and Copper Ions in Sodium Urate Crystallization Inhibition.

Although many studies have focused on the role of individual biomolecules or metal ions in the crystallization behavior of sodium urate, the regulatory effects of multiple molecular species still remain mysterious. The synergistic cooperation of biomolecules and metal ions may contribute to unprecedented regulatory effects. Here, the cooperative effect of arginine-rich peptides (APs) and copper ions on the phase behavior, crystallization kinetics, and size/morphology of urate crystals was first investigated. Compared with the individual copper ion and AP, the nucleation induction time of sodium urate is prolonged dramatically (about 48 h), and the nucleation rate of sodium urate is reduced efficiently in a saturated solution due to the synergistic effect of Cu2+ and AP in stabilizing amorphous sodium urate (ASU). The length of sodium urate monohydrate crystals decreases obviously under the synergistic effect of Cu2+ and AP. The comparative experiments of common transition metal cations show that only copper ions can cooperate with AP, which may be due to the strong coordination effect between copper ions with urate and AP. Further studies show that the synergistic effect of copper ions and APs with different chain lengths on the crystallization behavior of sodium urate is significantly different. Both the guanidine functional groups and the length of peptide chains simultaneously determine the synergistic inhibition effect of polypeptides and Cu2+. This work highlights the synergistic inhibition effect of metal ions and cationic peptides on the crystallization of sodium urate, which enriches the understanding of the regulating mechanism of biological mineral crystallization using the synergy of multispecies and offers a new strategy for designing efficient inhibitors for sodium urate crystallization in gout stone diseases.

Fast proteomics with dia-PASEF and analytical flow-rate chromatography.

Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs, and facilitate new approaches in systems biology and biomedical research. Here we propose combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition, and data analysis with the DIA-NN software suite, to achieve high-quality proteomic experiments from limited sample amounts, at a throughput of up to 400 samples per day. For instance, when benchmarking our workflow using a 500-μL/min flow rate and 3-min chromatographic gradients, we report the quantification of 5211 proteins from 2μg of a mammalian cell-line standard at high quantitative accuracy and precision. We further used this platform to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-min chromatographic gradient and alternating column regeneration on a dual pump system. The method delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates.

Nutritional, biological, and structural properties of bioactive peptides from bellflower, Persian-willow, and bitter-orange pollens.

In this study, the composition of amino acids, nutritional characteristics, degree of hydrolysis (DH), antioxidant properties, and antibacterial activity of proteins and hydrolysates of bellflower (Campanula latifolia), Persian willow (Salix aegyptiaca), and bitter orange (Citrus aurantium L.) were investigated under the influence of different proteases (Alcalase: Al, trypsin: Tr, pancreatin: Pa, and pepsin: Pe). Evaluation of the structural features of the proteins showed amide regions (amide A, B, I-III) and secondary structures. Hydrophobic amino acids (∼38%), antioxidants (∼21%), and essential types (∼46%) form a significant part of the structure of flower pollen. The digestibility and nutritional quality (PER) of the hydrolyzed samples (CP: 1.67; CA: 1.89, and PW: 1.93) were more than the original protein. Among proteins and peptides, the highest degree of hydrolysis (34.6%: Al-PWH), inhibition of free radicals DPPH (84.2%: Al-CPH), ABTS (95.2%: Pa-CPH), OH (86.7%: Tr-CAH), NO (57.8%: Al-CPH), reducing power (1.31: Pa-CPH), total antioxidant activity (1.46: Pa-CPH), and chelation of iron ions (80%: Al-CPH and Al-CAH) and copper (50.3%: Pa-CAH) were affected by protein type, enzyme type, and amino acid composition. Also, the highest inhibition of the growth of Escherichia coli (25 mm) and Bacillus cereus (24 mm) were related to CP and PW hydrolysates, respectively. The results of this research showed that hydrolyzed flower pollens can be used as a rich source of essential amino acids as well as natural antioxidants and antibacterial in food and dietary products. PRACTICAL APPLICATION: Enzymatic hydrolysis of Campanula latifolia, Persian willow, and Citrus aurantium pollen proteins was performed. The hydrolyzed ones had high nutritional quality and digestibility (essential amino acids and PER index). Antioxidant properties and chelation of metal ions of peptides were affected by the type of protein and enzyme. The hydrolysates showed inhibitory activity against the growth of Esherichia coli and Bacillus cereus.

Thermochemical Study of the Interaction of Cytosine and Uracil with Peptides in a Buffered Saline: Complex Formation with beta-Endorphin 30-31 (Human), L-Glutathion (Reduced) and α-L-Alanyl-L-Tyrosine.

The complex formation of uracil and cytosine with glycyl-L-glutamic acid (β-endorphin 30-31), γ-L-glutamyl-L-cysteinyl-glycine (glutathione reduced), α-L-alanyl-L-tyrosine, and α-L-alanyl-α-L-alanine in a buffered saline has been studied using dissolution calorimetry. The values of the reaction constant, the change in Gibbs energy, enthalpy, and entropy were obtained. It is shown that the ratio of the enthalpy and entropy factors depends on the charge of the peptide ion, and the number of H-bond acceptors in the peptide structure. The contributions of interaction between charged groups and polar fragments, hydrogen bonding, and stacking interaction are discussed, taking into account the effect of solvent reorganization around the reactant molecules.

Lighting Up at High Potential: Effects of Voltage and Emitter Size in Nanoelectrospray Ionization.

Effects of electrospray voltage on cluster size and abundance formed from aqueous CsI were investigated with emitter tip diameters between 260 ± 7 nm and 2.45 ± 0.30 μm. Cluster size increases with increasing voltage, increasing solution concentration and increasing emitter diameter consistent with formation of larger initial droplet sizes. For emitters with tip diameters above ∼1 μm, varying the voltage either up or down leads to reproducible voltage-dependent extents of cluster formation. In contrast, higher voltages with submicron diameter emitters can lead to only Cs+ and Cs(H2O)+ and no clusters. This change in ion formation reproducibly occurs at spray potentials >1.3 kV for 260 nm emitters and appears to be induced by a corona discharge and material build-up at the emitter tip. Under conditions where abundant Cs+ is observed and no clusters are formed, ions such as K+ and Cu1+ are also observed but ions with more negative solvation energies, such as Ba2+, are not. Similarly, ions from bradykinin and ubiquitin are observed predischarge but not post discharge. Ions with more positive solvation energies can desorb directly from the air-water interface that is created at the tip of these emitters, whereas ions with more negative solvation energies as well as peptide and protein ions do not. These results indicate that ion desorption directly from solution can occur, and similar experiments with even smaller emitters may lead to new insights into ion formation in electrospray ionization.

Characterization of the natural peptidome of four leeches by integrated proteogenomics and pseudotargeted peptidomics

Animal-derived drugs are an indispensable part of folk medicine worldwide. However, their chemical constituents are poorly approached, which leads to the low level of the quality standard system of animal-derived drugs and further causes a chaotic market. Natural peptides are ubiquitous throughout the organism, especially in animal-derived drugs. Thus, in this study, we used multi-source leeches, including Hirudo nipponica (HN), Whitmania pigra (WP), Whitmania acranulata (WA), and Poecilobdella manillensis (PM), as a model. A strategy integrating proteogenomics and novel pseudotargeted peptidomics was developed to characterize the natural peptide phenotype and screen for signature peptides of four leech species. First, natural peptides were sequenced against an in-house annotated protein database of closely related species constructed from RNA-seq data from the Sequence Read Archive (SRA) website, which is an open-sourced public archive resource. Second, a novel pseudotargeted peptidomics integrating peptide ion pair extraction and retention time transfer was established to achieve high coverage and quantitative accuracy of the natural peptides and to screen for signature peptides for species authentication. In all, 2323 natural peptides were identified from four leech species whose databases were poorly annotated. The strategy was shown to significantly improve peptide identification. In addition, 36 of 167 differential peptides screened by pseudotargeted proteomics were identified, and about one-third of them came from the leucine-rich repeat domain (LRR) proteins, which are widely distributed in organisms. Furthermore, six signature peptides were screened with good specificity and stability, and four of them were validated by synthetic standards. Finally, a dynamic multiple reaction monitoring (dMRM) method based on these signature peptides was established and revealed that one-half of the commercial samples and all of the Tongxinluo capsules were derived from WP. All in all, the strategy developed in this study was effective for natural peptide characterization and signature peptide screening, which could also be applied to other animal-derived drugs, especially for modelless species that are less studied in protein database annotation.

Intact Transition Epitope Mapping—Serological Inspection by Epitope EXtraction (ITEM—SIX)

Precision medicine requests accurate serological inspections to precisely stratify patients for targeted treatment. Intact transition epitope mapping analysis proved surrogate seroconversion of a model organism's serum when spiked with a monoclonal murine anti-Ovalbumin antibody (mAb) with epitope resolution. Isolation of the IgG fraction from blood serum applied two consecutive protein precipitation steps followed by ultrafiltration and resulted in an ESI-MS analysis-ready IgG preparation. For epitope mapping by epitope extraction, the Ovalbumin antigen was digested with trypsin. After desalting, the peptide mixture was added to the ESI-MS-ready IgG preparation from mAb-spiked serum and the solution was incubated to form an immune complex between the Ovalbumin-derived epitope peptide and the anti-Ovalbumin mAb. Then, the entire mixture of proteins and peptides was directly electrosprayed. Sorting of ions in the mass spectrometer's gas phase, dissociation of the immune complex ions by collision-induced dissociation, and recording of the epitope peptide ion that had been released from the immune complex proved the presence of the anti-Ovalbumin mAb in serum. Mass determination of the complex-released epitope peptide ion with isotope resolution is highly accurate, guaranteeing high specificity of this novel analysis approach, which is termed Intact Transition Epitope Mapping-Serological Inspections by Epitope EXtraction (ITEM-SIX).

Carbene Cross-Linking in Gas-Phase Peptide Ion Scaffolds.

Scaffolds consisting of a peptide, a phthalate linker, and a 4,4-azipentyl group were synthesized and used to study intramolecular peptide-carbene cross-linking in gas-phase cations. Carbene intermediates were generated by UV-laser photodissociation at 355 nm of the diazirine ring in mass-selected ions, and the cross-linked products were detected and quantified by collision-induced dissociation tandem mass spectrometry (CID-MSn, n = 3-5). Peptide scaffolds containing Ala and Leu residues with a C-terminal Gly gave 21-26% yields of cross-linked products, while the presence of the Pro and His residues decreased the yields. Experiments using hydrogen-deuterium-hydrogen exchange, carboxyl group blocking, and analysis of CID-MSn spectra of reference synthetic products revealed that a significant fraction of cross-links involved the Gly amide and carboxyl groups. Interpretation of the cross-linking results was aided by Born-Oppenheimer molecular dynamics (BOMD) and density functional theory calculations that allowed us to establish the protonation sites and conformations of the precursor ions. Analysis of long (100 ps) BOMD trajectories was used to count close contacts between the incipient carbene and peptide atoms, and the counting statistics was correlated with the results of gas-phase cross-linking.

Improved Performance of Positive-Ion Mode Free Radical-Initiated Peptide Sequencing with p-TEMPO-Bz.

Free radical-initiated peptide sequencing (FRIPS) is a tandem mass spectrometry technique that generates sequence informative ions via collisionally initiated radical chemistry. Collision activation homolytically cleaves an installed radical precursor and initiates radical formation, extensive hydrogen atom transfer, and peptide backbone dissociation. While the FRIPS technique shows great promise, when applied to multiply charged derivatized peptide ions, a series of high-abundance mass losses are observed which siphon ion abundance from radically generated sequence ions. This loss of ion abundance reduces the sequence coverage generated by FRIPS fragmentation. In this work, we hypothesized that these mass losses were assisted by the ortho-orientation of the radical precursor undergoing facile conversion into five- or six-membered intermediates or products and that when combined with the lower bond dissociation energy of the para-precursor, conjugated peptides would not undergo this chemistry. To test this assertion, we synthesized p-TEMPO-Bz, conjugated it to these peptides, and collisionally activated each. Indeed, we see dramatic attenuation of these undesired collisional processes and a significant increase in radical precursor ion abundance. The increase in ion abundance leads to a significant increase in the sequence coverage generated. These results demonstrate that p-TEMPO-Bz significantly improves the performance of positive-ion mode FRIPS and may be a compelling alternative to the currently utilized o-TEMPO-Bz-based FRIPS.

Analysis and identification of suspected snake venom samples using nano-ultra-high performance liquid chromatography-high resolution mass spectrometry

Snake venom is a complex mixture secreted from the glands of poisonous snakes， which contains proteins， peptides， lipids， nucleosides， sugars， amino acids， amines， metal ions， and other components. According to the toxicological classification， snake venoms can be classified as neurotoxins， anticoagulants and procoagulant toxins， cardiac toxins， other toxin proteins， and enzymes. Proteins and peptides are the key components of snake venom. The establishment of rapid， accurate analysis and identification methods for proteins in snake venom is a prerequisite for snake venom-related forensic identification， intoxication events， and pharmaceutical development. Until now， the classical analysis and identification methods have mainly been biochemical or immunoassays for DNA or proteins， such as polymerase chain reaction， agglutination test， enzyme-linked immunosorbent assay， fluorescent immunoassay， and various biosensing approaches. These methods have some limitations such as a high false-positive ratio， low sensitivity， poor anti-interference ability， and limited species discrimination capability. In recent years， with the rapid development of mass spectrometry （MS） techniques， the proteomics of snake venom has also attracted much attention and has contributed to the identification of snake species， in which non-targeted and targeted proteomics represent two main divisions. However， species identification via proteomics is in its infancy in forensic science. First， the tandem MS spectra of peptide sequences are highly complex， which poses a great challenge for the strict and accurate matching of peptides based on the rational speculation of MS fragmentation rules and theoretical calculations in non-targeted proteomics. Second， for the confirmation and identification of unknown substances， reference substances are commonly needed， but those for snake venom are lacking. Proteomics in snake venom identification is still in progress to improve the identification confidence and clarify the identification rules. In this work， a method based on nano-ultra-high performance liquid chromatography-quadrupole-orbitrap high-resolution mass spectrometry （Nano LC-MS/HRMS） and size exclusion chromatography （SEC） was developed for identifying proteins and their source species， with strict rules for five suspected snake venom samples and their contamination in one case. Three SEC elution peaks were obtained from each of the five samples， which were lyophilized and treated with trypsin in solution， and then separated and analyzed by Nano LC-MS/HRMS. First， the Full MS/dd MS2 mode was used for the non-targeted acquisition of peptide information in the samples， and after submission to the Swiss-Prot database， the protein databases of Serpentes， Colubroidea， Elapidae， Elapinae， and Naja were contracted stepwise and compared. A total of 32 proteins from Naja atra were identified under the conditions of both peptide spectrum match and false discovery rate less than 1%， and number of characteristic peptides greater than or equal to two. All of these were derived from ten families of Naja atra， mainly three-finger toxins， metalloproteinases， and phospholipase A2. Proteins D3TTC2， D5LMJ3， Q7T1K6， Q9DEQ3， and Q9YGI4 were the most common among the five samples. Finally， the parallel reaction monitoring mode was adopted to select two unique peptides for each protein for targeted verification. It was considered that a protein in the samples was truly identified when it met the strict standard "the Δm/z of at least 75% y+ and b+ ions of each unique peptide was less than 5 ppm". After these consequently procedures， we identified that all five samples contained the venom of the Naja atra. Our identification method is a systematic and strict example that can provide effective technical support for the forensic identification of snake venom poisoning， as well as for pharmaceutical development toward snake venoms.

Characterization of Phosphorylation-Dependent Antibody Binding to Cancer-Mutated Linkers of C2H2 Zinc Finger Proteins by Intact Transition Epitope Mapping-Thermodynamic Weak-Force Order Analysis.

With Intact Transition Epitope Mapping-Thermodynamic Weak-force Order (ITEM-TWO) analysis in combination with molecular modeling, the phosphorylation-dependent molecular recognition motif of the anti-HpTGEKP antibody has been investigated with binary and ternary component mixtures consisting of antibody and (phospho-) peptides. Amino acid sequences have been selected to match either the antibody's recognition motif or the cancer-related zinc finger protein mutations and phosphorylations of the respective amino acid residues. Upon electrospraying of all the components of the mixtures, that is, hexapeptides, antibody, and intact immune complexes, the produced ions were subjected to mass spectrometric mass filtering. The antibody ions as well as the immune complex ions traversed into the mass spectrometer's collision chamber, whereas paths of unbound peptide ions were blocked prior to entering the collision cell. After dissociation of the multiply charged immune complexes in the gas phase, the complex-released peptide ions were recorded after having traversed the second mass filter. Complex-released peptides were unambiguously identified by their masses using mass analysis with isotope resolution. From the results of our studies with seven (phospho-) peptides with distinct amino acid sequences, which resembled either the antibody's binding motif or mutations, we conclude the following: (i) A negatively charged phospho group, located near the peptide's N-terminus is mandatory for antibody binding when placed on the peptide surface at a precise distance to the C-terminally located positively charged ε-amino group of a lysinyl residue. (ii) A bulky amino acid residue, such as the tyrosinyl residue at the N-terminal position of the (phospho-) threoninyl residue, abolishes antibody binding. (iii) Two closely spaced phospho groups negatively interfere with the surface polarity pattern and abolish antibody binding as well. (iv) Non-phosphorylated peptides are not binding partners of the anti-HpTGEKP antibody.

Nile blue as reporter dye in salt aggregation based-colorimetric aptasensors for peptide, small molecule and metal ion detection

Herein, we report a novel approach for the design of a colorimetric aptasensor, relying on a Dye Salt Aggregation-based Colorimetric Oligonucleotide assay (DYSACO assay). This method is based on the use of an intercalating agent, Nile Blue (NB), whose aggregation capacities (and thus modification of its absorption spectrum) are drastically amplified by adding salts to the working solution. The presence of an aptamer could protect NB from such aggregation process due to its intercalation into double-stranded DNA and/or interaction with nucleobases. In response to the addition of the specific ligand, the competition between NB and the target for binding to the aptamer occurs, resulting in an increase in the dye salt aggregation and then in the blue-to-blank color change of the solution. The proof-of-principle was demonstrated by employing the anti-l-tyrosinamide aptamer and the assay was successfully applied to the trace enantiomer detection, allowing the detection of an enantiomeric impurity down to approximately 2% in a non-racemic sample. Through a reversed mechanism based on the increased capture of NB by DNA upon analyte binding, the sensing platform was further demonstrated for the Hg(II) detection. Water samples of different origin were spiked with Hg(II) analyte at final range concentrations comprised between (0.5–15 μM). An excellent overall recovery of 122 ± 14%; 105 ± 14%; 99 ± 9%; was respectively obtained from river, tap and mineral water, suggesting that the sensor can be used under real sample conditions. The assay was also shown to work for sensing the ochratoxin A and d-arginine vasopressin compounds, revealing its simplicity and generalizability potentialities.

A stimuli-responsive polymer modified nanopore for measuring β-amyloid peptide and zinc ions in brains of live mice with Alzheimer's disease

A copolymer-modified glass nanopore combined with microdialysis was used for assaying cerebral Aβ monomer and Zn2+. In the presence of Aβ monomer, the copolymer stretched. Then, the Zn2+ altered surface charges and fluorescence.

The Effect and the Mechanism of miR-209 Targeted Regulating PI3K (Phosphatidylinositol3-Kinase)/AKT (Protein Kinase B)/FOXO3a (Forkhead box O3) Signaling Pathway on Glioma Stem Cells

To explore the role and mechanism of miR-209 target regulating PI3K/Akt/FOXO3a in glioma. GSCs were isolated from the lesions of glioma patients, cultured, passaged and characterized. Set blank control group (with saline solution), miR-209-mimics group (cells transfected with miR-209-mimics) and negative control group (cells transfected with meaningless sequences). After cell transfection, observe the transfection efficiency of miR-209 MIC, detect the miR-209 mRNA expression level and biological peptide ions such as proliferation, migration, invasion, and withering, and detect the expression of PI3K/Akt/FOXO3a-related proteins (PI3K, p-Akt, FOXO3a). The miR-209mRNA expression level in the miR-209 mimics group was much higher (P < 0.01), and they two had indifferent differentiation (P >0.05); 24, 48 and 72 hours after transfection, the cell migration, proliferation rate and invasion ability of the miR-209 mimics group were much stronger (P <0.05) and the cell apoptosis rate at 24, 48, and 72 hours after transfection was much less (P < 0.01) and they two had no scientific differences (P > 0.05). The PI3K and p-Akt protein expression in the glioma stem elements of the miR-209 transfected group was much higher (P <0.01). The expression of FOXO3a was much less (P <0.01), while the standard level of PI3K, P-Akt and FOXO3a protein had no obvious difference (P >0.05). miR-209 can activate PI3K/Akt/FOXO3a to promote the growth, reproduction and invasion of GSCs, and control the cells withering system. This will provide new avenues for clinical trials.

Application of a Novel Hybrid CNN-GNN for Peptide Ion Encoding.

Almost all state-of-the-art de novo peptide sequencing algorithms now use machine learning models to encode fragment peaks and hence identify amino acids in mass spectrometry (MS) spectra. Previous work has highlighted how the inherent MS challenges of noise and missing peptide peaks detrimentally affect the performance of these models. In the present research we extracted and evaluated the encoding modules from 3 state-of-the-art de novo peptide sequencing algorithms. We also propose a convolutional neural network-graph neural network machine learning model for encoding peptide ions in tandem MS spectra. We compared the proposed encoding module to those used in the state-of-the-art de novo peptide sequencing algorithms by assessing their ability to identify b-ions and y-ions in MS spectra. This included a comprehensive evaluation in both real and artificial data across various levels of noise and missing peptide peaks. The proposed model performed best across all data sets using two different metrics (area under the receiver operating characteristic curve (AUC) and average precision). The work also highlighted the effect of including additional features such as intensity rank in these encoding modules as well as issues with using the AUC as a metric. This work is of significance to those designing future de novo peptide identification algorithms as it is the first step toward a new approach.