Search

The transport of biopolymers across nanopores is an important biological process currently under investigation for the rapid analysis of DNA and proteins. While the transport of DNA is generally understood, methods to induce unfolded protein translocation have only recently been discovered (Yu et al., 2023, Sauciuc et al., 2023). Here, we found that during electroosmotically driven translocation of polypeptides, blob-like structures typically form inside nanopores, often obstructing their transport and preventing addressing individual amino acids. This is in contrast with the electrophoretic transport of DNA, where the formation of such structures has not been reported. Comparisons between different nanopore sizes and shapes and modifications by different surface chemistries allowed formulating a mechanism for blob formation. We also show that single-file transport can be achieved by using 1) nanopores that have an entry and an internal diameter smaller than the persistence length of the polymer, 2) nanopores with a nonsticky (i.e., nonaromatic) inner surface, and 3) moderate translocation velocities. These experiments provide a basis for understanding polypeptide transport under confinement and for improving the design and engineering of nanopores for protein analysis. [ABSTRACT FROM AUTHOR]

Over the past century, the field of antibody discovery has undergone significant evolution, excluding the current exploration stage of artificial intelligence‐based antibody generation and the often overlooked non‐animal sourced antibody discovery, which typically requires mature in vitro affinity and the selection of high‐quality antigen formulations. This journey has traversed various stages, from methods involving serum‐based antibody acquisition, the isolation of B cells capable of perpetual antibody production through hybridoma technology, to the in‐depth exploration of genetic material using the phage display system, and the current stage involving diverse single B cell screening techniques. Additionally, the emergence of machine learning has brought impressive scientific and technological breakthroughs across research domains, proving to be a powerful application in the field of antibody discovery. However, each technique comes with its limitations, such as variability and control challenges in serum‐based acquisition, lengthy and difficult hybridoma‐derived antibody development, potential limitations in sequence and epitope diversity due to immunization biases in phage display techniques, and costly single B cell screening. Protein mass spectrometry sequencing, with shorter acquisition time and lower costs, is seen as a shortcut by diagnostic companies, impacting traditional antibody development. In diagnostic antibody development, methodological differences in downstream assays and the impact of constant regions outside the Fv core are often neglected. This paper deeply analyzes challenges, proposing innovative strategies for the next generation of diagnostic antibody development. Aimed at moving closer to the gold standard of antibody discovery, these strategies enhance the competitiveness of diagnostic reagent products. [ABSTRACT FROM AUTHOR]

In recent decades, there has been a significant increase in the application of single‐molecule electrical analysis platforms in studying proteins and peptides. These advanced analysis methods have the potential for deep investigation of enzymatic working mechanisms and accurate monitoring of dynamic changes in protein configurations, which are often challenging to achieve in ensemble measurements. In this work, the prominent research progress in peptide and protein‐related studies are surveyed using electronic devices with single‐molecule/single‐event sensitivity, including single‐molecule junctions, single‐molecule field‐effect transistors, and nanopores. In particular, the successful commercial application of nanopores in DNA sequencing has made it one of the most promising techniques in protein sequencing at the single‐molecule level. From single peptides to protein complexes, the correlation between their electrical characteristics, structures, and biological functions is gradually being established. This enables to distinguish different molecular configurations of these biomacromolecules through real‐time electrical monitoring of their life activities, significantly improving the understanding of the mechanisms underlying various life processes. [ABSTRACT FROM AUTHOR]

Tomato is one of the most cultivated and highly consumed crops globally, often hampered by a soil borne fungal pathogen Fusarium oxysporum f. sp. lycopersici causing vascular wilt. Pathogenic proteins like formyl peptide receptor 1, mitogen-activated protein kinase encoding, class V chitin synthase and tomatinase have been investigated in this study using molecular modeling, docking and dynamics-based techniques as potential molecular targets during pathogenesis or defence response. Thus, MODELLER 9.16 was used to predict three dimensional structures of the above proteins further refined and minimized. To get the new and dominant lead molecule, Trichoderma secondary metabolites were extracted from Trichoderma biomass isolated from healthy rhizospheric soil from an infected wilt field. The crude ethyl acetate extracts were purified and analyzed by gas chromatography-mass spectrometric analysis followed by in silico and in vitro analysis. Eventually, 85 compounds were selected in the first phase selection criteria for docking and it was found that molecule 1-allyl-4-[(3,4-dimethoxy-phenyl)-(1-thiophen-2-ylmethyl-1H-tetrazol-5-yl)-methyl]-piperazine and p-dihydroartemisinin oxymethyl benzoic acid were showed highest binding affinity towards Fusarium proteins as their binding energy fall in range of between -7.64 to -8.76 Kcal/mol. To increase the efficiency of molecules the five derivatives were designed and based upon the docking results, three potential derivates undergone for molecular dynamic studies over 100 ns against pathogenic proteins. Thus, aiding future development of the designed potent derivatives can be explored for experimental validation against the Fusarium pathogenic proteins to complement the current management techniques. This improvised new strain of Trichoderma species would assist in controlling disease effectively, especially against soil-borne pathogens. [ABSTRACT FROM AUTHOR]

BackgroundMuscle is an important tissue of the human body. Muscle atrophy is common in people of all ages, which will lead to human weakness and decline of motor function, which is one of the important causes of disability. The common methods of genomics research are transcriptome, proteomics and metabolomics, which are important means to explore the molecular pathology of diseases. In recent years, combinatorial research has been carried out on a large scale in the field of muscle atrophy. However, no author in this field has carried out bibliometrics and visual analysis.MethodsIn this study, articles related to the histological study of muscular dystrophy since 2000 were searched from the Web of Science core database (WoSCC). We will retrieve the results through CiteSpace, VosViewer and R for data statistics and visual analysis.ResultsIn this study, a total of 141 publications were collected, and the number of publications increased year by year. These 141 articles came from 1031 co-authors from 361 institutions in 31 countries and were published in 92 journals. A total of 6286 articles from 1383 journals were cited. Authors from American institutions have published the most articles and have been cited the most, and authors from other countries have also made considerable contributions.ConclusionThis is the first bibliometric and visual analysis of published research in the field of muscular dystrophy through systematic data retrieval and combined with a variety of bibliometric analysis tools. Through these data, we summarize the previous studies of scholars, and provide prospects for future research in the field.

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions. However, proteins are usually folded in their native state and the mechanism of fast protein conformation transitions still remains unclear, which make protein sequencing challenging. Molecular dynamics simulations with accurate force field are now able to observe the entire folding/unfolding process, providing valuable insights into protein folding mechanisms. Given that proteins can be unfolded, nanopore technology shows great potential for protein sequencing. In this study, we proposed to use MoS2/SnS2 heterostructures to firstly unfold proteins and then detect them by a nanopore in the heterostructural membrane. All-atom molecular dynamics simulations performed in this work provided rich atomic-level information for a comprehensive understanding of protein unfolding process and mechanism on the MoS2/SnS2 heterostructure, it was found that the strong binding of protein to SnS2 nanostripe and hydrogen bond breaking were the main reasons for unfolding the protein on the heterostructure. After the protein was fully unfolded, it was restrained on the nanostripe because of the affinity of protein to the SnS2 nanostripe. Thus by integrating the proposed unfolding technique with nanopore technology, detection of linear unfolded peptide was realized in this work, allowing for the identification of protein components, which is essential for sequencing proteins in the near future. [ABSTRACT FROM AUTHOR]

This article discusses the advancements and challenges in nanopore protein sequencing. While DNA sequencing has been successful, protein sequencing presents unique complexities due to the diverse amino acids and heterogeneous charges in peptides. The article explores two methodologies for nanopore protein sequencing: full-length chain sequencing and enzyme-assisted sequencing. The authors propose a strategy combining enzymatic cleavage and host-guest interaction-assisted nanopore sensing for comprehensive peptide sequencing. The article concludes by highlighting the potential of nanopore protein sequencing in revolutionizing diagnostics and biomedical breakthroughs. [Extracted from the article]

Abstract Over the past century, the field of antibody discovery has undergone significant evolution, excluding the current exploration stage of artificial intelligence‐based antibody generation and the often overlooked non‐animal sourced antibody discovery, which typically requires mature in vitro affinity and the selection of high‐quality antigen formulations. This journey has traversed various stages, from methods involving serum‐based antibody acquisition, the isolation of B cells capable of perpetual antibody production through hybridoma technology, to the in‐depth exploration of genetic material using the phage display system, and the current stage involving diverse single B cell screening techniques. Additionally, the emergence of machine learning has brought impressive scientific and technological breakthroughs across research domains, proving to be a powerful application in the field of antibody discovery. However, each technique comes with its limitations, such as variability and control challenges in serum‐based acquisition, lengthy and difficult hybridoma‐derived antibody development, potential limitations in sequence and epitope diversity due to immunization biases in phage display techniques, and costly single B cell screening. Protein mass spectrometry sequencing, with shorter acquisition time and lower costs, is seen as a shortcut by diagnostic companies, impacting traditional antibody development. In diagnostic antibody development, methodological differences in downstream assays and the impact of constant regions outside the Fv core are often neglected. This paper deeply analyzes challenges, proposing innovative strategies for the next generation of diagnostic antibody development. Aimed at moving closer to the gold standard of antibody discovery, these strategies enhance the competitiveness of diagnostic reagent products.

Abstract In recent decades, there has been a significant increase in the application of single‐molecule electrical analysis platforms in studying proteins and peptides. These advanced analysis methods have the potential for deep investigation of enzymatic working mechanisms and accurate monitoring of dynamic changes in protein configurations, which are often challenging to achieve in ensemble measurements. In this work, the prominent research progress in peptide and protein‐related studies are surveyed using electronic devices with single‐molecule/single‐event sensitivity, including single‐molecule junctions, single‐molecule field‐effect transistors, and nanopores. In particular, the successful commercial application of nanopores in DNA sequencing has made it one of the most promising techniques in protein sequencing at the single‐molecule level. From single peptides to protein complexes, the correlation between their electrical characteristics, structures, and biological functions is gradually being established. This enables to distinguish different molecular configurations of these biomacromolecules through real‐time electrical monitoring of their life activities, significantly improving the understanding of the mechanisms underlying various life processes.

Protein sequencing and structure prediction is analytic to farther predict the tertiary structure, realize protein function and design drugs. However, experimental techniques are used to determine the structure of proteins which are time-consuming and expensive, and thus it's very intense to design significant computational methods for predicting protein structure based on optimization techniques. Existing deep learning-based methods have accomplished exceptional accomplishments of protein structure prediction, but the methods often utilize the features from prior knowledge with less focus on the error rate. To address this issue in this work, a Bartlett’s Principal Regressive and Arbitrary African Buffalo Optimization (BPR-AABO) for performing secondary Protein Structure Prediction is proposed. The BPR-AABO method has one input layer, three hidden layers and output layer for protein structure prediction with higher accuracy and minimal time consumption. In BPR-AABO method, protein data is considered as an input and transmitted to the input layer. Relevant features are extracted from input protein data in hidden layer 1 by applying Bartlett’s specificity test. The extracted features are transmitted to the hidden layer 2 where Principal Component Regression Analysis is applied with the chosen features for protein structure identification. Then, protein structure identification results are transmitted to the hidden layer 3. In that layer, Improved African Buffalo Optimization Model with sigmoid activation function is used for positioning the amino acids to form the protein structure and therefore performing protein structure prediction with higher accuracy and lesser time consumption. Experimental evaluation is carried out on factors such as, prediction accuracy, prediction time and ROC with respect to number of protein data. [ABSTRACT FROM AUTHOR]

Achieving high throughput protein sequencing at single molecule resolution remains a daunting challenge. Herein, relying on a solid‐state 2D phosphorene nanoslit device, an extraordinary biosensor to rapidly identify the key signatures of all twenty amino acids using an interpretable machine learning (ML) model is reported. The XGBoost regression algorithm allows the determination of the transmission function of all twenty amino acids with high accuracy. The resultant ML and DFT studies reveal that it is possible to identify individual amino acids through transmission and current signals readouts with high sensitivity and selectivity. Moreover, we thoroughly compared our results to those from graphene nanoslit and found that the phosphorene nanoslit device can be an ideal candidate for protein sequencing up to a 20‐fold increase in transmission sensitivity. The present study facilitates high throughput screening of all twenty amino acids and can be further extended to other biomolecules for disease diagnosis and therapeutic decision making. [ABSTRACT FROM AUTHOR]

Proteomic studies typically involve the use of different types of software for annotating experimental tandem mass spectrometric data (MS/MS) and thereby simplifying the process of peptide and protein identification. For such annotations, these softwares calculate the m/z values of the peptide/protein precursor and fragment ions, for which a database of protein sequences must be provided as an input file. The calculated m/z values are stored as another database, which the user usually cannot view. Database Creator for Mass Analysis of Peptides and Proteins (DC-MAPP) is a novel standalone software that can create custom databases for "viewing" the calculated m/z values of precursor and fragment ions, prior to the database search. It contains three modules. Peptide/Protein sequences as per user's choice can be entered as input to the first module for creating a custom database. In the second module, m/z values must be queried-in, which are searched within the custom database to identify protein/peptide sequences. The third module is suited for peptide mass fingerprinting, which can be used to analyze both ESI and MALDI mass spectral data. The feature of "viewing" the custom database can be helpful not only for better understanding the search engine processes, but also for designing multiple reaction monitoring (MRM) methods. Post-translational modifications and protein isoforms can also be analyzed. Since, DC-MAPP relies on the protein/peptide "sequences" for creating custom databases, it may not be applicable for the searches involving spectral libraries. Python language was used for implementation, and the graphical user interface was built with Page/Tcl, making this tool more user-friendly. It is freely available at https://vit.ac.in/DC-MAPP/. [ABSTRACT FROM AUTHOR]

Proteins are essential biological molecules to use as biomarkers for early disease diagnosis. Therefore, their detection is crucial. In recent years, protein sequencing has become one of the most promising techniques. In particular, solid-state nanopores (SSNs) are powerful platforms for single biological molecule sensing without any labeling and with high sensitivity. Atomically thin two-dimensional (2D) materials with nanometer-sized pores, such as single-layer MoS2, represent the ideal SSN because of their ultimate thinness. Despite the benefits they offer, their use for protein sequencing applications remains very challenging since the fast translocation speed provides a short observation time per single molecule. In this work, we performed extensive molecular dynamics simulations of the translocation of the 20 proteinogenic amino acids through single-layer MoS2 nanopores. From ionic current traces, we characterized peptide-induced blockade levels of current and duration for each of the 20 natural amino acids. Using clustering techniques, we demonstrate that positively and negatively charged amino acids present singular fingerprints and can be visually distinguished from neutral amino acids. Furthermore, we demonstrate that this information would be sufficient to identify proteins using the coarse-grained sequencing technique made of only three amino acid categories depending on their charge. Therefore, single-layer MoS2 nanopores have great potential as sensors for the identification of biomarkers.

The biomedical field has always fostered innovation and the development of various new technologies. Beginning in the last century, demand for picoampere-level current detection in biomedicine has increased, leading to continuous breakthroughs in biosensor technology. Among emerging biomedical sensing technologies, nanopore sensing has shown great potential. This paper reviews nanopore sensing applications, such as chiral molecules, DNA sequencing, and protein sequencing. However, the ionic current for different molecules differs significantly, and the detection bandwidths vary as well. Therefore, this article focuses on current sensing circuits, and introduces the latest design schemes and circuit structures of different feedback components of transimpedance amplifiers mainly used in nanopore DNA sequencing. [ABSTRACT FROM AUTHOR]

Background: Muscle is an important tissue of the human body. Muscle atrophy is common in people of all ages, which will lead to human weakness and decline of motor function, which is one of the important causes of disability. The common methods of genomics research are transcriptome, proteomics and metabolomics, which are important means to explore the molecular pathology of diseases. In recent years, combinatorial research has been carried out on a large scale in the field of muscle atrophy. However, no author in this field has carried out bibliometrics and visual analysis., Methods: In this study, articles related to the histological study of muscular dystrophy since 2000 were searched from the Web of Science core database (WoSCC). We will retrieve the results through CiteSpace, VosViewer and R for data statistics and visual analysis., Results: In this study, a total of 141 publications were collected, and the number of publications increased year by year. These 141 articles came from 1031 co-authors from 361 institutions in 31 countries and were published in 92 journals. A total of 6286 articles from 1383 journals were cited. Authors from American institutions have published the most articles and have been cited the most, and authors from other countries have also made considerable contributions., Conclusion: This is the first bibliometric and visual analysis of published research in the field of muscular dystrophy through systematic data retrieval and combined with a variety of bibliometric analysis tools. Through these data, we summarize the previous studies of scholars, and provide prospects for future research in the field., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yang, Meng, Dai, Zhang, Dai, Wang and Fei.)

Type I ribosome-inactivating proteins (RIPs) are plant toxins that inhibit protein synthesis by exerting rRNA N-glycosylase activity (EC 3.2.2.22). Due to the lack of a cell-binding domain, type I RIPs are not target cell-specific. However once linked to antibodies, so called immunotoxins, they are promising candidates for targeted anti-cancer therapy. In this study, sapovaccarin-S1 and -S2, two newly identified type I RIP isoforms differing in only one amino acid, were isolated from the seeds of Saponaria vaccaria L. Sapovaccarin-S1 and -S2 were purified using ammonium sulfate precipitation and subsequent cation exchange chromatography. The determined molecular masses of 28,763 Da and 28,793 Da are in the mass range typical for type I RIPs and the identified amino acid sequences are homologous to known type I RIPs such as dianthin 30 and saporin-S6 (79% sequence identity each). Sapovaccarin-S1 and -S2 showed adenine-releasing activity and induced cell death in Huh-7 cells. In comparison to other type I RIPs, sapovaccarin-S1 and -S2 exhibited a higher thermostability as shown by nano-differential scanning calorimetry. These results suggest that sapovaccarin-S1 and -S2 would be optimal candidates for targeted anti-cancer therapy. [ABSTRACT FROM AUTHOR]

This study is aimed at identifying and characterising the proteases we previously extracted from the red seaweed Gracilaria edulis with the potential as milk-clotting enzymes. The protease extract was first analysed by sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and zymography. Two protease bands with a molecular weight of 44 and 108 kDa were identified, and analysed using in-gel digestion and liquid chromatography-tandem mass spectrometry/mass spectrometry (LC-MS/MS). Eight peptides from the LC-MS/MS analysis matched those in existing protein databases but they were not related to any protease of the genera Gracilaria and Hydropuntia. Further analysis revealed that more than 80% of the peptide sequence of the algal proteases matched with those from members of the bacteria kingdom, including Gallaecimonas and Alteromonas. Among these, twelve matching homolog proteases were identified as metalloprotease and serine protease. The results indicated that the algal proteases have a close relationship with both algae and bacteria, and suggest that the proteases might have resulted from past bacterial colonisation of the algae and subsequent horizontal gene transfer between bacteria and algae. [ABSTRACT FROM AUTHOR]

Wheat allergies are potentially life-threatening because of the high risk of anaphylaxis. Wheats belong to four genotypes represented in thousands of lines and varieties. Monitoring changes to wheat allergens is critical to prevent inadvertent ntroduction of hyper-allergenic varieties via breeding. However, validated methods for this purpose are unavailable at present. As a proof-of-concept study, we tested the hypothesis that salt-soluble wheat allergens in our mouse model will be identical to those reported for humans. Groups of Balb/cJ mice were rendered allergic to durum wheat salt-soluble protein extract (SSPE). Using blood from allergic mice, a mini hyper-IgE plasma bank was created and used in optimizing an IgE Western blotting (IEWB) to identify IgE binding allergens. The LC-MS/MS was used to sequence the allergenic bands. An ancient Aegilops tauschii wheat was grown in our greenhouse and extracted SSPE. Using the optimized IEWB method followed by sequencing, the cross-reacting allergens in A. tauschii wheat were identified. Database analysis showed all but 2 of the durum wheat allergens and all A. tauschii wheat allergens identified in this model had been reported as human allergens. Thus, this model may be used to identify and monitor potential changes to salt-soluble wheat allergens caused by breeding. [ABSTRACT FROM AUTHOR]

The biomedical field has always fostered innovation and the development of various new technologies. Beginning in the last century, demand for picoampere-level current detection in biomedicine has increased, leading to continuous breakthroughs in biosensor technology. Among emerging biomedical sensing technologies, nanopore sensing has shown great potential. This paper reviews nanopore sensing applications, such as chiral molecules, DNA sequencing, and protein sequencing. However, the ionic current for different molecules differs significantly, and the detection bandwidths vary as well. Therefore, this article focuses on current sensing circuits, and introduces the latest design schemes and circuit structures of different feedback components of transimpedance amplifiers mainly used in nanopore DNA sequencing.

Monoclonal antibody (mAb) therapeutics targeting cancer, autoimmune diseases, inflammatory diseases, and infectious diseases are growing exponentially. Although numerous panels of mAbs targeting infectious disease agents have been developed, their progression into clinically useful mAbs is often hindered by the lack of sequence information and/or loss of hybridoma cells that produce them. Here we combine the power of crystallography and mass spectrometry to determine the amino acid sequence and glycosylation modification of the Fab fragment of a potent human astrovirus-neutralizing mAb. We used this information to engineer a recombinant antibody single-chain variable fragment that has the same specificity as the parent monoclonal antibody to bind to the astrovirus capsid protein. This antibody can now potentially be developed as a therapeutic and diagnostic agent.

Solid-state material-based protein sequencing techniques have emerged as a paradigm that is capable of decoding the sequence of amino acids in protein by electrical detection. We studied a graphene nanoslit device for ultrafast protein sequencing using electronic transport calculations. The first-principles consistent-exchange van der Waals density functional (vdW-DF-cx) calculations have been employed to study the structural and electronic properties of the pristine graphene nanoslit and graphene nanoslit + amino acid systems. Ten amino acid molecules, namely, alanine (Ala), arginine (Arg), aspartic acid (Asp), glutamic acid (Glu), glycine (Gly), histidine (His), lysine (Lys), phenylalanine (Phe), proline (Pro), and tyrosine (Tyr), are considered. The electronic quantum transport properties of pristine graphene nanoslit and graphene nanoslit + amino acid systems are studied using the nonequilibrium Green's function (NEGF) combined with the density functional theory (DFT) approach. Significant changes in the electronic transmission conductance are observed in the graphene nanoslit device in the presence of certain amino acids. The computed conductance sensitivity and current–voltage (I–V) characteristics indicate that selective identification of amino acids is possible through the graphene nanoslit device. This study may be a practical guide toward the development of a graphene nanoslit-based device for ultrafast protein sequencing applications. [ABSTRACT FROM AUTHOR]

The correct characterization and identification of different kinds of proteins is crucial for the survival and development of living organisms, and proteomics research promotes the analysis and understanding of future genome functions. Nanopore technique has been proved to accurately identify individual nucleotides. However, accurate and rapid protein sequencing is difficult due to the variability of protein structures that contains more than 20 amino acids, and it remains very challenging especially for uncharged peptides as they can not be electrophoretically driven through the nanopore. Graphene nanopores have the advantages of high accuracy, sensitivity and low cost in identifying protein phosphorylation modifications. Here, by using all-atom molecular dynamics simulations, charged graphene nanopores are employed to electroosmotically capture and sense uncharged peptides. By further mimicking AFM manipulation of single molecules, it is also found that the uncharged peptides and their phosphorylated states could also be differentiated by both the ionic current and pulling force signals during their pulling processes through the nanopore with a slow and constant velocity. The results shows ability of using nanopores to detect and discriminate single amino acid and its phosphorylation, which is essential for the future low-cost and high-throughput sequencing of protein residues and their post-translational modifications., (© 2024 Wiley-VCH GmbH.)

The use of mirror-image proteins for the purpose of information barcoding and storage media is reported. [Display omitted] A mirror-image protein-based information barcoding and storage technology wherein D-amino acids are used to encode information into mirror-image proteins that are chemically synthesized is described. These mirror-image proteins were then fused into various materials from which information-encoded objects were produced. Subsequently, the mirror-image proteins were extracted from the objects using biotin-streptavidin resin-mediated specific enrichment and cleaved using an Ni(II)-mediated selective peptide cleavage. Protein sequencing was accomplished using liquid chromatography/tandem mass spectrometry (LC-MS/MS) and then transcoded into the recorded information. We demonstrated the use of this technology to encode Chinese words into mirror-image proteins, which were then fused onto a poly(ethylene terephthalate) (PET) film and retrieved and decoded by LC-MS/MS sequencing. Compared to information barcoding and storage technologies using natural biopolymers, the mirror-image biopolymers used in our technology may be more stable and durable. [ABSTRACT FROM AUTHOR]

Proteins are responsible for the occurrence and treatment of many diseases, and therefore protein sequencing will revolutionize proteomics and clinical diagnostics. Biological nanopore approach has proved successful for single‐molecule DNA sequencing, which resolves the identities of 4 natural deoxyribonucleotides based on the current blockages and duration times of their translocations across the nanopore confinement. However, open challenges still remain for biological nanopores to sequentially identify each amino acid (AA) of single proteins due to the inherent complexity of 20 proteinogenic AAs in charges, volumes, hydrophobicity and structures. Herein, we focus on recent exciting advances in biological nanopores for single‐molecule protein sequencing (SMPS) from native protein unfolding, control of peptide translocation, AA identification to applications in disease detection. [ABSTRACT FROM AUTHOR]

Transmembrane α-helical domains of membrane proteins tend to remain structured in the gas phase, presenting a challenge for efficient electron capture/transfer dissociation during top-down dissociation mass spectrometry (MS) experiments. In this study, we compare results from different dissociation modes on a modern Orbitrap platform applied to a model integral membrane protein containing two transmembrane helices, the c-subunit of the Fo domain of the chloroplast ATP synthase. Using commercially available options, we compare collisionally activated dissociation (CAD) with the related variant higher-energy collisional dissociation (HCD) and with electron transfer dissociation (ETD). HCD performed better than CAD and ETD. A combined method utilizing both ETD and HCD (EThcD) demonstrates significant synergy over HCD or ETD alone, representing a robust option analogous to activated ion electron capture dissociation, whereby an infrared laser was used to heat the protein ion alongside electron bombardment. Ultraviolet photodissociation at 213 nm displays at least three backbone dissociation mechanisms and covered nearly 100% of backbone bonds, suggesting significant potential for this technique. [ABSTRACT FROM AUTHOR]

Protein post-translational modifications (PTMs) play pivotal roles in almost every cellular process, influencing protein stability, localization, interactions, and enzymatic activities. PTM analysis is crucial for biological and medical advancements, prompting interest in clinical-compatible methods. Nanopore technology emerges as an ideal solution due to its single-molecule sensitivity, ionic current insights, and real-time detection, allowing label-free and high-throughput PTM analysis. This is particularly valuable for exploring low-abundance modifications and dynamic processes. As PTMs pose challenges in protein sequencing, nanopore technology is positioned to impact a broad research domain, promising groundbreaking insights into biological systems and clinical applications. This review summarizes studies on PTM detection using nanopores, showcasing the technology's potential. With its promising development, nanopore research is expected to inspire further advancements and eventual commercialization for PTM detection. [Display omitted] • Protein post-translational modification detection stands at the frontier of modern biology and medicine. • Nanopores are emerging tools for post-translational modification detections. • Studies of both biological and solid-state nanopores are summarized. • Nanopore analysis will drive the advancement of post-translational modification proteomics, and facilitate clinical trials. [ABSTRACT FROM AUTHOR]

Type I ribosome-inactivating proteins (RIPs) are plant toxins that inhibit protein synthesis by exerting rRNA N-glycosylase activity (EC 3.2.2.22). Due to the lack of a cell-binding domain, type I RIPs are not target cell-specific. However once linked to antibodies, so called immunotoxins, they are promising candidates for targeted anti-cancer therapy. In this study, sapovaccarin-S1 and -S2, two newly identified type I RIP isoforms differing in only one amino acid, were isolated from the seeds of Saponaria vaccaria L. Sapovaccarin-S1 and -S2 were purified using ammonium sulfate precipitation and subsequent cation exchange chromatography. The determined molecular masses of 28,763 Da and 28,793 Da are in the mass range typical for type I RIPs and the identified amino acid sequences are homologous to known type I RIPs such as dianthin 30 and saporin-S6 (79% sequence identity each). Sapovaccarin-S1 and -S2 showed adenine-releasing activity and induced cell death in Huh-7 cells. In comparison to other type I RIPs, sapovaccarin-S1 and -S2 exhibited a higher thermostability as shown by nano-differential scanning calorimetry. These results suggest that sapovaccarin-S1 and -S2 would be optimal candidates for targeted anti-cancer therapy.

Single molecule protein sequencing would tremendously impact in proteomics and human biology and it would promote the development of novel diagnostic and therapeutic approaches. However, its technological realization can only be envisioned, and huge challenges need to be overcome. Major difficulties are inherent to the structure of proteins, which are composed by several different amino-acids. Despite long standing efforts, only few complex techniques, such as Edman degradation, liquid chromatography and mass spectroscopy, make protein sequencing possible. Unfortunately, these techniques present significant limitations in terms of amount of sample required and dynamic range of measurement. It is known that proteins can distinguish closely similar molecules. Moreover, several proteins can work as biological nanopores in order to perform single molecule detection and sequencing. Unfortunately, while DNA sequencing by means of nanopores is demonstrated, very few examples of nanopores able to perform reliable protein-sequencing have been reported so far. Here, we investigate, by means of molecular dynamics simulations, how a re-engineered protein, acting as biological nanopore, can be used to recognize the sequence of a translocating peptide by sensing the "shape" of individual amino-acids. In our simulations we demonstrate that it is possible to discriminate with high fidelity, 9 different amino-acids in a short peptide translocating through the engineered construct. The method, here shown for fluorescence-based sequencing, does not require any labelling of the peptidic analyte. These results can pave the way for a new and highly sensitive method of sequencing. [ABSTRACT FROM AUTHOR]

Introduction: Proteomic profiling plays an important role in the exploration of cancer from molecular mechanisms to clinical diagnosis and treatment. In recent years, the advent of new technologies has promoted oncoproteomics from the initial global style to a refined single-cell level. Areas Covered: Among them, the development of microfluidic devices, the improvement of liquid mass spectrometry in accuracy and trace sample handling processes, and the emergence of protein sequencing have contributed to the oncoproteomic analysis at the single-cell level. Expert Opinion: The proteomic analysis at the global level and the single-cell level gives different perspectives while combining them can reveal more comprehensive oncoproteomics and help cancer research and treatment strategies. [ABSTRACT FROM AUTHOR]

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions and is of utmost importance in molecular diagnostics and medication development. Nanopores have become an effective tool for single molecule sensing, however, the weak charge and non-uniform charge distribution of protein make capturing and sensing very challenging, which poses a significant obstacle to the development of nanopore-based protein sequencing. In this study, to facilitate capturing of the unfolded protein, highly charged peptide was employed in our simulations, we found that the velocity of unfolded peptide translocating through a hybrid nanopore composed of silicon nitride membrane and carbon nanotube is much slower compared to bare silicon nitride nanopore, it is due to the significant interaction between amino acids and the surface of carbon nanotube. Moreover, by introducing variations in the charge states at the boundaries of carbon nanotube nanopores, the competition and combination of the electrophoretic and electroosmotic flows through the nanopores could be controlled, we then successfully regulated the translocation velocity of unfolded proteins through the hybrid nanopores. The proposed hybrid nanopore effectively retards the translocation velocity of protein through it, facilitates the acquisition of ample information for accurate amino acid identification., (© 2024 Wiley‐VCH GmbH.)

Only a small percent of human genomic DNA encodes for proteins. Additionally, protein isoforms variants and chemical modifications are not coded in the genome read by the cell machinery. The resulting protein diversity is deeply involved in regular and diseased cellular processes. One challenge for the field of biotechnology, after human genome sequencing, will be to decipher the proteome at a single molecule scale to analyze single‐cell protein variability. In fact, cellular proteic information, often used as a source of biomarkers, is of great importance for early disease detection. This review discusses the proteome's complexity from its genetic source to fully modified proteins. It focuses on the principle of nanopore data analysis and how to obtain information from an electrical current trace. Specifically, the most recent developments in detection, sequencing and post‐translational discrimination of amino acids, peptides and proteins, are described. The main results obtained in this field are discussed and the nanopore techniques to other classical or single‐molecule approaches are compared. [ABSTRACT FROM AUTHOR]

Protein sequencing holds the key to unveiling protein dynamics, which is significant for molecular diagnostics and drug design. Single‐molecule sensing based on 2D nanopores is a versatile technique for realizing low‐cost and high‐throughput protein sequencing targets. However, the remaining challenge is that protein translocates rapidly through nanopores, where few current signals can be gathered for accurate protein sequencing. It is theoretically found that adding nonionic detergents to a solution can slow protein molecules by almost one order when they permeate through a 1.4 nm MoS2 nanopore that is slightly larger than the diameter of the peptide but smaller than the diameter of the protein–detergent complex. This slowdown is due to the strong interaction between the hydrophobic parts of the peptide and detergents. Although detergent molecules are added to the system, ionic current blockade levels can be observed for different residues, indicating that the nonionic detergents are excellent candidates for controlling protein translocation process but do not affect the discrimination of single amino acids. This theoretical work motivates experimental efforts in this area and paves a new way for protein manipulation that brings the nanopore technique closer to satisfying the requirement of high‐precision nanopore protein sequencing. [ABSTRACT FROM AUTHOR]

Next-generation approaches for protein sequencing are now emerging that could have the potential to revolutionize the field in proteomics. One such sequencing method involves fluorescence-based imaging of immobilized peptides in which the N-terminal amino acid of a polypeptide is readout sequentially by a series of fluorescently labeled biomolecules. When selectively bound to a specific N-terminal amino acid, the NAAB (N-terminal amino acid binder) affinity reagent identifies the amino acid through its associated fluorescence tag. A key technical challenge in implementing this fluoro-sequencing approach is the need to develop NAAB affinity reagents with the high affinity and selectivity for specific N-terminal amino acids required for this biotechnology application. One approach to develop such a NAAB affinity reagent is to leverage naturally occurring biomolecules that bind amino acids and/or peptides. Here, we describe several candidate biomolecules that could be considered for this purpose and discuss the potential for developability of each. Key points • Next-generation sequencing methods are emerging that could revolutionize proteomics. • Sequential readout of N-terminal amino acids by fluorescent-tagged affinity reagents. • Native peptide/amino acid binders can be engineered into affinity reagents. • Protein size and structure contribute to feasibility of reagent developability. [ABSTRACT FROM AUTHOR]

Background: A neutral, heat-sensitive serine protease (NHSSP) originating from the feather-degrading fungus Onygena corvina (O. corvina) was described and defined as an alkaline serine protease of the subtilisin type S8 family, exhibiting an enzymatic activity at neutral pH. Generally, broad specificity proteases, such as proteinase K or trypsin, have found numerous applications in research and biotechnology. Results: We report the cloning and expression in the yeast PichiaPink™ system, as well as purification, and characterization of the NHSSP. Recombinant, His6-tagged NHSSP was efficiently expressed from an optimized, synthetic gene and purified using a simple protocol based on ammonium sulfate fractionation and hydrophobic interaction chromatography. The enzyme shows atypical C-terminal processing, the coded preproprotein undergoes signal peptide removal and maturation through the clipping of a propeptide section and 10 amino acids (aa) from the C-terminus, including the His6-tag. The deletion variant has been constructed, devoid of the C-terminal ORF segment, thus eliminating the need for C-terminal processing. Both NHSSP variants exhibit very similar enzymatic characteristics. The purified enzymes were characterized to determine the optimal proteolytic conditions. We revealed that the mature NHSSP is reproducibly active over a wide pH range from neutral to mild acidic (pH of 5.0 to 8.5), with an optimum at pH 6.8, and at temperatures of 15 to 50 °C with an optimum at 38–42 °C. Interestingly, we demonstrated that the protease can be fully deactivated by a moderate increase in temperature of about 15 °C from the optimum to over 50 °C. The protease was partially sensitive to serine protease inhibitors, and not inhibited by chelating or reducing agents and detergents. SDS induced autolysis of NHSSP, which points to a high stimulation of its proteolytic activity. Conclusions: The NHSSP was produced as a recombinant protein with high efficiency. Compared to proteinase K, the most common serine protease used, NHSSP shows an approx. twofold higher specific activity. Protein sequencing can be a valuable technical application for the protease. The protein coverage is significantly higher in comparison to trypsin and reaches about 84–100% for β-lactoglobulin (BLG), antibody (mAb) light and heavy chains. Furthermore, the option to perform digestions at neutral to slightly acidic pH-values down to pH 5.0 avoids modification of peptides, e.g. due to deamidation. [ABSTRACT FROM AUTHOR]

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions. However, proteins are usually folded in their native state and the mechanism of fast protein conformation transitions still remains unclear, which make protein sequencing challenging. Molecular dynamics simulations with accurate force field are now able to observe the entire folding/unfolding process, providing valuable insights into protein folding mechanisms. Given that proteins can be unfolded, nanopore technology shows great potential for protein sequencing. In this study, we proposed to use MoS 2 /SnS 2 heterostructures to firstly unfold proteins and then detect them by a nanopore in the heterostructural membrane. All-atom molecular dynamics simulations performed in this work provided rich atomic-level information for a comprehensive understanding of protein unfolding process and mechanism on the MoS 2 /SnS 2 heterostructure, it was found that the strong binding of protein to SnS 2 nanostripe and hydrogen bond breaking were the main reasons for unfolding the protein on the heterostructure. After the protein was fully unfolded, it was restrained on the nanostripe because of the affinity of protein to the SnS 2 nanostripe. Thus by integrating the proposed unfolding technique with nanopore technology, detection of linear unfolded peptide was realized in this work, allowing for the identification of protein components, which is essential for sequencing proteins in the near future., (© 2024 IOP Publishing Ltd.)

Ornithine decarboxylase (ODC) is a key enzyme in the biosynthesis of polyamines, organic cations that are implicated in many cellular processes. The enzyme is regulated at the post-translational level by an unusual system that includes antizymes (AZs) and antizyme inhibitors (AZINs). Most studies on this complex regulatory mechanism have been focused on human and rodent cells, showing that AZINs (AZIN1 and AZIN2) are homologues of ODC but devoid of enzymatic activity. Little is known about Xenopus ODC and its paralogues, in spite of the relevance of Xenopus as a model organism for biomedical research. We have used the information existing in different genomic databases to compare the functional properties of the amphibian ODC1, AZIN1 and AZIN2/ODC2, by means of transient transfection experiments of HEK293T cells. Whereas the properties of xlODC1 and xlAZIN1 were similar to those reported for their mammalian orthologues, the former catalyzing the decarboxylation of L-ornithine preferentially to that of L-lysine, xlAZIN2/xlODC2 showed important differences with respect to human and mouse AZIN2. xlAZIN2 did not behave as an antizyme inhibitor, but it rather acts as an authentic decarboxylase forming cadaverine, due to its higher affinity to L-lysine than to L-ornithine as substrate; so, in accordance with this, it should be named as lysine decarboxylase (LDC) or lysine/ornithine decarboxylase (LODC). In addition, AZ1 stimulated the degradation of xlAZIN2 by the proteasome, but the removal of the 21 amino acid C-terminal tail, with a sequence quite different to that of mouse or human ODC, made the protein resistant to degradation. Collectively, our results indicate that in Xenopus there is only one antizyme inhibitor (xlAZIN1) and two decarboxylases, xlODC1 and xlLDC, with clear preferences for L-ornithine and L-lysine, respectively. [ABSTRACT FROM AUTHOR]

Dendrograms are a way to represent relationships between organisms. Nowadays, these are inferred based on the comparison of genes or protein sequences by taking into account their differences and similarities. The genetic material of choice for the sequence alignments (all the genes or sets of genes) results in distinct inferred dendrograms. In this work, we evaluate differences between dendrograms reconstructed with different methodologies and for different sets of organisms chosen at random from a much larger set. A statistical analysis is performed to estimate fluctuations between the results obtained from the different methodologies that allows us to validate a systematic approach, based on the comparison of the organisms’ metabolic networks for inferring dendrograms. This has the advantage that it allows the comparison of organisms very far away in the evolutionary tree even if they have no known ortholog gene in common. Our results show that dendrograms built using information from metabolic networks are similar to the standard sequence-based dendrograms and can be a complement to them. [ABSTRACT FROM AUTHOR]

Flavodoxins are small electron transfer proteins containing flavin mononucleotide (FMN) as a prosthetic group, which play an important role during oxidative stress or iron limitation. The aims of this study were the identification and characterization of flavodoxins in the model aromatic-degrader Paraburkholderia xenovorans LB400 and the analyses of their protective effects during oxidative stress induced by paraquat and H2O2. Two genes (BxeA0278 and BxeB0391) encoding flavodoxins (hereafter referred to as fldX for avooxin from P. enovorans), were identified at the LB400 major and minor chromosome. Genomic context of the flavodoxin-encoding genes showed genes encoding membrane proteins, transporters, and proteins involved in redox processes and biosynthesis of macromolecules. A secondary structure prediction of both LB400 flavodoxins showed the characteristic flavodoxin structure of five ß-sheets intercalated with five α-helices. FldX1 contains a loop intercalated in the fifth β-strand, which indicates that it belongs to the long-chain flavodoxins, whereas FldX2 is a short-chain flavodoxin. A phylogenetic analysis of 73 flavodoxins from 43 bacterial genera revealed eight clusters (I-VIII), while FldX1 and FldX2 grouped separately within a long-chain and a short-chain flavodoxin clades. FldX1 and FldX2 were overexpressed in P. xenovorans. Interestingly, the strain overexpressing the long-chain flavodoxin FldX1 (p2-fldX1) showed a faster growth in glucose than the control strain. The recombinant strain overexpressing the long-chain flavodoxin FldX1 (p2-fldx1) exposed to paraquat (20 mM) possessed lower susceptibility to growth inhibition on plates and higher survival in liquid medium than the control strain. The strains overexpressing the flavodoxins FldX1 and FldX2 showed higher survival during exposure to 1 mM paraquat (>95%) than the control strain (68%). Compared to the control strain, strains overexpressing FldX1 and FldX2 showed lower lipid peroxidation (>20%) after exposure to 1 mM paraquat and a lower protein carbonylation (~30%) after exposure to 1 mM H2O2 was observed. During exposure to paraquat, strain p2-fldx1 downregulated the katG4, hpf, trxB1 and ohr genes (> 2-fold), whereas strain p2-fldx2 upregulated the oxyR and ahpC1 genes (> 2-fold). In conclusion, the flavodoxins FldX1 and FldX2 of P. xenovorans LB400 conferred protection to cells exposed to the oxidizing agents paraquat and H2O2. [ABSTRACT FROM AUTHOR]