Computational methods in mass spectrometry-based structural proteomics for studying protein structure, dynamics, and interactions

Supramolecular self-assembly strategies of natural-based β-lactoglobulin modulating bitter perception of goat milk-derived bioactive peptides

Complete self-assembly and reassembly behavior of bitter peptide-protein necessitates multilevel theories that encompass phenomena ranging from the self-assembly of recombinant complex to atomic trajectories. An extension to the level of mechanism method was put forth, involves limited enzymatic digestion and bottom-up proteomics to dissect inherent heterogeneity within β-LG and β-LG-PPGLPDKY complex and uncover conformational and dynamic alterations occurring in specific local regions of the model protein. Bitter peptide PPGLPDKY spontaneously bound to IIAEKTK, IDALNENK, and YLLFCMENSAEPEQSLACQCLVR regions of β-LG in a 1:1 stoichiometric ratio to mask bitterness perception. Molecular dynamic simulation and free energy calculation provided time-varying atomic trajectories of the recombinant complex and found that a peptide was stabilized in the upper region of the hydrophobic cavity with the binding free energy of -30.56 kJ mol-1 through 4 hydrogen bonds (Glu74, Glu55, Lys69, and Ser116) and hydrophobic interactions (Asn88, Asn90, and Glu112). Current research aims to provide valuable physical insights into the macroscopic self-assembly behavior between proteins and bitter peptides, and the meticulous design of highly acceptable taste characteristics in goat milk products.

Deep learning framework for peak detection at the intact level of therapeutic proteins

While automated peak detection functionalities are available in commercially accessible software, achieving optimal true positive rates frequently necessitates visual inspection and manual adjustments. In the initial phase of this study, hetero-variants (glycoforms) of a monoclonal antibody were distinguished using liquid chromatography-mass spectrometry, revealing discernible peaks at the intact level. To comprehensively identify each peak (hetero-variant) in the intact-level analysis, a deep learning approach utilizing convolutional neural networks (CNNs) was employed in the subsequent phase of the study. In the current case study, utilizing conventional software for peak identification, five peaks were detected using a 0.5 threshold, whereas seven peaks were identified using the CNN model. The model exhibited strong performance with a probability area under the curve (AUC) of 0.9949, surpassing that of partial least squares discriminant analysis (PLS-DA) (probability AUC of 0.8041), and locally weighted regression (LWR) (probability AUC of 0.6885) on the data acquired during experimentation in real-time. The AUC of the receiver operating characteristic curve also illustrated the superior performance of the CNN over PLS-DA and LWR.

Green Chemistry to Modify Functional Properties of Crambe Protein Isolate-Based Thermally Formed Films

Proteins are promising precursors to be used in production of sustainable materials with properties resembling plastics, although protein modification or functionalization is often required to obtain suitable product characteristics. Here, effects of protein modification were evaluated by crosslinking behavior using high-performance liquid chromatography (HPLC), secondary structure using infrared spectroscopy (IR), liquid imbibition and uptake, and tensile properties of six crambe protein isolates modified in solution before thermal pressing. The results showed that a basic pH (10), especially when combined with the commonly used, although moderately toxic, crosslinking agent glutaraldehyde (GA), resulted in a decrease in crosslinking in unpressed samples, as compared to acidic pH (4) samples. After pressing, a more crosslinked protein matrix with an increase in β-sheets was obtained in basic samples compared to acidic samples, mainly due to the formation of disulfide bonds, which led to an increase in tensile strength, and liquid uptake with less material resolved. A treatment of pH 10 + GA, combined either with a heat or citric acid treatment, did not increase crosslinking or improve the properties in pressed samples, as compared to pH 4 samples. Fenton treatment at pH 7.5 resulted in a similar amount of crosslinking as the pH 10 + GA treatment, although with a higher degree of peptide/irreversible bonds. The strong bond formation resulted in lack of opportunities to disintegrate the protein network by all extraction solutions tested (even for 6 M urea + 1% sodium dodecyl sulfate + 1% dithiothreitol). Thus, the highest crosslinking and best properties of the material produced from crambe protein isolates were obtained by pH 10 + GA and pH 7.5 + Fenton, where Fenton is a greener and more sustainable solution than GA. Therefore, chemical modification of crambe protein isolates is effecting both sustainability and crosslinking behavior, which might have an effect on product suitability.

Structural and dynamic insights into α-synuclein dimer conformations

Parkinson disease is associated with the aggregation of the protein α-synuclein. While α-synuclein can exist in multiple oligomeric states, the dimer has been a subject of extensive debates. Here, using an array of biophysical approaches, we demonstrate that α-synuclein in vitro exhibits primarily a monomer-dimer equilibrium in nanomolar concentrations and up to a few micromolars. We then use spatial information from hetero-isotopic cross-linking mass spectrometry experiments as restrains in discrete molecular dynamics simulations to obtain the ensemble structure of dimeric species. Out of eight structural sub-populations of dimers, we identify one that is compact, stable, abundant, and exhibits partially exposed β-sheet structures. This compact dimer is the only one where the hydroxyls of tyrosine 39 are in proximity that may promote dityrosine covalent linkage upon hydroxyl radicalization, which is implicated in α-synuclein amyloid fibrils. We propose that this α-synuclein dimer features etiological relevance to Parkinson disease.

Cross-linking reactions in food proteins and proteomic approaches for their detection

Various protein cross-linking reactions leading to molecular polymerization and covalent aggregates have been described in processed foods. They are an undesired side effect of processes designed to reduce bacterial load, extend shelf life, and modify technological properties, as well as being an expected result of treatments designed to modify raw material texture and function. Although the formation of these products is known to affect the sensory and technological properties of foods, the corresponding cross-linking reactions and resulting protein polymers have not yet undergone detailed molecular characterization. This is essential for describing how their generation can be related to food processing conditions and quality parameters. Due to the complex structure of cross-linked species, bottom-up proteomic procedures developed to characterize various amino acid modifications associated with food processing conditions currently offer a limited molecular description of bridged peptide structures. Recent progress in cross-linking mass spectrometry for the topological characterization of protein complexes has facilitated the development of various proteomic methods and bioinformatic tools for unveiling bridged species, which can now also be used for the detailed molecular characterization of polymeric cross-linked products in processed foods. We here examine their benefits and limitations in terms of evaluating cross-linked food proteins and propose future scenarios for application in foodomics. They offer potential for understanding the protein cross-linking formation mechanisms in processed foods, and how the inherent beneficial properties of treated foodstuffs can be preserved or enhanced.

Mapping the plant proteome: tools for surveying coordinating pathways

Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein-protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

Proteomics and plant biology: contributions to date and a look towards the next decade

INTRODUCTION

This review presents the view of the author, that is opinionable and even speculative, on the field of proteomics, its application to plant biology knowledge, and translation to biotechnology. Written in a more academic than scientific style, it is based on past original and review articles by the author´s group, and those published by leading scientists in the last two years.

AREAS COVERED

Starting with a general definition and references to historical milestones, it covers sections devoted to the different platforms employed, the plant biology discourse in the protein language, challenges and future prospects, ending with the author opinion.

EXPERT OPINION

In 25 years, five proteomics platform generations have appeared. We are now moving from proteomics to Systems Biology. While feasible with model organisms, proteomics of orphan species remains challenging. Proteomics, even in its simplest approach, sheds light on plant biological processes, central dogma, and molecular bases of phenotypes of interest, and it can be translated to areas such as food traceability and allergen detection. Proteomics should be validated and optimized to each experimental system, objectives, and hypothesis. It has limitations, artifacts, and biases. We should not blindly accept proteomics data and just create a list of proteins, networks, and avoid speculative biological interpretations. From the hundred to thousand proteins identified and quantified, it is important to obtain a focus and validate some of them, otherwise it is merely. We are starting to have the protein pieces, so let, from now, build the proteomics and biological puzzle.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

The Dystrophin Node as Integrator of Cytoskeletal Organization, Lateral Force Transmission, Fiber Stability and Cellular Signaling in Skeletal Muscle

The systematic bioanalytical characterization of the protein product of the DMD gene, which is defective in the pediatric disorder Duchenne muscular dystrophy, led to the discovery of the membrane cytoskeletal protein dystrophin. Its full-length muscle isoform Dp427-M is tightly linked to a sarcolemma-associated complex consisting of dystroglycans, sarcoglyans, sarcospan, dystrobrevins and syntrophins. Besides these core members of the dystrophin-glycoprotein complex, the wider dystrophin-associated network includes key proteins belonging to the intracellular cytoskeleton and microtubular assembly, the basal lamina and extracellular matrix, various plasma membrane proteins and cytosolic components. Here, we review the central role of the dystrophin complex as a master node in muscle fibers that integrates cytoskeletal organization and cellular signaling at the muscle periphery, as well as providing sarcolemmal stabilization and contractile force transmission to the extracellular region. The combination of optimized tissue extraction, subcellular fractionation, advanced protein co-purification strategies, immunoprecipitation, liquid chromatography and two-dimensional gel electrophoresis with modern mass spectrometry-based proteomics has confirmed the composition of the core dystrophin complex at the sarcolemma membrane. Importantly, these biochemical and mass spectrometric surveys have identified additional members of the wider dystrophin network including biglycan, cavin, synemin, desmoglein, tubulin, plakoglobin, cytokeratin and a variety of signaling proteins and ion channels.

Protocol for the Bottom-Up Proteomic Analysis of Mouse Spleen

This protocol describes the comparative proteomic profiling of the spleen of wild type versus mdx-4cv mouse, a model of dystrophinopathy. We detail sample preparation for bottom-up proteomic mass spectrometry experiments, including homogenization of tissue, protein concentration measurements, protein digestion, and removal of interfering chemicals. We then describe the steps for mass spectrometric analysis and bioinformatic evaluation. For complete details on the use and execution of this protocol, please refer to Dowling et al. (2020).