Protocol to reveal the binding partner of secreted housekeeping enzymes in Listeria monocytogenes via in silico prediction to in vivo validation.

Numerous interacting protein partners exist without recognized interactive domains, necessitating a standardized methodology to decipher more in-depth interaction profiles. Here, we present a protocol to reveal the binding partner of a secreted housekeeping enzyme, alcohol acetaldehyde dehydrogenase (Listeria adhesion protein), in Listeria monocytogenes through in silico modeling and in vivo experiments. We describe steps for target protein modeling, biophysical profiling, ClusPro docking optimization, protein variant modeling, and docking comparison. We then provide detailed procedures for in vitro and in vivo protein binding validation. For complete details on the use and execution of this protocol, please refer to Liu et al.1.

Comparison of the specific mechanical energy, specific thermal energy, and functional properties of cold and hot extruded pea protein isolate.

Pea protein is a popular source of plant-based protein, though its application in meat and dairy analog products is still lacking. This is particularly true in the development of products with fatty and creamy textures. Cold denaturation may be a way to induce these types of textures in food since this is a universal phenomenon in protein that occurs due to a weakening of hydrophobic interactions at cold temperatures. This work utilizes a single screw extruder to systematically study the impacts of moisture content (50-65 %) and pH (2,4.5,8) on the outlet temperatures, specific mechanical energy, specific thermal energy, and texture of cold-extruded pea protein. It was found that at pH 2 and moistures of 60 % and greater, the temperature of the product exiting the extruder is <5.5 °C, and also produced 13.7 %-36.5 % more specific thermal energy, indicating the occurrence of cold denaturation in these products. Based on these findings, a comparison of hot and cold extrusion was conducted as a function of pH and oil content. It was found that cold extrusion imparts 43.0 %-56.2 % more mechanical energy into the protein than hot extrusion, and the cold extruded protein had higher values of Young's modulus and breaking stress. The protein extruded at low temperatures was also able to bind 32.93 % more oil than hot extruded proteins when extruded with 10 % added oil, which may aid in the formation of protein-based fat memetics for the food industry.

Bioinformatic Approaches for Characterizing Molecular Structure and Function of Food Proteins.

Structural bioinformatics analyzes protein structural models with the goal of uncovering molecular drivers of food functionality. This field aims to develop tools that can rapidly extract relevant information from protein databases as well as organize this information for researchers interested in studying protein functionality. Food bioinformaticians take advantage of millions of protein amino acid sequences and structures contained within these databases, extracting features such as surface hydrophobicity that are then used to model functionality, including solubility, thermostability, and emulsification. This work is aided by a protein structure-function relationship framework, in which bioinformatic properties are linked to physicochemical experimentation. Strong bioinformatic correlations exist for protein secondary structure, electrostatic potential, and surface hydrophobicity. Modeling changes in protein structures through molecular mechanics is an increasingly accessible field that will continue to propel food science research.

Complexation with Polysaccharides Enhances the Stability of Isolated Anthocyanins.

Isolated anthocyanins have limited colonic bioavailability due to their instability as free forms. Thus, many methods have been fabricated to increase the stability of anthocyanins. Complexation, encapsulation, and co-pigmentation with other pigments, proteins, metal ions, and carbohydrates have been reported to improve the stability and bioavailability of anthocyanins. In this study, anthocyanins extracted from purple potatoes were complexed with four different polysaccharides and their mixture. The anthocyanin-polysaccharide complexes were characterized using a zeta potential analyzer, particle size analyzer, scanning electron microscopy, and Fourier-transform infrared spectroscopy. Complexes were subjected to simulated digestion for assessing the stability of anthocyanins. Furthermore, complexes were subjected to different pH conditions and incubated at high temperatures to monitor color changes. A Caco-2 cell monolayer was used to evaluate the colonic concentrations of anthocyanins. In addition, the bioactivity of complexes was assessed using LPS-treated Caco-2 cell monolayer. Results show that pectin had the best complexation capacity with anthocyanins. The surface morphology of the anthocyanin-pectin complex (APC) was changed after complexation. APC was more resistant to the simulated upper gastrointestinal digestion, and high pH and temperature conditions for a longer duration. Furthermore, APC restored the lipopolysaccharide (LPS)-induced high cell permeability compared to isolated anthocyanins. In conclusion, complexation with pectin increased the stability and colonic bioavailability and the activity of anthocyanins.

Physicochemical characterization of changes in pea protein as the result of cold extrusion.

Pea protein is a popular plant-based protein for mimicking textures in meat and dairy analogues which are more sustainable than their animal-based counterparts. However, precise mechanisms for generating specific textures through different processing methods are still being evaluated. This work utilizes a novel low-temperature extrusion process to selectively alter the chemical structure of pea protein. Changes in secondary structure, surface hydrophobicity, electrostatic interactions, and disulfide bonding are characterized through FTIR, ANS- probes, zeta potential, and SDS-PAGE. Extrudates are further characterized using texture parameter analysis. It was found that a linear combination of physicochemical data, generated with multiple linear regression modelling, led to reasonable estimates of the specific mechanical energy and textural properties. This work offers a new method of reactive extrusion to selectively modify interactions in pea protein using low temperature extrusion, and applications may include fatty textures, since the extrudates are found to be largely stabilized through hydrophobic interactions evaluated with surface hydrophobicity measurements.

Cell-surface anchoring of Listeria adhesion protein on L. monocytogenes is fastened by internalin B for pathogenesis.

Listeria adhesion protein (LAP) is a secreted acetaldehyde alcohol dehydrogenase (AdhE) that anchors to an unknown molecule on the Listeria monocytogenes (Lm) surface, which is critical for its intestinal epithelium crossing. In the present work, immunoprecipitation and mass spectrometry identify internalin B (InlB) as the primary ligand of LAP (KD ∼ 42 nM). InlB-deleted and naturally InlB-deficient Lm strains show reduced LAP-InlB interaction and LAP-mediated pathology in the murine intestine and brain invasion. InlB-overexpressing non-pathogenic Listeria innocua also displays LAP-InlB interplay. In silico predictions reveal that a pocket region in the C-terminal domain of tetrameric LAP is the binding site for InlB. LAP variants containing mutations in negatively charged (E523S, E621S) amino acids in the C terminus confirm altered binding conformations and weaker affinity for InlB. InlB transforms the housekeeping enzyme, AdhE (LAP), into a moonlighting pathogenic factor by fastening on the cell surface.

Applying text mining to identify relevant literature in food science: Cold denaturation as a case study.

In a research environment characterized by the five V's of big data, volume, velocity, variety, value, and veracity, the need to develop tools that quickly screen a large number of publications into relevant work is an increasing area of concern, and the data-rich food industry is no exception. Here, a combination of latent Dirichlet allocation and food keyword searches were employed to analyze and filter a dataset of 6102 publications about cold denaturation. After using the Python toolkit generated in this work, the approach yielded 22 topics that provide background and insight on the direction of research in this field, as well as identified the publications in this dataset which are most pertinent to the food industry with precision and recall of 0.419 and 0.949, respectively. Precision is related to the relevance of a paper in the filtered dataset and the recall represents papers which were not identified in the screening method. Lastly, gaps in the literature based on keyword trends are identified to improve the knowledge base of cold denaturation as it relates to the food industry. This approach is generalizable to any similarly organized dataset, and the code is available upon request. Practical Application: A common problem in research is that when you are an expert in one field, learning about another field is difficult, because you may lack the vocabulary and background needed to read cutting edge literature from a new discipline. The Python toolkit developed in this research can be applied by any researcher that is new to a field to identify what the key literature is, what topics they should familiarize themselves with, and what the current trends are in the field. Using this structure, researchers can greatly speed up how they identify new areas to research and find new projects.

Cold Denaturation of Proteins: Where Bioinformatics Meets Thermodynamics to Offer a Mechanistic Understanding: Pea Protein As a Case Study.

Protein structure can be altered with heat, but models which predict denaturation show that globular proteins also spontaneously unfold at low temperatures through cold denaturation. By an analysis of the primary structure of pea protein using bioinformatic modeling, a mechanism of pea protein cold denaturation is proposed. Pea protein is then fractionated into partially purified legumin and vicilin components, suspended in ethanol, and subjected to low temperatures (-10 to -20 °C). The structural characterizations of the purified fractions are conducted through FTIR, ζ potential, dynamic light scattering, and oil binding, and these are compared to the results of commercial protein isolates. The observed structural changes suggest that pea protein undergoes changes in structure as the result of low-temperature treatments, which could lead to innovative industrial processing techniques for functionalization by low-temperature processing.