With the advancement of liquid chromatography–mass spectrometry (LC–MS/MS), the quantification of glycerophospholipid (PL) molecules has become more accessible, leading to the discovery of numerous enzymes responsible for determining the acyl groups attached to these molecules. Metabolic tracer experiments using radioisotopes and stable isotopes are powerful tools for defining the function of metabolic enzymes and metabolic flux. We have established an ex vivo muscle experimental system using stable isotope–labeled fatty acids to evaluate fatty acid incorporation into PL molecules. Here, we describe a method to incorporate fatty acids with stable isotope labels into excised skeletal muscle and detect the PL molecules containing labeled acyl chains by LC–MS/MS.

Myosin-5a (Myo5a) is an actin-dependent molecular motor that recognizes a diverse range of cargo proteins through its tail domain, playing a crucial role in the transport and localization of various organelles within the cell. We have identified a new interaction between Myo5a and its cargo protein melanophilin (Mlph), i.e., the interaction between the middle tail domain of Myo5a (Myo5a-MTD) and the actin-binding domain of Mlph (Mlph-ABD), by GST pulldown assay. We then intend to obtain the dissociation constant between Myo5a-MTD and Mlph-ABD using isothermal titration calorimetry (ITC) or microscale thermophoresis (MST), both of which are two commonly used methods for determining quantitative data on protein interactions. The advantages of MST over ITC include less protein usage, shorter operation time, and higher sensitivity. In this protocol, we present a method for using MST to determine the dissociation constants of Myo5a-MTD and Mlph-ABD, which were purified through overexpression in bacteria using affinity chromatography. The dissociation constant values obtained directly reflect the binding strength between these two proteins and provide a foundation for the isolation and purification of the complex in the future.

Ribosomes are an archetypal ribonucleoprotein assembly. Due to ribosomal evolution and function, r-proteins share specific physicochemical similarities, making the riboproteome particularly suited for tailored proteome profiling methods. Moreover, the structural proteome of ribonucleoprotein assemblies reflects context-dependent functional features. Thus, characterizing the state of riboproteomes provides insights to uncover the context-dependent functionality of r-protein rearrangements, as they relate to what has been termed the ribosomal code, a concept that parallels that of the histone code, in which chromatin rearrangements influence gene expression. Compared to high-resolution ribosomal structures, omics methods lag when it comes to offering customized solutions to close the knowledge gap between structure and function that currently exists in riboproteomes. Purifying the riboproteome and subsequent shot-gun proteomics typically involves protein denaturation and digestion with proteases. The results are relative abundances of r-proteins at the ribosome population level. We have previously shown that, to gain insight into the stoichiometry of individual proteins, it is necessary to measure by proteomics bound r-proteins and normalize their intensities by the sum of r-protein abundances per ribosomal complex, i.e., 40S or 60S subunits. These calculations ensure that individual r-protein stoichiometries represent the fraction of each family/paralog relative to the complex, effectively revealing which r-proteins become substoichiometric in specific physiological scenarios. Here, we present an optimized method to profile the riboproteome of any organism as well as the synthesis rates of r-proteins determined by stable isotope-assisted mass spectrometry. Our method purifies the r-proteins in a reversibly denatured state, which offers the possibility for combined top-down and bottom-up proteomics. Our method offers a milder native denaturation of the r-proteome via a chaotropic GuHCl solution as compared with previous studies that use irreversible denaturation under highly acidic conditions to dissociate rRNA and r-proteins. As such, our method is better suited to conserve post-translational modifications (PTMs). Subsequently, our method carefully considers the amino acid composition of r-proteins to select an appropriate protease for digestion. We avoid non-specific protease cleavage by increasing the pH of our standardized r-proteome dilutions that enter the digestion pipeline and by using a digestion buffer that ensures an optimal pH for a reliable protease digestion process. Finally, we provide the R package ProtSynthesis to study the fractional synthesis rates of r-proteins. The package uses physiological parameters as input to determine peptide or protein fractional synthesis rates. Once the physiological parameters are measured, our equations allow a fair comparison between treatments that alter the biological equilibrium state of the system under study. Our equations correct peptide enrichment using enrichments in soluble amino acids, growth rates, and total protein accumulation. As a means of validation, our pipeline fails to find “false” enrichments in non-labeled samples while also filtering out proteins with multiple unique peptides that have different enrichment values, which are rare in our datasets. These two aspects reflect the accuracy of our tool. Our method offers the possibility of elucidating individual r-protein family/paralog abundances, PTM status, fractional synthesis rates, and dynamic assembly into ribosomal complexes if top-down and bottom-up proteomic approaches are used concomitantly, taking one step further into mapping the native and dynamic status of the r-proteome onto high-resolution ribosome structures. In addition, our method can be used to study the proteomes of all macromolecular assemblies that can be purified, although purification is the limiting step, and the efficacy and accuracy of the proteases may be limited depending on the digestion requirements.