Methodological approaches for the analysis of transmembrane domain interactions: A systematic review

A signal transduction blind spot: the function of adenylyl cyclase transmembrane domains

Signal transduction of external primary signals into intracellular elevations of the second messenger cyclic AMP is an ancient and universal regulatory mechanism in biology. In mammals, 9 of the 10 adenylyl cyclases (ACs) share a common topology that includes a large transmembrane (TM) domain assembled from two clusters of six helices. This domain accounts for ~ 35% of the coding sequence but, remarkably, its function is still an open question. In this viewpoint, we consider how the first primary AC sequences spurred ideas for the purpose of AC TM domains, including voltage-sensing and transporter functions. In the original conceptions of second messenger signalling, ACs were put forward as potential receptors, and we discuss emerging evidence in support of this function. We also consider growing evidence that cyclase TM helical bundles help to organise multiprotein signalling complexes by engaging in interactions with other membrane-embedded proteins. Cyclase TM regions are more diverse between isoforms than the catalytic domain-we conclude by considering how this might be exploited in therapeutic strategies targeting specific cyclase isoforms.

Transmembrane proteins in grape immunity: current knowledge and methodological advances

Transmembrane proteins (TMPs) are pivotal components of plant defence mechanisms, serving as essential mediators in the response to biotic stresses. These proteins are among the most complex and diverse within plant cells, making their study challenging. In spite of this, relatively few studies have focused on the investigation and characterization of TMPs in plants. This is particularly true for grapevine. This review aims to provide a comprehensive overview of TMP-encoding genes involved in grapevine immunity. These genes include Lysin Motif Receptor-Like Kinases (LysM-RLKs), which are involved in the recognition of pathogens at the apoplastic level, Plant Respiratory Burst Oxidase Homologs (Rbohs), which generate reactive oxygen species (ROS) for host defense, and Sugars Will Eventually be Exported Transporters (SWEETs), which play a role in nutrient allocation and stress responses. Furthermore, the review discusses the methodologies employed to study TMPs, including in vivo, in vitro and in silico approaches, highlighting their strengths and limitations. In vivo studies include the assessment of TMP function in whole plants or plant tissues, while in vitro experiments focus on isolating and characterizing either specific TMPs or their components. In silico analyses utilize computational tools to predict protein structure, function, and interactions. By identifying and characterizing genes encoding TMPs involved in grapevine immunity, researchers can develop strategies to enhance grapevine resilience and lead to more sustainable viticulture.

Chemical mapping of the surface interactome of PIEZO1 identifies CADM1 as a modulator of channel inactivation

The propeller-shaped blades of the PIEZO1 and PIEZO2 ion channels partition into the plasma membrane and respond to indentation or stretching of the lipid bilayer, thus converting mechanical forces into signals that can be interpreted by cells, in the form of calcium flux and changes in membrane potential. While PIEZO channels participate in diverse physiological processes, from sensing the shear stress of blood flow in the vasculature to detecting touch through mechanoreceptors in the skin, the molecular details that enable these mechanosensors to tune their responses over a vast dynamic range of forces remain largely uncharacterized. To survey the molecular landscape surrounding PIEZO channels at the cell surface, we employed a mass spectrometry-based proteomic approach to capture and identify extracellularly exposed proteins in the vicinity of PIEZO1. This PIEZO1-proximal interactome was enriched in surface proteins localized to cell junctions and signaling hubs within the plasma membrane. Functional screening of these interaction candidates by calcium imaging and electrophysiology in an overexpression system identified the adhesion molecule CADM1/SynCAM that slows the inactivation kinetics of PIEZO1 with little effect on PIEZO2. Conversely, we found that CADM1 knockdown accelerates inactivation of endogenous PIEZO1 in Neuro-2a cells. Systematic deletion of CADM1 domains indicates that the transmembrane region is critical for the observed effects on PIEZO1, suggesting that modulation of inactivation is mediated by interactions in or near the lipid bilayer.

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins

BACKGROUND

Most of the important biological mechanisms and functions of transmembrane proteins (TMPs) are realized through their interactions with non-transmembrane proteins(nonTMPs). The interactions between TMPs and nonTMPs in cells play vital roles in intracellular signaling, energy metabolism, investigating membrane-crossing mechanisms, correlations between disease and drugs.

RESULTS

Despite the importance of TMP-nonTMP interactions, the study of them remains in the wet experimental stage, lacking specific and comprehensive studies in the field of bioinformatics. To fill this gap, we performed a comprehensive statistical analysis of known TMP-nonTMP interactions and constructed a deep learning-based predictor to identify potential interactions. The statistical analysis describes known TMP-nonTMP interactions from various perspectives, such as distributions of species and protein families, enrichment of GO and KEGG pathways, as well as hub proteins and subnetwork modules in the PPI network. The predictor implemented by an end-to-end deep learning model can identify potential interactions from protein primary sequence information. The experimental results over the independent validation demonstrated considerable prediction performance with an MCC of 0.541.

CONCLUSIONS

To our knowledge, we were the first to focus on TMP-nonTMP interactions. We comprehensively analyzed them using bioinformatics methods and predicted them via deep learning-based solely on their sequence. This research completes a key link in the protein network, benefits the understanding of protein functions, and helps in pathogenesis studies of diseases and associated drug development.

Interaction of Substrates with γ-Secretase at the Level of Individual Transmembrane Helices-A Methodological Approach

Intramembrane proteases, such as γ secretase, typically recruit multiple substrates from an excess of single-span membrane proteins. It is currently unclear to which extent substrate recognition depends on specific interactions of their transmembrane domains (TMDs) with TMDs of a protease. Here, we investigated a large number of potential pairwise interactions between TMDs of γ secretase and a diverse set of its substrates using two different configurations of BLaTM, a genetic reporter system. Our results reveal significant interactions between TMD2 of presenilin, the enzymatic subunit of γ secretase, and the TMD of the amyloid precursor protein, as well as of several other substrates. Presenilin TMD2 is a prime candidate for substrate recruitment, as has been shown from previous studies. In addition, the amyloid precursor protein TMD enters interactions with presenilin TMD 4 as well as with the TMD of nicastrin. Interestingly, the Gly-rich interfaces between the amyloid precursor protein TMD and presenilin TMDs 2 and 4 are highly similar to its homodimerization interface. In terms of methodology, the economics of the newly developed library-based method could prove to be a useful feature in related future work for identifying heterotypic TMD-TMD interactions within other biological contexts.