Clustering of the Membrane Protein by Molecular Self-Assembly Downregulates the Signaling Pathway for Cancer Cell Inhibition.

This work reports a cyclic peptide appended self-assembled scaffold that recognizes the membrane protein EGFR and arrests the EGFR signaling through multivalent interactions by assembly-induced aggregation. When incubated with cells, the oligomers of PAD-1 first recognize the overexpressed EGFR on cancer cell membranes for arresting EGFR, which then initiates cellular uptake through endocytosis. The accumulation of PAD-1 and EGFR in the lysosome results in the formation of nanofibers, leading to the lysosomal membrane permeabilization (LMP). These processes disrupt the homeostasis of EGFR and inhibit the downstream signaling transduction of EGFR for cancer cell survival. Moreover, LMP induced the release of protein aggregates that could generate endoplasmic reticulum (ER) stress, resulting in cancer cell death selectively. In vivo studies indicate the efficient antitumor efficiency of PAD-1 in tumor-bearing mice. As a first example, this work provides an alternative strategy for controlling protein behavior for tuning cellular events in living cells.

Proximity labeling and identification of endogenous client proteins recruited to Y15-based artificial granules tethering a bait protein.

Protein clustering is a ubiquitous event in diverse cellular processes. Self-association of proteins triggers recruitment of downstream proteins to regulate cellular signaling. To investigate the interactions in detail, chemical biology tools to identify proteins recruited to defined assemblies are required. Here, we exploit an identification of proteins recruited in artificial granules (IPRAG) platform that combines intracellular Y15-based supramolecule construction with a proximity labeling method. We validated the IPRAG tool using Nck1 as a target bait protein. We constructed Nck1-tethering granules, labeled the recruited proteins with biotin, and analyzed them by LC-MS/MS. As a result, we successfully identified proteins that directly or indirectly interact with Nck1.

Munc18-dependent and -independent clustering of syntaxin in the plasma membrane of cultured endocrine cells.

Syntaxin helps in catalyzing membrane fusion during exocytosis. It also forms clusters in the plasma membrane, where both its transmembrane and SNARE domains are thought to homo-oligomerize. To study syntaxin clustering in live PC12 cells, we labeled granules with neuropeptide-Y-mCherry and syntaxin clusters with syntaxin-1a green fluorescent protein (GFP). Abundant clusters appeared under total internal reflection (TIRF) illumination, and some of them associated with granules ("on-granule clusters"). Syntaxin-1a-GFP or its mutants were expressed at low levels and competed with an excess of endogenous syntaxin for inclusion into clusters. On-granule inclusion was diminished by mutations known to inhibit binding to Munc18-1 in vitro. Knock-down of Munc18-1 revealed Munc18-dependent and -independent on-granule clustering. Clustering was inhibited by mutations expected to break salt bridges between syntaxin's Hb and SNARE domains and was rescued by additional mutations expected to restore them. Most likely, syntaxin is in a closed conformation when it clusters on granules, and its SNARE and Hb domains approach to within atomic distances. Pairwise replacements of Munc18-contacting residues with alanines had only modest effects, except that the pair R114A/I115A essentially abolished on-granule clustering. In summary, an on-granule cluster arises from the specific interaction between a granule and a dense cluster of syntaxin-Munc18-1 complexes. Off-granule clusters, by contrast, were resistant to even the strongest mutations we tried and required neither Munc18-1 nor the presence of a SNARE domain. They may well form through the nonstoichiometric interactions with membrane lipids that others have observed in cell-free systems.

Calcium levels in the Golgi complex regulate clustering and apical sorting of GPI-APs in polarized epithelial cells.

Glycosylphosphatidylinositol-anchored proteins (GPI-APs) are lipid-associated luminal secretory cargoes selectively sorted to the apical surface of the epithelia where they reside and play diverse vital functions. Cholesterol-dependent clustering of GPI-APs in the Golgi is the key step driving their apical sorting and their further plasma membrane organization and activity; however, the specific machinery involved in this Golgi event is still poorly understood. In this study, we show that the formation of GPI-AP homoclusters (made of single GPI-AP species) in the Golgi relies directly on the levels of calcium within cisternae. We further demonstrate that the TGN calcium/manganese pump, SPCA1, which regulates the calcium concentration within the Golgi, and Cab45, a calcium-binding luminal Golgi resident protein, are essential for the formation of GPI-AP homoclusters in the Golgi and for their subsequent apical sorting. Down-regulation of SPCA1 or Cab45 in polarized epithelial cells impairs the oligomerization of GPI-APs in the Golgi complex and leads to their missorting to the basolateral surface. Overall, our data reveal an unexpected role for calcium in the mechanism of GPI-AP apical sorting in polarized epithelial cells and identify the molecular machinery involved in the clustering of GPI-APs in the Golgi.

In Situ DNA Self-Assembly on the Cell Surface Drives Unidirectional Clustering of Membrane Proteins for the Modulation of Cell Behaviors.

Cell membrane proteins play a pivotal role in regulating intracellular signal transductions and cell behaviors. Many membrane proteins form clusters in order to initiate downstream signaling pathways for the modulation of cell behaviors. Developing rational methods to program the in situ clustering of designated membrane proteins on the cell surface to form large assemblies remains challenging. Here we use the membrane-anchored DNA hybridization chain reaction (HCR) to induce DNA self-assembly on the live cell surface and drive the unidirectional clustering of membrane proteins for the modulation of cell behaviors. Reactive DNA strands are specifically anchored onto the membrane proteins of interest by using DNA aptamers. Upon activation, the chain reaction between the protein-anchored DNA strands drives the assembly of membrane proteins forming one-dimensional clusters. We demonstrate both homogeneous and heterogeneous clustering of membrane proteins on multiple cell types that exhibit a potent capability for modulating cell behaviors including migration, proliferation, and survival.

Genome-Wide Identification and Characterization of the Calmodulin-Binding Transcription Activator (CAMTA) Gene Family in Plants and the Expression Pattern Analysis of CAMTA3/SR1 in Tomato under Abiotic Stress.

Calmodulin-binding transcription activator (CAMTA) plays an important regulatory role in plant growth, development, and stress response. This study identified the phylogenetic relationships of the CAMTA family in 42 plant species using a genome-wide search approach. Subsequently, the evolutionary relationships, gene structures, and conservative structural domain of CAMTA3/SR1 in different plants were analyzed. Meanwhile, in the promoter region, the cis-acting elements, protein clustering interaction, and tissue-specific expression of CAMTA3/SR1 in tomato were identified. The results show that SlCAMTA3/SR1 genes possess numerous cis-acting elements related to hormones, light response, and stress in the promoter regions. SlCAMTA3 might act together with other Ca2+ signaling components to regulate Ca2+-related biological processes. Then, the expression pattern of SlCAMTA3/SR1 was also investigated by quantitative real-time PCR (qRT-PCR) analysis. The results show that SlCAMTA3/SR1 might respond positively to various abiotic stresses, especially Cd stress. The expression of SlCAMTA3/SR1 was scarcely detected in tomato leaf at the seedling and flowering stages, whereas SlCAMTA3/SR1 was highly expressed in the root at the seedling stage. In addition, SlCAMTA3/SR1 had the highest expression levels in flowers at the reproductive stage. Here, we provide a basic reference for further studies about the functions of CAMTA3/SR1 proteins in plants.

Entropic forces drive clustering and spatial localization of influenza A M2 during viral budding.

The influenza A matrix 2 (M2) transmembrane protein facilitates virion release from the infected host cell. In particular, M2 plays a role in the induction of membrane curvature and/or in the scission process whereby the envelope is cut upon virion release. Here we show using coarse-grained computer simulations that various M2 assembly geometries emerge due to an entropic driving force, resulting in compact clusters or linearly extended aggregates as a direct consequence of the lateral membrane stresses. Conditions under which these protein assemblies will cause the lipid membrane to curve are explored, and we predict that a critical cluster size is required for this to happen. We go on to demonstrate that under the stress conditions taking place in the cellular membrane as it undergoes large-scale membrane remodeling, the M2 protein will, in principle, be able to both contribute to curvature induction and sense curvature to line up in manifolds where local membrane line tension is high. M2 is found to exhibit linactant behavior in liquid-disordered-liquid-ordered phase-separated lipid mixtures and to be excluded from the liquid-ordered phase, in near-quantitative agreement with experimental observations. Our findings support a role for M2 in membrane remodeling during influenza viral budding both as an inducer and a sensor of membrane curvature, and they suggest a mechanism by which localization of M2 can occur as the virion assembles and releases from the host cell, independent of how the membrane curvature is produced.

Submillisecond Freezing Permits Cryoprotectant-Free EPR Double Electron-Electron Resonance Spectroscopy.

Double electron-electron resonance (DEER) EPR spectroscopy is a powerful method for obtaining distance distributions between pairs of engineered nitroxide spin-labels in proteins and other biological macromolecules. These measurements require the use of cryogenic temperatures (77 K or less) to prolong the phase memory relaxation time (Tm ) sufficiently to enable detection of a DEER echo curve. Generally, a cryoprotectant such as glycerol is added to protein samples to facilitate glass formation and avoid protein clustering (which can result in a large decrease in Tm ) during relatively slow flash freezing in liquid N2 . However, cryoprotectants are osmolytes and can influence protein folding/unfolding equilibria, as well as species populations in weak multimeric systems. Here we show that submillisecond rapid freezing, achieved by high velocity spraying of the sample onto a rapidly spinning, liquid nitrogen cooled copper disc obviates the requirement for cryoprotectants and permits high quality DEER data to be obtained in absence of glycerol. We demonstrate this approach on five different protein systems: protein A, the metastable drkN SH3 domain, urea-unfolded drkN SH3, HIV-1 reverse transcriptase, and the transmembrane domain of HIV-1 gp41 in lipid bicelles.

Stability Analysis of a Bulk-Surface Reaction Model for Membrane Protein Clustering.

Protein aggregation on the plasma membrane (PM) is of critical importance to many cellular processes such as cell adhesion, endocytosis, fibrillar conformation, and vesicle transport. Lateral diffusion of protein aggregates or clusters on the surface of the PM plays an important role in governing their heterogeneous surface distribution. However, the stability behavior of the surface distribution of protein aggregates remains poorly understood. Therefore, understanding the spatial patterns that can emerge on the PM solely through protein-protein interaction, lateral diffusion, and feedback is an important step toward a complete description of the mechanisms behind protein clustering on the cell surface. In this work, we investigate the pattern formation of a reaction-diffusion model that describes the dynamics of a system of ligand-receptor complexes. The purely diffusive ligand in the cytosol can bind receptors in the PM and the resultant ligand-receptor complexes not only diffuse laterally but can also form clusters resulting in different oligomers. Finally, the largest oligomers recruit ligands from the cytosol using positive feedback. From a methodological viewpoint, we provide theoretical estimates for diffusion-driven instabilities of the protein aggregates based on the Turing mechanism. Our main result is a threshold phenomenon, in which a sufficiently high recruitment of ligands promotes the input of new monomeric components and consequently drives the formation of a single-patch spatially heterogeneous steady state.

Dissecting single-cell molecular spatiotemporal mobility and clustering at focal adhesions in polarised cells by fluorescence fluctuation spectroscopy methods.

Quantitative fluorescence fluctuation spectroscopy from optical microscopy datasets is a very powerful tool to resolve multiple spatiotemporal cellular and subcellular processes at the molecular level. In particular, raster image correlation spectroscopy (RICS) and number and brightness analyses (N&B) yield molecular mobility and clustering dynamic information extracted from real-time cellular processes. This quantitative information can be inferred in a highly flexible and detailed manner, i.e. 1) at the localisation level: from full-frame datasets and multiple regions of interest within; and 2) at the temporal level: not only from full-frame and multiple regions, but also intermediate temporal events. Here we build on previous research in deciphering the molecular dynamics of paxillin, a main component of focal adhesions. Cells use focal adhesions to attach to the extracellular matrix and interact with their local environment. Through focal adhesions and other adhesion structures, cells sense their local environment and respond accordingly; due to this continuous communication, these structures can be highly dynamic depending on the extracellular characteristics. By using a previously well-characterised model like paxillin, we examine the powerful sensitivity and some limitations of RICS and N&B analyses. We show that cells upon contact to different surfaces show differential self-assembly dynamics in terms of molecular diffusion and oligomerisation. In addition, single-cell studies show that these dynamics change gradually following an antero-posterior gradient.

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia.

BACKGROUND: Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly dependent on the quality of the model construction algorithms and the specific methods used to compare the ensuing models. Thus far, reliable and robust methods that can group the IG 3D models based on their structural characteristics are missing. RESULTS: Here we propose a novel method for clustering a set of proteins based on their 3D structure focusing on 3D structures of BcR IG from a large series of patients with CLL. The method combines techniques from the areas of bioinformatics, 3D object recognition and machine learning. The clustering procedure is based on the extraction of 3D descriptors, encoding various properties of the local and global geometrical structure of the proteins. The descriptors are extracted from aligned pairs of proteins. A combination of individual 3D descriptors is also used as an additional method. The comparison of the automatically generated clusters to manual annotation by experts shows an increased accuracy when using the 3D descriptors compared to plain bioinformatics-based comparison. The accuracy is increased even more when using the combination of 3D descriptors. CONCLUSIONS: The experimental results verify that the use of 3D descriptors commonly used for 3D object recognition can be effectively applied to distinguishing structural differences of proteins. The proposed approach can be applied to provide hints for the existence of structural groups in a large set of unannotated BcR IG protein files in both CLL and, by logical extension, other contexts where it is relevant to characterize BcR IG structural similarity. The method does not present any limitations in application and can be extended to other types of proteins.

A phenomenological model of cell-cell adhesion mediated by cadherins.

We present a phenomenological model intended to describe at the protein population level the formation of cell-cell junctions by the local recruitment of homophilic cadherin adhesion receptors. This modeling may have a much wider implication in biological processes since many adhesion receptors, channel proteins and other membrane-born proteins associate in clusters or oligomers at the cell surface. Mathematically, it consists in a degenerate reaction-diffusion system of two partial differential equations modeling the time-space evolution of two cadherin populations over a surface: the first one represents the diffusing cadherins and the second one concerns the fixed ones. After discussing the stability of the solutions of the model, we perform numerical simulations and show relevant analogies with experimental results. In particular, we show patterns or aggregates formation for a certain set of parameters. Moreover, perturbing the stationary solution, both density populations converge in large times to some saturation level. Finally, an exponential rate of convergence is numerically obtained and is shown to be in agreement, for a suitable set of parameters, with the one obtained in some in vitro experiments.

Do mechanical forces contribute to nanoscale membrane organisation in T cells?

Mechanotransduction describes how a cell senses and interacts with its environment. The concept originated in adhesion biology where adhesion receptors, integrins, facilitate force transmission between the extracellular matrix and the intracellular actin cytoskeleton. Indeed, during any adhesive contacts, cells do exert mechanical force. Hence, the probing of the local environment by cells results in mechanical cues that contribute to cellular functions and cell fate decisions such as migration, proliferation, differentiation and apoptosis. On the molecular level, mechanical forces can rearrange proteins laterally within the membrane, regulate their activity by inducing conformational changes and probe the mechanical properties and bond strength of receptor-ligands. From this point of view, it appears surprising that molecular forces have been largely overlooked in membrane organisation and ligand discrimination processes in lymphocytes. During T cell activation, the T cell receptor recognises and distinguishes antigenic from benign endogenous peptides to initiate the reorganisation of membrane proteins into signalling clusters within the immunological synapse. In this review, we asked whether characteristics of fibroblast force sensing could be applied to immune cell antigen recognition and signalling, and outline state-of-the-art experimental strategies for studying forces in the context of membrane organisation. This article is part of a Special Issue entitled: Nanoscale membrane orgainisation and signalling.

Serotonin transporter clustering in blood lymphocytes predicts the outcome on anhedonia scores in naïve depressive patients treated with antidepressant medication.

BACKGROUND: We have shown that serotonin transporter (SERT) clustering in blood lymphocytes is altered in major depression and correlates with pharmacological therapeutic responses measured with the Hamilton scale. In the present report, we extend these results to the self-assessment anhedonia scale, as anhedonia is a cardinal symptom of major depression that is difficult to treat with first-line antidepressants. METHODS: We collected blood samples from 38 untreated depression patients at the time of enrolment and 8 weeks after pharmacological treatment. We used the self-assessment anhedonia scale to evaluate anhedonia symptoms before and after treatment. We also used quantitative immunocytochemistry to measure SERT clusters in blood lymphocytes. RESULTS: Evaluation of the distribution of SERT clusters size in the plasma membrane of lymphocytes identified two subpopulations of naive depression patients: Depression I (D-I) and Depression II (D-II). While naïve D-I and D-II patients initially showed similar anhedonia scores, D-II patients showed a good response in anhedonia symptoms after 8 weeks of psychopharmacological treatment, whereas D-I patients failed to show any improvement. Psychopharmacological treatment also induced an increase in the number of SERT clusters in lymphocytes in the D-II group, and this increase correlated with the improvement in anhedonia symptoms. CONCLUSIONS: SERT clustering in peripheral lymphocytes can be used to identify patient response to antidepressant therapy as ascertained by anhedonia scores.

Discovery of a Thermostable Tagatose 4-Epimerase Powered by Structure- and Sequence-Based Protein Clustering.

d-Tagatose is a highly promising functional sweetener known for its various physiological functions. In this study, a novel tagatose 4-epimerase from Thermoprotei archaeon (Thar-T4Ease), with the ability to convert d-fructose to d-tagatose, was discovered through a combination of structure similarity search and sequence-based protein clustering. The recombinant Thar-T4Ease exhibited optimal activity at pH 8.5 and 85 °C, in the presence of 1 mM Ni2+. Its kcat and kcat/Km values toward d-fructose were measured to be 248.5 min-1 and 2.117 mM-1·min-1, respectively. Notably, Thar-T4Ease exhibited remarkable thermostability, with a t1/2 value of 198 h at 80 °C. Moreover, it achieved a conversion ratio of 18.9% using 100 g/L d-fructose as the substrate. Finally, based on sequence and structure analysis, crucial residues for the catalytic activity of Thar-T4Ease were identified by molecular docking and site-directed mutagenesis. This research expands the repertoire of enzymes with C4-epimerization activity and opens up new possibilities for the cost-effective production of d-tagatose from d-fructose.

Creating a bionic scaffold via light-curing liquid crystal ink to reveal the role of osteoid-like microenvironment in osteogenesis.

Osteoid plays a crucial role in directing cell behavior and osteogenesis through its unique characteristics, including viscoelasticity and liquid crystal (LC) state. Thus, integrating osteoid-like features into 3D printing scaffolds proves to be a promising approach for personalized bone repair. Despite extensive research on viscoelasticity, the role of LC state in bone repair has been largely overlooked due to the scarcity of suitable LC materials. Moreover, the intricate interplay between LC state and viscoelasticity in osteogenesis remains poorly understood. Here, we developed innovative hydrogel scaffolds with osteoid-like LC state and viscoelasticity using digital light processing with a custom LC ink. By utilizing these LC scaffolds as 3D research models, we discovered that LC state mediates high protein clustering to expose accessible RGD motifs to trigger cell-protein interactions and osteogenic differentiation, while viscoelasticity operates via mechanotransduction pathways. Additionally, our investigation revealed a synergistic effect between LC state and viscoelasticity, amplifying cell-protein interactions and osteogenic mechanotransduction processes. Furthermore, the interesting mechanochromic response observed in the LC hydrogel scaffolds suggests their potential application in mechanosensing. Our findings shed light on the mechanisms and synergistic effects of LC state and viscoelasticity in osteoid on osteogenesis, offering valuable insights for the biomimetic design of bone repair scaffolds.

Rapid Optogenetic Clustering in the Cytoplasm with BcLOVclust.

Protein clustering is a powerful form of optogenetic control, yet remarkably few proteins are known to oligomerize with light. Recently, the photoreceptor BcLOV4 was found to form protein clusters in mammalian cells in response to blue light, although clustering coincided with its translocation to the plasma membrane, potentially constraining its application as an optogenetic clustering module. Herein we identify key amino acids that couple BcLOV4 clustering to membrane binding, allowing us to engineer a variant that clusters in the cytoplasm and does not associate with the membrane in response to blue light. This variant-called BcLOVclust-clustered over many cycles with substantially faster clustering and de-clustering kinetics compared to the widely used optogenetic clustering protein Cry2. The magnitude of clustering could be strengthened by appending an intrinsically disordered region from the fused in sarcoma (FUS) protein, or by selecting the appropriate fluorescent protein to which it was fused. Like wt BcLOV4, BcLOVclust activity was sensitive to temperature: light-induced clusters spontaneously dissolved at a rate that increased with temperature despite constant illumination. At low temperatures, BcLOVclust and Cry2 could be multiplexed in the same cells, allowing light control of independent protein condensates. BcLOVclust could also be applied to control signaling proteins and stress granules in mammalian cells. While its usage is currently best suited in cells and organisms that can be cultured below ∼30 °C, a deeper understanding of BcLOVclust thermal response will further enable its use at physiological mammalian temperatures.

Actin cytoskeleton differently regulates cell surface organization of GPI-anchored proteins in polarized epithelial cells and fibroblasts.

The spatiotemporal compartmentalization of membrane-associated glycosylphosphatidylinositol-anchored proteins (GPI-APs) on the cell surface regulates their biological activities. These GPI-APs occupy distinct cellular functions such as enzymes, receptors, and adhesion molecules, and they are implicated in several vital cellular processes. Thus, unraveling the mechanisms and regulators of their membrane organization is essential. In polarized epithelial cells, GPI-APs are enriched at the apical surface, where they form small cholesterol-independent homoclusters and larger heteroclusters accommodating multiple GPI-AP species, all confined within areas of approximately 65-70 nm in diameter. Notably, GPI-AP homoclustering occurs in the Golgi apparatus through a cholesterol- and calcium-dependent mechanism that drives their apical sorting. Despite the critical role of Golgi GPI-AP clustering in their cell surface organization and the importance of cholesterol in heterocluster formation, the regulatory mechanisms governing GPI-AP surface organization, particularly in the context of epithelial polarity, remain elusive. Given that the actin cytoskeleton undergoes substantial remodeling during polarity establishment, this study explores whether the actin cytoskeleton regulates the spatiotemporal apical organization of GPI-APs in MDCK cells. Utilizing various imaging techniques (number and brightness, FRET/FLIM, and dSTORM coupled to pair correlation analysis), we demonstrate that the apical organization of GPI-APs, at different scales, does not rely on the actin cytoskeleton, unlike in fibroblastic cells. Interestingly, calcium chelation disrupts the organization of GPI-APs at the apical surface by impairing Golgi GPI-AP clustering, emphasizing the existence of an interplay among Golgi clustering, apical sorting, and surface organization in epithelial cells. In summary, our findings unveil distinct mechanisms regulating the organization of GPI-APs in cell types of different origins, plausibly allowing them to adapt to different external signals and different cellular environments in order to achieve specialized functions.

Complet+: a computationally scalable method to improve completeness of large-scale protein sequence clustering.

A major challenge for clustering algorithms is to balance the trade-off between homogeneity, i.e., the degree to which an individual cluster includes only related sequences, and completeness, the degree to which related sequences are broken up into multiple clusters. Most algorithms are conservative in grouping sequences with other sequences. Remote homologs may fail to be clustered together and instead form unnecessarily distinct clusters. The resulting clusters have high homogeneity but completeness that is too low. We propose Complet+, a computationally scalable post-processing method to increase the completeness of clusters without an undue cost in homogeneity. Complet+ proves to effectively merge closely-related clusters of protein that have verified structural relationships in the SCOPe classification scheme, improving the completeness of clustering results at little cost to homogeneity. Applying Complet+ to clusters obtained using MMseqs2's clusterupdate achieves an increased V-measure of 0.09 and 0.05 at the SCOPe superfamily and family levels, respectively. Complet+ also creates more biologically representative clusters, as shown by a substantial increase in Adjusted Mutual Information (AMI) and Adjusted Rand Index (ARI) metrics when comparing predicted clusters to biological classifications. Complet+ similarly improves clustering metrics when applied to other methods, such as CD-HIT and linclust. Finally, we show that Complet+ runtime scales linearly with respect to the number of clusters being post-processed on a COG dataset of over 3 million sequences. Code and supplementary information is available on Github: https://github.com/EESI/Complet-Plus.

Clustering Highly Divergent Homologous Proteins: An Alignment-Free Method.

The comparative analysis of amino acid sequences is an important tool in molecular biology that often requires multiple sequence alignments. In comparisons between less closely related genomes, however, it becomes more difficult to accurately align protein-coding sequences, or even to identify homologous regions in different genomes. In this article, we describe an alignment-free method for the classification of homologous protein-coding regions from different genomes. This methodology was originally developed for comparing genomes within virus families, but may be adapted for other organisms. We quantify sequence homology from the overlap (intersection distance) of the k-mer (word) frequency distributions for different protein sequences. Next, we extract groups of homologous sequences from the resulting distance matrix using a combination of dimensionality reduction and hierarchical clustering methods. Finally, we demonstrate how to generate visualizations of the composition of clusters with respect to protein annotations, and by coloring protein-coding regions of genomes by cluster assignments. These provide a useful means to quickly assess the reliability of the clustering results based on the distribution of homologous genes among genomes. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Data collection and processing Basic Protocol 2: Calculating k-mer distances Basic Protocol 3: Extracting clusters of homology Support Protocol: Genome plot based on clustering results.