Systematic in silico discovery of novel solute carrier-like proteins from proteomes

Integrative Approaches to Soybean Resilience, Productivity, and Utility: A Review of Genomics, Computational Modeling, and Economic Viability

Soybean is a vital crop globally and a key source of food, feed, and biofuel. With advancements in high-throughput technologies, soybeans have become a key target for genetic improvement. This comprehensive review explores advances in multi-omics, artificial intelligence, and economic sustainability to enhance soybean resilience and productivity. Genomics revolution, including marker-assisted selection (MAS), genomic selection (GS), genome-wide association studies (GWAS), QTL mapping, GBS, and CRISPR-Cas9, metagenomics, and metabolomics have boosted the growth and development by creating stress-resilient soybean varieties. The artificial intelligence (AI) and machine learning approaches are improving genetic trait discovery associated with nutritional quality, stresses, and adaptation of soybeans. Additionally, AI-driven technologies like IoT-based disease detection and deep learning are revolutionizing soybean monitoring, early disease identification, yield prediction, disease prevention, and precision farming. Additionally, the economic viability and environmental sustainability of soybean-derived biofuels are critically evaluated, focusing on trade-offs and policy implications. Finally, the potential impact of climate change on soybean growth and productivity is explored through predictive modeling and adaptive strategies. Thus, this study highlights the transformative potential of multidisciplinary approaches in advancing soybean resilience and global utility.

Predicting substrates for orphan solute carrier proteins using multi-omics datasets

Solute carriers (SLC) are integral membrane proteins responsible for transporting a wide variety of metabolites, signaling molecules and drugs across cellular membranes. Despite key roles in metabolism, signaling and pharmacology, around one third of SLC proteins are 'orphans' whose substrates are unknown. Experimental determination of SLC substrates is technically challenging, given the wide range of possible physiological candidates. Here, we develop a predictive algorithm to identify correlations between SLC expression levels and intracellular metabolite concentrations by leveraging existing cancer multi-omics datasets. Our predictions recovered known SLC-substrate pairs with high sensitivity and specificity compared to simulated random pairs. CRISPR-Cas9 dependency screen data and metabolic pathway adjacency data further improved the performance of our algorithm. In parallel, we combined drug sensitivity data with SLC expression profiles to predict new SLC-drug interactions. Together, we provide a novel bioinformatic pipeline to predict new substrate predictions for SLCs, offering new opportunities to de-orphanise SLCs with important implications for understanding their roles in health and disease.

A hybrid machine learning framework for functional annotation of mitochondrial glutathione transport and metabolism proteins in cancers

BACKGROUND

Alterations of metabolism, including changes in mitochondrial metabolism as well as glutathione (GSH) metabolism are a well appreciated hallmark of many cancers. Mitochondrial GSH (mGSH) transport is a poorly characterized aspect of GSH metabolism, which we investigate in the context of cancer. Existing functional annotation approaches from machine (ML) or deep learning (DL) models based only on protein sequences, were unable to annotate functions in biological contexts.

RESULTS

We develop a flexible ML framework for functional annotation from diverse feature data. This hybrid ML framework leverages cancer cell line multi-omics data and other biological knowledge data as features, to uncover potential genes involved in mGSH metabolism and membrane transport in cancers. This framework achieves strong performance across functional annotation tasks and several cell line and primary tumor cancer samples. For our application, classification models predict the known mGSH transporter SLC25A39 but not SLC25A40 as being highly probably related to mGSH metabolism in cancers. SLC25A10, SLC25A50, and orphan SLC25A24, SLC25A43 are predicted to be associated with mGSH metabolism in multiple biological contexts and structural analysis of these proteins reveal similarities in potential substrate binding regions to the binding residues of SLC25A39.

CONCLUSION

These findings have implications for a better understanding of cancer cell metabolism and novel therapeutic targets with respect to GSH metabolism through potential novel functional annotations of genes. The hybrid ML framework proposed here can be applied to other biological function classifications or multi-omics datasets to generate hypotheses in various biological contexts. Code and a tutorial for generating models and predictions in this framework are available at: https://github.com/lkenn012/mGSH_cancerClassifiers .

Cryo-EM reveals cholesterol binding in the lysosomal GPCR-like protein LYCHOS

Cholesterol plays a pivotal role in modulating the activity of mechanistic target of rapamycin complex 1 (mTOR1), thereby regulating cell growth and metabolic homeostasis. LYCHOS, a lysosome-localized G-protein-coupled receptor-like protein, emerges as a cholesterol sensor and is capable of transducing the cholesterol signal to affect the mTORC1 function. However, the precise mechanism by which LYCHOS recognizes cholesterol remains unknown. Here, using cryo-electron microscopy, we determined the three-dimensional structural architecture of LYCHOS in complex with cholesterol molecules, revealing a unique arrangement of two sequential structural domains. Through a comprehensive analysis of this structure, we elucidated the specific structural features of these two domains and their collaborative role in the process of cholesterol recognition by LYCHOS.

The impact of solute carrier proteins on disrupting substance regulation in metabolic disorders: insights and clinical applications

Carbohydrates, lipids, bile acids, various inorganic salt ions and organic acids are the main nutrients or indispensable components of the human body. Dysregulation in the processes of absorption, transport, metabolism, and excretion of these metabolites can lead to the onset of severe metabolic disorders, such as type 2 diabetes, non-alcoholic fatty liver disease, gout and hyperbilirubinemia. As the second largest membrane receptor supergroup, several major families in the solute carrier (SLC) supergroup have been found to play key roles in the transport of substances such as carbohydrates, lipids, urate, bile acids, monocarboxylates and zinc ions. Based on common metabolic dysregulation and related metabolic substances, we explored the relationship between several major families of SLC supergroup and metabolic diseases, providing examples of drugs targeting SLC proteins that have been approved or are currently in clinical/preclinical research as well as SLC-related diagnostic techniques that are in clinical use or under investigation. By highlighting these connections, we aim to provide insights that may contribute to the development of improved treatment strategies and targeted therapies for metabolic disorders.

Coupling metabolomics and exome sequencing reveals graded effects of rare damaging heterozygous variants on gene function and human traits

Genetic studies of the metabolome can uncover enzymatic and transport processes shaping human metabolism. Using rare variant aggregation testing based on whole-exome sequencing data to detect genes associated with levels of 1,294 plasma and 1,396 urine metabolites, we discovered 235 gene-metabolite associations, many previously unreported. Complementary approaches (genetic, computational (in silico gene knockouts in whole-body models of human metabolism) and one experimental proof of principle) provided orthogonal evidence that studies of rare, damaging variants in the heterozygous state permit inferences concordant with those from inborn errors of metabolism. Allelic series of functional variants in transporters responsible for transcellular sulfate reabsorption (SLC13A1, SLC26A1) exhibited graded effects on plasma sulfate and human height and pinpointed alleles associated with increased odds of diverse musculoskeletal traits and diseases in the population. This integrative approach can identify new players in incompletely characterized human metabolic reactions and reveal metabolic readouts informative of human traits and diseases.

Carnitine traffic and human fertility

Carnitine is a vital molecule in human metabolism, prominently involved in fatty acid β-oxidation within mitochondria. Predominantly sourced from dietary intake, carnitine also derives from endogenous synthesis. This review delves into the complex network of carnitine transport and distribution, emphasizing its pivotal role in human fertility. Together with its role in fatty acid oxidation, carnitine modulates the acety-CoA/CoA ratio, influencing carbohydrate metabolism, lipid biosynthesis, and gene expression. The intricate regulation of carnitine homeostasis involves a network of membrane transporters, notably OCTN2, which is central in its absorption, reabsorption, and distribution. OCTN2 dysfunction, results in Primary Carnitine Deficiency (PCD), characterized by systemic carnitine depletion and severe clinical manifestations, including fertility issues. In the male reproductive system, carnitine is crucial for sperm maturation and motility. In the female reproductive system, carnitine supports mitochondrial function necessary for oocyte quality, folliculogenesis, and embryonic development. Indeed, deficiencies in carnitine or its transporters have been linked to asthenozoospermia, reduced sperm quality, and suboptimal fertility outcomes in couples. Moreover, the antioxidant properties of carnitine protect spermatozoa from oxidative stress and help in managing conditions like polycystic ovary syndrome (PCOS) and endometriosis, enhancing sperm viability and fertilization potential of oocytes. This review summarizes the key role of membrane transporters in guaranteeing carnitine homeostasis with a special focus on the implications in fertility and possible treatments of infertility and other related disorders.

The Role of ABCB1, ABCG2, and SLC Transporters in Pharmacokinetic Parameters of Selected Drugs and Their Involvement in Drug-Drug Interactions

Membrane transporters are expressed in a wide range of tissues in the human organism. These proteins regulate the penetration of various substances such as simple ions, xenobiotics, and an extensive number of therapeutics. ABC and SLC drug transporters play a crucial role in drug absorption, distribution, and elimination. Recent decades have shown their contribution to the systemic exposure and tissue penetration of numerous drugs, thereby having an impact on pharmacokinetic and pharmacodynamic parameters. Importantly, the activity and expression of these transporters depend on numerous conditions, including intestinal microbiome profiles or health conditions. Moreover, the combined intake of other drugs or natural agents further affects the functionality of these proteins. In this review, we will discuss the involvement of ABC and SLC transporters in drug disposition. Moreover, we will present current evidence of the potential role of drug transporters as therapeutic targets.

Protein Binder Toolbox for Studies of Solute Carrier Transporters

Transporters of the solute carrier superfamily (SLCs) are responsible for the transmembrane traffic of the majority of chemical substances in cells and tissues and are therefore of fundamental biological importance. As is often the case with membrane proteins that can be heavily glycosylated, a lack of reliable high-affinity binders hinders their functional analysis. Purifying and reconstituting transmembrane proteins in their lipidic environments remains challenging and standard approaches to generate binders for multi-transmembrane proteins, such as SLCs, channels or G protein-coupled receptors (GPCRs) are lacking. While generating protein binders to 27 SLCs, we produced full length protein or cell lines as input material for binder generation by selected binder generation platforms. As a result, we obtained 525 binders for 22 SLCs. We validated the binders with a cell-based validation workflow using immunofluorescent and immunoprecipitation methods to process all obtained binders. Finally, we demonstrated the potential applications of the binders that passed our validation pipeline in structural, biochemical, and biological applications using the exemplary protein SLC12A6, an ion transporter relevant in human disease. With this work, we were able to generate easily renewable and highly specific binders against SLCs, which will greatly facilitate the study of this neglected protein family. We hope that the process will serve as blueprint for the generation of binders against the entire superfamily of SLC transporters.

ProteoMutaMetrics: machine learning approaches for solute carrier family 6 mutation pathogenicity prediction

The solute carrier transporter family 6 (SLC6) is of key interest for their critical role in the transport of small amino acids or amino acid-like molecules. Their dysfunction is strongly associated with human diseases such as including schizophrenia, depression, and Parkinson's disease. Linking single point mutations to disease may support insights into the structure-function relationship of these transporters. This work aimed to develop a computational model for predicting the potential pathogenic effect of single point mutations in the SLC6 family. Missense mutation data was retrieved from UniProt, LitVar, and ClinVar, covering multiple protein-coding transcripts. As encoding approach, amino acid descriptors were used to calculate the average sequence properties for both original and mutated sequences. In addition to the full-sequence calculation, the sequences were cut into twelve domains. The domains are defined according to the transmembrane domains of the SLC6 transporters to analyse the regions' contributions to the pathogenicity prediction. Subsequently, several classification models, namely Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) with the hyperparameters optimized through grid search were built. For estimation of model performance, repeated stratified k-fold cross-validation was used. The accuracy values of the generated models are in the range of 0.72 to 0.80. Analysis of feature importance indicates that mutations in distinct regions of SLC6 transporters are associated with an increased risk for pathogenicity. When applying the model on an independent validation set, the performance in accuracy dropped to averagely 0.6 with high precision but low sensitivity scores.

TreeViewer: Flexible, modular software to visualise and manipulate phylogenetic trees

Phylogenetic trees illustrate evolutionary relationships between taxa or genes. Tree figures are crucial when presenting results and data, and by creating clear and effective plots, researchers can describe many kinds of evolutionary patterns. However, producing tree plots can be a time-consuming task, especially as multiple different programs are often needed to adjust and illustrate all data associated with a tree. We present TreeViewer, a new software to draw phylogenetic trees. TreeViewer is flexible, modular, and user-friendly. Plots are produced as the result of a user-defined pipeline, which can be finely customised and easily applied to different trees. Every feature of the program is documented and easily accessible, either in the online manual or within the program's interface. We show how TreeViewer can be used to produce publication-ready figures, saving time by not requiring additional graphical post-processing tools. TreeViewer is freely available for Windows, macOS, and Linux operating systems and distributed under an AGPLv3 licence from https://treeviewer.org. It has a graphical user interface (GUI), as well as a command-line interface, which is useful to work with very large trees and for automated pipelines. A detailed user manual with examples and tutorials is also available. TreeViewer is mainly aimed at users wishing to produce highly customised, publication-quality tree figures using a single GUI software tool. Compared to other GUI tools, TreeViewer offers a richer feature set and a finer degree of customisation. Compared to command-line-based tools and software libraries, TreeViewer's graphical interface is more accessible. The flexibility of TreeViewer's approach to phylogenetic tree plotting enables the program to produce a wide variety of publication-ready figures. Users are encouraged to create their own custom modules to expand the functionalities of the program. This sets the scene for an ever-expanding and ever-adapting software framework that can easily adjust to respond to new challenges.

Apical annuli are specialised sites of post-invasion secretion of dense granules in Toxoplasma

Apicomplexans are ubiquitous intracellular parasites of animals. These parasites use a programmed sequence of secretory events to find, invade, and then re-engineer their host cells to enable parasite growth and proliferation. The secretory organelles micronemes and rhoptries mediate the first steps of invasion. Both secrete their contents through the apical complex which provides an apical opening in the parasite's elaborate inner membrane complex (IMC) - an extensive subpellicular system of flattened membrane cisternae and proteinaceous meshwork that otherwise limits access of the cytoplasm to the plasma membrane for material exchange with the cell exterior. After invasion, a second secretion programme drives host cell remodelling and occurs from dense granules. The site(s) of dense granule exocytosis, however, has been unknown. In Toxoplasma gondii, small subapical annular structures that are embedded in the IMC have been observed, but the role or significance of these apical annuli to plasma membrane function has also been unknown. Here, we determined that integral membrane proteins of the plasma membrane occur specifically at these apical annular sites, that these proteins include SNARE proteins, and that the apical annuli are sites of vesicle fusion and exocytosis. Specifically, we show that dense granules require these structures for the secretion of their cargo proteins. When secretion is perturbed at the apical annuli, parasite growth is strongly impaired. The apical annuli, therefore, represent a second type of IMC-embedded structure to the apical complex that is specialised for protein secretion, and reveal that in Toxoplasma there is a physical separation of the processes of pre- and post-invasion secretion that mediate host-parasite interactions.

Experimental and Computational Analysis of Newly Identified Pathogenic Mutations in the Creatine Transporter SLC6A8

Creatine is an essential metabolite for the storage and rapid supply of energy in muscle and nerve cells. In humans, impaired metabolism, transport, and distribution of creatine throughout tissues can cause varying forms of mental disability, also known as creatine deficiency syndrome (CDS). So far, 80 mutations in the creatine transporter (SLC6A8) have been associated to CDS. To better understand the effect of human genetic variants on the physiology of SLC6A8 and their possible impact on CDS, we studied 30 missense variants including 15 variants of unknown significance, two of which are reported here for the first time. We expressed these variants in HEK293 cells and explored their subcellular localization and transport activity. We also applied computational methods to predict variant effect and estimate site-specific changes in thermodynamic stability. To explore variants that might have a differential effect on the transporter's conformers along the transport cycle, we constructed homology models of the inward facing, and outward facing conformations. In addition, we used mass-spectrometry to study proteins that interact with wild type SLC6A8 and five selected variants in HEK293 cells. In silico models of the protein complexes revealed how two variants impact the interaction interface of SLC6A8 with other proteins and how pathogenic variants lead to an enrichment of ER protein partners. Overall, our integrated analysis disambiguates the pathogenicity of 15 variants of unknown significance revealing diverse mechanisms of pathogenicity, including two previously unreported variants obtained from patients suffering from the creatine deficiency syndrome.

Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine

The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments.

Transporter-Mediated Drug Delivery

Transmembrane transport of small organic and inorganic molecules is one of the cornerstones of cellular metabolism. Among transmembrane transporters, solute carrier (SLC) proteins form the largest, albeit very diverse, superfamily with over 400 members. It was recognized early on that xenobiotics can directly interact with SLCs and that this interaction can fundamentally determine their efficacy, including bioavailability and intertissue distribution. Apart from the well-established prodrug strategy, the chemical ligation of transporter substrates to nanoparticles of various chemical compositions has recently been used as a means to enhance their targeting and absorption. In this review, we summarize efforts in drug design exploiting interactions with specific SLC transporters to optimize their therapeutic effects. Furthermore, we describe current and future challenges as well as new directions for the advanced development of therapeutics that target SLC transporters.

A structure and evolutionary-based classification of solute carriers

Solute carriers are an operationally defined diverse family of membrane proteins involved in the transport of nutrients, metabolites, xenobiotics, and drugs. Here, we provide an integrative classification of solute carriers by combining evolutionary information with proteome-wide structure models recently made available through the AlphaFold resource. Analyses of orthologous relations among 455 protein-coding genes currently classified as human solute carriers, over the fully sequenced genomes of 2,100 species, suggest no more than approximately 180 independent evolutionary origins. Structural comparative analyses provided further insight revealing a total of 24 structurally distinct transmembrane folds, increasing by approximately 40% the number of previously described SLC structural folds. In addition, a structural comparative analysis identified a new human solute carrier member and revealed details of noncanonical ones. Our analyses uncover new ancestral relations between solute carrier genes, provide insights into the evolution of remote homologs and a platform to test hypotheses of functional deorphanization.