Structural insights into vesicular monoamine storage and drug interactions.

Biogenic monoamines-vital transmitters orchestrating neurological, endocrinal and immunological functions1-5-are stored in secretory vesicles by vesicular monoamine transporters (VMATs) for controlled quantal release6,7. Harnessing proton antiport, VMATs enrich monoamines around 10,000-fold and sequester neurotoxicants to protect neurons8-10. VMATs are targeted by an arsenal of therapeutic drugs and imaging agents to treat and monitor neurodegenerative disorders, hypertension and drug addiction1,8,11-16. However, the structural mechanisms underlying these actions remain unclear. Here we report eight cryo-electron microscopy structures of human VMAT1 in unbound form and in complex with four monoamines (dopamine, noradrenaline, serotonin and histamine), the Parkinsonism-inducing MPP+, the psychostimulant amphetamine and the antihypertensive drug reserpine. Reserpine binding captures a cytoplasmic-open conformation, whereas the other structures show a lumenal-open conformation stabilized by extensive gating interactions. The favoured transition to this lumenal-open state contributes to monoamine accumulation, while protonation facilitates the cytoplasmic-open transition and concurrently prevents monoamine binding to avoid unintended depletion. Monoamines and neurotoxicants share a binding pocket that possesses polar sites for specificity and a wrist-and-fist shape for versatility. Variations in this pocket explain substrate preferences across the SLC18 family. Overall, these structural insights and supporting functional studies elucidate the mechanism of vesicular monoamine transport and provide the basis to develop therapeutics for neurodegenerative diseases and substance abuse.

Cutting Edge: The Tetraspanin CD53 Promotes CXCR4 Signaling and Bone Marrow Homing in B Cells.

B cell trafficking involves the coordinated activity of multiple adhesive and cytokine-receptor interactions, and the players in this process are not fully understood. In this study, we identified the tetraspanin CD53 as a critical regulator of both normal and malignant B cell trafficking. CXCL12 is a key chemokine in B cell homing to the bone marrow and secondary lymphoid organs, and both normal and malignant B cells from Cd53-/- mice have reduced migration toward CXCL12 in vitro, as well as impaired marrow homing in vivo. Using proximity ligation studies, we identified the CXCL12 receptor, CXCR4, as a novel, to our knowledge, CD53 binding partner. This interaction promotes receptor function, because Cd53-/- B cells display reduced signaling and internalization of CXCR4 in response to CXCL12. Together, our data suggest that CD53 interacts with CXCR4 on both normal and malignant B cells to promote CXCL12 signaling, receptor internalization, and marrow homing.

Distinct enzymatic strategies for de novo generation of disulfide bonds in membranes.

Disulfide bond formation is a catalyzed reaction essential for the folding and stability of proteins in the secretory pathway. In prokaryotes, disulfide bonds are generated by DsbB or VKOR homologs that couple the oxidation of a cysteine pair to quinone reduction. Vertebrate VKOR and VKOR-like enzymes have gained the epoxide reductase activity to support blood coagulation. The core structures of DsbB and VKOR variants share the architecture of a four-transmembrane-helix bundle that supports the coupled redox reaction and a flexible region containing another cysteine pair for electron transfer. Despite considerable similarities, recent high-resolution crystal structures of DsbB and VKOR variants reveal significant differences. DsbB activates the cysteine thiolate by a catalytic triad of polar residues, a reminiscent of classical cysteine/serine proteases. In contrast, bacterial VKOR homologs create a hydrophobic pocket to activate the cysteine thiolate. Vertebrate VKOR and VKOR-like maintain this hydrophobic pocket and further evolved two strong hydrogen bonds to stabilize the reaction intermediates and increase the quinone redox potential. These hydrogen bonds are critical to overcome the higher energy barrier required for epoxide reduction. The electron transfer process of DsbB and VKOR variants uses slow and fast pathways, but their relative contribution may be different in prokaryotic and eukaryotic cells. The quinone is a tightly bound cofactor in DsbB and bacterial VKOR homologs, whereas vertebrate VKOR variants use transient substrate binding to trigger the electron transfer in the slow pathway. Overall, the catalytic mechanisms of DsbB and VKOR variants have fundamental differences.

The tetraspanin CD53 protects stressed hematopoietic stem cells via promotion of DREAM complex-mediated quiescence.

The hematopoietic stem cell (HSC) cycle responds to inflammatory and other proliferative stressors; however, these cells must quickly return to quiescence to avoid exhaustion and maintain their functional integrity. The mechanisms that regulate this return to quiescence are not well understood. Here, we show that tetraspanin CD53 is markedly upregulated in HSCs in response to a variety of inflammatory and proliferative stimuli and that the loss of CD53 is associated with prolonged cycling and reduced HSC function in the context of inflammatory stress. Mechanistically, CD53 promotes the activity of the dimerization partner, RB-like, E2F, and multi-vulva class B (DREAM) transcriptional repressor complex, which downregulates genes associated with cycling and division. Proximity labeling and confocal fluorescence microscopy studies showed that CD53 interacts with DREAM-associated proteins, specifically promoting the interaction between Rbl2/p130 and its phosphatase protein phosphatase 2A (PP2A), effectively stabilizing p130 protein availability for DREAM binding. Together, these data identified a novel mechanism by which stressed HSCs resist cycling.

Multipattern graph convolutional network-based autism spectrum disorder identification.

The early diagnosis of autism spectrum disorder (ASD) has been extensively facilitated through the utilization of resting-state fMRI (rs-fMRI). With rs-fMRI, the functional brain network (FBN) has gained much attention in diagnosing ASD. As a promising strategy, graph convolutional networks (GCN) provide an attractive approach to simultaneously extract FBN features and facilitate ASD identification, thus replacing the manual feature extraction from FBN. Previous GCN studies primarily emphasized the exploration of topological simultaneously connection weights of the estimated FBNs while only focusing on the single connection pattern. However, this approach fails to exploit the potential complementary information offered by different connection patterns of FBNs, thereby inherently limiting the performance. To enhance the diagnostic performance, we propose a multipattern graph convolution network (MPGCN) that integrates multiple connection patterns to improve the accuracy of ASD diagnosis. As an initial endeavor, we endeavored to integrate information from multiple connection patterns by incorporating multiple graph convolution modules. The effectiveness of the MPGCN approach is evaluated by analyzing rs-fMRI scans from a cohort of 92 subjects sourced from the publicly accessible Autism Brain Imaging Data Exchange database. Notably, the experiment demonstrates that our model achieves an accuracy of 91.1% and an area under ROC curve score of 0.9742. The implementation codes are available at https://github.com/immutableJackz/MPGCN.

Towards an accurate autism spectrum disorder diagnosis: multiple connectome views from fMRI data.

Functional connectome has revealed remarkable potential in the diagnosis of neurological disorders, e.g. autism spectrum disorder. However, existing studies have primarily focused on a single connectivity pattern, such as full correlation, partial correlation, or causality. Such an approach fails in discovering the potential complementary topology information of FCNs at different connection patterns, resulting in lower diagnostic performance. Consequently, toward an accurate autism spectrum disorder diagnosis, a straightforward ambition is to combine the multiple connectivity patterns for the diagnosis of neurological disorders. To this end, we conduct functional magnetic resonance imaging data to construct multiple brain networks with different connectivity patterns and employ kernel combination techniques to fuse information from different brain connectivity patterns for autism diagnosis. To verify the effectiveness of our approach, we assess the performance of the proposed method on the Autism Brain Imaging Data Exchange dataset for diagnosing autism spectrum disorder. The experimental findings demonstrate that our method achieves precise autism spectrum disorder diagnosis with exceptional accuracy (91.30%), sensitivity (91.48%), and specificity (91.11%).

Topological properties analysis and identification of mild cognitive impairment based on individual morphological brain network connectome.

Mild cognitive impairment is considered the prodromal stage of Alzheimer's disease. Accurate diagnosis and the exploration of the pathological mechanism of mild cognitive impairment are extremely valuable for targeted Alzheimer's disease prevention and early intervention. In all, 100 mild cognitive impairment patients and 86 normal controls were recruited in this study. We innovatively constructed the individual morphological brain networks and derived multiple brain connectome features based on 3D-T1 structural magnetic resonance imaging with the Jensen-Shannon divergence similarity estimation method. Our results showed that the most distinguishing morphological brain connectome features in mild cognitive impairment patients were consensus connections and nodal graph metrics, mainly located in the frontal, occipital, limbic lobes, and subcortical gray matter nuclei, corresponding to the default mode network. Topological properties analysis revealed that mild cognitive impairment patients exhibited compensatory changes in the frontal lobe, while abnormal cortical-subcortical circuits associated with cognition were present. Moreover, the combination of multidimensional brain connectome features using multiple kernel-support vector machine achieved the best classification performance in distinguishing mild cognitive impairment patients and normal controls, with an accuracy of 84.21%. Therefore, our findings are of significant importance for developing potential brain imaging biomarkers for early detection of Alzheimer's disease and understanding the neuroimaging mechanisms of the disease.

Effects of individual metabolic brain network changes co-affected by T2DM and aging on the probabilities of T2DM: protective and risk factors.

Neuroimaging markers for risk and protective factors related to type 2 diabetes mellitus are critical for clinical prevention and intervention. In this work, the individual metabolic brain networks were constructed with Jensen-Shannon divergence for 4 groups (elderly type 2 diabetes mellitus and healthy controls, and middle-aged type 2 diabetes mellitus and healthy controls). Regional network properties were used to identify hub regions. Rich-club, feeder, and local connections were subsequently obtained, intergroup differences in connections and correlations between them and age (or fasting plasma glucose) were analyzed. Multinomial logistic regression was performed to explore effects of network changes on the probability of type 2 diabetes mellitus. The elderly had increased rich-club and feeder connections, and decreased local connection than the middle-aged among type 2 diabetes mellitus; type 2 diabetes mellitus had decreased rich-club and feeder connections than healthy controls. Protective factors including glucose metabolism in triangle part of inferior frontal gyrus, metabolic connectivity between triangle of the inferior frontal gyrus and anterior cingulate cortex, degree centrality of putamen, and risk factors including metabolic connectivities between triangle of the inferior frontal gyrus and Heschl's gyri were identified for the probability of type 2 diabetes mellitus. Metabolic interactions among critical brain regions increased in type 2 diabetes mellitus with aging. Individual metabolic network changes co-affected by type 2 diabetes mellitus and aging were identified as protective and risk factors for the likelihood of type 2 diabetes mellitus, providing guiding evidence for clinical interventions.

The tetraspanin transmembrane protein CD53 mediates dyslipidemia and integrates inflammatory and metabolic signaling in hepatocytes.

Tetraspanins are transmembrane signaling and proinflammatory proteins. Prior work demonstrates that the tetraspanin, CD53/TSPAN25/MOX44, mediates B-cell development and lymphocyte migration to lymph nodes and is implicated in various inflammatory diseases. However, CD53 is also expressed in highly metabolic tissues, including adipose and liver; yet its function outside the lymphoid compartment is not defined. Here, we show that CD53 demarcates the nutritional and inflammatory status of hepatocytes. High-fat exposure and inflammatory stimuli induced CD53 in vivo in liver and isolated primary hepatocytes. In contrast, restricting hepatocyte glucose flux through hepatocyte glucose transporter 8 deletion or through trehalose treatment blocked CD53 induction in fat- and fructose-exposed contexts. Furthermore, germline CD53 deletion in vivo blocked Western diet-induced dyslipidemia and hepatic inflammatory transcriptomic activation. Surprisingly, metabolic protection in CD53 KO mice was more pronounced in the presence of an inciting inflammatory event. CD53 deletion attenuated tumor necrosis factor alpha-induced and fatty acid + lipopolysaccharide-induced cytokine gene expression and hepatocyte triglyceride accumulation in isolated murine hepatocytes. In vivo, CD53 deletion in nonalcoholic steatohepatitis diet-fed mice blocked peripheral adipose accumulation and adipose inflammation, insulin tolerance, and liver lipid accumulation. We then defined a stabilized and trehalase-resistant trehalose polymer that blocks hepatocyte CD53 expression in basal and over-fed contexts. The data suggest that CD53 integrates inflammatory and metabolic signals in response to hepatocyte nutritional status and that CD53 blockade may provide a means by which to attenuate pathophysiology in diseases that integrate overnutrition and inflammation, such as nonalcoholic steatohepatitis and type 2 diabetes.

Open conformation of tetraspanins shapes interaction partner networks on cell membranes.

Tetraspanins, including CD53 and CD81, regulate a multitude of cellular processes through organizing an interaction network on cell membranes. Here, we report the crystal structure of CD53 in an open conformation poised for partner interaction. The large extracellular domain (EC2) of CD53 protrudes away from the membrane surface and exposes a variable region, which is identified by hydrogen-deuterium exchange as the common interface for CD53 and CD81 to bind partners. The EC2 orientation in CD53 is supported by an extracellular loop (EC1). At the closed conformation of CD81, however, EC2 disengages from EC1 and rotates toward the membrane, thereby preventing partner interaction. Structural simulation shows that EC1-EC2 interaction also supports the open conformation of CD81. Disrupting this interaction in CD81 impairs the accurate glycosylation of its CD19 partner, the target for leukemia immunotherapies. Moreover, EC1 mutations in CD53 prevent the chemotaxis of pre-B cells toward a chemokine that supports B-cell trafficking and homing within the bone marrow, a major CD53 function identified here. Overall, an open conformation is required for tetraspanin-partner interactions to support myriad cellular processes.

Wavelet transform-based frequency self-adaptive model for functional brain network.

The accurate estimation of functional brain networks is essential for comprehending the intricate relationships between different brain regions. Conventional methods such as Pearson Correlation and Sparse Representation often fail to uncover concealed information within diverse frequency bands. To address this limitation, we introduce a novel frequency-adaptive model based on wavelet transform, enabling selective capture of highly correlated frequency band sequences. Our approach involves decomposing the original time-domain signal from resting-state functional magnetic resonance imaging into distinct frequency domains, thus constructing an adjacency matrix that offers enhanced separation of features across brain regions. Comparative analysis demonstrates the superior performance of our proposed model over conventional techniques, showcasing improved clarity and distinctiveness. Notably, we achieved the highest accuracy rate of 89.01% using Sparse Representation based on Wavelet Transform, outperforming Pearson Correlation based on Wavelet Transform with an accuracy of 81.32%. Importantly, our method optimizes raw data without significantly altering feature topology, rendering it adaptable to various functional brain network estimation approaches. Overall, this innovation holds the potential to advance the understanding of brain function and furnish more accurate samples for future research and clinical applications.

Advances in mass spectrometry-based footprinting of membrane proteins.

Structural biology is entering an exciting time where many new high-resolution structures of large complexes and membrane proteins (MPs) are determined regularly. These advances have been driven by over 15 years of technological improvements, first in macromolecular crystallography, and recently in cryo-electron microscopy. Obtaining information about MP higher order structure and interactions is also a frontier, important but challenging owing to their unique properties and the need to choose suitable detergents/lipids for their study. The development of mass spectrometry (MS), both instruments and methodology in the past 10 years, has also advanced it as a complementary method to study MP structure and interactions. In this review, we discuss advances in MS-based footprinting for MPs and highlight recent methodologies that offer new promise for MP study by chemical footprinting and mass spectrometry.

The catalytic mechanism of vitamin K epoxide reduction in a cellular environment.

Vitamin K epoxide reductases (VKORs) constitute a major family of integral membrane thiol oxidoreductases. In humans, VKOR sustains blood coagulation and bone mineralization through the vitamin K cycle. Previous chemical models assumed that the catalysis of human VKOR (hVKOR) starts from a fully reduced active site. This state, however, constitutes only a minor cellular fraction (5.6%). Thus, the mechanism whereby hVKOR catalysis is carried out in the cellular environment remains largely unknown. Here we use quantitative mass spectrometry (MS) and electrophoretic mobility analyses to show that KO likely forms a covalent complex with a cysteine mutant mimicking hVKOR in a partially oxidized state. Trapping of this potential reaction intermediate suggests that the partially oxidized state is catalytically active in cells. To investigate this activity, we analyze the correlation between the cellular activity and the cellular cysteine status of hVKOR. We find that the partially oxidized hVKOR has considerably lower activity than hVKOR with a fully reduced active site. Although there are more partially oxidized hVKOR than fully reduced hVKOR in cells, these two reactive states contribute about equally to the overall hVKOR activity, and hVKOR catalysis can initiate from either of these states. Overall, the combination of MS quantification and biochemical analyses reveals the catalytic mechanism of this integral membrane enzyme in a cellular environment. Furthermore, these results implicate how hVKOR is inhibited by warfarin, one of the most commonly prescribed drugs.

Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer's disease: a preliminary study.

OBJECTIVES: Subjective cognitive decline (SCD) may be a preclinical stage of Alzheimer's disease (AD). Neuroimaging studies suggest that abnormal brain connectivity plays an important role in the pathophysiology of SCD. However, most previous studies focused on single modalities only. Multimodal combinations can more effectively utilize various information and little is known about their diagnostic value in SCD. METHODS: One hundred ten SCD individuals and well-matched healthy controls (HCs) were recruited in this study (the primary sample: 35 SCD and 36 HC; the validation sample: 21 SCD and 18 HC). Multimodal imaging data were used to construct functional, anatomical, and morphological networks, respectively. These networks were used in combination with a multiple kernel learning-support vector machine to predict SCD individuals. We validated our model on another independent sample. Multiple linear regression (MLR) analyses were conducted to investigate the relationships among network metrics, cognition, and pathological biomarkers. RESULTS: We found that the characteristics identified from the multimodal network were primarily located in the default mode network (DMN) and salience network (SN), achieving an accuracy of 88.73% (an accuracy of 79.49% for an independent sample) based on the integration of the three modalities. MLR analyses showed that increased AV45 SUVRs were significantly associated with impaired memory function, the enhanced functional connectivity, and the decreased morphological connectivity. CONCLUSION: This study suggests that abnormal multimodal connections within DMN and SN can be used as effective biomarkers to identify SCD and provide insight into understanding the pathophysiological mechanisms underlying SCD. KEY POINTS: • Multimodal brain networks improve the detection accuracy of SCD. • Abnormal connections within DMN and SN can be used as effective biomarkers for the identification of SCD.

The Tetraspanin CD53 Regulates Early B Cell Development by Promoting IL-7R Signaling.

The tetraspanin CD53 has been implicated in B cell development and function. CD53 is a transcriptional target of EBF1, a critical transcription factor for early B cell development. Further, human deficiency of CD53 results in recurrent infections and reduced serum Igs. Although prior studies have indicated a role for CD53 in regulating mature B cells, its role in early B cell development is not well understood. In this study, we show that CD53 expression, which is minimal on hematopoietic stem and progenitor cells, increases throughout bone marrow B cell maturation, and mice lacking CD53 have significantly decreased bone marrow, splenic, lymphatic, and peripheral B cells. Mixed bone marrow chimeras show that CD53 functions cell autonomously to promote B lymphopoiesis. Cd53-/- mice have reduced surface expression of IL-7Rα and diminished phosphatidylinositol 3 kinase and JAK/STAT signaling in prepro- and pro-B cells. Signaling through these pathways via IL-7R is essential for early B cell survival and transition from the pro-B to pre-B cell developmental stage. Indeed, we find increased apoptosis in developing B cells and an associated reduction in pre-B and immature B cell populations in the absence of CD53. Coimmunoprecipitation and proximity ligation studies demonstrate physical interaction between CD53 and IL-7R. Together, these data, to our knowledge, suggest a novel role for CD53 during IL-7 signaling to promote early B cell differentiation.

The Molecular Basis of FIX Deficiency in Hemophilia B.

Coagulation factor IX (FIX) is a vitamin K dependent protein and its deficiency causes hemophilia B, an X-linked recessive bleeding disorder. More than 1000 mutations in the F9 gene have been identified in hemophilia B patients. Here, we systematically summarize the structural and functional characteristics of FIX and the pathogenic mechanisms of the mutations that have been identified to date. The mechanisms of FIX deficiency are diverse in these mutations. Deletions, insertions, duplications, and indels generally lead to severe hemophilia B. Those in the exon regions generate either frame shift or inframe mutations, and those in the introns usually cause aberrant splicing. Regarding point mutations, the bleeding phenotypes vary from severe to mild in hemophilia B patients. Generally speaking, point mutations in the F9 promoter region result in hemophilia B Leyden, and those in the introns cause aberrant splicing. Point mutations in the coding sequence can be missense, nonsense, or silent mutations. Nonsense mutations generate truncated FIX that usually loses function, causing severe hemophilia B. Silent mutations may lead to aberrant splicing or affect FIX translation. The mechanisms of missense mutation, however, have not been fully understood. They lead to FIX deficiency, often by affecting FIX's translation, protein folding, protein stability, posttranslational modifications, activation to FIXa, or the ability to form functional Xase complex. Understanding the molecular mechanisms of FIX deficiency will provide significant insight for patient diagnosis and treatment.

Carbocation Footprinting of Soluble and Transmembrane Proteins.

Here, we introduce carbocations (R3C+) as laser-initiated footprinting reagents for proteins. We screened seven candidates and selected trifluomethoxy benzyl bromide (TFBB) as an effective precursor for the electrophilic trifluomethoxy benzyl carbocation (TFB+) under laser (248 nm) irradiation on the fast photochemical oxidation of proteins (FPOP) platform. Initial results demonstrate that this electrophilic cation reagent affords residue coverage of nucleophilic amino acids including H, W, M, and S. Further, the addition of TFB+ increases the hydrophobicity of the peptides so that separation of isomeric peptide products by reversed-phase LC is improved, suggesting opportunities for subresidue footprinting. Comparison of apo- and holo-myoglobin footprints shows that the TFB+ footprinting is sensitive to protein conformational change and solvent accessibility. Interestingly, because the TFB+ is amphiphilic, the reagent can potentially footprint membrane proteins as demonstrated for vitamin K epoxide reductase (VKOR) stabilized in a micelle. Not only does footprinting of the extra-membrane domain occur, but also some footprinting of the hydrophobic transmembrane domain is achieved owing to the interaction of TFB+ with the micelle. Carbocation precursors are stable and amenable for tailoring their properties and those of the incipient carbocation, enabling targeting their soluble or membrane-associated or embedded regions and distinguishing between the extra- and trans-membrane domains of membrane proteins.

Footprinting Mass Spectrometry of Membrane Proteins: Ferroportin Reconstituted in Saposin A Picodiscs.

Membrane proteins participate in a broad range of cellular processes and represent more than 60% of drug targets. One approach to their structural analyses is mass spectrometry (MS)-based footprinting including hydrogen/deuterium exchange (HDX), fast photochemical oxidation of proteins (FPOP), and residue-specific chemical modification. Studying membrane proteins usually requires their isolation from the native lipid environment, after which they often become unstable. To overcome this problem, we are pursuing a novel methodology of incorporating membrane proteins into saposin A picodiscs for MS footprinting. We apply different footprinting approaches to a model membrane protein, mouse ferroportin, in picodiscs and achieve high coverage that enables the analysis of the ferroportin structure. FPOP footprinting shows extensive labeling of the extramembrane regions of ferroportin and protection at its transmembrane regions, suggesting that the membrane folding of ferroportin is maintained throughout the labeling process. In contrast, an amphipathic reagent, N-ethylmaleimide (NEM), efficiently labels cysteine residues in both extramembrane and transmembrane regions, thereby affording complementary footprinting coverage. Finally, optimization of sample treatment gives a peptic-map of ferroportin in picodiscs with 92% sequence coverage, setting the stage for HDX. These results, taken together, show that picodiscs are a new platform broadly applicable to mass spectrometry studies of membrane proteins.

Free-Radical Membrane Protein Footprinting by Photolysis of Perfluoroisopropyl Iodide Partitioned to Detergent Micelle by Sonication.

A free-radical footprinting approach is described for integral membrane protein (IMP) that extends, significantly, the "fast photochemical oxidation of proteins" (FPOP) platform. This new approach exploits highly hydrophobic perfluoroisopropyl iodide (PFIPI) together with tip sonication to ensure efficient transport into the micelle interior, allowing laser dissociation and footprinting of the transmembrane domains. In contrast to water soluble footprinters, PFIPI footprints both the hydrophobic intramembrane and the hydrophilic extramembrane domains of the IMP vitamin K epoxide reductase (VKOR). The footprinting is fast, giving high coverage for Tyr (100 %) and Trp. The incorporation of the reagent with sonication does not significantly affect VKOR's enzymatic function, and tyrosine iodination does not compromise protease digestion and the subsequent analysis. The locations for the modifications are largely consistent with the corresponding solvent accessibilities, recommending this approach for future membrane protein footprinting.

Bringing Bioactive Compounds into Membranes: The UbiA Superfamily of Intramembrane Aromatic Prenyltransferases.

The UbiA superfamily of intramembrane prenyltransferases catalyzes a key biosynthetic step in the production of ubiquinones, menaquinones, plastoquinones, hemes, chlorophylls, vitamin E, and structural lipids. These lipophilic compounds serve as electron and proton carriers for cellular respiration and photosynthesis, as antioxidants to reduce cell damage, and as structural components of microbial cell walls and membranes. This article reviews the biological functions and enzymatic activities of representative members of the superfamily, focusing on the remarkable recent research progress revealing that the UbiA superfamily is centrally implicated in several important physiological processes and human diseases. Because prenyltransferases in this superfamily have distinctive substrate preferences, two recent crystal structures are compared to illuminate the general mechanism for substrate recognition.