Development of pluripotent stem cell-derived epidermal organoids that generate effective extracellular vesicles in skin regeneration.

Cellular skin substitutes such as epidermal constructs have been developed for various applications, including wound healing and skin regeneration. These cellular models are mostly derived from primary cells such as keratinocytes and fibroblasts in a two-dimensional (2D) state, and further development of three-dimensional (3D) cultured organoids is needed to provide insight into the in vivo epidermal phenotype and physiology. Here, we report the development of epidermal organoids (EpiOs) generated from induced pluripotent stem cells (iPSCs) as a novel epidermal construct and its application as a source of secreted biomolecules recovered by extracellular vesicles (EVs) that can be utilized for cell-free therapy of regenerative medicine. Differentiated iPSC-derived epidermal organoids (iEpiOs) are easily cultured and expanded through multiple organoid passages, while retaining molecular and functional features similar to in vivo epidermis. These mature iEpiOs contain epidermal stem cell populations and retain the ability to further differentiate into other skin compartment lineages, such as hair follicle stem cells. By closely recapitulating the epidermal structure, iEpiOs are expected to provide a more relevant microenvironment to influence cellular processes and therapeutic response. Indeed, iEpiOs can generate high-performance EVs containing high levels of the angiogenic growth factor VEGF and miRNAs predicted to regulate cellular processes such as proliferation, migration, differentiation, and angiogenesis. These EVs contribute to target cell proliferation, migration, and angiogenesis, providing a promising therapeutic tool for in vivo wound healing. Overall, the newly developed iEpiOs strategy as an organoid-based approach provides a powerful model for studying basic and translational skin research and may also lead to future therapeutic applications using iEpiOs-secreted EVs.

Diphenolic boldine, an aporphine alkaloid: inhibitory effect evaluation on α-glucosidase by molecular dynamics integrating enzyme kinetics.

Screening α-glucosidase inhibitors with novel structures is an important field in the development of anti-diabetic drugs due to their application in postprandial hyperglycemia control. Boldine is one of the potent natural antioxidants with a wide range of pharmacological activities. Virtual screening and biochemical inhibition kinetics combined with molecular dynamics simulations were conducted to verify the inactivation function of boldine on α-glucosidase. A series of inhibition kinetics and spectrometry detections were conducted to analyze the α-glucosidase inhibition. Computational simulations of molecular dynamics/docking analyses were conducted to detect boldine docking sites' details and evaluate the key binding residues. Boldine displayed a typical reversible and mixed-type inhibition manner. Measurements of circular dichroism and fluorescence spectrum showed boldine changed the secondary structure and loosened the tertiary conformation of target α-glucosidase. The computational molecular dynamics showed that boldine could block the active pocket site through close interaction with binding key residues, and two phenolic hydroxyl groups of boldine play a core function in α-glucosidase inhibition via ligand binding. This investigation reveals the boldine function on interaction with the α-glucosidase active site, which provides a new inhibitor candidate.Communicated by Ramaswamy H. Sarma.

Inhibitory effect of acarbose on tyrosinase: application of molecular dynamics integrating inhibition kinetics.

Due to its clinical and cosmetic applications, investigators have paid attention to tyrosinase (TYR) inhibitor development. In this study, a TYR inhibition study with acarbose was investigated to gain insights into the regulation of the catalytic function. Biochemical assay results indicated that acarbose was turned to be an inhibitor of TYR in a reversible binding manner and probed as a distinctive mixed-type inhibitor via measurement of double-reciprocal kinetic (Ki = 18.70 ± 4.12 mM). Time-interval kinetic measurement indicated that TYR catalytic function was gradually inactivated by acarbose in a time-dependent behavior displaying with a monophase process that was evaluated by semi-logarithmic plotting. Spectrofluorimetric measurement by integrating with a hydrophobic residue detector (1-anilinonaphthalene-8-sulfonate) showed that the high dose of acarbose derived a conspicuous local structural deformation of the TYR catalytic site pocket. Computational docking simulation showed that acarbose bound to key residues such as HIS61, TYR65, ASN81, HIS244, and HIS259. Our study extends an understanding of the functional application of acarbose and proposes that acarbose is an alternative candidate drug for a whitening agent via direct retardation of TYR catalytic function and it would be applicable for the relevant skin hyperpigmentation disorders concerning the dermatologic clinical purpose.Communicated by Ramaswamy H. Sarma.

Improving Geometric Validation Metrics and Ensuring Consistency with Experimental Data through TrioSA: An NMR Refinement Protocol.

Protein model refinement a the crucial step in improving the quality of a predicted protein model. This study presents an NMR refinement protocol called TrioSA (torsion-angle and implicit-solvation-optimized simulated annealing) that improves the accuracy of backbone/side-chain conformations and the overall structural quality of proteins. TrioSA was applied to a subset of 3752 solution NMR protein structures accompanied by experimental NMR data: distance and dihedral angle restraints. We compared the initial NMR structures with the TrioSA-refined structures and found significant improvements in structural quality. In particular, we observed a reduction in both the maximum and number of NOE (nuclear Overhauser effect) violations, indicating better agreement with experimental NMR data. TrioSA improved geometric validation metrics of NMR protein structure, including backbone accuracy and the secondary structure ratio. We evaluated the contribution of each refinement element and found that the torsional angle potential played a significant role in improving the geometric validation metrics. In addition, we investigated protein-ligand docking to determine if TrioSA can improve biological outcomes. TrioSA structures exhibited better binding prediction compared to the initial NMR structures. This study suggests that further development and research in computational refinement methods could improve biomolecular NMR structural determination.

Potent inhibition of human tyrosinase inhibitor by verproside from the whole plant of Pseudolysimachion rotundum var. subintegrum.

Affinity-based ultrafiltration-mass spectrometry coupled with ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry was utilised for the structural identification of direct tyrosinase ligands from a crude Pseudolysimachion rotundum var. subintegrum extract. False positives were recognised by introducing time-dependent inhibition in the control for comparison. The P. rotundum extract contained nine main metabolites in the UPLC-QTOF-MS chromatogram. However, four metabolites were reduced after incubation with tyrosinase, indicating that these metabolites were bound to tyrosinase. The IC50 values of verproside (1) were 31.2 µM and 197.3 µM for mTyr and hTyr, respectively. Verproside showed 5.6-fold higher efficacy than that of its positive control (kojic acid in hTyr). The most potent tyrosinase inhibitor, verproside, features a 3,4-dihydroxybenzoic acid moiety on the iridoid glycoside and inhibits tyrosinase in a time-dependent and competitive manner. Among these three compounds, verproside is bound to the active site pocket with a docking energy of -6.9 kcal/mol and four hydrogen bonding interactions with HIS61 and HIS85.

Human Activity Prediction Based on Forecasted IMU Activity Signals by Sequence-to-Sequence Deep Neural Networks.

Human Activity Recognition (HAR) has gained significant attention due to its broad range of applications, such as healthcare, industrial work safety, activity assistance, and driver monitoring. Most prior HAR systems are based on recorded sensor data (i.e., past information) recognizing human activities. In fact, HAR works based on future sensor data to predict human activities are rare. Human Activity Prediction (HAP) can benefit in multiple applications, such as fall detection or exercise routines, to prevent injuries. This work presents a novel HAP system based on forecasted activity data of Inertial Measurement Units (IMU). Our HAP system consists of a deep learning forecaster of IMU activity signals and a deep learning classifier to recognize future activities. Our deep learning forecaster model is based on a Sequence-to-Sequence structure with attention and positional encoding layers. Then, a pre-trained deep learning Bi-LSTM classifier is used to classify future activities based on the forecasted IMU data. We have tested our HAP system for five daily activities with two tri-axial IMU sensors. The forecasted signals show an average correlation of 91.6% to the actual measured signals of the five activities. The proposed HAP system achieves an average accuracy of 97.96% in predicting future activities.

Verproside, the Most Active Ingredient in YPL-001 Isolated from Pseudolysimachion rotundum var. subintegrum, Decreases Inflammatory Response by Inhibiting PKCδ Activation in Human Lung Epithelial Cells.

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease which causes breathing problems. YPL-001, consisting of six iridoids, has potent inhibitory efficacy against COPD. Although YPL-001 has completed clinical trial phase 2a as a natural drug for COPD treatment, the most effective iridoid in YPL-001 and its mechanism for reducing airway inflammation remain unclear. To find an iridoid most effectively reducing airway inflammation, we examined the inhibitory effects of the six iridoids in YPL-001 on TNF or PMA-stimulated inflammation (IL-6, IL-8, or MUC5AC) in NCI-H292 cells. Here, we show that verproside among the six iridoids most strongly suppresses inflammation. Both TNF/NF-κB-induced MUC5AC expression and PMA/PKCδ/EGR-1-induced IL-6/-8 expression are successfully reduced by verproside. Verproside also shows anti-inflammatory effects on a broad range of airway stimulants in NCI-H292 cells. The inhibitory effect of verproside on the phosphorylation of PKC enzymes is specific to PKCδ. Finally, in vivo assay using the COPD-mouse model shows that verproside effectively reduces lung inflammation by suppressing PKCδ activation and mucus overproduction. Altogether, we propose YPL-001 and verproside as candidate drugs for treating inflammatory lung diseases that act by inhibiting PKCδ activation and its downstream pathways.

Nanocomposite Engineering of a High-Capacity Partially Ordered Cathode for Li-Ion Batteries.

Understanding the local cation order in the crystal structure and its correlation with electrochemical performances has advanced the development of high-energy Mn-rich cathode materials for Li-ion batteries, notably Li- and Mn-rich layered cathodes (LMR, e.g., Li1.2 Ni0.13 Mn0.54 Co0.13 O2 ) that are considered as nanocomposite layered materials with C2/m Li2 MnO3 -type medium-range order (MRO). Moreover, the Li-transport rate in high-capacity Mn-based disordered rock-salt (DRX) cathodes (e.g., Li1.2 Mn0.4 Ti0.4 O2 ) is found to be influenced by the short-range order of cations, underlining the importance of engineering the local cation order in designing high-energy materials. Herein, the nanocomposite is revealed, with a heterogeneous nature (like MRO found in LMR) of ultrahigh-capacity partially ordered cathodes (e.g., Li1.68 Mn1.6 O3.7 F0.3 ) made of distinct domains of spinel-, DRX- and layered-like phases, contrary to conventional single-phase DRX cathodes. This multi-scale understanding of ordering informs engineering the nanocomposite material via Ti doping, altering the intra-particle characteristics to increase the content of the rock-salt phase and heterogeneity within a particle. This strategy markedly improves the reversibility of both Mn- and O-redox processes to enhance the cycling stability of the partially ordered DRX cathodes (nearly ≈30% improvement of capacity retention). This work sheds light on the importance of nanocomposite engineering to develop ultrahigh-performance, low-cost Li-ion cathode materials.

Identification of New N-methyl-piperazine Chalcones as Dual MAO-B/AChE Inhibitors.

Monoamine oxidase-B (MAO-B), acetylcholinesterase (AChE), and butyrylcholinesterase (BChE) have been considered target enzymes of depression and neurodegenerative diseases, including Alzheimer's disease (AD). In this study, seventeen N-methyl-piperazine chalcones were synthesized, and their inhibitory activities were evaluated against the target enzymes. Compound 2k (3-trifluoromethyl-4-fluorinated derivative) showed the highest selective inhibition against MAO-B with an IC50 of 0.71 µM and selectivity index (SI) of 56.34, followed by 2n (2-fluoro-5-bromophenyl derivative) (IC50 = 1.11 µM, SI = 16.04). Compounds 2k and 2n were reversible competitive MAO-B inhibitors with Ki values of 0.21 and 0.28 µM, respectively. Moreover, 2k and 2n effectively inhibited AChE with IC50 of 8.10 and 4.32 µM, which underscored their multi-target inhibitory modes. Interestingly, compound 2o elicited remarkable inhibitions over MAO-B, AChE, and BChE with IC50 of 1.19-3.87 µM. A cell-based assay of compounds 2k and 2n against Vero normal cells pointed out their low cytotoxicity. In a docking simulation, 2k showed the lowest energy for MAO-B (-11.6 kcal/mol) with four hydrogen bonds and two π-π interactions. Furthermore, in silico studies were conducted, and disclosed that 2k and 2n are expected to possess favorable pharmacokinetic properties, such as the ability to penetrate the blood-brain barrier (BBB). In view of these findings, compounds 2k and 2n could serve as promising potential candidates for the treatment of neurodegenerative diseases.

Characterization and tissue expression analysis of mitochondrial creatine kinases (types I and II) from Pelodiscus sinensis.

The aim of this study was to characterize the functions of the mitochondrial creatine kinases in the Chinese soft-shelled turtle Pelodiscus sinensis (PSCK-MT1 and PSCK-MT2) to characterize function in relation to hibernation. Computational prediction via molecular dynamics simulations showed that PSCK-MT1 had stronger kinase- and creatine-binding affinity than PSCK-MT2. We measured PSCK-MT1 and PSCK-MT2 levels in the myocardium, liver, spleen, lung, kidney, and ovary of P. sinensis before and after hibernation and found that the expression of these enzymes was the most significantly upregulated in the ovary. We enumerated the ovarian follicles and evaluated the physiological indices of P. sinensis and discovered that fat was the main form of energy storage in P. sinensis. Moreover, both PSCK-MTs promoted follicular development during hibernation. Immunohistochemistry was used to study follicular development and revealed that both PSCK-MTs were expressed primarily in the follicular fluid and granulosa layer before and after hibernation. We found that PSCK-MT1 and PSCK-MT2 could play important roles in ovarian follicular development under hibernation. Hence, both PSCK-MTs probably function effectively under the conditions of low temperature and oxygen during hibernation. Communicated by Ramaswamy H. Sarma.

Characterization and activity-folding relationship of serine protease from Antarctic krill (Euphausia superba).

Euphausia superba (Antarctic krill) serine protease (ESP) was investigated to gain insights into the activity-structural relationship, folding behavior, and regulation of the catalytic function. We purified ESP from the krill muscle and characterized biochemical distinctions via enzyme kinetics. Studies of inhibition kinetics and unfolding in the presence of a serine residue modifier, such as phenylmethanesulfonyl fluoride, were conducted. Structural characterizations were measured by spectrofluorimetry, including 1-anilinonaphthalene-8-sulfonate dye labeling for hydrophobic residues. The computational simulations such as docking and molecular dynamics were finally conducted to detect key residues and folding behaviors in a nano-second range. The kinetic parameters of ESP were measured as KmBANH = 0.97 ± 0.15 mM and kcat/KmBANH = 4.59 s-1/mM. The time-interval kinetics measurements indicated that ESP inactivation was transformed from a monophase to a biphase process to form a thermodynamically stable state. Spectrofluorimetry measurements showed that serine is directly connected to the regional folding of ESP. Several osmolytes such as proline and glycine only partially protected the inactive form of ESP by serine modification. Computational molecular dynamics and docking simulations showed that three serine residues (Ser183, Ser188, and Ser207) and Cys184, Val206, and Gly209 are key residues of catalytic functions. Our study revealed the functional roles of serine residues as key residues of catalytic function at the active site and of the structural conformation as key folding factors, where ESP displays a flexible property of active site pocket compared to the overall structure.Communicated by Ramaswamy H. Sarma.

BERN2: an advanced neural biomedical named entity recognition and normalization tool.

In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e.g. diseases and drugs) from the ever-growing biomedical literature. In this article, we present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by employing a multi-task NER model and neural network-based NEN models to achieve much faster and more accurate inference. We hope that our tool can help annotate large-scale biomedical texts for various tasks such as biomedical knowledge graph construction. AVAILABILITY AND IMPLEMENTATION: Web service of BERN2 is publicly available at http://bern2.korea.ac.kr. We also provide local installation of BERN2 at https://github.com/dmis-lab/BERN2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Application of Computational Simulation Integrating Inhibition Kinetics for Detecting Tyrosinase Inhibitor: Salsalate Is a New Inhibitor.

BACKGROUND: Tyrosinase inhibitor developments have been widely attended by investigators for their various applications. OBJECTIVE: A combination of virtual screening of docking simulations and biochemical inhibition kinetics was performed to find a new inhibitor of tyrosinase for the clinical application of an antipigment agent. METHODS: We conducted docking simulations to detect tyrosinase key binding residues and used the detected binding residues to screen the NCBI PubChem database for probing tyrosinase binding compounds. The serial inhibition kinetics and spectrofluorimetry measurements were performed to validate the inhibitory effect on tyrosinase. RESULTS: We have detected 200 candidates and categorized them into four clusters. Among them, we successfully confirmed salsalate as a new inhibitor of tyrosinase measured by serial enzyme kinetics. Salsalate was detected as a reversible inhibitor of tyrosinase displaying a typical mixedtype inhibition manner (IC50 = 22.19 ± 1.01 mM; Ki = 19.98 ± 2.11 mM). Spectrofluorimetry measurement by integrating with 1-anilinonaphthalene-8-sulfonate showed that salsalate mainly induced a slight regional conformation distortion of the tyrosinase active site accompanied by a slight hydrophobic disruption. CONCLUSION: Our study suggests that salsalate is a potential anti-pigment drug via inhibition of tyrosinase activity and it might be applicable for dermatologic clinical application. Also, our study enlarges an insight into the salsalate drug application.

Structural resemblance of the DNAJA-family protein, Tid1, to the DNAJB-family Hsp40.

The specific pair of heat shock protein 70 (Hsp70) and Hsp40 constitutes an essential molecular chaperone system involved in numerous cellular processes, including the proper folding/refolding and transport of proteins. Hsp40 family members are characterized by the presence of a conserved J-domain (JD) that functions as a co-chaperone of Hsp70. Tumorous imaginal disc 1 (Tid1) is a tumor suppressor protein belonging to the DNAJA3 subfamily of Hsp40 and functions as a co-chaperone of the mitochondrial Hsp70, mortalin. In this work, we performed nuclear magnetic resonance spectroscopy to determine the solution structure of JD and its interaction with the glycine/phenylalaninerich region (GF-motif) of human Tid1. Notably, Tid1-JD, whose conformation was consistent with that of the DNAJB1 JD, appeared to stably interact with its subsequent GF-motif region. Collectively with our sequence analysis, the present results demonstrate that the functional and regulatory mode of Tid1 resembles that of the DNAJB1 subfamily members rather than DNAJA1 or DNAJA2 subfamily proteins. Therefore, it is suggested that an allosteric interaction between mortalin and Tid1 is involved in the mitochondrial Hsp70/Hsp40 chaperone system. [BMB Reports 2022; 55(10): 488-493].

A comprehensive evaluation of regression-based drug responsiveness prediction models, using cell viability inhibitory concentrations (IC50 values).

MOTIVATION: Predicting drug response is critical for precision medicine. Diverse methods have predicted drug responsiveness, as measured by the half-maximal drug inhibitory concentration (IC50), in cultured cells. Although IC50s are continuous, traditional prediction models have dealt mainly with binary classification of responsiveness. However, since there are few regression-based IC50 predictions, comprehensive evaluations of regression-based IC50 prediction models, including machine learning (ML) and deep learning (DL), for diverse data types and dataset sizes, have not been addressed. RESULTS: Here, we constructed 11 input data settings, including multi-omics settings, with varying dataset sizes, then evaluated the performance of regression-based ML and DL models to predict IC50s. DL models considered two convolutional neural network architectures: CDRScan and residual neural network (ResNet). ResNet was introduced in regression-based DL models for predicting drug response for the first time. As a result, DL models performed better than ML models in all the settings. Also, ResNet performed better than or comparable to CDRScan and ML models in all settings. AVAILABILITY AND IMPLEMENTATION: The data underlying this article are available in GitHub at https://github.com/labnams/IC50evaluation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pandemics are catalysts of scientific novelty: Evidence from COVID-19.

Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First-time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pretrained on 29 million PubMed articles, and first-time collaboration increased after the outbreak of COVID-19, and international collaboration witnessed a sudden decrease. During COVID-19, papers with more first-time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic.

Second-Generation JK-206 Targets the Oncogenic Signal Mediator RHOA in Gastric Cancer.

Ras homologous A (RHOA), a signal mediator and a GTPase, is known to be associated with the progression of gastric cancer (GC), which is the fourth most common cause of death in the world. Previously, we designed pharmacologically optimized inhibitors against RHOA, including JK-136 and JK-139. Based on this previous work, we performed lead optimization and designed novel RHOA inhibitors for greater anti-GC potency. Two of these compounds, JK-206 and JK-312, could successfully inhibit the viability and migration of GC cell lines. Furthermore, using transcriptomic analysis of GC cells treated with JK-206, we revealed that the inhibition of RHOA might be associated with the inhibition of the mitogenic pathway. Therefore, JK-206 treatment for RHOA inhibition may be a new therapeutic strategy for regulating GC proliferation and migration.

PATHOME-Drug: a subpathway-based polypharmacology drug-repositioning method.

MOTIVATION: Drug repositioning reveals novel indications for existing drugs and in particular, diseases with no available drugs. Diverse computational drug repositioning methods have been proposed by measuring either drug-treated gene expression signatures or the proximity of drug targets and disease proteins found in prior networks. However, these methods do not explain which signaling subparts allow potential drugs to be selected, and do not consider polypharmacology, i.e. multiple targets of a known drug, in specific subparts. RESULTS: Here, to address the limitations, we developed a subpathway-based polypharmacology drug repositioning method, PATHOME-Drug, based on drug-associated transcriptomes. Specifically, this tool locates subparts of signaling cascading related to phenotype changes (e.g. disease status changes), and identifies existing approved drugs such that their multiple targets are enriched in the subparts. We show that our method demonstrated better performance for detecting signaling context and specific drugs/compounds, compared to WebGestalt and clusterProfiler, for both real biological and simulated datasets. We believe that our tool can successfully address the current shortage of targeted therapy agents. AVAILABILITY AND IMPLEMENTATION: The web-service is available at http://statgen.snu.ac.kr/software/pathome. The source codes and data are available at https://github.com/labnams/pathome-drug. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A study of Pb2+ induced unfolding and aggregation of arginine kinase from Euphausia superba: kinetics and computational simulation integrating study.

Arginine kinase is a crucial phosphagen kinase in invertebrates, which is associated to the environmental stress response, plays a key role in cellular energy metabolism. In this study, we investigated the Pb2+-induced inhibition and aggregation of Euphausia superba arginine kinase (ESAK) and found that significantly inactivated ESAK in a dose-dependent manner (IC50 = 0.058 ± 0.002 mM). Spectrofluorimetry results showed that Pb2+ induced tertiary structural changes via the internal polarity increased and the non-polarity decreased in ESAK and directly induced ESAK aggregation. The ESAK aggregation process induced by Pb2+ occurred with multi-phase kinetics. The addition of osmolytes did not show protective effect on Pb2+-induced inactivation of ESAK. The computational molecular dynamics (MD) simulation showed that three Pb2+ interrupt the entrance of the active site of ESAK and it could be the reason on the loss of activity of ESAK. Several important residues of ESAK were detected that were importantly contributed the conformation and catalytic function of ESAK. Our study showed that Pb2+-induced misfolding of ESAK and the complete loss of activity irreversibly, which cannot be recovered by osmolytes.Communicated by Ramaswamy H. Sarma.

Marine invertebrate sialyltransferase of the sea squirt Ciona savignyi sialylated core 1 O-linked glycans.

An invertebrate sialyltransferase, cST3Gal-I, identified from the sea squirt Ciona savignyi, was functionally characterized in vitro using recombinant enzyme expressed in yeast strains. cST3Gal-I was localized to the Golgi membrane when expressed in Saccharomyces cerevisiae. Enzymatic characterization for substrate specificity and kinetic property indicate that cST3Gal-I prefers O-glycans, rather than N-glycan, of asialoglycoproteins as substrates. Interestingly, C. savignyi sialyltransferase exhibited effectively Neu5Ac transfer to core 1 O-glycan, Gal ß(1,3)GalNAc, compared to orthologous human glycosyltransferase. Further, it is shown that cST3Gal-I catalyzes the formation of α(2,3)-linkage, through lectin blot analysis with Maackia amurensis lectin and by linkage-specific sialidase treatments. The putative active sites of cST3Gal-I for putative acid/base catalysts and sialic acid acceptor/donor substrate bindings were also identical to the counterpart residues of a mammalian enzyme, porcine ST3Gal-I, as predicted through homologous structure modeling. These results could imply that an ancestral tunicate ST3Gal-I in C. savignyi would prefer O-glycan onto glycoproteins as its sialic acid acceptor than vertebrate enzymes.