Investigating the impact of empagliflozin on the retina of diabetic mice.

BACKGROUND: Diabetic retinopathy (DR) frequently results in compromised visual function, with hyperglycemia-induced disruption of the blood-retinal barrier (BRB) through various pathways as a critical mechanism. Existing DR treatments fail to address early and potentially reversible microvascular alterations. This study examined the effects of empagliflozin (EMPA), a selective Sodium-glucose transporter 2 (SGLT2) inhibitor, on the retina of db/db mice. The objective of this study is to investigate the potential role of EMPA in the prevention and delay of DR. METHODS: db/db mice were randomly assigned to either the EMPA treatment group (db/db + Emp) or the model group (db/db), while C57 mice served as the normal control group (C57). Mice in the db/db + Emp group received EMPA for eight weeks. Body weight, fasting blood glucose (FBG), and blood VEGF were subsequently measured in all mice, along with the detection of specific inflammatory factors and BRB proteins in the retina. Retinal SGLT2 protein expression was compared using immunohistochemical analysis, and BRB structural changes were observed via electron microscopy. RESULTS: EMPA reduced FBG, blood VEGF, and retinal inflammatory factors TNF-α, IL-6, and VEGF levels in the eye tissues of db/db mice. EMPA also increased Claudin-1, Occludin-1, and ZO-1 levels while decreasing ICAM-1 and Fibronectin, thereby preserving BRB function in db/db mice. Immunohistochemistry revealed that EMPA reduced SGLT2 expression in the retina of diabetic mice, and electron microscopy demonstrated that EMPA diminished tight junction damage between retinal vascular endothelial cells and prevented retinal vascular basement membrane thickening in diabetic mice. CONCLUSION: EMPA mitigates inflammation and preserves BRB structure and function, suggesting that it may prevent DR or serve as an effective early treatment for DR.

T Cell Receptor-Directed Bispecific T Cell Engager Targeting MHC-Linked NY-ESO-1 for Tumor Immunotherapy.

Antibody-based bispecific T cell engagers (TCEs) that redirect T cells to kill tumor cells have shown a promising therapeutic effect on hematologic malignancies. However, tumor-specific targeting is still a challenge for TCEs, impeding the development of TCEs for solid tumor therapy. The major histocompatibility complex (MHC) presents almost all intracellular peptides (including tumor-specific peptides) on the cell surface to be scanned by the TCR on T cells. With the premise of choosing optimal peptides, the final complex peptide-MHC could be the tumor-specific target for TCEs. Here, a novel TCR-directed format of a TCE targeting peptide-MHC was designed named IgG-T-TCE, which was modified from the IgG backbone and prepared in a mammalian cell expression system. The recombinant IgG-T-TCE-NY targeting NY-ESO-1157-165/HLA-A*02:01 could be generated in HEK293 cells with a glycosylated TCR and showed potency in T cell activation and redirecting T cells to specifically kill target tumor cells. We also found that the in vitro activity of IgG-T-TCE-NY could be leveraged by various anti-CD3 antibodies and Fc silencing. The IgG-T-TCE-NY efficiently inhibited tumor growth in a tumor-PBMC co-engrafted mouse model without any obvious toxicities.

Lower-dose intravenous immunoglobulin therapy for geriatric inflammatory bowel disease accompanied by COVID-19 multisystem inflammatory syndrome: A case report.

RATIONALE: This article presents a complex case of refractory severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related inflammatory bowel disease (IBD) and outlines its diagnostic and therapeutic challenges. Considering inadequate responses to conventional and steroid treatments, the potential efficacy of intravenous immunoglobulin is explored. PATIENT CONCERNS: The patient, an elderly individual, experienced short-term fever and sore throat after encountering the coronavirus disease 2019 pandemic. Despite receiving a 3-dose inactivated SARS-CoV-2 vaccine, the patient tested positive for the viral antigen and developed worsening symptoms, including diarrhea and recurrent fever. Initial antibiotic treatment for bacterial enteritis proved ineffective. DIAGNOSES: Further evaluation, including endoscopy and pathology, confirmed the diagnosis of IBD with concurrent multisystem inflammatory syndrome (MIS) in adults, as evidenced by tachycardia and elevated inflammatory markers. INTERVENTIONS: Following unsuccessful treatment with mesalazine, probiotics, corticosteroids, and supportive care, the patient underwent lower-dose intravenous immunoglobulin therapy. OUTCOMES: The patient experienced symptom improvement, with resolution of fever, diarrhea, and inflammation. At the 30-day follow-up, the patient remained afebrile, without diarrhea, and exhibited favorable mental status. LESSONS: Elderly individuals infected with SARS-CoV-2 may develop severe systemic inflammatory responses. The patients in this report predominantly presented with IBD following SARS-CoV-2 infection, accompanied by MIS. Favorable clinical outcomes were achieved following lower-dose intravenous immunoglobulin immunotherapy, which demonstrated superior efficacy compared to glucocorticoids in managing such conditions. Future research should prioritize investigating immunotherapy application strategies in IBD and MIS. Notably, the significant clinical improvement observed with lower-dose intravenous immunoglobulin administration could optimize the utilization of this limited medical resource.

Viscosities of the Baryon-Rich Quark-Gluon Plasma from Beam Energy Scan Data.

This work presents the first Bayesian inference study of the (3+1)D dynamics of relativistic heavy-ion collisions and quark-gluon plasma viscosities using an event-by-event (3+1)D hydrodynamics+hadronic transport theoretical framework and data from the Relativistic Heavy Ion Collider Beam energy scan program. Robust constraints on initial state nuclear stopping and the baryon chemical potential-dependent shear viscosity of the produced quantum chromodynamic (QCD) matter are obtained. The specific bulk viscosity of the QCD matter is found to exhibit a preferred maximum around sqrt[s_{NN}]=19.6 GeV. This result allows for the alternative interpretation of a reduction (and/or increase) of the speed of sound relative to that of the employed lattice-QCD based equation of state for net baryon chemical potential µ_{B}∼0.2(0.4) GeV.

Development of an RBD-Fc fusion vaccine for COVID-19.

Although the global pandemic of SARS-CoV-2 has passed, there are still regional outbreaks that continue to jeopardize human health. Hence, there is still a great deal of interest in developing an efficient vaccine that can quickly and effectively prevent reemerging outbreaks of SARS-CoV-2. Delta variant was once a dominant strain in the world in 2021, and we first constructed a recombinant RBDdelta-Fc fusion vaccine by coupling the RBD of Delta variant with the human Fc fragment. This Fc fusion strategy increases the immunogenicity of the recombinant RBD vaccine, with a long-lasting high level of IgG antibodies and neutralizing antibodies induced by RBDdelta-Fc vaccine. This RBDdelta-Fc vaccine, as well as the RBD-Fc vaccine prepared in our previously study, could trigger a durable immune effect by the heterologous boosting immunity, and the RBD-Fc induced a quicker humoral immune response than the homologous immunization with inactivated vaccines. In conclusion, the Fc fusion strategy has a significant role in enhancing the immunogenicity of recombinant protein vaccines, thus promising the development of a safe and efficient vaccine for the heterologous boosting against SARS-CoV-2.

Enhancing the safety of CAR-T cell therapy: Synthetic genetic switch for spatiotemporal control.

Chimeric antigen receptor T (CAR-T) cell therapy is a promising and precise targeted therapy for cancer that has demonstrated notable potential in clinical applications. However, severe adverse effects limit the clinical application of this therapy and are mainly caused by uncontrollable activation of CAR-T cells, including excessive immune response activation due to unregulated CAR-T cell action time, as well as toxicity resulting from improper spatial localization. Therefore, to enhance controllability and safety, a control module for CAR-T cells is proposed. Synthetic biology based on genetic engineering techniques is being used to construct artificial cells or organisms for specific purposes. This approach has been explored in recent years as a means of achieving controllability in CAR-T cell therapy. In this review, we summarize the recent advances in synthetic biology methods used to address the major adverse effects of CAR-T cell therapy in both the temporal and spatial dimensions.

Rational Identification of Novel Antibody-Drug Conjugate with High Bystander Killing Effect against Heterogeneous Tumors.

Bystander-killing payloads can significantly overcome the tumor heterogeneity issue and enhance the clinical potential of antibody-drug conjugates (ADC), but the rational design and identification of effective bystander warheads constrain the broader implementation of this strategy. Here, graph attention networks (GAT) are constructed for a rational bystander killing scoring model and ADC construction workflow for the first time. To generate efficient bystander-killing payloads, this model is utilized for score-directed exatecan derivatives design. Among them, Ed9, the most potent payload with satisfactory permeability and bioactivity, is further used to construct ADC. Through linker optimization and conjugation, novel ADCs are constructed that perform excellent anti-tumor efficacy and bystander-killing effect in vivo and in vitro. The optimal conjugate T-VEd9 exhibited therapeutic efficacy superior to DS-8201 against heterogeneous tumors. These results demonstrate that the effective scoring approach can pave the way for the discovery of novel ADC with promising bystander payloads to combat tumor heterogeneity.

Robust and Wet Adhesive Self-Gelling Powders for Rapid Hemostasis and Efficient Wound Healing.

Healing traumatic wounds is arduous, leaving miscellaneous demands for ideal wound dressings, such as rapid hemostasis, superior wet tissue adhesion, strong mechanical properties, and excellent antibacterial activity. Herein, we report a self-gelling, wet adhesive, stretchable (polyethylenimine/poly(dimethylammonium chloride)/(poly(acrylic acid)/poly(sodium styrenesulfonate)/alkylated chitosan)) ((PEI/PDDA)/(PAA/PSS)/ACS) powder as a new option. The self-gel utilizes noncovalent interactions among in situ formed PDDA/PSS nanoparticles and PEI/PAA polymetric matrices to earn sensational mechanical properties and tensile strength while incorporating ACS to obtain fast hemostasis and therapeutic capacities. The powder can form a hydrogel patch in situ within 3 s upon liquid absorption, capable of resisting pressure higher than twice the blood pressure. Deposition of the self-gelling powders on various wounds, such as rat liver and femoral artery wounds, can stop bleeding in 10 s and lessen the amount of bleeding 6-fold plus in corresponding models. Furthermore, the self-gelling powders can significantly advance the chronic wound healing process by displaying a high wound healing rate and a low inflammatory response and promoting the formation of new blood vessels and tissue regeneration. The satisfactory mechanical properties, strong wet adhesion, sufficient antibacterial properties, ease of usage, adaptability to complex wounds, rapid hemostasis, and superior therapeutic capacities of (PEI/PDDA)/(PAA/PSS)/ACS self-gelling powders render them as a profound wound dressing biomaterial.

Diversity of Culturable Bacteria from the Coral Reef Areas in the South China Sea and Their Agar-Degrading Abilities.

The South China Sea (SCS) is abundant in marine microbial resources with high primary productivity, which is crucial for sustaining the coral reef ecosystem and the carbon cycle. Currently, research on the diversity of culturable bacteria in the SCS is relatively extensive, yet the culturable bacteria in coral reefs has been poorly understood. In this study, we analyzed the bacterial community structure of seawater samples among Daya Bay (Fujian Province), Qionghai (Hainan Province), Xisha Islands, and the southern South China Sea based on culturable methods and detected their abilities for agar degradation. There were 441 bacterial strains, belonging to three phyla, five classes, 43 genera, and 101 species, which were isolated by marine agar 2216E (MA; Becton Dickinson). Strains within Gammaproteobacteria were the dominant group, accounting for 89.6% of the total bacterial isolates. To investigate vibrios, which usually correlated with coral health, 348 isolates were obtained from TCBS agar, and all isolates were identified into three phylum, three classes, 14 orders, 25 families, and 48 genera. Strains belonging to the genus Vibrio had the greatest number (294 strains), indicating the high selectivity of TCBS agar for vibrios. Furthermore, nineteen strains were identified as potentially novel species according to the low 16S rRNA gene similarity (<98.65%), and 28 strains (15 species) had agar-degrading ability. These results indicate a high diversity of culturable bacteria in the SCS and a huge possibility to find novel and agar-degrading species. Our study provides valuable microbial resources to maintain the stability of coral ecosystems and investigate their roles in the marine carbon cycle.

Emergence of a novel ISS1N-optrA-carrying transposon within an integrative and conjugative element from Streptococcus parasuis.

OBJECTIVES: To investigate the genetic context and transferability of the oxazolidinone resistance gene optrA in a Streptococcus parasuis isolate. METHODS: The optrA-carrying S. parasuis isolate SFJ45 was characterized by PCR, antimicrobial susceptibility testing, complete genome sequencing and bioinformatic analysis. The transferability of optrA was verified by conjugation, followed by SmaI-PFGE and Southern blotting. RESULTS: The S. parasuis isolate SFJ45 was positive for optrA, mef(A), msr(D), erm(B), tetAB(P)', tet(M), aadE, aphA3, catQ, dfrG and mdt(A), conferring an MDR phenotype. The optrA gene was flanked by ISS1N at both termini in the same orientation, representing a novel 8750 bp pseudo-compound transposon, organized as the ISS1N-hth-clb-4hp-optrA-2hp-ISS1N structure. The ISS1N-optrA-carrying transposon was further inserted within an integrative and conjugative element, ICESpsuSFJ45, at 3' end of the fda gene. Conjugative transfer of the ISS1N-optrA-carrying transposon with ICESpsuSFJ45 was observed from S. parasuis to Streptococcus suis at a frequency of (1.01 ± 3.12) × 10-7. CONCLUSIONS: ISS1N was found to be associated with optrA spreading for the first time. Integration of the ISS1N-optrA transposon within ICESpsuSFJ45 may lead to the co-selection of optrA with other antimicrobial resistance genes, contributing to its horizontal transfer from S. parasuis to clinically more important bacterial pathogens.

Superantigen-fused T cell engagers for tumor antigen-mediated robust T cell activation and tumor cell killing.

Inadequate T cell activation has severely limited the success of T cell engager (TCE) therapy, especially in solid tumors. Enhancing T cell activity while maintaining the tumor specificity of TCEs is the key to improving their clinical efficacy. However, currently, there needs to be more effective strategies in clinical practice. Here, we design novel superantigen-fused TCEs that display robust tumor antigen-mediated T cell activation effects. These innovative drugs are not only armed with the powerful T cell activation ability of superantigens but also retain the dependence of TCEs on tumor antigens, realizing the ingenious combination of the advantages of two existing drugs. Superantigen-fused TCEs have been preliminarily proven to have good (>30-fold more potent) and specific (>25-fold more potent) antitumor activity in vitro and in vivo. Surprisingly, they can also induce the activation of T cell chemotaxis signals, which may promote T cell infiltration and further provide an additional guarantee for improving TCE efficacy in solid tumors. Overall, this proof-of-concept provides a potential strategy for improving the clinical efficacy of TCEs.

Improving antibody optimization ability of generative adversarial network through large language model.

Generative adversarial networks (GANs) have successfully generated functional protein sequences. However, traditional GANs often suffer from inherent randomness, resulting in a lower probability of obtaining desirable sequences. Due to the high cost of wet-lab experiments, the main goal of computer-aided antibody optimization is to identify high-quality candidate antibodies from a large range of possibilities, yet improving the ability of GANs to generate these desired antibodies is a challenge. In this study, we propose and evaluate a new GAN called the Language Model Guided Antibody Generative Adversarial Network (AbGAN-LMG). This GAN uses a language model as an input, harnessing such models' powerful representational capabilities to improve the GAN's generation of high-quality antibodies. We conducted a comprehensive evaluation of the antibody libraries and sequences generated by AbGAN-LMG for COVID-19 (SARS-CoV-2) and Middle East Respiratory Syndrome (MERS-CoV). Results indicate that AbGAN-LMG has learned the fundamental characteristics of antibodies and that it improved the diversity of the generated libraries. Additionally, when generating sequences using AZD-8895 as the target antibody for optimization, over 50% of the generated sequences exhibited better developability than AZD-8895 itself. Through molecular docking, we identified 70 antibodies that demonstrated higher affinity for the wild-type receptor-binding domain (RBD) of SARS-CoV-2 compared to AZD-8895. In conclusion, AbGAN-LMG demonstrates that language models used in conjunction with GANs can enable the generation of higher-quality libraries and candidate sequences, thereby improving the efficiency of antibody optimization. AbGAN-LMG is available at http://39.102.71.224:88/.

Study on the mechanism of vitamin E alleviating non-alcoholic fatty liver function based on non-targeted metabolomics analysis in rats.

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of metabolic syndrome. Vitamin E (VE) has antioxidant properties and can mediate lipid metabolism. Non-targeted metabolomics technology was employed to uncover comprehensively the metabolome of VE in NAFLD rats. NAFLD model was created with a high-fat and high-cholesterol diet (HFD) in rats. NAFLD rats in the VE group were given 75 mg/(kg day) VE. The metabolites in the serum of rats were identified via UPLC and Q-TOF/MS analysis. KEGG was applied for the pathway enrichment. VE improved the liver function, lipid metabolism, and oxidative stress in NAFLD rats induced by HFD. Based on the metabolite profile data, 132 differential metabolites were identified between VE group and the HFD group, mainly including pyridoxamine, betaine, and bretylium. According to the KEGG results, biosynthesis of cofactors was a key metabolic pathway of VE in NAFLD rats. VE can alleviate NAFLD induced by HFD, and the underlying mechanism is associated with the biosynthesis of cofactors, mainly including pyridoxine and betaine.

Vertical dynamics of free-living and particle-associated vibrio communities in the eastern tropical Indian Ocean.

Members of the family Vibrionaceae (vibrios) are widely distributed in estuarine, offshore, and marginal seas and perform an important ecological role in the marine organic carbon cycle. Nevertheless, there is little knowledge about whether vibrios play ecological roles in the oligotrophic pelagic area, which occupies a larger water volume. In this study, we investigated the abundance, diversity, and composition of free-living and particle-associated vibrios and their relationships with environmental factors along the water depth in the eastern tropical Indian Ocean (ETIO). The abundance of vibrios in free-living fractions was significantly higher than that of particle-associated fractions on the surface. Still, both were similar at the bottom, indicating that vibrios may shift from free-living lifestyles on the surface to mixed lifestyles at the bottom. Vibrio-specific 16S rRNA gene amplicon sequencing revealed that Paraphotobacterium marinum and Vibrio rotiferianus were dominant species in the water column, and Vibrio parahaemolyticus (a clinically important pathogen) was recorded in 102 samples of 111 seawater samples in 10 sites, which showed significant difference from the marginal seas. The community composition also shifted, corresponding to different depths in the water column. Paraphotobacterium marinum decreased with depth, and V. rotiferianus OTU1528 was mainly distributed in deeper water, which significantly correlated with the alteration of environmental factors (e.g., temperature, salinity, and dissolved oxygen). In addition to temperature and salinity, dissolved oxygen (DO) was an important factor that affected the composition and abundance of Vibrio communities in the ETIO. Our study revealed the vertical dynamics and preferential lifestyles of vibrios in the ETIO, helping to fill a knowledge gap on their ecological distribution in oligotrophic pelagic areas and fully understanding the response of vibrios in a global warming environment.

Investigating subtypes of lung adenocarcinoma by oxidative stress and immunotherapy related genes.

Lung adenocarcinoma (LUAD) is one of the most widespread and fatal types of lung cancer. Oxidative stress, resulting from an imbalance in the production and accumulation of reactive oxygen species (ROS), is considered a promising therapeutic target for cancer treatment. Currently, immune checkpoint blockade (ICB) therapy is being explored as a potentially effective treatment for early-stage LUAD. In this research, we aim to identify distinct subtypes of LUAD patients by investigating genes associated with oxidative stress and immunotherapy. Additionally, we aim to propose subtype-specific therapeutic strategies. We conducted a thorough search of the Gene Expression Omnibus (GEO) datasets. From this search, we pinpointed datasets that contained both expression data and survival information. We selected genes associated with oxidative stress and immunotherapy using keyword searches on GeneCards. We then combined expression data of LUAD samples from both The Cancer Genome Atlas (TCGA) and 11 GEO datasets, forming a unified dataset. This dataset was subsequently divided into two subsets, Dataset_Training and Dataset_Testing, using a random bifurcation method, with each subset containing 50% of the data. We applied consensus clustering (CC) analysis to identify distinct LUAD subtypes within the Dataset_Training. Molecular variances associated with oxidative stress levels, the tumor microenvironment (TME), and immune checkpoint genes (ICGs) were then investigated among these subtypes. Employing feature selection combined with machine learning techniques, we constructed models that achieved the highest accuracy levels. We validated the identified subtypes and models from Dataset_Training using Dataset_Testing. A hub gene with the highest importance values in the machine learning model was identified. We then utilized virtual screening to discover potential compounds targeting this hub gene. In the unified dataset, we integrated 2,154 LUAD samples from TCGA-LUAD and 11 GEO datasets. We specifically selected 1,311 genes associated with immune and oxidative stress processes. The expression data of these genes were then employed for subtype identification through CC analysis. Within Dataset_Training, two distinct subtypes emerged, each marked by different levels of immune and oxidative stress pathway values. Consequently, we named these as the OX+ and IM+ subtypes. Notably, the OX+ subtype showed increased oxidative stress levels, correlating with a worse prognosis than the IM+ subtype. Conversely, the IM+ subtype demonstrated enhanced levels of immune pathways, immune cells, and ICGs compared to the OX+ subtype. We reconfirmed these findings in Dataset_Testing. Through gene selection, we identified an optimal combination of 12 genes for predicting LUAD subtypes: ACP1, AURKA, BIRC5, CYC1, GSTP1, HSPD1, HSPE1, MDH2, MRPL13, NDUFS1, SNRPD1, and SORD. Out of the four machine learning models we tested, the support vector machine (SVM) stood out, achieving the highest area under the curve (AUC) of 0.86 and an accuracy of 0.78 on Dataset_Testing. We focused on HSPE1, which was designated as the hub gene due to its paramount importance in the SVM model, and computed the docking structures for four compounds: ZINC3978005 (Dihydroergotamine), ZINC52955754 (Ergotamine), ZINC150588351 (Elbasvir), and ZINC242548690 (Digoxin). Our study identified two subtypes of LUAD patients based on oxidative stress and immunotherapy-related genes. Our findings provided subtype-specific therapeutic strategies.

BERT2DAb: a pre-trained model for antibody representation based on amino acid sequences and 2D-structure.

Prior research has generated a vast amount of antibody sequences, which has allowed the pre-training of language models on amino acid sequences to improve the efficiency of antibody screening and optimization. However, compared to those for proteins, there are fewer pre-trained language models available for antibody sequences. Additionally, existing pre-trained models solely rely on embedding representations using amino acids or k-mers, which do not explicitly take into account the role of secondary structure features. Here, we present a new pre-trained model called BERT2DAb. This model incorporates secondary structure information based on self-attention to learn representations of antibody sequences. Our model achieves state-of-the-art performance on three downstream tasks, including two antigen-antibody binding classification tasks (precision: 85.15%/94.86%; recall:87.41%/86.15%) and one antigen-antibody complex mutation binding free energy prediction task (Pearson correlation coefficient: 0.77). Moreover, we propose a novel method to analyze the relationship between attention weights and contact states of pairs of subsequences in tertiary structures. This enhances the interpretability of BERT2DAb. Overall, our model demonstrates strong potential for improving antibody screening and design through downstream applications.

Distinct coral environments shape the dynamic of planktonic Vibrio spp.

BACKGROUND: Coral reefs are one of the most biodiverse and productive ecosystems, providing habitat for a vast of species. Reef-building scleractinian corals with a symbiotic microbiome, including bacteria, archaea, viruses and eukaryotic microbes, are referred to coral holobionts. Among them, coral diseases, mainly caused by Vibrio spp., have significantly contributed to the loss of coral cover and diversity. Habitat filtering across the globe has led to a variety structure of marine bacterial communities. Coral species, quantity and characteristics are significant differences between the Xisha Islands and Daya Bay (Guangdong Province). Thus, the Vibrio communities may be distinct between coral rich and poor areas. RESULTS: Through comparison of Vibrio dynamics between coral-rich (Xisha Islands) and coral-poor (Daya Bay) locations, we uncovered differences in Vibrio abundance, diversity, community composition and assembly mechanisms associated with corals. The higher abundance of Vibrio in coral rich areas may indicate a strong interaction between vibrios and corals. V. campbellii, Paraphotobacterium marinum and V. caribbeanicus were widely distributed in both coral rich and poor areas, likely indicating weak species specificity in the coral-stimulated growth of Vibrio. Random-forest prediction revealed Vibrio species and Photobacterium species as potential microbial indicators in the coral rich and coral poor areas, respectively. Ecological drift rather than selection governed the Vibrio community assembly in the Xisha Islands. Comparatively, homogenizing selection was more important for the Daya Bay community, which may reflect a role of habitat filtration. CONCLUSION: This study revealed the different distribution pattern and assembly mechanism of Vibrio spp. between coral rich and poor areas, providing the background data for the research of Vibrio community in coral reef areas and may help the protection of coral reef at the biological level. The main reasons for the difference were different number and species of corals, environmental (e.g., temperature) and spatial factors. It reflected the strong interaction between Vibrio and corals, and provided a new perspective for the investigation of Vibrio in coral reef ecosystem.

Photobacterium obscurum sp. nov., a marine bacterium isolated from the coast of Qingdao.

A Gram-stain-negative, facultative anaerobic, rod-shaped strain, named SDRW27T, was isolated from offshore seawater collected near Qingdao. Strain SDRW27T was able to grow at 16-37 °C (optimum, 28 °C), pH 6.0-9.0 (optimum, pH 6.0) and in the presence of 1-7 % (w/v) NaCl (optimum, 3 %). Phylogenetic analysis using 16S rRNA gene sequences indicated that strain SDRW27T was most closely related to Photobacterium toruni H01100410BT (97.89 % sequence similarity), Photobacterium andalusiense H01100409BT (97.89 %) and Photobacterium leiognathi ATCC 25521T (97.82 %). The predominant fatty acids were summed feature 3 (C16 : 1 ω7c and/or iso-C15 : 0 2-OH), summed feature 8 (C18 : 1 ω7c and/or C18 : 1 ω6c) and C16 : 0. The polar lipids of strain SDRW27T comprised phosphatidylglycerol, phosphatidylinositol dimannoside, phosphatidylcholine, phosphatidylethanolamine and three unidentified lipids. The major respiratory quinone was ubiquinone-8. The G+C content was 47.71 mol%. The genome size was 5.84 Mbp, including 85 contigs with an N50 value of 223 542. The average nucleotide identity (ANI) values of SDRW27T with its three most similar strains, P. toruni H01100410BT, P. andalusiense H01100409BT and P. leiognathi ATCC 25521T, were 71.36, 71.58 and 72.23 %, respectively (all lower than the 95-96 % ANI threshold), and the DNA-DNA hybridization (DDH) values were 20.4, 20.8 and 20.4 % (all lower than the 70 % DDH threshold). The obtained results of polyphasic analysis demonstrate that strain SDRW27T represents a novel species, for which the name Photobacterium obscurum sp. nov. is proposed. The type strain is SDRW27T (=MCCC 1K06286T=KCTC 82892T).

DeepCIP: A multimodal deep learning method for the prediction of internal ribosome entry sites of circRNAs.

Circular RNAs (circRNAs) have been found to have the ability to encode proteins through internal ribosome entry sites (IRESs), which are essential RNA regulatory elements for cap-independent translation. Identification of IRES elements in circRNA is crucial for understanding its function. Previous studies have presented IRES predictors based on machine learning techniques, but they were mainly designed for linear RNA IRES. In this study, we proposed DeepCIP (Deep learning method for CircRNA IRES Prediction), a multimodal deep learning approach that employs both sequence and structural information for circRNA IRES prediction. Our results demonstrate the effectiveness of the sequence and structure models used by DeepCIP in feature extraction and suggest that integrating sequence and structural information efficiently improves the accuracy of prediction. The comparison studies indicate that DeepCIP outperforms other comparative methods on the test set and real circRNA IRES dataset. Furthermore, through the integration of an interpretable analysis mechanism, we elucidate the sequence patterns learned by our model, which align with the previous discovery of motifs that facilitate circRNA translation. Thus, DeepCIP has the potential to enhance the study of the coding potential of circRNAs and contribute to the design of circRNA-based drugs. DeepCIP as a standalone program is freely available at https://github.org/zjupgx/DeepCIP.

Targeted genome mining for microbial antitumor agents acting through DNA intercalation.

Microbial natural products have been one of the most important sources for drug development. In the current postgenomic era, sequence-driven approaches for natural product discovery are becoming increasingly popular. Here, we develop an effective genome mining strategy for the targeted discovery of microbial metabolites with antitumor activities. Our method employs uvrA-like genes as genetic markers, which have been identified in the biosynthetic gene clusters (BGCs) of several chemotherapeutic drugs of microbial origin and confer self-resistance to the corresponding producers. Through systematic genomic analysis of gifted actinobacteria genera, identification of uvrA-like gene-containing BGCs, and targeted isolation of products from a BGC prioritized for metabolic analysis, we identified a new tetracycline-type DNA intercalator timmycins. Our results thus provide a new genome mining strategy for the efficient discovery of antitumor agents acting through DNA intercalation.