Proteins are fundamental molecules central to life activity, with their three-dimensional structures determining their biological functions and mechanisms of action. Although experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR), and cryo-electron microscopy (cryo-EM) have achieved significant success in structural elucidation, they still face challenges such as high cost, long time consumption, and limited applicability. In recent years, rapid advancements in artificial intelligence, particularly deep learning techniques, have revolutionized protein structure prediction. From early statistical energy functions and homology modeling to cutting-edge deep learning models integrating multi-head attention mechanisms and large-scale parameterized networks, there have been substantial improvements in both prediction accuracy and efficiency. Algorithms represented by AlphaFold and RoseTTAFold have not only consistently achieved remarkable results in static structure prediction but also demonstrated broad application prospects in variant screening, drug design, and precision medicine. Furthermore, this review systematically presents structure-prediction methods based on protein language models (such as ESM-3), and further explores two categories of exploratory strategies－those based on spectral descriptors and those employing sampling-augmented deep learning with large-scale biophysical data－while assessing their research progress and application potential, thereby providing theoretical and practical guidance for future studies.

With the rapid advancement of synthetic biology and microbial metabolic engineering, the construction of microbial cell factories has achieved significant progress, facilitating the transition from traditional fossil resource-dependent industrial production to green biosynthesis based on renewable resources. Microbial cell factories enable the biosynthesis of chemicals, offering substantial environmental and economic benefits while providing critical technological support for sustainable production of bulk chemicals, high-value-added compounds, and biofuels. However, microbial metabolic engineering still faces numerous challenges, including the accumulation of intermediate metabolites, insufficient catalytic activity of key enzymes, and low yields and conversion rates of target products, all of which hinder its industrial application. To address these challenges, transcription factor-based biosensors have emerged as essential tools. Their ability to sense and transmit signals allows dynamic optimization of microbial metabolic fluxes, enhanced activity of critical enzymes, and high-throughput screening of superior strains, effectively mitigating these bottlenecks. This review systematically summarized the classification and characteristics of transcription factor-based biosensors, highlighting key strategies for optimizing signal sensing elements, signal transduction components, and output modules. Furthermore, it explored their practical applications in dynamic metabolic flux control, metabolic pathway optimization, and high-throughput screening. Finally, this review provided a perspective on future directions in this field, aiming to guide further advancements in biosensor development and applications.

This review systematically summarized strategies for modifying nicotine-degrading microbial strains and key enzymes using synthetic biology approaches. It highlighted the application progress of engineered strains and enzymes in three key areas: tobacco waste bioremediation, biosynthesis of high-value compounds, and tobacco leaf quality enhancement. The analysis identified significant bottlenecks hindering technological industrialization, including insufficient environmental adaptability of engineered strains and significant carbon catabolite repression. Future research should focus on: optimizing chassis microorganism performance through synthetic biology approaches; elucidating metabolic regulatory networks through integrated multi-omics technologies; and exploring the high-value utilization pathways of degradation products. These efforts aim to establish a green technological system enabling “efficient pollutant treatment-resource recycling and regeneration”. This review aimed to provide a reference for systematic solutions to nicotine pollution control and resource utilization, and to promote sustainable development and ecological security within the tobacco industry.

Low-protein diets is one of the important methods to solve the shortage of feed protein resources in China’s livestock and poultry industry. This approach is a low-protein feed pattern that is based on amino acid nutrition balance theory. It adds an appropriate amount of essential amino acids to meet the balanced amino acid nutrition required during the growth process of animals without affecting their healthy growth. However, the chemical synthesis of some limiting amino acids is complex, and the production efficiency is relatively low, while the production of amino acids through biological synthesis is of higher quality and lower cost. It is the core of low-protein diet development and application to develop high-efficiency amino acid biosynthesis technology. In this article, the biosynthetic pathways of several important amino acids in the low-protein diet model were systematically reviewed. This review pointed out that the selection of host strains and metabolic engineering modification was key to high-yield strains. The advantageous strains were introduced for the biosynthesis of amino acids, providing methods and directions for high-yield strain modification. The bioproduction of limiting amino acids in low-protein diet can better promote the healthy development of China’s animal husbandry industry.

To rapidly develop tryptophan overproducers, high-throughput screening was performed on key enzyme in the tryptophan biosynthetic pathway and the chassis strains. The tube fermentation system was optimized to maintain high production consistency with flask fermentation. A colorimetric method compatible with the tube fermentation system was established for tryptophan quantification, using the reaction of tryptophan with naphthylethylenediamine dihydrochloride, providing a detection range of 50 mg/L to 1000 mg/L. Using this method, a superior enzyme mutant, TktA2, was successfully identified from a random mutagenesis library of transketolase TktA. Compared to the wild-type TktA, TktA2 exhibited a more compact dimer structure and a larger substrate-binding pocket, which contributed to the enhanced enzyme stability and substrate turnover rate. Additionally, a dominant chassis strain, T51, was isolated from a genome-reduced strain library of MG1655. Overexpression of TktA2 in T51 yielded the tryptophan overproducer, T51A2ΔtrpRΔtnaB, producing 31.37 g/L tryptophan in a 3 L bioreactor, at a sugar-to-acid conversion rate of 19.01% and an 80.49% higher titer than that of the parental strain. This employed a rapid tryptophan detection method for cost-effective and efficient screening of key enzyme and chassis strains at the tube fermentation level. The integrated high-yielding tryptophan producer maintained high-performance even after fermentation scale-up, laying a foundation for the development of tryptophan overproduction strains.

The starting strain，Escherichia coliMG1655 (M0)， was selected for this study, and the CRISPR/Cas9 genome editing technology was utilized to optimize theL-arginine synthesis gene cluster. Initially, the ornithine decarboxylase genesspeCandspeFwere knocked out to enhance the ornithine supply, a precursor of arginine. Subsequently, integration of theargCJBDFgene cluster fromCorynebacterium glutamatewas used to deactivate the arginine decarboxylase geneadiA, blockingL-arginine degradation while enhancing its synthesis pathway. The resulting recombinant strain M1 (MG1655ΔspeCΔspeFΔadiA::argCJBDF) achieved an arginine yield of 1.35 g/L, representing a 0.88 g/L increase compared to strain M0. Untargeted metabolomics analysis revealed significant alterations in the arginine metabolic pathway and related metabolite concentrations in recombinant strain M1, impacting amino acid synthesis such as arginine and lysine, organic acids, and other metabolites. This study offers insights into potential strategies for regulating these alternate metabolic pathways and developing high-yieldL-arginine engineering strains.

This study investigated how miR-556 affects proliferation, genome-wide transcription and gene-function networks in human glioblastoma U-87 MG cells. A miR-556-overexpressing line was generated by lentiviral transduction and puromycin selection; precursor and mature miR-556 levels were quantified by qRT-PCR and standard RT-PCR. Cell proliferation and clonogenic capacity were assessed with CCK-8 and crystal-violet assays, respectively. RNA-seq was used to map transcriptional and pathway changes. Relative to the control (rLV) group, the miR-556-overexpressing (rLV-miR-556) group exhibited significantly increasedin vitroproliferation and colony formation (P<0.01). RNA-seq revealed 2028 differentially expressed genes (165 up- and 1863 down-regulated) between the two groups. miR-556 up-regulatedHMOX1,SERPINB2andATOH8while down-regulatingMACF1,PEG10andHIF1A, thereby modulating pathways related to gene transcription, transmembrane transport, RNA polymerase Ⅱ activity, post-translational modification, protein metabolism, immune responses and disease-related pathways. These findings indicate that miR-556 enhances glioblastoma cell growth and reshapes the transcriptional landscape, providing a basis for future intervention strategies.

In this study, specific primers were designed for molecular cloning from the genomic DNA of three cone snails from the South China Sea:Conus imperialis, Conus virgo, andConus marmoreus. The authors cloned the complete sequence of 8 A-superfamily conotoxin precursor genes, with 4 fromC. imperialis, 2 fromC. virgo, and 2 fromC. marmoreus. The authors analyzed the intron sequence characteristics and the relationship between molecular evolution and diet, conducted a systematic analysis of the sequence structural A-superfamily conotoxin gene structures, and constructed an intron-based phylogenetic tree. The intron lengths of the A-superfamily conotoxin genes ranged from 139 bp to 1010 bp, and the GT or TG dinucleotide simple repeat sequences (units) were all located at the intron ends, indicating possible insertions/deletions in the A-superfamily conotoxin intron region. This study represented the first complete cloning of A-superfamily conotoxin genes fromC. imperialis,C. virgo, andC. marmoreus. It indicated that the evolution of introns in the A-superfamily conotoxin precursor genes was influenced by diet, and elaborated on the structural features and the molecular evolutionary mechanisms of this superfamily gene. Additionally, intron conservation in conotoxin precursor genes of the same superfamily served as molecular markers for primer design, which discovered more new conopeptide amino acid sequences from different species and individuals ofConus. This research is expected to provide a plethora of new molecules for subsequent artificial synthesis and new drug development.

The calcium ion channel of Yvc1 on the vacuolar membrane inSaccharomyces cerevisiaeis one of the important ways to regulate the intracellular Ca2+ concentration. As a second messenger, Ca2+ can improve the ethanol production capacity ofSaccharomyces cerevisiae. Therefore, it will lay the foundation for the further study of calcium channel function that theYVC1gene deletion strain is constructed. The presence of theYVC1gene inSaccharomyces cerevisiaeDL5168 was confirmed by PCR. The chromosome ploidy of strain DL5168 was identified by Ziehl-Neelsen’s stain and genome-specific PCR. Based on the principle of Cre/loxP system,YVC1gene knockout module was constructed and transformed into the strain of DL5168 via lithium acetate conversion method, and positive recombiners were screened on YPD medium supplemented with 100 μg/mL G418. The pSH65 plasmid was transferred into the positive recombinant to remove the resistance gene ofKanMX. The results showed that the genome ofSaccharomyces cerevisiaeDL5168 contained the vacuole conductivity-1 geneYVC1. Strain DL5168 was proved to be an aα-type diploid. The pUG6-YVC1-loxP-KanMX knockout module successfully underwent homologous recombination with DL5168, yielding positive recombinants. The resistance geneKanMXon the recombinant DL5168-yvc1Δ-kanmxwas successfully removed with the pSH65 plasmid producing Cre recombinase under the induction of galactose. This resulted in the generation of aYVC1deficient allele strain, designated DL5168-yvc1Δ. The allele ofYVC1on the other homologous chromosome was deleted by the same method. Finally, theYVC1gene diploidy deletion strain of DL5168-yvc1Δ/Δ was successfully constructed in this study.

This study aimed at the problem of poor regularity in the secretion efficiency of heterologous proteins guided by signal peptides. Eight datasets were constructed from the relevant data of the secretion of heterologous proteins guided by signal peptides fromBacillus subtilis, and prediction models of signal peptide secretion efficiency were developed using support vector machine (SVM) and Random Forest (RF) algorithms. Through various permutations of datasets, sequence features, and computational algorithms, a total of 458 classification models and 228 regression models were devised. The RF algorithm demonstrated superior classification performance, achieving 83.21% accuracy with the α-amylase dataset. In regression analysis, RF also outperformed other methods for the α-amylase dataset, yielding a model with a determination coefficient of 0.43. Additionally, the work revealed compositional differences in amino acids and GC3 content (the frequency of G and C nucleotides at the third position of codons) between high- and low-efficiency signal peptides, highlighting that good-performing signal peptides tended to have a higher proportion of unfolded amino acids and elevated GC3 content. In this study, the prediction of signal peptide secretion efficiency was realized, and the factors affecting the secretion efficiency of signal peptide were explored.

Previously, the glycosyltransferase mutant TW (S129T/F168W) was obtained to improve the production of salidroside. In this research, a cascade reaction comprising glycosyltransferase mutant TW and sucrose synthaseAtSuSy for salidroside synthesis was constructed. The cascade reaction conditions including temperature, pH, uridine diphosphate (UDP), sucrose, tyrosol, metal ions and two-enzyme ratio were optimized. Furthermore, the fed-batch cascade reaction was carried out under the optimal conditions to achieve the regeneration of uridine diphosphate-glucose (UDPG) and promote salidroside synthesis. Optimal conditions for salidroside synthesis were determined as: temperature of 35 ℃, pH 8.0, UDP concentration of 0.5 mmol/L, sucrose concentration of 1 mol/L, tyrosol concentration of 5 mmol/L, Ca2+ concentration of 5 mmol/L, and TW∶AtSuSy enzyme activity ratio of 0.5∶6. In a 10 mL reaction system, the yield of salidroside reached 10.3 g/L by cascade reaction using fed-batch strategy. Moreover, the possible molecular mechanism responsible for salidroside synthesis was also investigated by molecular docking, demonstrating that effective hydrogen bonds contributed to the efficient synthesis of salidroside. This study establishes a foundation for efficient salidroside preparation in industrial application in the future.

To effectively control the spread ofSolanum rostratum, this study used the principle of biological allelopathy to treat the seeds ofS. rostratumwith different concentrations of extracts from the aboveground and underground parts ofStellera chamaejasme, and corn seeds were used as the control to investigate effects ofS. chamaejasmeextracts on seed germination and embryo development ofS. rostratum. The allelopathic effect index and comprehensive allelopathic effect index were calculated by measuring germination rate, germination potential, germination index, radicle and hypocotyl length to evaluate the allelopathic effect ofS. chamaejasmeextract. The results showed that the inhibitory effect of the extract from the underground part ofS. chamaejasmeon seed germination and embryo development ofS. rostratumwas significantly stronger than that of the extract from the aboveground part. The inhibitory effect ofS. chamaejasmeextract onS. rostratumseeds was significantly greater than that of corn seeds. With the increase of extract concentration, the germination rate, germination potential and germination index ofS. rostratumand corn seeds showed downward trends, and the radicle length and germ length of corn seeds showed a trend of “low promotion and high inhibition”. While ensuring a small impact on corn seed germination, 40 g/L of underground part ofS. chamaejasmeextract was the optimal treatment mass concentration. At this mass concentration, the germination rate ofS. rostratumseeds was 0.08%, and the comprehensive allelopathic effect index was －0.78. The germination rate of corn seeds was 63.33%, and the comprehensive allelopathic effect index was －0.31.

This study investigated the effects of tetracycline mass concentration and tetracycline degrading bacteriumSerratia entomophilastrain TC-1 on the removal rate of pollutants in the microalgal-bacterial symbiotic system. Through scanning electron microscopy observation and high-throughput sequencing technology, the changes in microbial community structure were further analyzed to reveal the pollutant removal patterns and microbial response mechanisms of the bacterial algal symbiotic system under tetracycline stress. The research results showed that the higher the tetracycline concentration, the lower the microalgal biomass, and the lower the ammonia nitrogen removal rate of the microalgal-bacterial symbiotic system. When the mass concentration of tetracycline was 50 mg/L, the chlorophyll mass concentration was 19.19 mg/L, and the ammonia nitrogen removal rate of the microalgal-bacterial symbiotic system was the lowest, at 75.27%. Through scanning electron microscopy observation, it was found that bacteria could alleviate the stress effect of tetracycline by attaching to the surface of microalgae cells and secreting extracellular polymeric substances. Microbial community analysis showed that the mass concentration of tetracycline had a significantly greater impact on bacterial community structure than the inoculation of degrading bacteria. Inoculating degrading bacteria alleviated the effects of low mass concentrations of tetracycline on bacterial community structure. The tetracycline degrading bacteriaTrichococcusreduced the impact of low mass concentrations of tetracycline on the microalgal bacterial consortia, while the stress resistant bacteriaPseudomonasand denitrifying polyphosphate accumulating bacteriaComamonasreduced the impact of high mass concentrations of tetracycline on the microalgal bacterial consortia.

In this study, the effect of different temperatures on locomotor performance and antioxidant enzyme activities inEremias roborowskiiwas investigated. Our results indicated that there was a significant positive correlation between the body temperature and cloaca temperature inE. roborowskii, and both of them increased with the rising ambient temperature. Compared with the control group, the elevated temperature significantly increased the sprint speed and the length of continuous locomotion, while the pause frequency significantly decreased. The high-temperature group exhibited greater locomotor activity, with a significant positive correlation between environmental temperature and maximum sprint speed. Furthermore, high temperatures induced oxidative stress inE. roborowskii, resulting in a marked increase in hepatic malondialdehyde levels and significant upregulation of catalase and glutathione peroxidase activities. Peroxidase activity showed an increasing trend, while superoxide dismutase activity declined.E. roborowskiidemonstrated a certain capacity to adapt to short-term warming, but the frequency and intensity of extreme heat events might increase due to global warming, excessive temperatures could exacerbate heat stress and oxidative damage, potentially threatening their survival. This study provides an important foundation to the physiological and ecological research of extreme desert animals, offering theoretical data for the adaptation mechanism ofEremias roborowskiito extreme environment under global warming.

The morphology of the jaws and denticles ofSinospelaeobdella wulingensisandHaemadipsa tianmushanawas examined using stereomicroscopy and scanning electron microscopy. The main results showed that inSinospelaeobdella wulingensis, the triple jaws were minute and soft in texture, with large spacing between the jaws, and with approximately 80－90 denticles in a single row on the free margin of the jaws. In contrast, inHaemadipsa tianmushana, the triple jaws were well-developed, and hard in texture, with small spacing between the jaws, and with approximately 110－120 denticles in a single row on the free edge of the jaws. Salivary gland secretory pores were exclusively observed at the base of adjacent denticles inHaemadipsa tianmushana. The morphological features of the jaws and the number of denticles of leechers were closely related to their feeding habits. WhileH. tianmushanais an obligate blood-feeder,S. wulingensisis a facultative blood-feeder. These differences suggested morphological adaptations have occurred in their jaws and denticles of these two species. This study provided new morphological evidences for distinguishingSinospelaeobdellafromHaemadipsa, and contributes to further investigation on taxonomy, functional morphology, behavioral ecology and evolutionary ecology for Haemadipsidae.

Streptomyces, as an important group of microorganisms, produces a wide range of natural products, including anticancer, antiviral, antifungal, and antiparasitic bioactive compounds, and plays a crucial role in pharmaceuticals, agriculture, and the chemical industry. The secondary metabolites ofStreptomycesmainly consist of polyketide compounds and non-ribosomal peptides. However, due to the extremely complex metabolic network and regulatory mechanisms ofStreptomyces, coupled with the fact that their biosynthetic gene clusters are silent under most environmental conditions, the yield of natural products is low, which limits their application in industrial production. Therefore, studying how to activate silent biosynthetic gene clusters and using molecular biology breeding strategies to increase the production of natural products are of great significance. Given the agricultural significance of secondary metabolites, this review outlined the biosynthetic pathways of polyketide compounds and non-ribosomal peptides inStreptomyces, and summarized the strategies to improve the yield of natural products inStreptomycesin recent years, such as mutation breeding, carbon, nitrogen and phosphorus metabolic pathway modification and heterologous expression. Future research directions integrating high-throughput screening with computational prediction were proposed, aiming to advance the research of secondary metabolites ofStreptomycesand provide a basis for the development and application of polyketide compounds and non-ribosomal peptides.

The sedimentation velocity analytical ultracentrifugation （AUC-SV） is a classical biophysical technique for determining the size and shape of molecules in solution, enabling characterization of molecular interactions with regard to the number, size, stoichiometry, and affinity of complexes formed in association processes. A method for the analysis of receptor and ligand interactions between CD32b, an important immune marker molecule, and Fc fragment of Human IgG1 antibody, was established by AUC-SV. Parallel experiments were conducted alongside classical methods for protein-protein interaction （PPI） analysis, such as surface plasmon resonance （SPR） and micro-scale thermophoresis （MST）. The reliability of the SV-AUC methodology for the analysis of PPI was further validated.

To cultivate students’ interest and develop professionals who can adapt to industry developments, building on our team’s research in transgenic zebrafish genetic engineering, this course introduced an experimental system that features visual intuition, pathological phenomena, dynamic real-time observation, and hands-on operations. The transgenic fish expressing nitroreductase (NTR) and fluorescent proteins based on the metronidazole/nitroreductase (MTZ/NTR) cell ablation system was constructed. Treatment with MTZ eliminated fluorescent-positive cells, and pathological manifestations including brain hemorrhage, thereby generating visually intuitive results. This experiment covered all core experiments in the cell genetic engineering course. Applying these research findings to course teaching enhanced the advanced and innovative nature of undergraduate courses and provide new approaches for integrated undergraduate-graduate genetic engineering education, improving the quality and efficiency of training. This addressed the demands for experimental teaching innovation and practice. This experimental reform practice empowered the construction of double first-class disciplines, and the development of national first-class undergraduate disciplines in biomedical engineering and bioengineering, thereby advancing national first-class undergraduate programs in bioengineering.

This study investigated the effectiveness of the case-based study (CBS) teaching method in standardized residency training and evaluated its impact on clinical reasoning, comprehensive competence, and doctor-patient communication skills. In the CBS group, a scenario-driven, interactive approach based on real cases was implemented, whereas the control group received traditional lecture-based instruction supplemented literature review. Outcomes were assessed through examinations basic knowledge, case analysis, and procedural skills using the Set Elicit Give Understand End (SEGUE) framework; and training feedback and satisfaction surveys. Results demonstrated that the CBS group achieved significantly higher mean scores all three examinations the control group (P<0.05). Post-training SEGUE scores improved markedly (P<0.001), higher in the CBS group (P<0.001). These findings suggest that the CBS teaching model enhances oncology residents theoretical knowledge, clinical thinking, procedural skills, and communication abilities, demonstrating its efficacy.

The traditional “teaching-learning” model primarily relies on teacher-centered instruction, where students passively acquire knowledge without opportunities to verify scientific hypotheses, thereby impeding the development of innovative thinking and skills. The “teaching-learning-application” model was adopted to integrate the topic of “environment and health” into undergraduate teaching of laboratory animal science. The course focused on the pathogenesis of cancers, diabetes, arteriosclerosis and other diseases caused by heavy metal cadmium and lead pollution, and the construction methods of related animal pathological models. The course guided students to explore scientific issues related to the topic of “environment and health”, applying acquired knowledge to formulate scientific hypotheses and designing their original experimental protocols. The experimental plan was discussed between teacher and students, and scientific hypotheses were verified through group experiments. Compared with the “teaching-learning” model, the “teaching-learning-application” model significantly improved students’ subjective initiative, evidenced by a significant increase in the proportion of students who actively search for literature, conduct experimental plan discussions, and propose scientific hypotheses after class. Assessment data demonstrated significant improvement in students’ ability to optimize experimental plans, address scientific problems, collaborate effectively, and verify scientific hypotheses. Several student-generated hypotheses were subsequently validated by international researchers. Integrating the topic of “environment and health” into undergraduate teaching of laboratory animal science and adopting the “teaching-learning-application” model can effectively enhance students’ subjective initiative and innovative thinking and ability of independent exploration, aligning with the national requirements for cultivating innovative talents.