Yunnan Normal University

Accurate subtyping of lung cancer is essential for improving patient prognosis and enabling personalized treatment. However, current clinical techniques are often time-consuming and heavily dependent on the operator's subjective judgment and experience, which limits the accuracy and timeliness of intraoperative subtype diagnosis and margin assessment. In this study, we developed an intelligent diagnostic model by integrating Fourier transform infrared (FTIR) spectroscopy with a Random Forest (RF) classifier. A total of 210 tumor and adjacent tissue samples from 105 patients, including adenocarcinoma, squamous cell carcinoma, and benign lung tumors were analyzed. The constructed RF model achieved an accuracy of 97.95% with an Area Under the Curve (AUC) of 0.99 in binary classification (lung cancer vs. adjacent tissues), and an accuracy of 94.91% in multiclass classification of lung cancer subtypes, significantly outperforming conventional algorithms such as Support Vector Machine, Naive Bayes, and Logistic Regression. In addition, spectral analysis methods, including peak area comparison, peak fitting, and second derivative analysis, revealed distinct differences in nucleic acids, proteins, and lipids, highlighting the characteristic bands responsible for subtype discrimination and providing spectroscopic insights into the pathological features of different lung cancer subtypes. Collectively, our findings demonstrate that the diagnostic model is a powerful approach for distinguishing lung cancer tissues from normal tissues and for subtype classification, offering a promising tool for lung cancer diagnosis.

Betulinic acid (BA) is a lupane-type pentacyclic triterpenoid with promising anti-inflammatory, antitumor, and anti-HIV activities. Currently, its commercial supply largely relies on plant extraction, which is suffering from low yield and high cost. Synthetic biology offers a sustainable and cost-effective alternative for BA production, yet its efficient microbial production is often hindered by insufficient precursor supply and poor fitness of plant-derived P450 enzymes. Here, we first engineered the precursor supply pathway inYarrowia lipolyticathrough modular metabolic engineering, boosting squalene production by 813-fold. Subsequently, we applied a semi-rational design strategy integrating computational tools with evolutionary information to functionally engineer CYP716A520 bottleneck. The optimal variant L359V exhibited markedly improved catalytic performance, with 4- and 3-fold increase in activity and specificity over wild-type enzyme, respectively. Molecular dynamics (MD) simulations revealed that the L359V mutation expands the substrate and water tunnels, thereby enhancing proton shuttle efficiency and facilitating substrate access. This study provides both a promising platform for scalable BA production and a broadly applicable strategy for engineering plant-derived P450s in microbial hosts for the production of high-value natural products.

The plastisphere, a unique ecological niche on plastic surfaces, enriches microbial antibiotic resistance genes (ARGs) and virulence factors (VFs), posing environmental and health risks. Although aquatic sediment is a major sink for plastic contaminants, the resistance, virulence and dissemination potentials of sedimented plastispheres remain poorly characterized compared to floating plastics. Through investigation of metagenomes from two sites in the Pearl River in China, one of the world's plastic pollution hotspots, we report that water plastisphere showed 2.4 and 3.6 times more ARG and VF genes than those in sediment plastisphere and surrounding environments, together with higher mobile genetic element (MGE) abundances and a denser ARG-VF co-occurrence network (5,879 vs. 2,874 edges; density 0.043 vs. 0.025), indicating enhanced horizontal gene transfer potential. These differences coincide with contrasting ARG/VF assembly mechanisms, with deterministic and stochastic assembly processes dominating ARG/VF profiles in water and sediment plastispheres, respectively. Genome-resolved analyses further revealed that dominant plastisphere populations harbored multiple ARGs and VFs, with 41 MAGs predicted with pathogenicity capacities, most of which belonged to the families Mycobacteriaceae, Aeromonadaceae, Moraxellaceae, and Pseudomonadaceae. Notably, these taxa have been repeatedly reported as common plastisphere members across diverse ecosystems, suggesting that elevated resistance and virulence in floating plastispheres may be a widespread phenomenon across aquatic ecosystems. Together, our findings demonstrate that floating plastics act as dynamic vectors of antimicrobial resistance and pathogenicity, as well as their dissemination potentials, highlighting water-sediment transition may reduce these ecological risks within the plastisphere.