Science China Life Sciences最新文献

Biological taxonomy faces an inflection point. In this review, we trace its progress through three technology-driven eras-morphology, molecular, and today's emerging artificial intelligence (AI)-driven stage-and discuss how each successive toolkit has expanded rather than replaced the last. This review elucidates the transformative impact of deep learning across four domains: biological image-based classification, bioacoustics-based classification, genetic sequence-based classification, and the elucidation of species traits. Foundation models that treat genomes as a "language" have begun to link sequence variation with protein structure, phenotype, and ecological niche, hinting at a more fundamental, data-driven basis for delimiting species. We highlight the recent breakthroughs in deep learning and foundation models and argue that fully integrated, causality-aware models could deliver a step-change in biological taxonomy. However, key challenges persist, spanning data quality, algorithmic robustness, reference-library completeness, model transparency, and shared standards. Taxonomists' deep knowledge of trait evolution gives them a unique role in the ongoing convergence of AI and biological taxonomy, particularly in guiding foundation-model development. As AI moves toward reasoning over complex biological causality, even core taxonomic concepts may evolve; recognizing and steering that transformation is both the challenge and the opportunity of this AI-driven era.

Macrophage polarization of tumor-associated macrophages (TAMs) is critical for cancer development, while the impact of N⁶-methyladenosine (m⁶A) on the polarization of TAMs remains poorly understood. This study investigated the function of m⁶A modification in macrophages and demonstrated that methyltransferase-like 3 (METTL3) can downregulate the alternatively activated macrophages (M2) polarization level of TAMs via suppression of snail family transcriptional repressor 1 (Snail) protein translation. Independent of protein stability, METTL3 restrained the translation efficiency of Snail in an m⁶A-dependent manner, thereby inhibiting M2 polarization of TAMs. The m⁶A binding protein insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) recognized the 3'-untranslated region (3'-UTR) m⁶A modification site of Snail and regulated the translation of Snail through its influence on the binding of eukaryotic translation release factor 1 (eRF1) and eukaryotic translation release factor 3 (eRF3) to Snail mRNA. Targeted specific demethylation of Snail m⁶A by the dm⁶ACRISPR system can significantly increase the protein expression of Snail and M2 polarization of TAMs. In a mouse xenograft model, knocking down the expression of METTL3 in macrophages significantly promoted tumor growth. Meanwhile, database analyses indicated the level of m⁶A in macrophages was inversely proportional to the degree of macrophage infiltration in tumors. Collectively, m⁶A suppressed M2 polarization of TAMs via Snail protein translation, which attenuated cancer cell growth and cancer development.

Melanin is an advanced polymer with exceptional properties, widely used across cosmetics, pharmaceuticals, environmental applications, and more. However, its broader use is constrained by high production costs and limited availability. Lignin, the most abundant and renewable aromatic compound in nature, presents a promising alternative for synthesizing melanin. This study focuses on converting plentiful and cost-effective lignin into melanin through the metabolic engineering of Cupriavidus necator H16. By constructing and optimizing metabolic pathways, engineered C. necator strains were developed to synthesize melanin from lignin monomers and lignin hydrolysates. Using substrates like p-coumaric acid, caffeic acid, ferulic acid, and lignin hydrolysates, the resting cell method with C. necator produced 0.86, 1.00, 0.52, and 0.32 g L^-1 of melanin, respectively. The purified melanin was analyzed and identified spectrally, revealing characteristics of isomelanin. Furthermore, sun protection factor studies demonstrated that the produced melanin offered significant UV protection. The use of engineered C. necator to convert abundant lignin hydrolysates into melanin holds great promise for reducing production costs and expanding its applications.

We aimed to firstly explore characteristics and prognostic factors of therapy-related acute myeloid leukemia (t-AML) in multi-center samples in China. We analyzed 228 t-AML patients from 14 centers across China. The median age at t-AML diagnosis was 52 years (range, 1.3-89 years). The median latency interval was 45.8 months (19.2-142.8 months). Next generation sequencing (NGS) results were available in 150 (65.8%) patients. The overall survival (OS) and disease-free survival rates of all t-AML were 58.3% and 63.7%, respectively. In t-AML patients, NPM1 mutation (85.0% vs. 54.4%, P=0.01), core binding factor (CBF) (RUNX1/RUNX1T1 and CBFβ/MYH11) (70.7% vs. 55.1%, P=0.03), and allogeneic hematopoietic stem cell transplantation (allo-HSCT) (86.0% vs. 67.9%, P=0.02) were associated with significantly better OS, while the 2022 ELN intermediate-adverse risk group had worse OS than the favorable group (55.9% vs. 73.1%, P=0.02). In multivariable analyses, NPM1 mutation, CBF t-AML, primary tumor remission, WBC count ⩽15×10⁹ L^-1, CRc after one course and allo-HSCT were associated with favorable OS. Regarding NGS molecular analysis, in addition to the positive effects of NPM1 on OS, our study identified TP53 mutation as a risk factor associated with poor OS (40.0% vs. 66.6%, P=0.03, HR=2.64). We developed a prognostic scoring system including clinical and molecular profiles termed NTCTH (NPM1 (HR=0.16), TP53 (HR=3.45), CBF t-AML (HR=0.09), first course intensive induction Therapy regime (HR=0.24), and allo-HSCT (HR=0.36)) in patients who performed NGS. Our study first demonstrated prognostic factors of t-AML in large samples from multiple centers in China and found that NPM1 and CBF t-AML were associated with superior OS, and TP53 was associated with inferior OS.

An accurate map of intracellular organelle pH is crucial for comprehending cellular metabolism and organellar functions. However, a unified intracellular pH spectrum using a single probe is still lacking. Here, we developed a novel quantum entanglement-enhanced pH- sensitive probe called SITE-pHorin (single excitation and two emissions pH sensor protein), which features a wide pH-sensitive range and ratiometric quantitative measurement capabilities. We subsequently measured the pH of various organelles and their subcompartments, including mitochondrial subspaces, Golgi stacks, endoplasmic reticulum (ER), lysosomes, peroxisomes, and endosomes in COS-7 cells. For the long-standing debate on the pH of the mitochondrial compartments, we measured the pH of the mitochondrial cristae (mito-cristae) as 6.60±0.40, the pH of the mitochondrial intermembrane space (mito-IMS) as 6.95±0.30, and the pH of the two populations of the mitochondrial matrix (mito-matrix) at approximately 7.20±0.27 and 7.50±0.16, respectively. Notably, the pH of the lysosome exhibited a single, narrow Gaussian distribution centered at 4.79±0.17, which is consistent with an optimal lysosomal acidic pH between 4.5 and 5.0. Furthermore, quantum chemistry computations revealed that both the deprotonation of the residue Y182 and the discrete curvature of the deformed benzene ring in the chromophore are necessary for the quantum entanglement mechanism of SITE-pHorin. Intriguingly, our findings reveal an accurate pH gradient (0.6-0.9 pH units) between the mitochondrial cristae and the mitochondrial matrix, suggesting that prior knowledge about ΔpH (0.4-0.6) and the mitochondrial proton motive force (pmf) is underestimated.