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Biology subjects

Su, Z.

Publications and source records attributed to Su, Z..

At least 37 records · Page 2Linked to original sources

tRF-3021a, a tRNA-Ala-TGC derived 3' fragment, promotes glioblastoma cell invasion, suppresses apoptosis, and is required for normal levels of protein synthesis

tRNA-derived fragments (tRFs) are a relatively recently discovered class of small RNAs implicated in gene-regulatory processes in diverse biological contexts but there have been very few reports of a clear phenotypic role of these small RNAs in cancer progression. To select tRFs that should receive priority for mechanistic experiments, we analyzed small RNA-seq data from The Cancer Genome Atlas (TCGA) and found that high expression of three 3' tRFs (tRF-3a), tRF-3009a, tRF-3021a or tRF-3030a, is significantly associated with poor overall survival in low-grade glioma (LGG). In glioblastoma cells, tRF-3009a, tRF-3021a and tRF-3030a enhance cell invasion and migration but tRF-3021a was uniquely required for cell proliferation and suppression of apoptosis. Interestingly, tRF-3021a knockdown decreases global protein synthesis prior to and independent of apoptosis in a number of cancer cell lines, both from and outside the glioblastoma lineage. RNA-seq reveals that the results cannot be explained by microRNA-like functions of tRF-3021a. These data indicate that tRF-3021a supports cancer cell survival and particularly protein synthesis while promoting cellular invasion and migration and suggests that strategies to downregulate this short RNA could be a potential therapeutic approach in cancers. ImplicationtRF-3021a promotes malignant cell phenotypes, sustains global protein synthesis and prevents spontaneous apoptosis, motivating efforts to evaluate it as a biomarker and therapeutic target.

cancer biology↗

Spent Mushroom Substrate Adsorbs Fusaric Acid to Protect the Cucumber Rhizosphere Microbiome and Alleviates Fusarium Wilt

Caused by Fusarium oxysporum f. sp. cucumerinum, cucumber Fusarium wilt threatens cucumber production worldwide. In addition to pesticides, using spent mushroom substrate (SMS) has a protective effect against Fusarium infection in cucumber, partly through effects on the microbiome. Fusaric acid (FA), a phytotoxic virulence factor secreted by Fusarium, disrupts both plant physiology and the rhizosphere microbial community. Herein, we investigated the relationship between SMS and this virulence factor. Bioassays demonstrated that SMS adsorbed FA both in culture supernatants and in soil. Adsorption behaviour conformed to the Langmuir-Freundlich isotherm model, with a maximum adsorption capacity of 52.72 g/g. Kinetics followed a pseudo-second-order model, indicating physical and chemical adsorption. Scanning electron microscopy showed that SMS had a porous surface, facilitating FA capture. Fourier transform infrared spectroscopy and chemical blocking assays were used to identify secondary amide groups as the key binding sites. In a dual-compartment pot system designed to isolate adsorption from other direct effects, SMS treatment significantly reduced the FA concentration in the cucumber rhizosphere and mitigated FA-induced disease aggravation. This lowered the disease index by up to 25%. Bacterial 16S metabarcoding showed that FA disrupted the rhizosphere bacterial diversity and community structure. However, when FA was adsorbed by SMS, the microbial diversity and community stability were restored. FA reduced the abundance of sensitive taxa such as Bacillus. Meanwhile, SMS-adsorbed FA preserved its relative abundance, suggesting a selective protective effect for FA-sensitive rhizobacteria. These findings indicate that SMS protects cucumber against Fusarium by alleviating FA toxicity toward beneficial microbes. Through FA adsorption, SMS amendment stabilised the rhizosphere microbial community and reduced disease incidence. This highlights the potential of SMS as a sustainable and microbiome-friendly strategy for managing soil-borne diseases.

microbiology↗

Template-based RNA structure prediction advanced through a blind code competition

Automatically predicting RNA 3D structure from sequence remains an unsolved challenge in biology and biotechnology. Here, we describe a Kaggle code competition engaging over 1700 teams and 43 previously unreleased structures to tackle this challenge. The top three submitted algorithms achieved scores within statistical error of the winners of the recent CASP16 competition. Unexpectedly, the top Kaggle strategy involved a pipeline for discovering 3D templates, without the use of deep learning. We integrated this template-modeling pipeline and other Kaggle strategies to develop a single model RNAPro that retrospectively outperformed individual Kaggle models on the same test set. These results suggest a growing importance of template-based modeling in RNA structure prediction.

biophysics↗

Conformation-specific Antibody Deciphers K27-linked Ubiquitination in Chaperone-Mediated Proteostasis

Lysine 27 (K27)-linked polyubiquitination plays critical yet incompletely defined roles in proteostasis, innate immunity, and disease progression; however, investigations into this process have long been hindered by its extremely low abundance and the lack of conformation-specific enrichment tools. Herein, we describe the development of a long-sought conformation-specific antibody, K27-IgG, which can selectively recognize--among all ubiquitin chain types--the unique architecture of K27-linked polyubiquitin (K27-polyUb) characterized by a distinct buried K27-isopeptide bond, with high affinity (KD = 4.66 nM). This antibody was derived from synthetic antibodies initially generated via phage display, using chemically synthesized K27-linked diubiquitin (K27-diUb) as the antigen. High-resolution co-crystal structures uncovered the unique K27-diUb interface targeted by these sAbs. Subsequent reformatting of these sAbs into a full-length human immunoglobulin G (IgG) scaffold yielded K27-IgG, notably exhibiting markedly enhanced affinity without compromising selectivity. Using K27-IgG as a tool, we achieved sensitive detection and immunoprecipitation (IP) of endogenous K27-polyUb in cells, and delineated the intracellular interaction landscape of K27-polyUb through complementary proteomic approaches. Two key findings emerged: 1) The molecular chaperone DNAJB1 is a specific reader of K27-linked ubiquitin chains (but not other linkages) and that K27-polyUb chains themselves exhibit chaperone-like activity, suggesting a novel mechanism by which K27-polyUb regulates chaperone-mediated proteostasis; 2) The E2 enzyme UBE2Q1 assembles K27-diUb, identifying it as a potential writer for this ubiquitin chain topology. Collectively, this study establishes K27-IgG as a robust tool for deciphering the K27-linked ubiquitin code, thereby opening new avenues for investigating the biological functions of K27-linked polyubiquitination. HighlightsO_LIFirst K27-linkage conformation-specific antibody with nanomolar affinity overcomes a major barrier in the field. C_LIO_LIK27-IgG unlocks functional mapping of the K27 ubiquitin landscape under proteotoxic stress. C_LIO_LIMolecular chaperone DNAJB1 is a selective "reader" of K27-linked ubiquitin chains. C_LIO_LIK27 chains possess intrinsic chaperone activity, enabling protein refolding and suppressing aggregation. C_LIO_LIE2 enzyme UBE2Q1 is a "writer" that directly assembles K27-linked ubiquitin chains. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/695067v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@113b980org.highwire.dtl.DTLVardef@1f7c1a0org.highwire.dtl.DTLVardef@c91656org.highwire.dtl.DTLVardef@1d9a507_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

NanoporeDB: A Structural Resource Of Multimeric Protein Nanopores In Single-Molecule Sensing

Protein nanopores are essential molecular gateways in biology and have inspired transformative technologies in biosensing and single-molecule sequencing. While this technology has transformed genomics and biosensing, the discovery of novel nanopore scaffolds remains limited due to the scarcity of experimentally resolved pore structures. Here, we present NanoporeDB, an open-access structural resource comprising over 6,600 high-confidence multimeric models across four representative pore types. Candidate proteins were systematically mined from large-scale datasets, including the AlphaFold Protein Structure Database, UniRef90, and MGnify90, and assembled using AlphaFold-Multimer and AlphaFold3. We performed membrane embedding, pore axis annotation, and constriction profiling to enable functional interpretation. NanoporeDB features an interactive web interface with 3D visualization and quantitative metrics such as insertion depth, tilt angle, and pore geometry. This resource provides a structural foundation for advancing nanopore-based molecular sensing, precision diagnostics, and synthetic biology.

bioinformatics↗

Detection of a novel Puccinia coronata f. sp. avenae genotypic lineage in Australia during the 2024 oat growing season

Crown rust, caused by Puccinia coronata f. sp. avenae (Pca), remains a persistent threat to oat production in Australia. To monitor recent shifts in virulence and population structure, 30 Pca isolates collected during the 2024 growing season across major Australian oat-producing regions were analysed. Virulence analysis of 30 isolates using 52 oat differential lines identified 25 unique races that were not detected in previous years. Whole-genome sequencing of 28 of these isolates were analysed in the context of a broader historical Australian and international genomic datasets including isolates from Taiwan, South Africa, USA. Results confirmed the uniqueness of the Australian Pca population and revealed well-established genotypic lineages persisting over multiple years, with L18 and L16 being dominant. Notably, L16 was again present in Western Australia after being undetected in 2023, while L18 maintained its prevalence for a third consecutive season. Beyond these dominant groups, phylogenetic analysis and a k-mer containment analysis also identified a novel and genetically distinct lineage, designated as L19, represented by one isolate collected in WA. To add to the characterisation of lineage L19, we recorded virulence phenotypes on a small collection of current commercial cultivars. These findings enhance understanding of Pca diversity and emphasise the importance of surveillance approaches that integrate phenotypic and genomic surveillance.

pathology↗

Cascade-Targeting Nanoparticles for Reversing Chemoresistance in Osteosarcoma

Osteosarcoma (OS) remains the most prevalent primary malignant bone tumor in adolescents, with chemotherapy resistance significantly limiting the efficacy of current treatments. To address the challenges of chemoresistance driven by DNA repair mechanisms and drug efflux, we developed a biomimetic cascade-targeting drug delivery system, TAT-mPDO@cRGD-M. This system combines a polydopamine (mPDA) core with strong photothermal and drug-loading capacities, enabling the co-delivery of cisplatin (CDDP) and olaparib (OLA). Surface functionalization with the nuclear localization peptide TAT and cloaking with osteosarcoma cell membranes modified with cRGD peptides allows for selective tumor recognition, nuclear targeting, and stimuli-responsive drug release. Upon near-infrared (NIR) irradiation, the platform enhances DNA damage, suppresses the PI3K-AKT signaling pathway, and promotes apoptosis while inhibiting epithelial-mesenchymal transition (EMT). In vitro and in vivo studies demonstrated that TAT-mPDO@cRGD-M exhibits potent antitumor activity against cisplatin-resistant osteosarcoma, maintaining strong therapeutic efficacy under low-power NIR irradiation without causing significant damage to normal tissues. This study highlights a highly specific and biocompatible therapeutic approach that offers promising potential for overcoming chemotherapy resistance in osteosarcoma and advancing clinical treatment strategies.

cancer biology↗

Structure-based Predictions of Conformational B Cell Epitopes by Protein Language Model and Deep Learning

Mapping conformational B-cell epitopes remains a central challenge for antibody discovery: experiments are costly and most computational tools trained on generic protein-protein interfaces transfer poorly to antibody-antigen recognition. We introduce a patch-centric framework that predicts epitopes directly on antigen structures. Each surface "patch" is defined as a triad of neighboring residues, capturing the smallest local unit that encodes both shape and chemistry. We evaluate two classifiers: (i) a protein language model (PLM) approach that averages ESM-2 embeddings over each triad and scores them with a small multilayer perceptron [1], and (ii) a convolutional baseline that consumes a hand-crafted 15x20 feature matrix summarizing amino-acid identity, secondary structure, solvent accessibility, and shape index. Trained with five-fold cross-validation on 1,151 AbDb antibody-antigen complexes, the PLM model markedly outperforms the CNN at the patch level (e.g., F1{approx} 0.986, ROC-AUC{approx} 0.998). Aggregating patch scores to residues with an ensemble over all folds yields robust residue-wise performance, surpassing the CNN (ROC-AUC 0.689{+/-}0.072 vs. 0.548{+/-}0.018). Against widely used sequence- and structure-based tools on AbDb, our PLM achieves the best summary metrics (ROC-AUC 0.67, PR- AUC 0.56) with full coverage of all antigens. On five external complexes unseen during development, the model generalizes well (ROC-AUC 0.663) and accurately localizes binding regions qualitatively. The method converts PLM representations into interpretable epitope likelihood maps, offering a practical aid for antigen prioritization, antibody engineering, and vaccine design.

bioinformatics↗

Inferring Dynamic Information from Protein Structures by Gaussian Integrals and Deep Learning

Protein conformational flexibility underlies a wide range of biological functions, yet experimentally probing dynamics at atomic resolution remains costly and low-throughput. Here, we present a deep learning framework that predicts protein flexibility directly from static structural descriptors, bypassing the need for molecular dynamics (MD) simulations. Using the ATLAS database of standardized all-atom MD trajectories, we encoded 1,374 protein chains as 30-dimensional Gaussian integral (GI) vectors--global shape and topology invariants of the protein backbone. Principal component analysis of GI profiles revealed four structural clusters with distinct secondary structure compositions and flexibility distributions. We trained an attention-based one-dimensional convolutional neural network (1D-CNN) to classify proteins as flexible or non-flexible based on their root-mean-square fluctuation (RMSF) relative to the dataset-wide mean. The classifier achieved an AUC of 0.772 (95% CI: 0.712-0.826) on an independent test set, with balanced sensitivity and specificity, and identified a small subset of GI components as the most predictive. In a regression setting, a recurrent neural network outperformed other architectures, attaining an R2 of 0.537, though high-flexibility values were systematically underestimated. Cluster-specific analyses indicated that coil-rich and {beta}-sheet-dominated proteins were more amenable to flexibility prediction than -helical proteins, likely due to greater structural heterogeneity. Our results demonstrate that compact GI descriptors preserve sufficient information to recover MD-derived flexibility trends, offering a computationally efficient complement to simulation-based approaches. This framework enables large-scale screening of protein dynamics from structural data alone, with potential applications in structural bioinformatics, drug design, and functional annotation.

bioinformatics↗

Comparative Landscape of Small RNAs in Tissue and Liquid Biopsies for Liver Transplant Outcomes

BackgroundIschemia-reperfusion injury (IRI) is an inevitable consequence of liver transplantation, arising during donor organ procurement and reoxygenation. Severe IRI is a leading contributor to early allograft dysfunction (EAD), a post-transplant complication associated with reduced graft survival. Current postoperative biomarkers provide limited time for intervention, highlighting a need to identify preoperative biomarkers of IRI. Meanwhile, tRNA fragments (tRFs) have emerged as novel biomarkers in various diseases but remain unexplored in the context of liver transplant. ResultsWe performed small RNA sequencing on 96 paired donor liver biopsies from 48 patients to investigate IRI-associated transcript changes. In parallel, 161 donor liver perfusates were analyzed as a non-invasive surrogate for tissue. Across samples, microRNAs (miRNAs) and tRFs were the most abundant. Perfusate expression strongly correlated with biopsies, supporting their value as a non-invasive source of small RNAs. Comparison between post-reperfusion and pre-implantation biopsies revealed that IRI reprogrammed tRF expression. Stratification by clinical outcome showed that patients who developed EAD exhibited specific small RNA signatures in both biopsy and perfusate. Receiver operating characteristic (ROC) analysis revealed a miRNA-based model that achieved an AUC of 0.772, outperforming donor risk index alone (AUC = 0.665), representing a 10.7% increase in discriminative capacity. ConclusionsThese results are the first to establish tRFs as IRI-responsive biomolecules abundant in both donor liver tissue and non-invasive perfusate. In particular, various small RNAs emerged as promising candidate biomarkers for early detection of EAD. These results lay the foundation to further investigate the prognostic utility of tRFs/miRNAs in liver transplantation.

genomics↗

PATTY corrects open chromatin bias for improved bulk and single-cell CUT&Tag profiling

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5s preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open-chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open-chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open-chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

bioinformatics↗

QTL mapping of oat crown rust resistance in Australian fields and identification of a seedling resistance locus in oat line GS7

The development of oat cultivars with resistance to crown rust caused by Puccinia coronata f. sp. Avenae (Pca) is key for sustainable disease control. This study examined two recombinant inbred line populations, Provena x GS7 and Boyer x GS7, to identify adult plant resistance QTL in Australian fields. Seven distinct QTL associated with rust resistance were identified, with KASP markers developed for single nucleotide polymorphisms (SNPs) tightly linked to the four most significant QTL on chromosomes 4A and 7A. A major QTL named QPc_GS7_4A.2 with a resistance allele derived from line GS7 was mapped to chromosome 4A, overlapping with genomic regions previously associated with both resistance gene Pc61 and adult plant resistance. Genetic mapping for rust resistance at seedling stage using a subset of Provena x GS7 lines with contrasting alleles at QPc_GS7_4A.2 confirmed the role of this locus on seedling resistance, likely by Pc61. Furthermore, we found similar resistance profiles between GS7 and the Pc61 differential line against 20 Pca isolates at the seedling stage. Haplotype analysis of QPc_GS7_4A.2 in the oat crown rust differential set and an oat collection revealed the resistance haplotype in lines previously postulated to carry resistance gene Pc61. These results suggest that the QTL QPc_GS7_4A.2 is closely linked to the Pc61 locus on chromosome 4A. The KASP markers associated with Pc61 and QTL identified in this study will be valuable tools, allowing breeders to efficiently integrate the resistance allele for gene combinations in new cultivars, particularly in regions where Pc61 remains effective.

plant biology↗

Retinal pigment epithelium-derived PD-L1 reprograms microglial cells and protects against retinal degeneration in mouse models of experimental AMD and genetic retinitis pigmentosa

Retinal degeneration is a leading cause of blindness and a significant health burden during aging worldwide. Because of its complex pathogenic mechanisms, however, effective interventions applicable to multiple retinal degenerations remain limited. Excessive microglia-mediated inflammation is a common pathological feature of different retinal degenerative diseases, and inhibiting these overactive inflammatory responses by reprogramming microglia may provide a therapeutic strategy with broad-spectrum potential. Here, we uncover a novel retinal pigment epithelium (RPE) homeostatic signal, PD-L1, that drives the reprogramming of activated microglial toward a retinal-protective phenotype. Using multiple analyses, including gene expression profiling bioinformatics, adeno-associated virus-mediated RPE-specific gene overexpression, pharmacological, and genetic manipulations, we show that RPE cells upregulate the expression of PD-L1 to modulate microglia for protection against retinal degeneration in an experimental dry AMD mouse model. Bioinformatics enrichment analysis of the high-expression gene signatures of subretinal microglia in AMD patients, combined with pharmacological blocking of NF-{kappa}B activity or using Nlrp3 knockout mice, show that PD-L1/PD-1 signaling suppresses NF-{kappa}B activation in microglia, thereby inhibiting NLRP3 inflammasome priming and attenuating microglia-mediated excessive inflammation. Furthermore, the overexpression of PD-L1 by the AAV8 virus exerts similar microglial reprogramming and retinal protective effects to alleviate retinal degeneration in a preclinical model of retinitis pigmentosa. These findings reveal that RPE-derived PD-L1 suppresses inflammatory reprogramming of subretinal microglia and mitigates retinal degeneration, highlighting a promising proof of concept for PD-L1 as a potential therapeutic target for the broad treatment of retinal degenerative diseases.

genetics↗

Transcriptome Reprogramming Associated with Autoimmunity Reveals Key Points of the Growth-Defence Trade-off in Arabidopsis thaliana

Growth and defence are inversely correlated processes requiring balance for optimal fitness. While each is well studied, their regulatory trade-offs are less understood. Using DANGEROUS MIX (DM) autoimmune plants with stunted growth in Arabidopsis thaliana, we investigated the balancing act. Transcriptome analysis of three DM cases and pathogen-treated seedlings identified two major modules representing defence and growth. These core modules, comprising 4,712 genes ([~]17% of the transcriptome), were sufficient for projecting the trade-off across immune transcriptome meta-datasets. Removing all three ADR1s, the helper NLRs, reversed the expression patterns of both modules and shifted the trade-off balance. ADR1s had a stronger impact on growth-associated RLK genes than on defence genes. Autoimmune plants also showed greater chromatin accessibility changes in growth loci than in defence loci. Our findings suggest an unexpected mechanism where immune signalling, partly mediated by ADR1s, actively suppresses growth genes, providing a strategy to regulate the growth-defence trade-off.

plant biology↗

Post-replicative initial expression of the cell fate regulator PAX6 during neuroectoderm differentiation

The development of multicellular organisms requires precise coordination between cell division and differentiation. Cell division generates the necessary number of cells, while differentiation creates distinct cell identities, forming tissues and organs. The transcription factors SOX2 and PAX6 specify neuroepithelial cells, the earliest neural progenitor cells (NPCs) during brain development. How lineage specification is coordinated with the cell cycle is not fully understood. Here, we show that PAX6 expression occurs during a narrow time window--between 48 and 72 hours--after neural induction of human embryonic stem cells (ESCs). Flow cytometry analyses and time-lapse imaging further show that PAX6 expression starts during the G2 phase of the cell cycle. We identify a novel 500-bp PAX6 promoter that drives its G2-specific expression. PAX6 expression is independent of known regulators of cell-cycle-dependent transcription, suggesting the existence of a novel mechanism. S-phase block by hydroxyurea prevents PAX6 expression and differentiation into NPC. Thus, NPC fate specification is coupled to cell cycle progression and occurs after the completion of DNA replication. This post-replicative lineage commitment ensures the creation of two daughter cells of identical cell fate following cell division.

cell biology↗

Functional relevance of CASP16 nucleic acid predictions as evaluated by structure providers

Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular. Here, we report quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs, however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, e.g., the nucleic-acid backbone bends or a base forms a non-standard hydrogen bond. These bends and non-canonical interactions are integral to form functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life-cycle, posing a future challenge for the community.

biophysics↗

SLC44A1 deficiency impedes myelin development in the central nervous system

Axon-wrapping myelin sheath is essential for the proper functioning of the central nervous system (CNS). Defects in myelination occur in various neurodevelopmental disorders. Human deficiency of the solute carrier 44A1 (SLC44A1) causes a new type of childhood-onset neurodegeneration with leukoencephalopathy. Currently, there is no effective treatment for this devastating disease, and little is known about its pathological mechanisms. In this study we identified that SLC44A1 is enriched in oligodendrocytes and required for myelin development in the CNS of zebrafish and rodents, which is crucial for normal motor coordination and cognitive function. Defective oligodendroglial maturation and myelinogenesis can be visualized by in vivo time-lapse imaging in the spinal cord of zebrafish with Slc44a1b deficiency. Mechanistically, SLC44A1 deficiency disrupts the expression of genes involved in phosphatidylcholine production pathway, and subsequently inhibiting phospholipid biosynthesis and disturbing the lipid composition of myelin sheaths. More importantly, supplementation with citicoline, a natural choline metabolite, restores developmental myelination in SLC44A1-deficient animals. These findings demonstrate that SLC44A1 is essential for CNS myelination and citicoline supplementation represents a potential therapeutic strategy to address the developmental hypomyelination.

neuroscience↗

THA_1941 from Thermosipho africanus: A Thermostable β-1,3-Glucan Phosphorylase for Efficient β-1,3-Glucan Synthesis

{beta}-1,3-Glucan phosphorylases capable of utilizing glucose as a priming substrate are key biocatalysts for the synthesis of functional {beta}-1,3-glucan. In this study, we identified THA_1941 from Thermosipho africanus (Ta{beta}GP) as a GH161 {beta}-1,3-glucan phosphorylase exhibiting robust synthetic activity towards glucose, as confirmed by 13C nuclear magnetic resonance, liquid chromatography-mass spectrometry, and sequence and structural analyses. Ta{beta}GP displayed exceptional thermostability, retaining 93% of its activity at 60 {degrees}C for 180 h, and showed broad pH tolerance ranging from pH 5.0 to 10.0, surpassing the performance of previously reported homologs. In addition, Ta{beta}GP exhibited broad substrate flexibility, accepting both - and {beta}-linked disaccharides, and demonstrated strong resistance to metal ions and lignocellulose-derived inhibitors. In the presence of 150 mM glucose 1-phosphate as the donor substrate, Ta{beta}GP synthesized {beta}-1,3-glucan with a tunable average degree of polymerization (10-32), depending on the concentration of glucose used as the primer. The combination of thermostability, inhibitor resistance, and substrate versatility makes Ta{beta}GP a promising biocatalyst for the economically viable and environmentally sustainable synthesis of {beta}-1,3-glucan from non-food biomass sources.

biochemistry↗