Biology subjects

Lin, S.

Publications and source records attributed to Lin, S..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Oncogenic RAS Induces a Distinctive Form of Non-Canonical Autophagy Mediated by the P38-ULK1-PI4KB Axis

Cancer cells with RAS mutations exhibit enhanced autophagy, essential for their proliferation and survival, making it a potential target for therapeutic intervention. However, the regulatory differences between RAS-induced autophagy and physiological autophagy remain poorly understood, complicating the development of cancer-specific anti-autophagy treatments. In this study, we identified a form of non-canonical autophagy induced by oncogenic KRAS expression, termed RAS-induced non-canonical autophagy via ATG8ylation (RINCAA). RINCAA involves distinct autophagic factors compared to those in starvation-induced autophagy and incorporates non-autophagic components, resulting in the formation of non-canonical autophagosomes with multivesicular/multilaminar structures labeled by ATG8 family proteins (e.g., LC3 and GABARAP). We have designated these structures as RAS-induced multivesicular/multilaminar bodies of ATG8ylation (RIMMBA). A notable feature of RINCAA is the substitution of the class III PI3K in canonical autophagy for PI4KB. We identified a regulatory P38-ULK1-PI4KB-WIPI2 signaling cascade governing this process, where ULK1 phosphorylation at S317, S479, S556, and S758 activates PI4KB. This activation involves PI4KB phosphorylation at S256 and T263, initiating PI4P production, ATG8ylation, and non-canonical autophagy. Importantly, elevated PI4KB phosphorylation at S256 and T263 was observed in RAS-mutated cancer cells and colorectal cancer specimens. Inhibition of PI4KB S256 and T263 phosphorylation led to a reduction in RINCAA activity and tumor growth in both xenograft and KPC models of pancreatic cancer, suggesting that ULK1-mediated PI4KB-Peptide-1 phosphorylation could represent a promising therapeutic target for RAS-mutated cancers.

cell biology↗

bioRxiv2024

Bridging the Dimensional Gap from Planar Spatial Transcriptomics to 3D Cell Atlases

Spatial transcriptomics (ST) has revolutionized our understanding of tissue architecture, yet constructing comprehensive three-dimensional (3D) cell atlases remains challenging due to technical limitations and high cost. Current approaches typically capture only sparsely sampled two-dimensional sections, leaving substantial gaps that limit our understanding of continuous organ organization. Here, we present SpatialZ, a computational framework that bridges these gaps by generating virtual slices between experimentally measured sections, enabling the construction of dense 3D cell atlases from planar ST data. SpatialZ is designed to operate at single-cell resolution and function independently of gene coverage limitations inherent to specific spatial technologies. Comprehensive validation using real 3D ST and independent serial sectioning datasets demonstrates that SpatialZ accurately reconstructs virtual slices while preserving cell identities, gene expression patterns, and spatial relationships. Leveraging the BRAIN Initiative Cell Census Network data, we constructed a 3D hemisphere atlas comprising over 38 million cells, a scale not feasible experimentally. This dense atlas enables unprecedented capabilities, including in silico sectioning at arbitrary angles, explorations of gene expression across both 3D volumes and surfaces, and 3D mapping of query tissue sections. While currently validated for spatial transcriptomics, the underlying principles of SpatialZ could potentially be adapted for spatial proteomics, spatial metabolomics, and even spatial multi-omics. Validated through internal and external testing, our computationally generated atlas maintains biological accuracy, providing unprecedented resolution of spatial molecular landscapes and demonstrating the potential of computational approaches in advancing 3D ST.

bioinformatics↗

bioRxiv2024

NicheTrans: Spatial-aware Cross-omics Translation

Spatial omics technologies have revolutionized our studies on tissue architecture and cellular interactions at single-cell resolution. While spatial multi-omics approaches offer unprecedented insights into complex biological systems, their widespread adoption is hindered by technical challenges, specialized requirements, and limited accessibility. To address these limitations, we present NicheTrans, the first spatially-aware cross-omics translation method and a flexible Transformer-based multi-modal deep learning framework. Unlike existing single-cell (non-spatial) translation methods, NicheTrans uniquely incorporates both cellular microenvironment information and flexible integration of multi-modal data, such as morphology and prior knowledge. We validated NicheTrans across diverse biological cases: Parkinsons Disease (PD), Alzheimers Disease (AD), breast cancer, and lymph nodes. Our approach demonstrated superior performance compared to existing single-cell methods, highlighting the crucial role of spatial and multi-modal information in cross-omics translation. Through NicheTrans, we uncovered spatial multi-omics domains that were not detectable through single-omics analysis alone. Model interpretation revealed key molecular relationships, including gene programs associated with dopamine metabolism and amyloid {beta}-associated cell states. Additionally, using translated protein markers as spatial landmarks, we quantified the spatial organization of key glial cell subtypes in the AD brain. NicheTrans represents a powerful tool for generating comprehensive spatial multi-omics insights from more accessible single-omics measurements, making multi-omics analysis more feasible for the broader research community.

bioinformatics↗

bioRxiv2024

RNA methylation controls stress granule formation and function during erythropoiesis

Stress granules (SGs) are crucial in RNA regulation, affecting cell fate and function. SGs contain RNAs, some of which can be methylated. We studied m6A RNA modifications during the human CD34+ HSPCs (hCD34+) differentiating into erythroid cells and found that mRNAs encoding many erythroid-specific proteins had decreased methylation during differentiation. Increased levels ALKBH5 demethylase during erythropoiesis controls the levels of the 3UTR methylation of these mRNAs. hCD34+ carrying ALKBH5 mutations demonstrated a block in erythropoiesis, and mass-spectrometry studies of the mutant cells showed decreased levels of SG proteins, including the core granule protein ATXN2. ALKBH5 directly regulates the methylation of the mRNA of ATXN2. ATXN2 overexpression accelerated the erythroid differentiation of HSPCs and rescued the erythroid differentiation of ALKBH5 mutant cells. Very few SGs are found in normal human erythroid progenitors. SGs accumulated substantially in ALKBH5 mutant cells, and surprisingly overexpression of ATNX2 reduced SG numbers to normal. Polysome analysis demonstrated m6A-modified RNAs to be enriched in the pre-polysome fractions that were less translated. This work establishes a mechanism by which during stress, ATXN2 facilitates the release of SG-stored m6A-modified RNAs including erythroid-specific and SG-enriched RNAs that are loaded onto functional ribosomes, allowing better translation and accelerated erythroid differentiation during stress.

cell biology↗

bioRxiv2024

Target-specific design of drug-like PPI inhibitors via hot-spot-guided generative deep learning

Protein-protein interactions (PPIs) are vital therapeutic targets. However, the large and flat PPI interfaces pose challenges for the development of small-molecule inhibitors. Traditional computer-aided drug design approaches typically rely on pre-existing libraries or expert knowledge, limiting the exploration of novel chemical spaces needed for effective PPI inhibition. To overcome these limitations, we introduce Hot2Mol, a deep learning framework for the de novo design of drug-like, target-specific PPI inhibitors. Hot2Mol generates small molecules by mimicking the pharmacophoric features of hot-spot residues, enabling precise targeting of PPI interfaces without the need for bioactive ligands. The framework integrates three key components: a conditional transformer for pharmacophore-guided, drug-likeness-constrained molecular generation; an E(n)-equivariant graph neural network for accurate alignment with PPI hot-spot pharmacophores; and a variational autoencoder for generating novel and diverse molecular structures. Experimental evaluations demonstrate that Hot2Mol outperforms baseline models across multiple metrics, including docking affinities, drug-likenesses, synthetic accessibility, validity, uniqueness, and novelty. Furthermore, molecular dynamics simulations confirm the good binding stability of the generated molecules. Case studies underscore Hot2Mols ability to design high-affinity and selective PPI inhibitors, demonstrating its potential to accelerate rational PPI drug discovery.

bioinformatics↗

bioRxiv2024

Hydroxy polyethylene glycol: a solution to evade human pre-existing anti-PEG antibodies for efficient delivery

Polyethylene glycol (PEG) has been extensively utilized in food, cosmetics, and pharmaceutical fields, especially in the realm of nanomedicines, where it serves as a pivotal excipient for extending the nanoparticles circulation half-life. Contrary to its historical perception as non-immunogenic, pre-existing anti-PEG antibodies have been widely detected in human who even have never been exposed to PEGylated therapeutics, which considered to be associated with serious side effects of PEGylated nanomedicines including infusion reactions and other hypersensitive reactions. Herein, we elucidated the prevalence and distribution characteristics of pre-existing anti-PEG antibodies in 2074 human blood samples, and investigated its binding with PEG. Pre-existing anti-PEG antibodies were found to primarily recognize the PEG terminus, especially methoxy, which is the only PEG terminus contained in currently marketed PEGylated nanomedicines. While hydroxy PEG (OH-PEG) significantly evaded binding with pre-existing anti-PEG antibodies among most clinical samples. Noteworthily, substituting OH-PEG for MeO-PEG significantly mitigated complement activation of lipid nanoparticle (LNP) caused by pre-existing anti-PEG antibodies, thereby markedly enhancing stability and reducing mRNA leakage in human serum. Additionally, LNP modified with OH-PEG exhibited reduced immunogenicity, which was crucial for repeated drug administrations. The present work elucidated the crucial role of OH-PEG in evading human pre-existing anti-PEG antibodies, and discovered that the current pre-clinical studies inadequately simulated the biological effects of clinical pre-existing anti-PEG antibodies on such formulations through interspecies study, which had a profound impact on clinical translation of PEGylated nanomedicines.

pharmacology and toxicology↗

bioRxiv2024

A novel approach to digital characterisation of Tertiary Lymphoid Structures in colorectal cancer

Tertiary Lymphoid Structures (TLS) in cancer tissue are potential sites for the organisation of immune responses to cancer, and correlate positively with improved clinical outcomes for patients including in colorectal cancer (CRC). However it has proven challenging to standardise assessment of TLS due to the highly variable appearances of circumscribed domains of TLS within tissue sections. A recent three-dimensional reconstruction of TLS in CRC tissue showed that TLS are often large, multi-lobular structures, suggesting that assessing TLS across whole sections may be necessary to provide an accurate view of TLS activity in a patients tumour. In a pilot study we therefore used whole slide scans of multiplexed immunofluorescence images to characterise TLS from 22 subjects with CRC. Multiplexed staining for CD20, CD3, CD8, FoxP3 and Ki-67 enabled us to identify B-cells, CD8+ T cells, FoxP3- CD4 T-cells, and Foxp3+ CD4 T cells in all sections, and quantify both the presence of these cell subsets in lymphocytic clusters and their degree of proliferation within those clusters. In total we identified 524 lymphocytic clusters with morphology consistent with TLS. The count of TLS domains varied substantially between samples (from 4 to 100, mean 24) as did the proportion of total section area occupied by TLS (0.2%-7.8%) as well as size, morphology and cellular constituents; reflecting the intersection of the section plane with complex 3-dimensional structures. We quantified proliferation of B-cells and T-cell subsets within TLS domains across entire sections and compared to the canonical approach of counting and phenotyping individual TLS domains. The whole-slide approach proved far simpler than the canonical approach, generating digital summaries across our sample set clearly identifying patients with strikingly different levels of immune activity within their TLS. It also allowed us to demonstrate strong correlations between the proliferation of B-cells within CRC TLS and that of T-cell subsets. In summary we find that whole-section digital quantification of immune cell activity within TLS has major advantages over canonical approaches. Such whole-section approaches should accelerate research into correlations between TLS status and clinical outcomes, and ultimately enable standardised clinical tests based on automated analysis of multiplexed images.

cancer biology↗

bioRxiv2024

Pharmacological inhibition of Fms-like kinase 3 (FLT3) promotes neuronal maturation and suppresses seizure in a mouse model

Fms-like tyrosine kinase 3 (FLT3) is a receptor tyrosine kinase predominantly expressed in blood and brain cells. While the FLT3 signaling pathway has been extensively studied in blood cell development and leukemia, its role in the brain remains largely unexplored. Through our groups previous high-throughput drug screening work unexpectedly found that several small molecule FLT3 inhibitors (FLT3i), including KW-2449 and Sunitinib, enhance expression of the gene encoding chloride transporter KCC2 in neurons. KCC2 is crucial for brain development and function, and its dysregulation is linked to many brain diseases. These findings suggest previously unrecognized roles of FLT3 signaling in brain health and disease that have yet to be systematically studied. In this study, we utilized a functional genomics approach to investigate the transcriptomic changes induced by pharmacological inhibition of the FLT3 pathway in brain cells, including cultured primary mouse neurons, a human stem cell-derived neuronal model of Rett syndrome (RTT), and human stem cell-derived microglia cultures. Our results show that treating human or mouse neurons with FLT3i drugs significantly upregulates genes crucial for brain development while downregulating genes linked to neuroinflammation. In contrast, FLT3i treatment of human microglia, which do not express FLT3, has no effect on their gene expression, highlighting the cell type-specific roles of FLT3 signaling in the brain. To further understand how FLT3 signaling regulates the expression of neuronal maturation genes such as KCC2, we conducted a curated CRISPR screen that identified a number of transcription factors involved in FLT3i-mediated KCC2 activation in neurons. The mRNA and protein levels of several neurodevelopmental disorder (NDD) risk genes are significantly upregulated in FLT3i-treated neurons, indicating potential therapeutic applications of FLT3i in rescuing underexpression and/or haploinsufficiency of disease-associated genes. In our in vivo studies, we evaluated the efficacy of the FLT3i drug KW-2449 in mice, demonstrating that it can effectively cross the blood-brain barrier, induce KCC2 protein expression for up to 24 hours after a single injection, and reduces seizure activity in a chemoconvulsant-induced mouse model of temporal lobe epilepsy. Collectively, our findings uncover previously unrecognized roles of neuron-specific FLT3 signaling in promoting neuronal maturation and reducing neuroinflammation. These results suggest that FLT3 kinase signaling regulates a transcriptional program vital for brain development and function, position it as a promising therapeutic target for NDD treatment.

neuroscience↗

bioRxiv2024

Age-related increases in PDE11A4 protein expression trigger liquid:liquid phase separation (LLPS) of the enzyme that can be reversed by PDE11A4 small molecules inhibitors

PDE11A is a little-studied phosphodiesterase sub-family that breaks down cAMP/cGMP, with the PDE11A4 isoform being enriched in the memory-related brain region called the hippocampus. Age-related increases in PDE11A expression occur in human and rodent hippocampus and cause age-related cognitive decline of social memories. Interestingly, the age-related increase in PDE11A4 protein ectopically accumulates in spherical clusters that group together in the brain to form linear filamentous patterns termed "ghost axons." The biophysical/physiochemical mechanisms underlying this age-related clustering of PDE11A4 are not yet known. As such, we determine here if age-related clustering of PDE11A4 may reflect liquid:liquid phase separation (LLPS), and if PDE11A inhibitors being developed for age-related cognitive decline can reverse this biomolecular condensation. We found that human and mouse PDE11A4 exhibit several LLPS-promoting sequence features including intrinsically disordered regions, non-covalent pi-pi interactions, and prion-like domains, with multiple bioinformatic tools predicting PDE11A4 undergoes LLPS. Consistent with these predictions, age-related PDE11A4 clusters were non-membrane bound spherical droplets that progressively fuse over time in a concentration-dependent manner. 5 different PDE11 inhibitors (tadalafil, BC11-38, SMQ-02-57, SMQ-03-30 and SMQ-03-20) across 3 scaffolds reversed PDE11A4 LLPS (a.k.a. remixing) in hippocampal HT22 cells, with PDE11A4 droplets reforming (a.k.a. de-mixing) following a 5-hour washout of low but not high concentrations of these compounds. Strikingly, a single oral administration of 30 mg/kg SMQ-03-20 substantially reduced the presence of PDE11A4 ghost axon in the aged mouse brain. Thus, PDE11A4 exhibits 4 defining criteria of LLPS, and PDE11A small molecule inhibitors reverse this age-related phenotype both in vitro and in vivo.

neuroscience↗

bioRxiv2024

Low-affinity ligands of the epidermal growth factor receptor are long-range signal transmitters during collective cell migration of epithelial cells

Epidermal growth factor receptor ligands (EGFRLs) consist of seven proteins. In stark contrast to the amassed knowledge concerning the epidermal growth factor receptors themselves, the extracellular dynamics of individual EGFRLs remain elusive. Here, employing fluorescent probes and a tool for triggering ectodomain shedding of EGFRLs, we show that EREG, a low-affinity EGFRL, exhibits the most rapid and efficient activation of EGFR in confluent epithelial cells and mouse epidermis. In Madin-Darby canine kidney (MDCK) renal epithelial cells, EGFR- and ERK-activation waves propagate during collective cell migration in an ADAM17 sheddase- and EGFRL-dependent manner. Upon induction of EGFRL shedding, radial ERK activation waves were observed in the surrounding receiver cells. Notably, the low-affinity ligands EREG and AREG mediated faster and broader ERK waves than the high-affinity ligands. The integrity of tight/adherens junctions was essential for the propagation of ERK activation, implying that the tight intercellular spaces prefer the low-affinity EGFRL to the high-affinity ligands for efficient signal transmission. To validate this observation in vivo, we generated EREG-deficient mice expressing the ERK biosensor and found that ERK wave propagation and cell migration were impaired during skin wound repair. In conclusion, we have quantitatively demonstrated the distinctions among EGFRLs in shedding, diffusion, and target cell activation in physiological contexts. Our findings underscore the pivotal role of low-affinity EGFRLs in rapid intercellular signal transmission.

cell biology↗

bioRxiv2024

Selective Agonism of Liver and Gut FXR Prevents Cholestasis and Intestinal Atrophy in Parenterally Fed Neonatal Pigs

BACKGROUND & AIMSWe aimed to investigate the relative efficacy of feeding different bile acids in preventing PNALD in neonatal pigs. METHODSNewborn pigs given total parenteral nutrition (TPN) combined with minimal enteral feeding of chenodeoxycholic acid (CDCA), or increasing doses of obeticholic acid (OCA) for 19 days. RESULTSEnteral OCA (5 and 15 mg/kg), but not CDCA (30 mg/kg) reduced blood cholestasis markers compared to TPN controls and increased bile acids in the gallbladder and intestine. Major bile acids in the liver and distal intestine were CDCA, HCA, HDCA and OCA, and their relative proportions were increased by the type of bile acid (CDCA or OCA) given enterally. High doses of OCA increased the total NR1H4-agonistic bile acid profile in the liver and intestine above 50% total bile acids. Both CDCA and OCA treatments suppressed hepatic cyp7a1 expression, but only OCA increased hepatobiliary transporters, ABCB11, ABCC$ and ABCB1. Plasma phytosterol levels were reduced and biliary levels were increased by CDCA and OCA and hepatic sterol transporters, abcg5/8, expression were increased by OCA. Both CDCA and OCA increased plasma FGF19 and OCA increased intestinal FGF19, FABP6, and SLC51A. Both CDCA and OCA increased intestinal mucosal growth, whereas CDCA increased the plasma GLP-2, GLP-1 and GIP. CONCLUSIONSEnteral OCA prevented cholestasis and phytosterolemia by increased hepatic bile acid and sterol transport via induction of hepatobiliary transporter FXR target genes and not by suppression of bile acid synthesis genes. We also showed an intestinal trophic action of OCA that demonstrates a dual clinical benefit of FXR agonism in the prevention of PNALD in piglets.

physiology↗

bioRxiv2024

Bioinformatics Copilot 2.0 for Transcriptomic Data Analysis

Large language models, when integrated into bioinformatics tools, offer valuable support for biologists in the analysis of single-cell transcriptomic data. Here, we introduce Bioinformatics Copilot 2.0, an advanced tool that builds upon its predecessor with four significant enhancements: 1) Internal server processing: users can now process large datasets on an internal server, thereby ensuring data privacy. 2) User-controlled analysis: users can take control of their data analysis when tasks exceed the copilots capabilities.3) Real-time information access: users can access up-to-date information from online resources, such as gene function queries and recent publications, thus enhancing data interpretation. 4) Data analysis and result documentation: the copilot now supports the generation of PDFs that include images and detailed analysis. These advancements represent a step towards building a bioinformatics autopilot. Demonstration videos showcasing these features are available at www.biochemml.com/tools.

bioinformatics↗

bioRxiv2024

GRATCR: epitope-specific T cell receptor sequence generation with data-efficient pre-trained models

T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep generative model has demonstrated remarkable capabilities in functional protein sequence generation, offering a promising solution for enhancing the acquisition of specific TCR sequences. Here, we propose GRATCR, a framework incorporates two pre-trained modules through a novel "grafting" strategy, to de-novo generate TCR sequences targeting specific epitopes. Experimental results demonstrate that TCRs generated by GRATCR exhibit higher specificity toward desired epitopes and are more biologically functional compared with state-of-the-art model, by using significantly fewer training data. Additionally, the generated sequences display novelty compared to natural sequences, and the interpretability evaluation further confirmed that the model is capable of capturing important binding patterns. GRATCR is freely available at https://github.com/zhzhou23/GRATCR.

bioinformatics↗

bioRxiv2024

Os-circANK negatively regulates resistance to bacterial blight in rice via Osa-miR398b/OsCSD1/OsCSD2 pathways

CircRNAs are widely present in plants, yet there have been no reports on the role of circRNA in the regulatory mechanisms of interactions between rice and pathogenic bacteria. As the sequence of circRNAs matches the parent gene except for the back splicing site, there is no feasible way to specifically knockdown circRNAs in plants. We identified a circRNA, named Os-circANK, derived from an ankyrin repeat protein, which was significantly downregulated post Xanthomonas oryzae pv. oryzae (Xoo) inoculation. We have created a CRISPR-Cas13d system to specifically knockdown a plant circular RNA, resulting in genetically edited rice with a targeted decrease in Os-circANK expression. Os-circANK was found to function as a sponge for Osa-miR398b, suppressing the cleavage of OsCSD1/OsCSD2 by Osa-miR398b, leading to a reduction in ROS levels following Xoo infection and a negative regulation of resistance to bacterial blight in rice. Our findings demonstrate that Os-circANK inhibits the resistance to bacterial blight in rice via the Osa-miR398b/OsCSD1/OsCSD2 pathways.

microbiology↗

bioRxiv2024

TransMetaSegmentation (TMS): a transcriptome-based segmentation method for spatial metabolomic data

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a powerful analytical tool that enables the visualization and comparison of relative abundances of metabolites across samples, shedding light on biological processes and disease mechanisms. Techniques such as scSpatMet enable the determination of cell boundaries and cell types through staining with 35 cell marker antibodies. Yet, distinguishing subpopulations of cells, such as astrocytes, oligodendrocytes, and neuronal clusters in the brain, remains challenging using antibodies. In this context, we introduce TransMetaSegmentation (TMS), an alternative segmentation and cell typing method that integrates MALDI MSI imagery with single-cell spatial transcriptomic analysis. This approach not only delineates cell boundaries and defines cell types based on a number of marker genes but also effectively allocates metabolites to specific cell types in a high-throughput manner. We anticipate that TMS will improve the granularity of MALDI MSI analyses, advance our understanding of metabolic alterations in diseases, and have an impact on various fields within biomedical sciences.

biochemistry↗

bioRxiv2024

Bola-amphiphilic dendrimer empowers imatinib to target metastatic ovarian cancer stem cells via beta-catenin-HRP2 signaling axis

Ovarian cancer is the leading cause of death among all gynecological malignancies, and drug resistance renders the current chemotherapy agents ineffective for patients with advanced metastatic tumors. We report an effective treatment strategy for targeting metastatic ovarian cancer involving a nanoformulation (Bola/IM) - bola-amphiphilic dendrimer (Bola)-encapsulated imatinib (IM) - to target the critical mediator of ovarian cancer stem cells (CSCs) CD117 (c-Kit). Bola/IM offered significantly more effective targeting of CSCs compared to IM alone, through a novel and tumor-specific {beta}-catenin/HRP2 axis, allowing potent inhibition of cancer cell survival, stemness and metastasis in metastatic and drug-resistant ovarian cancer cells. Promising results were also obtained in clinically relevant patient-derived ascites and organoids, alongside high tumor-oriented accumulation and favorable pharmacokinetic properties in mouse models. Furthermore, Bola/IM displayed synergistic anticancer activity when combined with the first-line chemotherapeutic drug cisplatin in patient-derived xenograft mouse models, without any adverse effects. Our findings support the use of Bola/IM as a nanoformulation to empower IM, providing targeted and potent treatment of metastatic ovarian cancer. Our study thus represents a significant advancement towards addressing the unmet medical need for improved therapies targeting this challenging disease.

cancer biology↗

bioRxiv2024

Pandemic Vibrio parahaemolyticus wave succession by gene loss

While spontaneous mutation and gene acquisition are well-established drivers of pathogen adaptation, the role of gene loss remains underexplored. Here, we investigated the emergence and diversification of the pandemic clone (PC) of Vibrio parahaemolyticus through large-scale phylogenomic analysis of 8,684 global isolates. The PC rapidly acquired multiple marker genes and genomic islands, subsequently diverging into successive sublineages mediating independent waves of cross-country transmission, as also observed in V. cholerae. Wave succession in the last two decades was driven by loss of putrescine utilization (Puu) genes, conferring phenotypic advantages for environmental adaptation (enhanced biofilm formation) and human transmission (increased cell adhesion/intestinal colonization, reduced virulence), consistent with the virulence trade-off hypothesis. We identified Puu-gene loss in multiple bacterial genera, with effects on biofilm and adhesion replicated in V. cholerae and Escherichia coli, suggesting convergent evolution and universal phenotypic effects. Our results highlight the indispensable role of gene loss in bacterial pathogen adaptation.

microbiology↗

bioRxiv2024

Cell-free synthesis and purification of recombinant nucleocapsid (N), membrane (M), and envelope (E) proteins

Rapid production of soluble recombinant antigens is important for developing in vitro diagnostics, vaccines, and drugs against virus such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this research, hard-to-express nucleocapsid, membrane, and envelope proteins were successfully expressed by an Escherichia coli-based cell-free protein synthesis system. The solubility of the proteins was optimized using various amphipathic molecules. Most of the impurities were easily removed by a one-step Ni-NTA affinity chromatography. This study provides an easy and quick alternative for viruss trans-membrane and nucleotides associated recombinant protein expression, which has potential downstream application for early screening of newly emerging viruses.

synthetic biology↗