Biology subjects

Cheng, X.

Publications and source records attributed to Cheng, X..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Amoebicidal Action of Licorice-Derived Compounds: Mechanisms and Effects Against Acanthamoeba castellanii

BackgroundAcanthamoeba is a widely distributed unicellular eukaryotic organism, causing Acanthamoeba keratitis, granulomatous amoebic encephalitis and chronic infectious ulcers. At present, there are no effective drugs available for treating Acanthamoeba infections, highlighting the urgent need for the development of novel anti-Acanthamoeba therapies. PurposeThis study aims to investigate the inhibitory effect of licorice on A. castellanii trophozoites growth and elucidate its molecular mechanisms. MethodsThe effect of licorice on trophozoite viability was assessed employing the CellTiter-Glo assay, while the viability of cells was evaluated via CCK-8 assay. Apoptotic cells were identified through Hoechst 33,342/PI double staining and caspase-3 detection. ROS level was measured via flow cytometry utilising DCFH-DA. Mitochondrial dysfunction was analysed with JC-1 and mtSOX Deep Red staining. RNA sequencing and RT-qPCR analysis were conducted to investigate the potential anti-Acanthamoeba mechanism. ResultsOur results showed that isoliquiritigenin (ISL) and glabridin (GLA) effectively inhibited A. castellaniitrophozoite growth in vitro dose-and time-dependently. ISL and GLA induced several apoptosis features, including Hoechst/PI-positive staining and increased caspase-3 expression. ISL and GLA increased intracellular ROS production, decreased SOD expression and mitochondrial membrane potential and enhanced mitochondrial ROS generation. ISL and GLA effectively prevent host cells from A. castellanii trophozoites invasion. RNA sequencing indicated that ISL may modulate the NAD+ metabolic process, while GLA may influence the sterol metabolic process. ISL reduced the NAD+/NADH ratio, while GLA lowered the levels of 7-dehydrocholesterol in A. castellanii trophozoites. ConclusionThese findings suggest that ISL and GLA may serve as the active components of licorice for treating A. castellanii trophozoites. Our findings suggest that ISL suppresses trophozoites by regulating NAD+ metabolism, while GLA inhibits trophozoites through the regulation of sterol metabolism. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/638758v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1e3ec1borg.highwire.dtl.DTLVardef@a212d2org.highwire.dtl.DTLVardef@81b710org.highwire.dtl.DTLVardef@19b003_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Intermittent Fasting Reprograms Chromatin Accessibility to Modulate Gene Expression in Brain and Muscle

Intermittent fasting (IF), a dietary regimen that mimics the natural feeding patterns observed across diverse organisms--from single-celled life to mammals--is thought to activate systemic survival responses and confer health benefits. However, the molecular mechanisms underlying these effects remain poorly understood. In this study, we utilized ATAC-Seq and RNA-Seq to investigate how IF influences chromatin accessibility and gene expression in brain and muscle tissues of mice, compared to ad libitum feeding. Our results reveal that IF induces significant changes in chromatin accessibility, modulating pathways related to metabolism, ribosome function, HIF-1 signaling, and glycolysis. Motif analysis identified tissue-specific transcription factors enriched in IF-regulated regions, including Sp1, Mef2a, NeuroD2, Banp, and NFIA in the brain, and SMAD4, TCF4, STAT5B, NKX3-1, and ZEB2 in muscle. Integrative analysis of ATAC-Seq and RNA-Seq data demonstrated that IF upregulates 50 genes and downregulates 15 in the cortex, while upregulating 31 genes and downregulating 10 in muscle. These gene expression changes are linked to pathways associated with neuroprotection and enhanced muscle function, offering mechanistic insights into the health benefits of IF. Our findings underscore the role of IF-induced chromatin remodeling in driving adaptive gene regulation.

bioinformatics↗

bioRxiv2025

Generalization but not strengthening of negative memories drives the development of depression-like behaviors

Individuals with depression exhibit intensified and generalized negative memories. However, how prior memories actually influence onset and/or progression of depression, particularly whether the strengthening or the generalization of prior memories play a key role, is poorly understood. Here, we introduced behavioral paradigms to differentiate between memory strengthening and generalization, and found that negative experiences that produced memory overgeneralization, but not strengthening, induced depression-like behaviors. Furthermore, we identified that the medial prefrontal cortex (mPFC) to the bed nucleus of the stria terminals (BNST) projection functionally linked memory generalization to depression, together with single-cell calcium imaging which revealed a significant overlap in the mPFCBNST neuronal ensemble encoding depression-like behaviors with that encoding generalized memory, but not memory strength. Circuit-based transcriptomic analysis and chromophore-assisted light inactivation demonstrated that triggering actin remodeling in the mPFCBNST neurons, a memory consolidation mechanism enhanced generalization while reducing memory strength, also induced depression-like behaviors. Collectively, these findings suggest generalization of negative memories as a primary factor that drives depression-like behaviors, highlighting the importance of early identification of individuals at risk for depression who exhibit overgeneralized negative memories, and targeting overgeneralized negative memories in the treatment of depression.

animal behavior and cognition↗

bioRxiv2025

Radiation exposure induced blood-brain barrier injury via mitochondria-mediated sterile inflammation

Radiation-induced brain injury (RIBI) is caused by exposure to high doses of ionizing radiation and characterized by severe cognitive dysfunction and brain necrosis. The widespread application of radiotherapy and rapid development of deep space exploration have substantially increased the risk of RIBI. However, the pathogenesis of RIBI is not fully understood, and no effective intervention is available. This work described a blood-brain barrier (BBB) microphysiological system (MPS), that allowed to explore the responses of BBB and distinct brain cells to radiation exposure. This BBB MPS can recapitulate the interface structure and function of BBB in brain microenvironment, including brain endothelial cells, astrocytes, pericytes and microglia co-cultured under flow condition. Following acute exposure to radiation of X-ray or {gamma}-ray, characteristic RIBI-associated pathological responses were observed, including BBB compromise, DNA breaks, inhibited cell proliferation, cell hypertrophy and pro-inflammatory cytokine release. Among the distinctive types of cells, brain endothelial cells showed the highest radiosensitivity as compared to other cells in the MPS. Intriguingly, X-ray and {gamma}-ray radiation consistently induced prominent sterile inflammation responses, especially type I interferon response, in the BBB MPS. These responses were mediated by radiation-induced mitochondrial DNA release and subsequent activation of cGAS-STING signaling pathway. Furthermore, we found abrocitinib (JAK1 inhibitor) and idebenone (mitochondrial protectant) can attenuate radiation-induced inflammation and ameliorate BBB injury. These findings revealed the involvement of mitochondria-mediated inflammation in RIBI pathogenesis, identifying mitochondria as a potential target for new radioprotective measures.

neuroscience↗

bioRxiv2025

Interferometric Ultra-High Resolution 3D Imaging through Brain Sections

Single-molecule super-resolution microscopy allows pin-pointing individual molecular positions in cells with nanometer precision. However, achieving molecular resolution through tissues is often difficult because of optical scattering and aberrations. We introduced 4Pi single-molecule nanoscopy for brain with in-situ point spread function retrieval through opaque tissue (4Pi-BRAINSPOT), integrating 4Pi single-molecule switching nanoscopy with dynamic in-situ coherent PSF modeling, single-molecule compatible tissue clearing, light-sheet illumination, and a novel quantitative analysis pipeline utilizing the highly accurate 3D molecular coordinates. This approach enables the quantification of protein distribution with sub-15-nm resolution in all three dimensions in complex tissue specimens. We demonstrated 4Pi-BRAINSPOTs capacities in revealing the molecular arrangements in various sub-cellular organelles and resolved the membrane morphology of individual dendritic spines through 50-{micro}m transgenic mouse brain slices. This ultra-high-resolution approach allows us to decipher nanoscale organelle architecture and molecular distribution in both isolated cells and native tissue environments with precision down to a few nanometers.

neuroscience↗

bioRxiv2025

Critical Evaluation of Sphingolipids Detection by MALDI-MSI

The increasing interest in the role of sphingolipids in (patho)physiology has led to the demand for visualization of these lipids within tissue samples (both from animal models and patient specimens) using techniques such as matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). While increasingly adopted, detection of sphingolipids with MALDI-MSI is challenging due to: i) the significant structural variations of sphingolipid molecules, ii) the potential breakdown of the more complex molecules into structurally simpler species which may confound the analysis, and iii) the great difference in levels among sphingolipid classes and subspecies, with the low-abundant ones often being close to the detection limit. In this study, we adopted a multi-pronged approach to establish a robust pipeline for the detection of sphingolipids by MALDI-MSI and to establish best practices and limitations of this technology. First, we evaluated the more commonly adopted methods [2,5-Dihydroxyacetophenon (DHA) or 2,5-Dihydroxybenzoic acid (DHB) matrix in positive ion mode and 1,5-Diaminonaphthalene (DAN) matrix in negative ion mode] using MALDI-MS on reference standards. These standards were used at ratios similar to their relative levels in biological samples to evaluate signal artifacts originating from fragmentation of more complex sphingolipids and impacting low level species. Next, by applying the most appropriate protocol for each sphingolipid class, MALDI-MSI signals were validated in cell culture by modulating specific sphingolipid species using sphingolipid enzymes and inhibitors. Finally, the optimized parameters were utilized on breast cancer tissue from the PyMT mouse model. We report the optimal signal for sphingomyelin (SM) and, for the first time, Sph in DHB positive ion mode (in cells and PyMT tissue), and the validated detection of ceramides and glycosphingolipids in DAN negative ion mode. We document the extensive fragmentation of SM into sphingosine-1-phosphate (S1P) and even more so into ceramide-1-phosphate (C1P) using DAN in negative ion mode and its effect in generating an artifactual C1P tissue signal; we also report the lack of detectable signal for S1P and C1P in biological samples (cells and tissue) using the more suitable DHB positive ion mode protocol.

cell biology↗

bioRxiv2024

MUTE drives asymmetric divisions to form stomatal subsidiary cells in Crassulaceae succulents

Amongst the evolutionary innovations of many succulents is a photosynthetic lifestyle, where stomatal gas exchange is decoupled from light-dependent carbon fixation. Stomatal complexes in the emerging succulent model Kalanchoe laxiflora consist of two guard cells surrounded by three anisocytic subsidiary cells (SCs). Here, we show that these SCs shuttle ions and thus likely support stomatal movements. Furthermore, gene editing, reporter lines and protein overexpression implicate the stomatal transcription factor MUTE in facilitating additional rounds of asymmetric divisions that form SCs in succulents. This is opposite to the role of MUTE in Arabidopsis thaliana, where it stops rather than induces asymmetric divisions, but reminiscent of MUTEs SC-related function in grasses. Together, our work deciphers an intricate genetic mechanism that generates innovative stomatal morphology in Crassulaceae succulents.

plant biology↗

bioRxiv2024

A molecularly defined brain circuit module for regulating the panic-like defensive state

Panic is an episode of strong defensive state, characterized by intense fear and severe physical symptoms such as elevated cardiorespiratory activities. How the brain generates panic state remains poorly understood. Here, we developed a robot-based experimental paradigm to evoke panic-like defensive state in mice. When stimulated by the robot, the mice exhibited jumping escapes and elevated cardiorespiratory activities. With this paradigm, we identified Cbln2-expressing (Cbln2+) neurons in the posterior hypothalamic nucleus (PHN) as a key neuronal population essential for the induction of panic-like defensive state. Activation of Cbln2+ PHN neurons induced behavioral and physical symptoms of panic-like defensive state. These neurons were strongly activated by noxious mechanical stimuli and encode jumping escape vigor. They were synaptically innervated by anxiety-associated brain areas and provoked panic-like defensive state via their projection to the periaqueductal gray. Together, our results reveal a molecularly defined circuit module that regulates the panic-like defensive state in mice.

neuroscience↗

bioRxiv2024

A comprehensive benchmark for multiple highly efficient base editors with broad targeting scope

As the toolbox of base editors (BEs) expands, selecting appropriate BE and guide RNA (gRNA) to achieve optimal editing efficiency and outcome for a given target becomes challenging. Here, we construct a set of 10 adenine and cytosine BEs with high activity and broad targeting scope, and comprehensively evaluate their editing profiles and properties head-to-head with 34,040 BE-gRNA-target combinations using genomically integrated long targets and tiling gRNA strategies. Interestingly, we observe widespread non-canonical protospacer adjacent motifs (PAMs) for these BEs. Using this large-scale benchmark data, we build a deep learning model, named BEEP (Base Editing Efficiency Predictor), for predicting the editing efficiency and outcome of these BEs. Guided by BEEP, we experimentally test and validate the installment of 3,558 disease-associated single nucleotide variants (SNVs) via BEs, including 20.1% of target sites that would be generally considered as "uneditable", due to the lack of canonical PAMs. We further predict candidate BE-gRNA-target combinations for modeling 1,752,651 ClinVar SNVs. We also identify several cancer-associated SNVs that drive the resistance to BRAF inhibitors in melanoma. These efforts benchmark the performance and illuminate the capabilities of multiple highly useful BEs for interrogating functional SNVs. A practical webserver (http://beep.weililab.org/) is freely accessible to guide the selection of optimal BEs and gRNAs for a given target.

molecular biology↗

bioRxiv2024

Balancing Locality and Reconstruction in Protein Structure Tokenizer

The structure of a protein is crucial to its biological function. With the expansion of available protein structures, such as those in the AlphaFold Protein Structure Database (AFDB), there is an increasing need for efficient methods to index, search, and generate these structures. Additionally, there is a growing interest in integrating structural information with models from other modalities, such as protein sequence language models. We present a novel VQ-VAE-based protein structure tokenizer, AIDO.StructureTokenizer (AIDO.St), which is a pretrained module for protein structures in an AI-driven Digital Organism [1]. AIDO.StructureTokenizer is a 300M parameter model consisting of an equivariant encoder to discretize input structures into tokens, and an invariant decoder to reconstruct the inputs from these tokens. In addition to evaluating structure reconstruction ability, we also compared our model to Foldseek, ProToken, and ESM3 in terms of protein structure retrieval ability. Through our experiments, we discovered an intriguing trade-off between the encoders locality and retrieval ability and the decoders reconstruction ability. Our results also demonstrate that a better balance between retrieval and reconstruction enables a better alignment between the structure tokens and a protein sequence language model, resulting in better structure prediction accuracy. Models and code are available through ModelGenerator in https://github.com/genbio-ai/AIDO and on Hugging Face.

bioinformatics↗

bioRxiv2024

Retrieval Augmented Protein Language Models for Protein Structure Prediction

The advent of advanced artificial intelligence technology has significantly accelerated progress in protein structure prediction, with AlphaFold2 setting a new benchmark for prediction accuracy by leveraging the Evoformer module to automatically extract co-evolutionary information from multiple sequence alignments (MSA). To address AlphaFold2s dependence on MSA depth and quality, we propose two novel models: AIDO.RAGPLM and AIDO.RAGFold, pretrained modules for Retrieval-AuGmented protein language model and structure prediction in an AI-driven Digital Organism (Song et al., 2024). AIDO.RAGPLM integrates pre-trained protein language models with retrieved MSA, surpassing single-sequence protein language models in perplexity, contact prediction, and fitness prediction. When sufficient MSA is available, AIDO.RAGFold achieves TM-scores comparable to AlphaFold2 while operating up to eight times faster, and significantly outperforms AlphaFold2 when MSA is insufficient ({Delta}TM-score=0.379, 0.116 and 0.059 for 0, 5 and 10 MSA sequences as input). Additionally, we developed an MSA retriever using hierarchical ID generation that is 45 to 90 times faster than traditional methods, expanding the MSA training set for AIDO.RAGPLM by 32%. Our findings suggest that AIDO.RAGPLM provides an efficient and accurate solution for protein structure prediction, particularly in scenarios with limited MSA data. The AIDO.RAGPLM model has been open-sourced and is available on https://huggingface.co/genbio-ai/AIDO.Protein-RAG-3B.

bioinformatics↗

bioRxiv2024

Scaling Dense Representations for Single Cell with Transcriptome-Scale Context

Developing a unified model of cellular systems is a canonical challenge in biology. Recently, a wealth of public single-cell RNA sequencing data as well as rapid scaling of self-supervised learning methods have provided new avenues to address this longstanding challenge. However, rapid parameter scaling has been essential to the success of large language models in text and images, while similar scaling has not been attempted with Transformer architectures for cellular modeling. To produce accurate, transferable, and biologically meaningful representations of cellular systems, we develop AIDO.Cell, a pretrained module for representing gene expression and cellular systems in an AI-driven Digital Organism [1]. AIDO.Cell contains a series of 3M, 10M, 100M, and 650M parameter encoder-only dense Transformer models pre-trained on 50 million human cells from diverse tissues using a read-depth-aware masked gene expression pretraining objective. Unlike previous models, AIDO.Cell is capable of handling the entire human transcriptome as input without truncation or sampling tricks, thus learning accurate and general representations of the human cells entire transcriptional context. This pretraining with a longer context was enabled through FlashAttention-2, mixed precision, and large-scale distributed systems training. AIDO.Cell (100M) achieves state-of-the-art results in tasks such as zero-shot clustering, cell-type classification, and perturbation modeling. Our findings reveal interesting loss scaling behaviors as we increase AIDO.Cells parameters from 3M to 650M, providing insights for future directions in single-cell modeling. Models and code are available through ModelGenerator in https://github.com/genbio-ai/AIDO and on Hugging Face.

bioinformatics↗

bioRxiv2024

Mixture of Experts Enable Efficient and Effective Protein Understanding and Design

Proteins play a fundamental role in life. Understanding the language of proteins offers significant potential for gaining mechanistic insights into biological systems and introduces new avenues for treating diseases, enhancing agriculture, and safeguarding the environment. While large protein language models (PLMs) like ESM2-15B and xTrimoPGLM-100B have achieved remarkable performance in diverse protein understanding and design tasks, these models, being dense transformer models, pose challenges due to their computational inefficiency during training and deployment. In this work, we introduce AIDO.Protein, a pretrained module for protein representation in an AI-driven Digital Organism [1]. AIDO.Protein is also the first mixture-of-experts (MoE) model in the protein domain, with model size scales to 16 billion parameters. Leveraging a sparse MoE architecture with 8 experts within each transformer block and selectively activating 2 experts for each input token, our model is significantly more efficient in training and inference. Through pre-training on 1.2 trillion amino acids collected from UniRef90 and ColabfoldDB, our model achieves state-of-the-art results across most tasks in the xTrimoPGLM benchmark. Furthermore, on over 280 ProteinGym Deep Mutational Scanning (DMS) assays, our model achieves nearly 99% of the overall performance of the best MSA-based model and significantly outperforms the previously reported state-of-the-art models that do not utilize MSA. We also adapted this model for structure-conditioned protein sequence generation tasks and achieved new SOTA in this domain. These results indicate that AIDO.Protein can serve as a strong foundation model for protein understanding and design. Models and codes are available through ModelGenerator in https://github.com/genbio-ai/AIDO and on Hugging Face.

bioinformatics↗

bioRxiv2024

Combining Glycosidases and Nanopore Technology for Glycan Sequencing

The efficient characterization of glycan structures remains a critical challenge. Direct glycan sequencing technologies with improved sensitivity and throughput are still needed. Here, we propose a glycan sequencing strategy based on glycosidase -assisted nanopore sensing. We used engineered nanopore -hemolysin (M113R/T115A), which provided high-resolution discrimination of monosaccharide volume differences and sensitivity to variations in glycan chain length. By utilizing the specificity of glycosidases, we sequentially hydrolyzed the terminal residues of the glycan chains and detected the characteristic shifts in electrical signals generated by the translocation of hydrolysis products. The accuracy of recognition of hydrolysis fragments achieved over 90 % using machine learning. This allowed us to efficiently and conveniently determine the sequence of consecutive monosaccharide units in the glycan chains. Based on this principle, we conducted a proof-of-concept demonstration on actual samples and verified the accuracy via HPLC-MS. We achieved the sequencing of consecutive units in glycan chains, confirming the theoretical feasibility of glycosidase -assisted nanopore glycan sequencing. With future optimization, the development of arrayed nanopore glycan sequencing technology based on hydrolysis strategy will provide an innovative approach for rapid decoding of glycans, which could promote the progress of glycomics research and glycobiology.

biochemistry↗

bioRxiv2024

The Cryo-EM structure of TRPC1 and TRPC5 heterotetramer

Ion channel heteromers display distinct electrophysiological and ligand-binding properties, allowing precise modulation of cellular functions in specific tissues. Among the TRPC subtypes, the TRPC1/4/5 heteromers are the most abundant isoform in the human brain and represent a primary target for treating anxiety and depression. However, the structural organization of TRPC1/4/5 heteromers remain unclear, limiting the advancement of research on these channels. Here, we report the cryo-EM structure of TRPC1/5 heterotatramer at a resolution of 2.84 [A]. It consists of an asymmetric structure with three TRPC5 subunits and one TRPC1 subunit. Further structural and functional analysis revealed that the TRPC1 subunit contributes to an asymmetrical ion conduction pathway, a characteristic that differentiates it from TRPC5 homomers. The unique features of the TRPC1 pore loop and its interface interactions with TRPC5 were shown to play crucial roles in modulating the ion conduction properties and gating mechanisms of the heteromeric complex. In addition, we identified key residues within the gating regions that influence channel activation and ion permeability, elucidating the structural basis for the functional divergence between the TRPC1/C5 heterotetramer and TRPC5 homotetramer. Notably, TRPC5 residues were found to dominate gating mechanisms, underscoring the complex interplay between subunit composition and functional outcomes in TRPC channels. Our findings provide novel insights into the structural and functional dynamics of TRPC1/C5 heteromers, paving the way for targeted therapeutic strategies in TRPC5-related disorders.

biophysics↗

bioRxiv2024

Nitroxoline evidence Amoebicidal Activity against Acanthamoeba castellanii through DNA damage and the stress response pathways

Acanthamoeba castellanii is a widespread unicellular eukaryote found in diverse environments, including tap water, soil, and swimming pools. It is responsible for severe infections, such as Acanthamoeba keratitis and granulomatous amebic encephalitis, particularly in individuals with immunocompromisation. The ability of protozoans to form dormant cysts complicates treatment, as current therapies are ineffective against cyst stages and suffer from poor specificity and side effects. Nitroxoline, a quinoline derivative with well-established antibacterial, antifungal, and antiviral properties, is a promising therapeutic candidate. This study aimed to elucidate cellular signalling events that counteract the effects of nitroxoline. In this study, nitroxoline significantly reduced the viability of A. castellanii trophozoites in a dose- and time-dependent manner, inducing morphological changes and apoptosis. Transcriptomic analysis revealed substantial alterations in gene expression, including enrichment of metabolic pathways, DNA damage responses, and iron ion binding. Nitroxoline treatment upregulated genes involved in DNA repair and oxidative stress response while regulating genes in the methionine and cysteine cycles. It also decreased the mitochondrial membrane potential, H2S production, and total iron amount in A. castellanii. Bioinformatics analyses and molecular docking studies suggest direct interactions between nitroxoline and A. castellanii proteins. Our research provides a comprehensive molecular map of the response of A. castellanii to nitroxoline, revealing significant changes in gene expression related to the stress response and metabolic pathways. These findings underscore the potential of nitroxoline as a potent anti-Acanthamoeba agent, offering new insights into its mechanism of action and paving the way for effective therapeutic strategies.

microbiology↗

bioRxiv2024

Developmental regulation of endothelial-to-hematopoietic transition from induced pluripotent stem cells

Hematopoietic stem cells (HSCs) arise in embryogenesis from a specialized hemogenic endothelium (HE). In this process, HE cells undergo a unique fate change termed endothelial-to-hematopoietic transition, or EHT. While induced pluripotent stem cells (iPSCs) give rise to HE with robust hemogenic potential, the generation of bona fide HSCs from iPSCs remains a challenge. Here, we map single cell dynamics of EHT during embryoid body differentiation from iPSCs and integrate it with human embryo datasets to identify key transcriptional differences between in vitro and in vivo cell states. We further map ligand-receptor interactions associated with differential expression of developmental programs in the iPSC system. We found that the expression of endothelial genes was incompletely repressed during iPSC EHT. Elevated FGF signaling by FGF23, an endothelial pathway ligand, was associated with differential gene expression between in vitro and in vivo EHT. Chemical inhibition of FGF signaling during EHT increased HSPC generation in the zebrafish, while an FGF agonist had the opposite effect. Consistently, chemical inhibition of FGF signaling increased hematopoietic output from iPSCs. In summary, we map the dynamics of EHT from iPSCs at single cell resolution and identify ligand-receptor interactions that can be modulated to improve iPSC differentiation protocols. We show, as proof of principle, that chemical inhibition of FGF signaling during EHT improves hematopoietic output in zebrafish and the iPSC system.

developmental biology↗

bioRxiv2024

The mechanism and consequences of amyloid-β modulating thiamine pyrophosphokinase-1 expression in microglia

Ample studies attribute cognitive decline in Alzheimers disease to amyloid-{beta} deposition 1-6. However, brain amyloid-{beta} accumulation that saturates years before the manifestation of clinical symptoms is dissociated with cognitive decline of the disease 7. It is unknown how these two processes are mechanistically linked. In this and our accompanied study, we report that thiamine pyrophosphokinase-1 (TPK) deficiency plays essential roles in both processes via distinct mechanisms. Here we describe that diminished microglia Tpk controls the propagation of amyloid-{beta} plaques. In APP/PS1 transgenic mice, microglia showed elevated Tpk expression at 2-month-old, but reduction in a plaque-centric manner at 8-month-old. Interestingly, lipopolysaccharide, but not amyloid-{beta}, induceed Tpk reduction in cultured microglia. Tpk reduction led to microglia dysfunction, showing volatile motility but reduced phagocytosis and weak response to focal tissue injury, with accumulation of intracellular lipid droplets and abnormal mitochrondria. In Alzheimers disease mice, microglia-specific knockout of Tpk caused diminished plaque coverage, exacerbated plaque burden and synaptic loss. However, increased plaques were not accompanied by the development of neurofibrillary tangles or brain atrophy, in contrast to the phenotype described in our accompanied paper with neuronal Tpk deletion. In conclusion, plaque-induced inflammation reduces Tpk in microglia, selectively exacerbating the spread of amyloid pathology.

neuroscience↗