Biology subjects

Hwang, Y.

Publications and source records attributed to Hwang, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Seq-Scope-eXpanded: Spatial Omics Beyond Optical Resolution

Sequencing-based spatial transcriptomics (sST) enables transcriptome-wide gene expression mapping but falls short of reaching the optical resolution (200-300 nm) of imaging-based methods. Here, we present Seq-Scope-X (Seq-Scope-eXpanded), which empowers submicrometer-resolution Seq-Scope with tissue expansion to surpass this limitation. By physically enlarging tissues, Seq-Scope-X minimizes transcript diffusion effects and increases spatial feature density by an additional order of magnitude. In liver tissue, this approach resolves nuclear and cytoplasmic compartments in nearly every single cell, uncovering widespread differences between nuclear and cytoplasmic transcriptome patterns. Independently confirmed by imaging-based methods, these results suggest that individual hepatocytes can dynamically switch their metabolic roles. Seq-Scope-X is also applicable to non-hepatic tissues such as brain and colon, and can be modified to perform spatial proteomic analysis, simultaneously profiling hundreds of barcode-tagged antibody stains at microscopic resolutions in mouse spleens and human tonsils. These findings establish Seq-Scope-X as a transformative tool for ultra-high-resolution whole-transcriptome and proteome profiling, offering unparalleled spatial precision and advancing our understanding of cellular architecture, function, and disease mechanisms.

genomics↗

bioRxiv2025

Heartbeat-like dynamics drives oxygen activation in methane monooxygenase

Soluble methane monooxygenase (sMMO) is an enzyme that hydroxylates methane (CH4), a potent greenhouse gas, at non-heme di-iron active sites under atmospheric conditions. The regulatory component (MMOB) is essential for the catalytic activity of hydroxylase (MMOH) as it induces conformational changes in the active site and facilitating substrate ingress. Recent advances in cryogenic electron microscopy (cryo-EM) have enabled us to elucidate the high resolution picture of sMMO catalytic mechanism. We describe the 2.85 [A] cryo-EM structure of MMOH-MMOB, with one equivalent of MMOB bound to MMOH (H-1B), which is in contrast with previously solved crystal structures. MMOB allosterically regulates the MMOH protomer ({beta}{gamma}) and induces conformational changes that propagate from the surface to the di-iron coordination site. The N-terminal region of the MMOH {beta}-subunit (NT-H{beta}) stabilizes helices essential for iron coordination and oxygen activation. The MMOB-bound protomer (HBA, {beta}{gamma}B) presents the first structural report of a 2.7 [A] Fe{middle dot}{middle dot}{middle dot}Fe distance, while the non-MMOB-bound protomer (HBB, {beta}{gamma}) and MMOH display a 3.1 [A] distance. The coordination of Fe-ligands is maintained by the structural stabilization provided by the {beta}- and {gamma}-subunits of MMOH. This novel cryo-EM structure reveals new coordination environments, offering crucial mechanistic insights into sMMO catalysis.

biochemistry↗

bioRxiv2025

c-di-GMP is required for swarming motility in E. coli

Many bacteria use flagella to swim individually through bulk liquid, or swarm collectively over a semi-solid surface. In E. coli, c-di-GMP inhibits swimming via the effector protein YcgR. We show in this study that contrary to its effect on swimming, a certain threshold level of c-di-GMP is required for swarming. Gene expression profiles first indicated that several c-di-GMP synthases - dgcJ, dgcM, dgcO - were upregulated during swarming. Of these, we found DgcO to play a critical role. DgcO is reported to affect PGA (poly-{beta}-1,6-N-acetylglucosamine) synthesis in E. coli. We show that DgcO also promotes production of colanic acid - one of the three major exopolysaccharides in E. coli, and that colanic acid has hitherto-unknown surfactant properties that are expected to aid swarming. ImportanceIt is well-established that in bacteria, c-di-GMP inhibits flagella-driven motility at various points in the pathway. Concomitantly, elevated c-di-GMP levels induce the expression and synthesis of a variety of exopolysaccharides that enmesh the bacteria in a biofilm, thereby also interfering with flagella function. This study reports the surprising finding that in E. coli, the exopolysaccharide colanic acid is required to enable surface navigation and that the diguanylate cyclase DgcO is employed for this purpose. For surface navigation, there appears to be a sweet spot where c-di-GMP levels are just right to produce polysaccharides that can serve as surfactants and wetting agents rather than promote formation of biofilms.

microbiology↗

bioRxiv2024

IL-17A primes an early progenitor compartment to tune the erythropoietic feedback circuit

Feedback control of erythropoiesis exemplifies conflicting goals in tissue homeostasis: maintaining fast reactivity to stress while minimizing proliferative burden on progenitors in the steady state. Here we show that these conflicting goals are tuned through the combinatorial action of cytokines. We find that IL-17A, a pro-inflammatory cytokine, mediates striking synergism with the negative feedback signal erythropoietin (Epo) in vivo, accelerating the erythropoietic response to hypoxia. A model of erythropoietic control shows increased reactivity may occur through two cell circuit designs, with one having far lower constitutive progenitor burden in normoxia. IL-17A acts through this optimal design by sensitizing progenitors to Epo, a model supported by multiple experimental observations. We suggest that IL-17A signals impending hypoxia during infections, tuning erythropoiesis in favor of a faster stress response. Our study highlights IL-17A as a potential erythropoietic therapeutic agent and serves as a model of homeostatic tuning in stem and progenitor cell circuits.

systems biology↗

bioRxiv2024

Gaia: A Context-Aware Sequence Search and Discovery Tool for Microbial Proteins

Protein sequence similarity search is fundamental to genomics research, but current methods are typically not able to consider crucial genomic context information that can be indicative of protein function, especially in microbial systems. Here we present Gaia (Genomic AI Annotator), a sequence annotation platform that enables rapid, context-aware protein sequence search across genomic datasets. Gaia leverages gLM2, a mixed-modality genomic language model trained on both amino acid sequences and their genomic neighborhoods to generate embeddings that integrate sequence-structure-context information. This approach allows for the identification of functionally related genes that are found in conserved genomic contexts, which may be missed by traditional sequence- or structure-based search alone. Gaia enables real-time search of a curated database comprising over 85M protein clusters (defined at 90% sequence identity) from 131,744 microbial genomes. We compare the sequence, structure and context sensitivity of gLM2 embedding-based search against existing tools like MMseqs2 and Foldseek. We showcase Gaia-enabled discoveries of phage tail proteins and siderophore synthesis loci that were previously difficult to annotate with traditional tools. Gaia search is freely available at https://gaia.tatta.bio.

bioinformatics↗

bioRxiv2024

The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling

Biological language model performance depends heavily on pretraining data quality, diversity, and size. While metagenomic datasets feature enormous biological diversity, their utilization as pretraining data has been limited due to challenges in data accessibility, quality filtering and deduplication. Here, we present the Open MetaGenomic (OMG) corpus, a genomic pretraining dataset totalling 3.1T base pairs and 3.3B protein coding sequences, obtained by combining two largest metagenomic dataset repositories (JGIs IMG and EMBLs MGnify). We first document the composition of the dataset and describe the quality filtering steps taken to remove poor quality data. We make the OMG corpus available as a mixed-modality genomic sequence dataset that represents multi-gene encoding genomic sequences with translated amino acids for protein coding sequences, and nucleic acids for intergenic sequences. We train the first mixed-modality genomic language model (gLM2) that leverages genomic context information to learn robust functional representations, as well as coevolutionary signals in protein-protein interfaces and genomic regulatory syntax. Furthermore, we show that deduplication in embedding space can be used to balance the corpus, demonstrating improved performance on downstream tasks. The OMG dataset is publicly hosted on the Hugging Face Hub at https://huggingface.co/datasets/tattabio/OMG and gLM2 is available at https://huggingface.co/tattabio/gLM2_650M.

systems biology↗

bioRxiv2024

Diverse Genomic Embedding Benchmark for functional evaluation across the tree of life

Biological foundation models hold significant promise for deciphering complex biological functions. However, evaluating their performance on functional tasks remains challenging due to the lack of standardized benchmarks encompassing diverse sequences and functions. Existing functional annotations are often scarce, biased, and susceptible to train-test leakage, hindering robust evaluation. Furthermore, biological functions manifest at multiple scales, from individual residues to large genomic segments. To address these limitations, we introduce the Diverse Genomic Embedding Benchmark (DGEB), inspired by natural language embedding benchmarks. DGEB comprises six embedding tasks across 18 expert curated datasets, spanning sequences from all domains of life and encompassing both nucleic acid and amino acid modalities. Notably, four datasets enable direct comparison between models trained on different modalities. Benchmarking protein and genomic language models (pLMs and gLMs) on DGEB reveals performance saturation with model scaling on numerous tasks, especially on those with underrepresented sequences (e.g. Archaea). This highlights the limitations of existing modeling objectives and training data distributions for capturing diverse biological functions. DGEB is available as an open-source package with a public leaderboard at https://github.com/TattaBio/DGEB.

bioinformatics↗

bioRxiv2024

Multimodal Precision Neuroimaging of the Individual Human Brain at Ultra-high fields

Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply "gradients" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.

neuroscience↗

bioRxiv2024

Ephrin Forward Signaling Controls Interspecies Cell Competition in Pluripotent Stem Cells

In the animal kingdom, evolutionarily conserved mechanisms known as cell competition eliminate unfit cells during development. Interestingly, cell competition also leads to apoptosis of donor cells upon direct contact with host cells from a different species during interspecies chimera formation. The mechanisms underlying how host animal cells recognize and transmit cell death signals to adjacent xenogeneic human cells remain incompletely understood. In this study, we developed an interspecies cell contact reporter system to dissect the mechanisms underlying competitive interactions between mouse and human pluripotent stem cells (PSCs). Through single-cell RNA-seq analyses, we discovered that Ephrin A ligands in mouse cells play a crucial role in signaling cell death to adjacent human cells that express EPHA receptors during interspecies PSC co-culture. We also demonstrated that blocking the Ephrin A-EPHA receptor interaction pharmacologically, and inhibiting Ephrin forward signaling genetically in the mouse cells, enhances the survival of human PSCs and promotes chimera formation both in vitro and in vivo. Our findings elucidate key mechanisms of interspecies PSC competition during early embryogenesis and open new avenues for generating humanized tissues or organs in animals, potentially revolutionizing regenerative medicine.

cell biology↗

bioRxiv2024

Regulation of fatty acid delivery to metastases by tumor endothelium

Tumor metastasis, the main cause of death in cancer patients, requires outgrowth of tumor cells after their dissemination and residence in microscopic niches. Nutrient sufficiency is a determinant of such outgrowth1. Fatty acids (FA) can be metabolized by cancer cells for their energetic and anabolic needs but impair the cytotoxicity of T cells in the tumor microenvironment (TME)2, 3, thereby supporting metastatic progression. However, despite the important role of FA in metastatic outgrowth, the regulation of intratumoral FA is poorly understood. In this report, we show that tumor endothelium actively promotes tumor growth and restricts anti-tumor cytolysis by transferring FA into developing metastatic tumors. This process uses transendothelial fatty acid transport via endosome cargo trafficking in a mechanism that requires mTORC1 activity. Thus, tumor burden was significantly reduced upon endothelial-specific targeted deletion of Raptor, a unique component of the mTORC1 complex (RptorECKO). In vivo trafficking of a fluorescent palmitic acid analog to tumor cells and T cells was reduced in RptorECKO lung metastatic tumors, which correlated with improved markers of T cell cytotoxicity. Combination of anti-PD1 with RAD001/everolimus, at a low dose that selectively inhibits mTORC1 in endothelial cells4, impaired FA uptake in T cells and reduced metastatic disease, corresponding to improved anti-tumor immunity. These findings describe a novel mechanism of transendothelial fatty acid transfer into the TME during metastatic outgrowth and highlight a target for future development of therapeutic strategies.

cancer biology↗

bioRxiv2024

Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics

Spatial transcriptomics (ST) technologies represent a significant advance in gene expression studies, aiming to profile the entire transcriptome from a single histological slide. These techniques are designed to overcome the constraints faced by traditional methods such as immunostaining and RNA in situ hybridization, which are capable of analyzing only a few target genes simultaneously. However, the application of ST in histopathological analysis is also limited by several factors, including low resolution, a limited range of genes, scalability issues, high cost, and the need for sophisticated equipment and complex methodologies. Seq-Scope--a recently developed novel technology--repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, thereby overcoming these limitations. Here we provide a detailed step-by-step protocol to implement Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell that allows for the profiling of multiple tissue sections in an area of 7 mm x 7 mm or larger. In addition to detailing how to prepare a frozen tissue section for both histological imaging and sequencing library preparation, we provide comprehensive instructions and a streamlined computational pipeline to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology. KEY POINTSO_LIThe protocol outlines a method for repurposing an Illumina NovaSeq 6000 flow cell as a spatial transcriptomics array, enabling the generation of high-resolution spatial datasets. C_LIO_LIThe protocol introduces a streamlined data analysis pipeline that produces a spatial digital gene expression matrix suitable for various single-cell and spatial transcriptome analysis methods. C_LIO_LIThe protocol allows for the capture of histology images from the same tissue section subjected to spatial transcriptomics analysis and allows users to precisely align the transcriptome dataset with the histological image using fiducial marks engraved on the flow cell surface. C_LIO_LILeveraging commonly available Illumina equipment, the protocol offers researchers ultra-high submicrometer resolution in spatial transcriptomics analysis with a comprehensive pipeline, rapid turnaround, cost efficiency, and versatility. C_LI

genomics↗

bioRxiv2024

High-Resolution Spatial Transcriptomic Atlas of Mouse Soleus Muscle: Unveiling Single Cell and Subcellular Heterogeneity in Health and Denervation

Skeletal muscle exhibits pronounced cellular and subcellular heterogeneity, but comprehensive spatial mapping has been constrained by cell/nuclei dissociation-based methods that lose tissue architecture and by spatial platforms with insufficient resolution or limited transcriptome coverage. Here we present a high-resolution spatial transcriptomic atlas of mouse soleus muscle in longitudinal sections with unbiased whole-transcriptome coverage, enabling myofiber-resolved transcriptomes while preserving subcellular expression domains across the length of fibers. Combining histology-guided myofiber segmentation with unbiased grid-based mapping, we recover canonical fiber types and reveal widespread hybrid myofiber states in situ, including type IIb-associated signatures that are rare in soleus muscle and evident only when intramyofiber heterogeneity is assessed. At subcellular scale, we delineate the neuromuscular junction (NMJ) as a multi-compartment niche comprising postsynaptic myonuclei and spatially distinct peri-synaptic and myelinating Schwann cell-associated regions, each with characteristic gene programs. Applying this framework to denervation (3 and 7 days) identifies robust fiber-type-specific stress responses, coordinated remodeling of macrophage and fibroblast transcriptomes, and marked intramyofiber heterogeneity, including spatially nonuniform activation of damage-response genes along individual myofibers, with distinct transcriptional domains proximal and distal to the NMJ and associated degenerative histological features. Together, this atlas provides a high-resolution reference for muscle biology and clarifies how denervation reshapes myofiber, synaptic, and stromal-immune programs across cells and within cells in intact tissue.

physiology↗

bioRxiv2024

FGF2 promotes the expansion of parietal mesothelial progenitor pools and inhibits BMP4-mediated smooth muscle cell differentiation

Mesothelial cells, in the outermost layer of internal organs, are essential for both organ development and homeostasis. Although the parietal mesothelial cell is the primary origin of mesothelioma that may highjack developmental signaling, the signaling pathways that orchestrate developing parietal mesothelial progenitor cell (MPC) behaviors, such as MPC pool expansion, maturation, and differentiation, are poorly understood. To address it, we established a robust protocol for culturing WT1+ MPCs isolated from developing pig and mouse parietal thorax. Quantitative qPCR and immunostaining analyses revealed that BMP4 facilitated MPC differentiation into smooth muscle cells (SMCs). In contrast, FGF2 significantly promoted MPC progenitor pool expansion but blocked the SMC differentiation. BMP4 and FGF2 counterbalanced these effects, but FGF2 had the dominant impact in the long-term culture. A Wnt activator, CHIR99021, was pivotal in MPC maturation to CALB2+ mesothelial cells, while BMP4 or FGF2 was limited. Our results demonstrated central pathways critical for mesothelial cell behaviors.

developmental biology↗

bioRxiv2023

Generation of salivary glands derived from pluripotent stem cells via conditional blastocyst complementation

Various patients suffer from dry mouth due to salivary gland dysfunction. Whole salivary gland generation and transplantation is a potential therapy to resolve this issue. However, the lineage permissible to design the entire salivary gland generation has been enigmatic. Here, we discovered Foxa2 as a lineage critical for generating a salivary gland via conditional blastocyst complementation (CBC). Foxa2 linage, but not Shh nor Pitx2, initiated to label between the boundary region of the endodermal and the ectodermal oral mucosa before primordial salivary gland formation, resulting in marking the entire salivary gland. The salivary gland was agenesis by depleting Fgfr2 under the Foxa2 lineage in the mice. We rescued this phenotype by injecting donor pluripotent stem cells into the mouse blastocysts. Those mice survived until adulthood with normal salivary glands compatible in size compared with littermate controls. These results indicated that CBC-based salivary gland generation is promising for next-generation cell-based therapy.

developmental biology↗

bioRxiv2023

FICTURE: Scalable segmentation-free analysis of sub-micron resolution spatial transcriptomics

Spatial transcriptomics (ST) technologies have advanced to enable transcriptome-wide gene expression analysis at submicron resolution over large areas. Analysis of high-resolution ST data relies heavily on image-based cell segmentation or gridding, which often fails in complex tissues due to diversity and irregularity of cell size and shape. Existing segmentation-free analysis methods scale only to small regions and a small number of genes, limiting their utility in high-throughput studies. Here we present FICTURE, a segmentation-free spatial factorization method that can handle transcriptome-wide data labeled with billions of submicron resolution spatial coordinates. FICTURE is orders of magnitude more efficient than existing methods and it is compatible with both sequencing- and imaging-based ST data. FICTURE reveals the microscopic ST architecture for challenging tissues, such as vascular, fibrotic, muscular, and lipid-laden areas in real data where previous methods failed. FICTUREs cross-platform generality, scalability, and precision make it a powerful tool for exploring high-resolution ST.

bioinformatics↗

bioRxiv2023

Flagellar motor remodeling during swarming requires FliL

FliL is an essential component of the flagellar machinery in some bacteria, but a conditional one in others. The conditional role is for optimal swarming in some bacteria. During swarming, physical forces associated with movement on a surface are expected to exert a higher load on the flagellum, requiring more motor torque to move. Bacterial physiology and morphology are also altered during swarming to cope with the challenges of surface navigation. FliL was reported to enhance motor output in several bacteria and observed to assemble as a ring around ion-conducting stators that power the motor. In this study we identify a common new function for FliL in diverse bacteria - Escherichia coli, Bacillus subtilis and Proteus mirabilis. During swarming, all these bacteria show increased cell speed and a skewed motor bias that suppresses cell tumbling. We demonstrate that these altered motor parameters, or motor remodeling, require FliL. Both swarming and motor remodeling can be restored in an E. coli fliL mutant by complementation with fliL genes from P. mirabilis and B. subtilis, showing conservation of swarming-associated FliL function across phyla. In addition, we demonstrate that the strong interaction we reported earlier between FliL and the flagellar MS-ring protein FliF is confined to the RBM-3 domain of FliF that links the periplasmic rod to the cytoplasmic C-ring. This interaction may explain several phenotypes associated with the absence of FliL.

microbiology↗

bioRxiv2023

Deep learning of genomic contexts predicts protein co-regulation and function

Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function paradigm from massive protein sequence datasets. However, to date, limited attempts have been made in extending this continuum to include higher order genomic context information. Evolutionary processes dictate the specificity of genomic contexts in which a gene is found across phylogenetic distances, and these emergent genomic patterns can be leveraged to uncover functional relationships between gene products. Here, we trained a genomic language model (gLM) on millions of metagenomic scaffolds to learn the latent functional and regulatory relationships between genes. gLM learns contextualized protein embeddings that capture the genomic context as well as the protein sequence itself, and encode biologically meaningful and functionally relevant information (e.g. enzymatic function, taxonomy). Our analysis of the attention patterns demonstrates that gLM is learning co-regulated functional modules (i.e. operons). Our findings illustrate that gLMs unsupervised deep learning of the metagenomic corpus is an effective and promising approach to encode functional semantics and regulatory syntax of genes in their genomic contexts and uncover complex relationships between genes in a genomic region.

bioinformatics↗

bioRxiv2023

p38γMAPK delays myelination and remyelination and is abundant in multiple sclerosis lesions

Multiple Sclerosis is a chronic inflammatory disease in which disability results from the disruption of myelin and axons. During the initial stages of the disease, injured myelin is replaced by mature myelinating oligodendrocytes that differentiate from oligodendrocyte precursor cells. However, myelin repair fails in secondary and chronic progressive stages of the disease and with aging, as the environment becomes progressively more hostile. This may be attributable to inhibitory molecules in the multiple sclerosis environment including activation of the p38MAPK family of kinases. We explored oligodendrocyte precursor cell differentiation and myelin repair using animals with conditional ablation of p38MAPK{gamma} from oligodendrocyte precursors. We found that p38{gamma}MAPK ablation accelerated oligodendrocyte precursor cell differentiation and myelination. This resulted in an increase in both the total number of oligodendrocytes and the migration of progenitors ex vivo and faster remyelination in the cuprizone model of demyelination/remyelination. Consistent with its role as an inhibitor of myelination, p38{gamma}MAPK was significantly downregulated as oligodendrocyte precursor cells matured into oligodendrocytes. Notably, p38{gamma}MAPK was enriched in samples of leukocortical multiple sclerosis lesions from patients, which represent areas of failed remyelination. Our data suggest that p38{gamma} could be targeted to improve myelin repair in multiple sclerosis.

neuroscience↗