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Biology subjects

Li, Y.-F.

Publications and source records attributed to Li, Y.-F..

13 recordsLinked to original sources

A split-control criterion for few-shot adaptation in single-cell perturbation prediction

Few-shot adaptation can help or harm single-cell perturbation prediction, but conventional evaluation shares a control estimate between calibration responses and held-out targets. We show how methods carry control error into their predictions and derive its contribution to score inflation. Nested control-depth experiments support inverse-depth scaling of inner-product inflation; correlation inflation also depends on the control noise-to-signal ratio. Independent-control scoring changed the rank of 40 of 52 configuration-dataset entries. We introduce SafeDelta, a split-control criterion that uses calibration data to decide whether to adapt. Across six datasets, mean gated gain was non-negative under the original two-control evaluation. On a deep plate, fixed predictions and decisions retained positive mean gains under three additional independent control references. The same reproducibility principle identified a fibrosis programme that localises to scar in human liver. These results inform adaptation decisions and control-depth planning.

bioinformatics↗

TLR7 Signaling Regulates Embryonic Hematopoietic Stem Cell Development by Sensing microRNA-146a in Vertebrates

The specification of hematopoietic stem cells (HSCs) is tightly regulated by multiple transcription factors and signaling pathways. Inflammatory signaling is pivotal for embryonic HSC development, but the mechanisms that activate it in vivo remain poorly understood. Here, we show that Toll-like receptor 7 (TLR7) is essential for the emergence of embryonic HSC in both zebrafish and mouse embryos. TLR7 deficiency reduces HSC numbers but not primitive or definitive progenitors. Conversely, the TLR7 agonist R848 enhances embryonic HSC development. Mechanistically, TLR7 signaling acts through interferon regulatory factor 5 (IRF5) to induce the expression of inflammatory cytokines, which subsequently activate Notch signaling to promote HSC emergence through a non-cell-autonomous mechanism. Notably, we identify microRNA-146a (miR-146a) as a potential endogenous activator of TLR7, inducing inflammatory signaling and promoting HSC development. Pharmacological treatment with miR-146a significantly increases HSC numbers in zebrafish embryos. Together, our findings reveal a crucial role for miR-146a-TLR7-IRF5 signaling axis in HSC emergence, providing insights into the endogenous factors that drive tonic inflammatory signaling during normal hematopoiesis and suggesting the translational potential of TLR7 agonists and miR-146a for stem-cell-based therapeutics. Significance StatementThe embryonic origin of hematopoietic stem cells (HSCs) requires inflammatory signals, but the endogenous factor that triggers this process remains elusive. We identify microRNA-146a (miR-146a) as a natural activator of Toll-like Receptor 7 (TLR7) signaling, which is essential for HSC emergence. This miR-146a-TLR7 axis functions through IRF5 and inflammatory cytokines to activate the Notch signaling, specifically promoting embryonic HSC development. Our work addresses the critical question of endogenous ligands that mediate tonic inflammatory signaling in normal hematopoiesis, uncovers novel crosstalk between miRNAs and innate immunity in HSC specification, and identifies promising candidates for stem cell-based therapeutics.

developmental biology↗

Angptl5 restricts primitive hematopoiesis by modulating retinoic acid signaling in zebrafish

Homeostasis is essential for hematopoiesis, and its dysregulation can lead to severe pathological conditions. Retinoic acid (RA) is a key regulator that exerts concentration-dependent effects on both embryonic and adult hematopoiesis. However, the mechanisms that modulate RA signaling in hematopoietic processes remain poorly understood. Using zebrafish as a model, we identified angiopoietin-like protein 5 (Angptl5) as a critical regulator of hematopoietic homeostasis. Loss of Angptl5 function resulted in myeloid hyperplasia in the anterior lateral plate mesoderm (ALPM) and anterior expansion of erythroid progenitors in the posterior lateral plate mesoderm (PLPM)-- phenotypes consistent with attenuated RA signaling. Molecular analyses confirmed impaired RA signaling in angptl5{Delta}10/{Delta}10 mutants, and exogenous RA supplementation fully rescued the hematopoietic defects. Mechanistically, we found that Angptl5 transcriptionally activates retinol dehydrogenase dhrs9 through its interaction with Integrin 6l{beta}5. Our findings establish Angptl5 as a novel and essential regulator of embryonic hematopoiesis and reveal a previously unrecognized mechanism controlling hematopoietic homeostasis. These insights position Angptl5 as a potential therapeutic target for hematological disorders.

developmental biology↗

A microfluidic model to recapitulate pH and oxygen gradients in solid tumors

The tumor microenvironment (TME) plays critical roles in cancer development, aggressiveness, and treatment resistance. The TME comprises cellular (stromal) components as well as gradients of physicochemical properties, including hypoxia and acidosis. Understanding of how hypoxia and acidosis gradients impact cancer phenotypes is lacking, in large part due to challenges in precisely mimicking and controlling such gradients in a manner compatible with the growth of cancer- and stromal cells. Here, we design and validate a microfluidic device enabling orthogonal gradients of oxygen and pH. Both gradients are established by diffusion from a nearby source and sink in the observation area in the absence of flow. This produces linear gradients at steady state. Our device enables a wide range of spatiotemporally resolved analyses, from omics to live cell imaging, interrogating the impact of the physicochemical TME on disease development. The design is easily adaptable, making it valuable for a wide range of questions involving physicochemical gradients.

cancer biology↗

From Archaea to the atmosphere: remotely sensing Arctic methane

Global atmospheric methane concentrations are rapidly rising and becoming isotopically more depleted, implying an unresolved microbial contribution. Rising Arctic temperatures are variably altering soil methane cycling, causing consequential uncertainty in the atmospheric methane budget. We demonstrated in an Arctic wetland that below-ground microbiota and methane-cycling features parallelled above-ground plant communities. To upscale emissions, we applied machine learning to remote sensing data to identify habitats, which were assigned average emissions. To upscale dynamically, we incorporated climate data, remotely-sensed water table variation, and habitat classes into a temporally-resolved biogeochemical model, to predict methane flux and isotope dynamics. This accurately estimated more depleted 13C-methane than previously used for Arctic habitats in global source partitioning. Remote-sensing of these rapidly changing inaccessible landscapes can thus help constrain the role of the Arctic in ongoing changes in global methane emissions.

microbiology↗

Stable states in an unstable landscape: microbial resistance at the front line of climate change

Microbiome responses to warming may amplify or ameliorate terrestrial carbon loss and thus are a critical unknown in predicting climate outcomes. Because the rapid thaw of permafrost peatlands makes a very large store of soil carbon available to microbial metabolism, understanding microbiome dynamics in these systems is particularly urgent. We quantified microbial warming response over seven years across three habitats in a thawing permafrost peatland, using large-scale multi-omics data. We integrated analyses of organisms (via taxonomy), functions (via metabolic pathways and proteins), and community organization (via network structure and ecological assembly) to deeply characterize response mechanisms. We consistently found a pattern of within-habitat microbiome stability, with virtually no signal of gradual change in the warming period studied. The resistance to change appeared bolstered by habitat-specific dispersal processes and community-level functional redundancy, particularly via versatile carbon generalists. Our findings also reveal key genome-inferred metabolic processes that underlie microbiome stability. Together, our results highlight the importance of understanding the limits of these stabilizing processes and suggest that future research should reorient towards critical habitat transitions.

microbiology↗

Mycn regulates vascular development through PI3K signaling pathway in zebrafish

Mycn, a MYC gene family member, is implicated in both carcinogenesis through amplification and Feingold syndrome through its deficiency. Previous studies have indicated that increased Mycn expression enhances vascularization in human neuroblastomas, yet its precise role in vascular development remains elusive. In this study, we utilized single-cell RNA-seq and live imaging analyses to confirm that mycn is expressed during zebrafish vasculogenesis. We investigated vascular development in zebrafish using a genetically engineered mycn mutation. Our findings reveal that mycn-deficient zebrafish exhibit reduced intersegmental vessels and malformed subintestinal vessels, primarily due to decreased cell proliferation in vascular cells. Importantly, we discovered that activation of PI3K signaling significantly ameliorates these vascular abnormalities.

developmental biology↗

Transcriptome brings variations of gene expression, alternative splicing, and structural variations into gene-scale trait dissection in soybean

Genome-wide association study (GWAS) identifies trait-associated loci, but due in part to slow decay of linkage disequilibrium (LD), identifying the causal genes can be a bottleneck. Transcriptome-wide association study (TWAS) addresses this by identifying gene expression-phenotype associations or integrating gene expression quantitative trait loci (eQTLs) with GWAS results. Here, we used self-pollinated soybean as a model to evaluate the application of TWAS in the genetic dissection of traits in plant species that exhibit slow LD decay. The first RNA-Seq analysis of a soybean diversity panel was conducted, which identified the genetic regulation of 29,286 genes. Different TWAS solutions were less affected by LD and robust with source of expression that identified known genes related to traits from different development stages and tissues. A novel gene named pod color L2 was identified via TWAS and functionally validated by genome editing. Our introduction of the new exon proportion feature significantly improves the capture of expression variations resulting from structural variations and alternative splicing. As a result, the genes identified by our TWAS approach exhibited a diverse range of causal variations, including SNP, insertion/deletion, gene fusion, copy number variation, and alternative splicing. Using our TWAS approach, we identified genes associated with flowering time, including both previously known candidates and novel genes that had not been linked to this trait before, providing complementary insights with GWAS. In summary, this study supports the application of TWAS for candidate gene identification in species with low rates of LD decay.

genetics↗

Population ecology and potential biogeochemical impacts of ssDNA and dsDNA soil viruses along a permafrost thaw gradient

Climate change is disproportionately warming northern peatlands, which may release large carbon stores via increased microbial activity. While there are many unknowns about such microbial responses, virus roles are especially poorly characterized with studies to date largely restricted to "bycatch" from bulk metagenomes. Here, we used optimized viral particle purification techniques on 20 samples along a highly contextualized peatland permafrost thaw gradient, extracted and sequenced viral particle DNA using two library kits to capture single-stranded (ssDNA) and double-stranded (dsDNA) virus genomes (40 total viromes), and explored their diversity and potential ecosystem impacts. Both kits recovered similar dsDNA virus numbers, but only one also captured thousands of ssDNA viruses. Combining these data, we explored population-level ecology using genomic representation from 9,560 viral operational taxonomic units (vOTUs); nearly a 4-fold expansion from permafrost-associated soils, and 97% of which were novel when compared against large datasets from soils, oceans, and the human gut. In silico predictions identified putative hosts for 44% (4,149 dsDNA + 17 ssDNA) of the identified vOTUs spanning 2 eukaryotic, 12 archaeal, and 30 bacterial phyla. The recovered vOTUs encoded 1,684 putative auxiliary metabolic genes (AMGs) and other metabolic genes carried by [~]10% of detected vOTUs, of which 46% were related to carbon processing and 644 were novel. These AMGs grouped into five functional categories and 11 subcategories, and nearly half (47%) of the AMGs were involved in carbon utilization. Of these, 112 vOTUs encoded 123 glycoside hydrolases spanning 15 types involved in the degradation of polysaccharides (e.g., cellulose) to monosaccharides (e.g., galactose), or further monosaccharide degradation, which suggests virus involvement in myriad metabolisms including fermentation and central carbon metabolism. These findings expand the scope of viral roles in microbial carbon processing and suggest viruses may be critical for understanding the fate of soil organic carbon in peatlands.

microbiology↗

Dissection of anterior mesendoderm segregation at single cell level in zebrafish

During gastrulation, the mesendoderm is firstly specified by morphogens such as Nodal, and then segregates into endoderm and mesoderm in a Nodal concentration-dependent manner. However, the mechanism underlying the segregation and crosstalk of different sub-groups within the meso- and endoderm lineages remains unclear. Here, taking zebrafish prechordal plate (PP) and anterior endoderm (Endo) as research model, using single-cell multi-omics and live imaging analyses, we show that anterior Endo progenitors originate directly from PP progenitors. A single-cell transcriptomic trajectory analysis of wild-type, ndr1 knockdown and lft1 knockout Nodal explants confirms the diversification of anterior Endo fate from PP progenitors. Gene Ontology (GO) enrichment analysis identifies that the change of chromatin organization potentiates the segregation of anterior endodermal cell fate from PP progenitors. Single-cell ATAC & RNA sequencing further reveals that two transcriptional regulators, gsc and ripply1, exhibit varied activation patterns in PP and anterior Endo cell trajectories at both the chromatin and RNA expression levels. We further demonstrate that Ripply1 functions coordinately with Gsc to repress anterior endodermal cell fate by directly binding to the cis-elements of sox32. Modulating the expression levels of these regulators tilts the cell fate decision between the PP and anterior Endo.

developmental biology↗

Control of Leaf Width by the APC/CTAD1-WL1-NAL1 Pathway in Rice

Leaf morphology is one of the most important features of the ideal plant architecture. However, the genetic and molecular mechanisms controlling leaf morphology in crops remain largely unknown, despite their central importance. Here we demonstrate that the APC/CTAD1-WL1-NAL1 pathway regulates leaf width in rice, and mutation of WL1 leads to width leaf variation. WL1 interacts with TAD1 and is degraded by APC/CTAD1, with the loss of TAD1 function resulting in narrow leaves. The WL1 protein directly binds to the regulatory region of NAL1 and recruits the corepressor TOPLESS-RELATED PROTEIN to inhibit NAL1 expression by down-regulating the level of histone acetylation of chromatin. Furthermore, biochemical and genetic analyses revealed that TAD1, WL1, and NAL1 function in a common pathway to control leaf width. Our study establishes an important framework for the APC/CTAD1-WL1-NAL1 pathway-mediated control of leaf width in rice and introduces novel perspectives for using this regulatory pathway for improving crop plant architecture.

plant biology↗

MonaGO: a novel Gene Ontology enrichment analysis visualisation system

MonaGO is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing gene ontology (GO) enrichment analysis and visualising the results. MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is the only platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options. In summary, MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.

bioinformatics↗

Glacier ice archives fifteen-thousand-year-old viruses

While glacier ice cores provide climate information over tens to hundreds of thousands of years, study of microbes is challenged by ultra-low-biomass conditions, and virtually nothing is known about co-occurring viruses. Here we establish ultra-clean microbial and viral sampling procedures and apply them to two ice cores from the Guliya ice cap (northwestern Tibetan Plateau, China) to study these archived communities. This method reduced intentionally contaminating bacterial, viral, and free DNA to background levels in artificial-ice-core control experiments, and was then applied to two authentic ice cores to profile their microbes and viruses. The microbes differed significantly across the two ice cores, presumably representing the very different climate conditions at the time of deposition that is similar to findings in other cores. Separately, viral particle enrichment and ultra-low-input quantitative viral metagenomic sequencing from [~]520 and [~]15,000 years old ice revealed 33 viral populations (i.e., species-level designations) that represented four known genera and likely 28 novel viral genera (assessed by gene-sharing networks). In silico host predictions linked 18 of the 33 viral populations to co-occurring abundant bacteria, including Methylobacterium, Sphingomonas, and Janthinobacterium, indicating that viruses infected several abundant microbial groups. Depth-specific viral communities were observed, presumably reflecting differences in the environmental conditions among the ice samples at the time of deposition. Together, these experiments establish a clean procedure for studying microbial and viral communities in low-biomass glacier ice and provide baseline information for glacier viruses, some of which appear to be associated with the dominant microbes in these ecosystems. ImportanceThis study establishes ultra-clean microbial and viral sampling procedures for glacier ice, which complements prior in silico decontamination methods and expands, for the first time, the clean procedures to viruses. Application of these methods to glacier ice confirmed prior common microbiological findings for a new ice core climate record, and provides a first window into viral genomes and their ecology from glacier ice across two time horizons, and emphasizes their likely impact on abundant microbial groups. Together these efforts provide clean sampling approaches and foundational datasets that should enable simultaneous access to an archived virosphere in glacier ice.

ecology↗