Biology subjects

Tu, F.

Publications and source records attributed to Tu, F..

13 recordsLinked to original sources

bioRxiv2026

Social anchors: how previous social locations shape current animal movement and habitat selection

Memory of past space use is an important factor in habitat selection, but memory of what? The concept of memory captures the geographic spaces that an animal has used in the past. There are, however, competing reasons why animals occupy a given space. Species may occupy space due to particular aspects of their memory. Using integrated step selection analysis, we tested the relative importance of memory: previous use of high forage quality or where social interactions occurred at two temporal scales in caribou (Ranger tarandus). The most important parameter to explain intra-seasonal movement was geographic memory. At the inter-annual scale, caribou more strongly revisited locations with high quality forage and where they had formed dyads with conspecifics. We posit that remembered locations of social fusion can function as social anchors. The effects of memory on movement behaviour depend upon the context, both social and resource-based, and not geographic space alone.

ecology↗

bioRxiv2025

Heme drives cardiac endothelial senescence in sepsis via STING activation

Sepsis-induced cardiac dysfunction is a major contributor to sepsis-related mortality, and many patients continue to experience long-term cardiac complications after recovery. Here, we demonstrate that cardiac senescence is a key feature of sepsis-associated cardiac dysfunction, with endothelial cells identified as the predominant senescent population in septic cardiac tissue. Yet, the pathogenic drivers of endothelial senescence in sepsis remain poorly characterized. Among potential mediators, we found that elevated levels of heme, a byproduct of hemolysis, strongly correlate with increased endothelial senescence and impaired cardiac function. Mechanistic studies revealed that heme acts as a novel ligand for STING, exacerbating bacterial infection induced STING polymerization and activation, thereby promoting endothelial senescence. Notably, either STING inhibition or enhanced heme clearance via increased hemopexin expression significantly alleviated cardiac endothelial senescence and facilitated cardiac functional recovery in septic mice. These findings identify heme as a critical pathogenic driver of endothelial senescence and highlight heme clearance as a promising therapeutic strategy for mitigating sepsis induced cardiac dysfunction.

cell biology↗

bioRxiv2025

Oncogene Silencing via ecDNA Micronucleation

Extrachromosomal DNA (ecDNA) contributes to cancer genome instability by enabling high-copy oncogene amplification, intratumoural heterogeneity and rapid genetic change. Micronuclei (MN) are frequently observed in chromosomally unstable cancers, yet their origins and relevance in ecDNA-driven tumours remain incompletely understood. Here, we investigate the relationship between ecDNA segregation errors and MN formation. We find that ecDNA frequently localizes to MN and represents a prominent source of MN content in ecDNA-positive cancer cells. Mitotic clustering of oncogene-bearing ecDNAs is associated with asymmetric inheritance and mis-segregation into MN. Transfer of oncogenes from ecDNA into MN is accompanied by reduced transcriptional output. Single-MN sequencing shows that individual MN are enriched for ecDNA to a degree that exceeds expectations from stochastic mis-segregation and that in MN oncogenes originating from multiple distinct ecDNAs coalesce. Using live-cell imaging, we observe that cells inheriting ecDNA-positive MN show limited proliferative capacity and an increased likelihood of cell death. In neuroblastoma patients with MYCN-amplified ecDNA, higher frequencies of ecDNA-positive MN at diagnosis are associated with improved event-free and overall survival. Together, these findings link ecDNA mis-segregation to MN formation and reduced cellular fitness, suggesting that ecDNA-positive MN may reflect a state of impaired oncogenic ecDNA function with potential relevance for clinical outcome.

cancer biology↗

bioRxiv2025

Sky islands of Southwest China. II: Unraveling hidden species diversity of talpid moles using phylogenomics and skull-based deep learning

The sky islands of Southwest China, characterized by dramatic topographical and climatic variations, are prominent hotspots of biodiversity and endemism. Organisms inhabiting middle-to-high elevation habitats in this region are geographically isolated within distinct mountain chains, which over geological time have been subjected to isolation-by-distance and isolation-by-environment. These processes have led to profound allopatric diversification and strong phylogeographic structuring, resulting in a plethora of genetically distinct cryptic species, as is becoming increasingly evident for many small mammal families. However, morphological conservatism can pose significant challenges in delineating these clades within species complexes. In this study, we leverage artificial intelligence technologies to unravel the hidden species diversity of moles (family Talpidae) in Southwest Chinas sky islands. We first employed ultraconserved elements (UCEs) to investigate the evolutionary history of talpid moles, conducted molecular species delimitation using mitochondrial and multi-locus genes, and utilized both traditional and geometric morphometrics to examine their morphological disparity. To address the challenges of morphology based cryptic species identification, we developed a deep learning Hierarchical Identification of Species NETwork (HIS-NET) to create an image-based model that analyzes four different views of the skull/mandible to distinguish genera and species hierarchically. HIS-NET not only achieved expert-level accuracy in species identification but also effectively distinguished between cryptic and known species, aiding in the identification of key morphological variation intervals. Our results support the recognition of allopatrically distributed taxa in Euroscaptor and Parascaptor as full species, thereby confirming that species diversity in this region remains underestimated. Beyond advancing our understanding of speciation in this unique and fragile ecosystem, our study serves as a proof-of-concept, demonstrating the power of deep learning in unraveling hidden biodiversity within this and other species complexes.

zoology↗

bioRxiv2023

Nifuroxazide enhances radiotherapy efficacy against hepatocellular carcinoma by upregulating PD-L1 degradation via the ubiquitin-proteasome pathway

Radiation therapy is a primary treatment for hepatocellular carcinoma (HCC), but its effectiveness can be diminished by various factors. The over-expression of PD-L1 has been identified as a critical reason for radiotherapy resistance. Previous studies have demonstrated that nifuroxazide exerts antitumor activity by damaging the Stat3 pathway, but its efficacy against PD-L1 has remained unclear. In this study, we investigated whether nifuroxazide could enhance the efficacy of radiotherapy in HCC by reducing PD-L1 expression. Our results showed that nifuroxazide significantly increased the sensitivity of tumor cells to radiation therapy by inhibiting cell proliferation and migration while increasing apoptosis in vitro. Additionally, nifuroxazide attenuated the up-regulation of PD-L1 expression induced by irradiation, which may be associated with increased degradation of PD-L1 through the ubiquitination-proteasome pathway. Furthermore, nifuroxazide greatly enhanced the efficacy of radiation therapy in H22-bearing mice by inhibiting tumor growth, improving survival, boosting the activation of T lymphocytes, and decelerating the ratios of Treg cells in spleens. Importantly, nifuroxazide limited the increased expression of PD-L1 in tumor tissues induced by radiation therapy. This study confirms, for the first time, that nifuroxazide can augment PD-L1 degradation to improve the efficacy of radiation therapy in HCC-bearing mice.

immunology↗

bioRxiv2022

Mutation divergence over space in tumour expansion

Mutation accumulation in tumour evolution is one major cause of intra-tumour heterogeneity (ITH), which often leads to drug resistance during treatment. Previous studies with multi-region sequencing have shown that mutation divergence among samples within the patient is common, and the importance of spatial sampling to obtain a complete picture in tumour measurements. However, quantitative comparisons of the relationship between mutation heterogeneity and tumour expansion modes, sampling distances as well as the sampling methods are still few. Here, we investigate how mutations diverge over space by varying the sampling distance and tumour expansion modes using individual based simulations. We measure ITH by the Jaccard index between samples and quantify how ITH increases with sampling distance, the pattern of which holds in various sampling methods and sizes. We also compare the inferred mutation rates based on the distributions of Variant Allele Frequencies (VAF) under different tumour expansion modes and sampling sizes. In exponentially fast expanding tumours, a mutation rate can always be inferred in any sampling size. However, the accuracy compared to the true value decreases when the sampling size decreases, where small sampling sizes result in a high estimate of the mutation rate. In addition, such an inference becomes unreliable when the tumour expansion is slower such as in surface growth.

cancer biology↗

bioRxiv2022

Machine learning and hypothesis driven optimization of bull semen cryopreservation media

Cryopreservation provides a critical tool for dairy herd genetics management. Due to widely varying inter- and within-bull post thaw fertility, recent research on cryoprotectant extender medium has not dramatically improved suboptimal post-thaw recovery in industry. This progress is stymied by the interactions between samples and the many components of extender media and is often compounded by industry irrelevant sample sizes. To address these challenges, here we demonstrate blank-slate optimization of bull sperm cryopreservation media by supervised machine learning. We considered two supervised learning models: artificial neural networks and Gaussian process regression (GPR). Eleven media components and initial concentrations were identified from publications in bull semen cryopreservation, and an initial 200 extender-post-thaw motility pairs were used to train and 32 extender-post-thaw motility pairs to test the machine learning algorithms. The median post-thaw motility after coupling differential evolution with GPR the increased from 52.6 {+/-} 6.9% to 68.3 {+/-} 6.0% at generations 7 and 17 respectively, with several media performing dramatically better than control media counterparts. This is the first study in which machine learning was used to determine the best combination of constituents to optimize bull sperm cryopreservation media, and provides a template for optimization in other cell types.

bioengineering↗

bioRxiv2022

Ordered deployment of distinct ciliary beating machines in growing axonemes of vertebrate multiciliated cells

The beating of motile cilia requires to coordinated action of diverse machineries that include not only the axonemal dynein arms, but also the central apparatus, the radial spokes, and the microtubule inner proteins. These machines exhibit complex radial and proximodistal patterns in mature axonemes, but little is known about the interplay between them during motile ciliogenesis. Here, we describe and quantify the relative rates of axonemal deployment for these diverse cilia beating machineries during the final stages of differentiation of Xenopus epidermal multiciliated cells.

developmental biology↗

bioRxiv2022

Using NAMs to characterize chemical bioactivity at the transcriptomic, proteomic and phosphoproteomic levels

Omic-based technologies are of particular interest and importance for non-animal chemical hazard and risk characterization based on the premise that any apical endpoint change must be underpinned by some alterations measured at the omic levels. In this work we studied cellular responses to caffeine and coumarin by generating and integrating multi-omic data from transcriptomic, proteomic and phosphoproteomic experiments. We have shown that the methodology presented here is able to capture the complete chain of events from the first compound-induced changes at the phosphoproteome level to changes in gene expression induced by transcription factors and lastly to changes in protein abundance that further influence changes at the cellular level. In HepG2 cells we found the metabolism of lipids and general cellular stress to be dominant biological processes in response to caffeine and coumarin exposure, respectively. The phosphoproteomic changes were detected early in time, at very low concentrations and provided a fast adaptive cellular response to chemical exposure. Changes in protein abundance were found much less frequently than the transcriptomic changes and can be used, together with the transcriptomic changes, to facilitate a more complete understanding of pathway responses to chemical exposure. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/492410v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1e348c8org.highwire.dtl.DTLVardef@bf50c5org.highwire.dtl.DTLVardef@4fea36org.highwire.dtl.DTLVardef@998cb8_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2018

Systematic discovery of endogenous human ribonucleoprotein complexes

RNA-binding proteins (RBPs) play essential roles in biology and are frequently associated with human disease. While recent studies have systematically identified individual RBPs, their higher order assembly into Ribonucleoprotein (RNP) complexes has not been systematically investigated. Here, we describe a proteomics method for systematic identification of RNP complexes in human cells. We identify 1,428 protein complexes that associate with RNA, indicating that over 20% of known human protein complexes contain RNA. To explore the role of RNA in the assembly of each complex, we identify complexes that dissociate, change composition, or form stable protein-only complexes in the absence of RNA. Importantly, these data also provide specific novel insights into the function of well-studied protein complexes not previously known to associate with RNA, including replication factor C (RFC) and cytokinetic centralspindlin complex. Finally, we use our method to systematically identify cell-type specific RNA-associated proteins in mouse embryonic stem cells. We distribute these data as a resource, rna.MAP (rna.proteincomplexes.org) which provides a comprehensive dataset for the study of RNA-associated protein complexes. Our system thus provides a novel methodology for further explorations across human tissues and disease states, as well as throughout all domains of life.\n\nSummaryAn exploration of human protein complexes in the presence and absence of RNA reveals endogenous ribonucleoprotein complexes

systems biology↗

bioRxiv2017

A phase separated organelle at the root of motile ciliopathy

Hundreds of different cell types emerge in the developing embryo, each of which must compartmentalize cell type specific biochemical processes in a crowded intracellular environment. To study cell type specific compartmentalization, we examined motile ciliated cells, which must assemble vast numbers of dynein motors to drive ciliary beating, as mutation of dyneins or their assembly factors causes motile ciliopathy. We show that dyneins, their assembly factors, and chaperones all concentrate together in Dynein Assembly Particles (DynAPs). These phase-separated organelles are specific to ciliated cells but share machinery with stress granules. Our data suggest that a common framework underlies ubiquitous and cell-type specific phase separated organelles and that one such organelle is defective in a human genetic disease.

cell biology↗

bioRxiv2017

High-content protein localization screening in vivo reveals novel regulators of multiciliated cell development and function

Multiciliated cells (MCCs) drive fluid flow in diverse tubular organs and are essential for development and homeostasis of the vertebrate central nervous system, airway, and reproductive tracts. These cells are characterized by dozens or hundreds of long, motile cilia that beat in a coordinated and polarized manner (Brooks and Wallingford, 2014). In recent years, genomic studies have not only elucidated the transcriptional hierarchy for MCC specification, but also identified myriad new proteins that govern MCC ciliogenesis, cilia beating, or cilia polarization (e.g. (Choksi et al., 2014b; Chung et al., 2014; Hoh et al., 2012; Ma et al., 2014; Treutlein et al., 2014)). Interestingly, this burst of genomic data has also highlighted the obvious importance of the \"ignorome,\" that large fraction of vertebrate genes that remain only poorly characterized (Pandey et al., 2014). Understanding the function of novel proteins with little prior history of study presents a special challenge, especially when faced with large numbers of such proteins. Here, we explored the MCC ignorome by defining the subcellular localization of 260 poorly defined proteins in vertebrate MCCs in vivo. Moreover, functional analyses that arose from results of the screen provide novel insights into the mechanisms by which the actin cytoskeleton simultaneously influences diverse aspects of MCC biology, including basal body docking, and ciliogenesis.

cell biology↗

bioRxiv2016

A synthesis of over 9,000 mass spectrometry experiments reveals the core set of human protein complexes

Macromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing >4,600 total complexes, >7,700 proteins and >56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k-cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations and the map overall shows improved coverage of many disease-associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease.

systems biology↗