Biology subjects

Li, C.

Publications and source records attributed to Li, C..

At least 469 records · Page 26Linked to original sources

bioRxiv2024

Multiplexed optical barcoding and sequencing for spatial omics

Spatial omics has brought a fundamental change in the way that we study cell and tissue biology in health and disease. Among various spatial omics methods, genome-scale imaging allows transcriptomic, 3D-genomic, and epigenomic profiling of individual cells with high spatial (subcellular) resolution but often requires a preselection of targeted genes or genomic loci. On the other hand, spatially dependent barcoding of molecules followed by sequencing provides untargeted, genome-wide profiling but typically lacks single-cell resolution. Here, we report a spatial omics method that could potentially combine the power of the two approaches by optically controlled spatial barcoding followed by sequencing. Specifically, we utilize patterned light to encode the locations of cells in tissues using oligonucleotide-based barcodes and then identify the barcoded molecular content, such as mRNAs, by sequencing. This optical barcoding method is designed with multiplexing and error-correction capacity and achieved by a light-directed ligation chemistry that attaches distinct nucleic-acid sequences to the reverse transcribed cDNA products at different locations. As a proof of principle for this method, we demonstrated high-efficiency in situ light-directed ligation, spatially dependent barcoding with multiplexed light-controlled ligations, and high-accuracy detection of spatially barcoded mRNAs in cells.

genomics↗

bioRxiv2024

Hepatic Macrophage Migration Inhibitory Factor Promotes Pancreatic Cancer Liver Metastasis in NAFLD

How pathological livers shape tumors, thereby driving pancreatic ductal adenocarcinoma (PDAC) metastasis to the liver, is poorly understood. In the present study, we focus on examining key molecules implicated in this process and assessing their translational significance. We demonstrated that patients with combined non-alcoholic fatty liver disease (NAFLD) have approximately a ninefold increased risk of developing liver metastasis compared to those without NAFLD. In mice model, NAFLD fosters an immunosuppressive microenvironment with increased tumor cell pluripotency and focal adhesion. Mechanistically, NAFLD-induced MIF mediated the progression of PDAC liver metastasis by attracting CD44 positive pancreatic cells. Hepatic MIF knockdown significantly reduced metastases burden with decreased stem-like cancer cells, tumor associated macrophages (TAMs) infiltration and focal adhesion. Targeting the MIF-CD44 axis by either a MIF tautomerase inhibitor, IPG1576, or by CD44 knockdown in tumor cells significantly attenuate liver metastasis of PDAC within the NAFLD context. Patients with PDAC liver metastasis and NAFLD had elevated hepatic MIF expression and increased number of stem-cell like cancer cells. Collectively, our study highlights a pivotal role for MIF-CD44 axis in cancer stemness and offer novel avenues for tailoring therapeutic strategies to individual patients with NAFLD as an underlying condition.

cancer biology↗

bioRxiv2024

Pencil Beam Based X-ray Luminescence Computed Tomography Imaging of Deep TargetsThree-dimensionally and Quantitatively

X-ray luminescence computed tomography (XLCT), especially pencil beam based XLCT, has been emerged for more than 15 years because it can image deep targets in tissue with high spatial resolution and high measurement sensitivity. However, its application is limited by long scanning time and the tedious efforts of finite element mesh generation for model based reconstruction. Our previous study has addressed the imaging speed issue. In this study, we propose to reconstruct XLCT with weighted filtered back projection (wFBP) which makes it possible to perform XLCT imaging three dimensionally for complex objects at a high spatial resolution. We have also proposed measurements with multiple detectors to obtain quantitative XLCT images. To evaluate the proposed methods, we have performed numerical simulations and different sets of phantom experiments including phantom experiments with a control contrast target, different concentrations, and different target sizes. We have also successfully reconstructed deep targets with a diameter of approximately 0.15 mm. For the phantom experiments with targets of different concentrations, using a 4-channel XLCT system and the wFBP, we achieved the ratio of 3.8:1.79:1, closely resembling the ground truth ratio of 4:2:1. Lastly, we have, for the first time, reconstructed different 3D targets at high spatial resolution, successfully, including a printed M target, a triangular hollow bar, and a hot background cuboid with "UCM Li Lab" slots. Our results indicate that the proposed wFBP advances the promising XLCT technology and makes it ready for in vivo studies in the future.

bioengineering↗

bioRxiv2024

Causal discovery in biodiversity-mediated social-ecological systems

Global biodiversity loss and climate change exacerbate feedbacks within social-ecological systems, i.e., between ecosystems, their services and well-being of human societies. Our ability to mediate these feedbacks is hampered by incomplete understanding of the underlying causal links, which could benefit from interdisciplinary approaches to discover theoretical or empirical links from heterogeneous data characteristic of social-ecological studies. We propose a novel framework connecting literature-based causal knowledge with data-driven inference of causality. We test this framework for the highly biodiverse island of Borneo by conducting a systematic literature review of 7473 studies over 170 years, and a causal inference analysis for three conceptual causal diagrams connecting global change, socio-economics, ecosystem services, and biodiversity-ecosystem function using a set of 227 spatially explicit variables. We find that, while natural or social processes have been mostly studied independently, a set of studies already documents causal links across social-ecological domains for processes related to deforestation, food or energy. Causal discovery unveiled consistent negative causal links between global change, social-economic landscape, and biodiversity-ecosystem function, and positive causal links between global change and socio-economics, and these links were robust to indicator selection and addition. We detected few and weak links between social-economic landscape, global change, and ecosystem services. When comparing the data-driven inferred causal links to those documented by the literature, we find that links between biodiversity and ecosystem function with global change, and links between social-economic landscape and ecosystem services were also consistent, and causal analysis uncovered new (potential) causal links not yet described in the literature. Significance StatementAddressing climate change and biodiversity loss in the Anthropocene requires us to recognize that human societies and ecological systems are inherently interconnected in complex adaptive systems. Causal understanding in social-ecological systems enables understanding system dynamics and response to pressures and shocks. While promising, few studies have studied these systems using a combination of big literature which provides the state-of-the-knowledge and big data that provides the underlying information for causal discovery. With this framework, we can specify and rigorously test, causal links in biodiversity-mediated social-ecological processes under global change and examine potential interventions that lead to much needed sustainable outcomes.

ecology↗

bioRxiv2024

Amygdala engages non-emotional multi-item working memory maintenance through amygdala-hippocampus interaction

Retaining information in working memory (WM) is an active process that requires neural activity within and between regions. The human amygdala (AMY) and hippocampus (HPC) are known to play crucial roles in WM processing. Although electrophysiological studies have revealed that the HPC supports multi-item maintenance in a load-dependent manner, the characteristics of the AMY and the circuit-level mechanisms underlying AMY-HPC interactions remain largely unexplored. To address this knowledge gap, intracranial EEG recordings from the AMY and HPC in nine epileptic patients were employed to evaluate intraregional neural representations and interregional communications during maintenance under different non-emotional WM loads. High load enhanced low-frequency power and intraregional theta-gamma phase-amplitude coupling (PAC) in the AMY and HPC. At the network level, a high load elicited an increase in the strength of the HPC theta phase modulation, which entrains the AMY gamma amplitude. Furthermore, a high load increased AMY-anterior HPC (aHPC) theta phase synchrony and directional connectivity strength from the aHPC to the AMY. Conversely, posterior HPC (pHPC)-AMY synchrony was not affected by load variations. Overall, these findings highlight the importance of the AMY in non-emotional WM tasks and provide new insights into the neurophysiological basis of AMY-HPC interactions during WM maintenance.

neuroscience↗

bioRxiv2024

Mining the UniProtKB/Swiss-Prot database forantimicrobial peptides

The ever-growing global health threat of antibiotic resistance is compelling researchers to explore alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are emerging as a promising solution to fill this need. Naturally occurring AMPs are produced by all forms of life as part of the innate immune system. High-throughput bioinformatics tools have enabled fast and large-scale discovery of AMPs from genomic, transcriptomic, and proteomic resources of selected organisms. Public protein sequence databases, comprising over 200 million records and growing, serve as comprehensive compendia of sequences from a broad range of source organisms. Yet, large-scale in silico probing of those databases for novel AMPs has never been reported. In the present study, we propose an AMP mining workflow to predict novel AMPs from the UniProtKB/Swiss-Prot database using the AMP prediction tool, AMPlify, as its discovery engine. Using this workflow, we identified 8,008 novel putative AMPs from all eukaryotic sequences in the database. Focusing on the practical use of AMPs as suitable antimicrobial agents with applications in the poultry industry, we prioritized 40 of those AMPs based on their similarities to known chicken AMPs in predicted structures. In our tests, 13 out of the 38 successfully synthesized peptides showed antimicrobial activity against Escherichia coli and/or Staphylococcus aureus.

bioinformatics↗

bioRxiv2024

Neuron-level prediction and noise can implement flexible reward-seeking behavior

We show that neural networks can implement reward-seeking behavior using only local predictive updates and internal noise. These networks are capable of autonomous interaction with an environment and can switch between explore and exploit behavior, which we show is governed by attractor dynamics. Networks can adapt to changes in their architectures, environments, or motor interfaces without any external control signals. When networks have a choice between different tasks, they can form preferences that depend on patterns of noise and initialization, and we show that these preferences can be biased by network architectures or by changing learning rates. Our algorithm presents a flexible, biologically plausible way of interacting with environments without requiring an explicit environmental reward function, allowing for behavior that is both highly adaptable and autonomous. Code is available at https://github.com/ccli3896/PaN.

neuroscience↗

bioRxiv2024

TRAPT: A multi-stage fused deep learning framework for transcriptional regulators prediction via integrating large-scale epigenomic data

It is a challenging task to identify functional transcriptional regulators, which control expression of gene sets via regulatory elements and epigenomic signals, involving context-specific studies such as development and diseases. Integrating large-scale multi-omics epigenomic data enables the elucidation of the complex epigenomic control patterns of regulatory elements and regulators. Here, we propose TRAPT, a multi-modality deep learning framework that predicts functional transcriptional regulators from a queried gene set by integrating large-scale multi-omics epigenomic data, including histone modifications, ATAC-seq and TR-ChIP-seq. We design two-stage self-knowledge distillation model to learn nonlinear embedded representation of upstream and downstream regulatory element activity, and merge multi-modality epigenomic features from TR and the queried gene sets for inferring regulator activity. Experimental results on 1072 TR-related datasets demonstrate that TRAPT outperforms current state-of-the-art methods in predicting transcriptional regulators, especially in the prediction of transcription co-factors and chromatin regulators. Additionally, we have successfully identified key transcriptional regulators associated with the disease, genetic variation, cell fate decisions, and tissues. Our method provides an innovative perspective for integrating epigenomic data and has the potential to significantly assist researchers in deepening their understanding of gene expression regulation mechanisms.

bioinformatics↗

bioRxiv2024

Hydrocarbon-degrading microbial populations in permanently cold deep-sea sediments in the NW Atlantic

Permanently cold deep-sea sediments (2500-3500 m water depth) with or without indications of thermogenic hydrocarbon seepage were exposed to naphtha to examine the presence and potential of aerobic hydrocarbon-degrading microbial populations. Monitoring these microcosms for volatile hydrocarbons by GC-MS revealed sediments without in situ hydrocarbons responded more rapidly to naphtha amendment than hydrocarbon seep sediments overall, but seep sediments removed BTEX compounds more readily. Naphtha-driven aerobic respiration was more evident in surface sediment (0-20 cmbsf) than deeper anoxic layers (>130 cmbsf) that responded less rapidly. In all cases, enrichment of Gammaproteobacteria included lineages of Oleispira, Pseudomonas, and Alteromonas known to be associated with marine oil spills. On the other hand, taxa known to be prevalent in situ and diagnostic for thermogenic hydrocarbon seepage in deep sea sediment did not respond to naphtha amendment. This suggests a limited role for seep-associated populations in the context of oil spill biodegradation.

microbiology↗

bioRxiv2024

Novel mark recapture surveys reveal stable pigmentation patterns but age-related melanism in the common frog Rana temporaria

Variations in melanin-based pigmentation patterns are frequent evolutionary adaptations in vertebrates and allow the study of phenotypic diversity across populations as well as individual recognition. Age-related changes in such pigmentation patterns have been demonstrated for several species but remain rarely explored in adult amphibians. For the wide-ranging European common frog (Rana temporaria) dorsal melanism was discussed in the context of UV protection at high altitude or as thermal adaptation at high latitude, yet patterns remain unquantified across most of its range or in terms of individual variation over time. We investigated dorsal pigmentation patterns in a wild population of R. temporaria in a lowland site in England which was the focus of a 7 year high-intensity mark recapture programme. We collected dorsal photographs using phone cameras and analysed pigmentation patterns using visual classifications and ImageJ image processing software. Pigmentation was highly variable between individuals but overall: (i) the number of melanin-based spots was largely stable or decreased over time as enlarging spots sometimes merged but never disappeared; (ii) the total melanin-based pigmented area increased significantly over time on average, albeit not for all individuals; and (iii) pigmentation was similar in males compared to females although the darkest individuals tended to be males. Our analysis reveals important patterns in pigmentation change and stability in this widespread species but the mechanisms and specific drivers remain unknown.

zoology↗

bioRxiv2024

Persistent lung inflammation and alveolar-bronchiolization due to Notch signaling dysregulation in SARS-CoV-2 infected hamster

Long COVID or Post-acute sequalae of COVID-19 (PASC) defines the persistent signs, symptoms, and conditions long after initial SARS-CoV-2 infection which affecting over 10% of COVID-19 patients, with 40% of them affecting respiratory system. The lung histopathological changes and underlying mechanism remain elusive. Here we systemically investigate histopathological and transcriptional changes at 7, 14, 42, 84 and 120 days-post-SARS-CoV-2-infection (dpi) in hamster. We demonstrate persistent viral residues, chronic inflammatory and fibrotic changes from 42dpi to 120dpi. The most prominent lung histopathological lesion is multifocal alveolar-bronchiolization observed in every animal from 14dpi until 120dpi. However, none of the above are observed in hamsters recovered from influenza A infection. We show airway progenitor CK14+ basal cells actively proliferate, differentiate into SCGB1A+ club cell or Tubulin+ ciliated cells, leading to alveolar-bronchiolization. Most importantly, Notch pathway is persistently upregulated. Intensive Notch3 and Hes1 protein expression are detected in alveolar-bronchiolization foci, suggesting the association of sustained Notch signaling with dysregulated lung regeneration. Lung spatial transcriptomics show upregulation of genes positively regulating Notch signaling is spatially overlapping with alveolar-bronchiolization region. To be noted, significant upregulation of tumor-related genes was detected in abnormal bronchiolization region by spatial transcriptomics analysis, indicating possible risk of lung carcinoma. Collectively, our data suggests SARS-CoV-2 infection caused chronic inflammatory and fibrotic tissue damages in hamster lung, sustained upregulation of Notch pathway signaling contributed to the dysregulated lung regeneration and CK14+ basal cells-driven alveolar-bronchiolization. The study provides important information for potential therapeutic approaches and probable long-term surveillance of malignancy in PASC management.

microbiology↗

bioRxiv2024

Spatial domains identification in spatial transcriptomics by domain knowledge-aware and subspace-enhanced graph contrastive learning

Spatial transcriptomics (ST) technologies have emerged as an effective tool to identify the spatial architecture of the tissue, facilitating a comprehensive understanding of organ function and tissue microenvironment. Spatial domain identification is the first and most critical step in ST data analysis, which requires thoughtful utilization of tissue microenvironment and morphological priors. To this end, we propose a graph contrastive learning framework, GRAS4T, which combines contrastive learning and subspace module to accurately distinguish different spatial domains by capturing tissue microenvironment through self-expressiveness of spots within the same domain. To uncover the pertinent features for spatial domain identification, GRAS4T employs a graph augmentation based on histological images prior, preserving information crucial for the clustering task. Experimental results on 8 ST datasets from 5 different platforms show that GRAS4T outperforms five state-of-the-art competing methods in spatial domain identification. Significantly, GRAS4T excels at separating distinct tissue structures and unveiling more detailed spatial domains. GRAS4T combines the advantages of subspace analysis and graph representation learning with extensibility, making it an ideal framework for ST domain identification.

bioinformatics↗

bioRxiv2024

Perinatal maternal undernutrition in baboons modulates hepatic mitochondrial function but not metabolites in aging offspring.

We previously demonstrated in baboons that maternal undernutrition (MUN), achieved by 70 % of control nutrition, impairs fetal liver function, but long-term changes associated with aging in this model remain unexplored. Here, we assessed clinical phenotypes of liver function, mitochondrial bioenergetics, and protein abundance in adult male and female baboons exposed to MUN during pregnancy and lactation and their control counterparts. Plasma liver enzymes were assessed enzymatically. Liver glycogen, choline, and lipid concentrations were quantified by magnetic resonance spectroscopy. Mitochondrial respiration in primary hepatocytes under standard culture conditions and in response to metabolic (1 mM glucose) and oxidative (100 {micro}M H2O2) stress were assessed with Seahorse XFe96. Hepatocyte mitochondrial membrane potential (MMP) and protein abundance were determined by tetramethylrhodamine ethyl ester staining and immunoblotting, respectively. Liver enzymes and metabolite concentrations were largely unaffected by MUN, except for higher aspartate aminotransferase levels in MUN offspring when male and female data were combined. Oxygen consumption rate, extracellular acidification rate, and MMP were significantly higher in male MUN offspring relative to control animals under standard culture. However, in females, cellular respiration was similar in control and MUN offspring. In response to low glucose challenge, only control male hepatocytes were resistant to low glucose-stimulated increase in basal and ATP-linked respiration. H2O2 did not affect hepatocyte mitochondrial respiration. Protein markers of mitochondrial respiratory chain subunits, biogenesis, dynamics, and antioxidant enzymes were unchanged. Male-specific increases in mitochondrial bioenergetics in MUN offspring may be associated with increased energy demand in these animals. The similarity in systemic liver parameters suggests that changes in hepatocyte bioenergetics capacity precede detectable circulatory hepatic defects in MUN offspring and that the mitochondria may be an orchestrator of liver programming outcome.

physiology↗

bioRxiv2024

Quantitative cancer-immunity cycle modeling for predicting disease progression in advanced metastatic colorectal cancer

Patients diagnosed with advanced metastatic colorectal cancer (mCRC) often exhibit heterogeneous disease progression and face poor survival prospects. In order to comprehensively analyze the varied treatment responses among individuals and the challenge of tumor recurrence resistant to drugs in advanced mRCR, we developed a novel quantitative cancer-immunity cycle (QCIC) model. The proposed model was meticulously crafted utilizing a blend of differential equations and randomized modeling techniques to quantitatively elucidate the intricate mechanisms governing the cancer-immunity cycle and forecast tumor dynamics under different treatment modalities. Furthermore, by integrating diverse clinical datasets and rigorous model analyses, we introduced two pivotal concepts: the treatment response index (TRI) and the death probability function (DPF). These concepts are crucial tools for translating model predictions into clinically relevant evaluation indexes. Using virtual patient technology, we extrapolated tumor predictive biomarkers from the model to predict survival outcomes for mCRC patients. Our findings underscore the significance of tumor-infiltrating CD8+CTL cell density as a key predictive biomarker for short-term treatment responses in advanced mCRC while emphasizing the potential predict value of the tumor-infiltrating CD4+Th1/Treg ratio in determining patient survival. This study presents a pioneering methodology bridging the divide between diverse clinical data sources and the generation of virtual patients, offering invaluable insights into understanding inter-individual treatment variations and forecasting survival outcomes in mCRC patients. Author summaryThis study introduces a sophisticated modeling approach to delineate the intricate dynamics of tumor-immune interactions within the cancer-immunity cycle. Utilizing a multi-compartmental, multi-scale, multi-dimensional differential equation model, we quantified the complex interplay between tumor cells, immune cells, cytokines, and chemokines. By integrating virtual patient technology, we have conducted in silico clinical trials that accurately predict disease progression across multiple treatment modalities for cancer patients, particularly in advanced mCRC. Through the combination of differential equations and randomized modeling, we effectively captured the diverse treatment responses and clinical manifestations of drug-resistant tumor recurrence. Furthermore, we explored the pivotal role of predictive biomarkers in determining patients survival prognosis, offering insights for tailored therapeutic strategies. Importantly, our computational framework holds promise for the extension to the investigation of patients with other tumor types, thus contributing to the personalized investigation of patients with other tumor types and cancer care.

systems biology↗

bioRxiv2024

Comparative Single Cell Analysis of Transcriptional Bursting Reveals the Role of Genome Organization on de novo Transcript Origination

Spermatogenesis is a key developmental process underlying the origination of newly evolved genes. However, rapid cell type-specific transcriptomic divergence of the Drosophila germline has posed a significant technical barrier for comparative single-cell RNA-sequencing (scRNA-Seq) studies. By quantifying a surprisingly strong correlation between species- and cell type-specific divergence in three closely related Drosophila species, we apply a new statistical procedure to identify a core set of 198 genes that are highly predictive of cell type identity while remaining robust to species-specific differences that span over 25-30 million years of evolution. We then utilize cell type classifications based on the 198-gene set to show how transcriptional divergence in cell type increases throughout spermatogenic developmental time. After validating these cross-species cell type classifications using RNA fluorescence in situ hybridization (FISH) and imaging, we then investigate the influence of genome organization on the molecular evolution of spermatogenesis vis-a-vis transcriptional bursting. We first show altering transcriptional burst size contributes to pre-meiotic transcription and altering bursting frequency contributes to post-meiotic expression. We then report global differences in autosomal vs. X chromosomal transcription may arise in a developmental stage preceding full testis organogenesis by showing evolutionarily conserved decreases in X-linked transcription bursting kinetics in all examined somatic and germline cell types. Finally, we provide evidence supporting the cultivator model of de novo gene origination by demonstrating how the appearance of newly evolved testis-specific transcripts potentially provides short-range regulation of neighboring genes transcriptional bursting properties during key stages of spermatogenesis. Significance StatementUnderstanding the divergence and evolution of novel genes and expression is an essential question in evolutionary biology. However, rapid transcriptomic divergence in tissues such as testis has significantly hindered comparative single-cell RNA-Seq studies and understanding of the rapidly evolving components of the cell types. Here, we provide a novel strategy that does not rely on preexisting marker genes for cell type identity to overcome the challenge. We found that genome organization affects expressional evolution through transcriptional bursting dynamics. Our results also support the cultivator model of de novo gene origination--a model emphasizing the genomic environment in shaping novel gene origination--by illustrating how newly evolved transcripts alter the transcriptional bursting kinetics of neighboring genes.

evolutionary biology↗

bioRxiv2024

Genome of tropical bed bug Cimex hemipterus (Cimicidae, Hemiptera) reveals tetraspanin expanded in bed bug ancestor

Cimex species are ectoparasites that exclusively feed on warm-blooded animals such as birds and mammals. Three cimicid species are known to be persistent pests for humans, including the tropical bed bug C. hemipterus, common bed bug C. lectularius, and Eastern bat bug Leptocimex boueti. To date, genomic information is restricted to the common bed bug C. lectularius, which limits understand their biology and to provide controls of bed bug infestations. Here, a chromosomal-level genome assembly of C. hemipterus (495 Mb) containing on 16 pseudochromosomes (scaffold N50 = 34 Mb), together with 9 messenger RNA and small RNA transcriptomes were obtained. Comparison between hemipteran genomes, we found that the tetraspanin superfamily were expanded in the Cimex ancestor. This study provides the first genome assembly for the tropical bed bug C. hemipterus, and offers an unprecedented opportunity to address to questions relating to bed bug infestations, as well as genomic evolution to hemipterans more widely.

genomics↗

bioRxiv2024

Intrinsic diving reflex enhances cognitive performance by alleviating microvascular dysfunction in vascular cognitive impairment

Vascular cognitive impairment (VCI) stands as the second-most prominent contributor to cognitive decline, lacking efficacious interventions. Chronic cerebral hypoperfusion (CCH) triggers microvascular dysfunction, which plays a critical role in VCI pathophysiology, emerging as a pivotal therapeutic target. While interventions addressing facets of microvascular dysfunction like angiogenesis and blood-brain barrier functionality show promise, the evaluation of microvascular constriction, another key component, remains unexplored. The diving reflex (DR) represents an oxygen-conserving response, characterized by robust vasodilation and potentially also inducing angiogenesis. In this investigation, we studied DRs functionality and underlying mechanisms within a rat bilateral common carotid artery occlusion induced CCH model. Remarkably, progressive hippocampal microvascular constriction exhibited strong correlations with short-term memory impairment during both early (R2=0.641) and late phases (R2=0.721) of CCH. Implementation of DR led to a significant reduction in microvascular constriction within the hippocampus ([~]2.8-fold) and striatum ([~]1.5-fold), accompanied by enhanced vasodilatory capacity and heightened expression of vasoactive neuropeptides. Furthermore, DR attenuated microvascular degeneration across various brain subregions affected by CCH, concomitant with increased levels of multiple angiogenic factors. The reinforced microvascular integrity facilitated by DR corresponded with significantly improved short-term recognition memory and long-term spatial memory functions observed during the late phase of CCH. The comprehensive and synergistic effects of DR on various aspects of microvascular function and cognitive preservation highlight its potential as a disease-modifying therapeutic strategy in VCI.

neuroscience↗

bioRxiv2024

Transcriptional regulators ensuring specific gene expression and decision making at high TGFβ doses

TGF{beta}-signaling regulates cancer progression by controlling cell division, migration and death. These outcomes are mediated by gene expression changes, but the mechanisms of decision making towards specific fates remain unclear. Here, we combine SMAD transcription factor imaging, genome-wide RNA sequencing and morphological assays to quantitatively link signaling, gene expression and fate decisions in mammary epithelial cells. Fitting genome-wide kinetic models to our time-resolved data, we find that the majority of TGF{beta} target genes can be explained as direct targets of SMAD transcription factors, whereas the remainder show signs of complex regulation, involving delayed regulation and strong amplification at high TGF{beta} doses. Knockdown experiments followed by global RNA sequencing revealed transcription factors interacting with SMADs in feedforward loops to control delayed and dose-discriminating target genes, thereby reinforcing the specific epithelial-to-mesenchymal transition at high TGF{beta} doses. We identified early repressors, preventing premature activation, and a late activator, boosting gene expression responses for a sufficiently strong TGF{beta} stimulus. Taken together, we present a global view of TGF{beta}-dependent gene regulation and describe specificity mechanisms reinforcing cellular decision making.

systems biology↗