Biology subjects

Luo, Q.

Publications and source records attributed to Luo, Q..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Cell-type specific epigenetic clocks to quantify biological age at cell-type resolution

The ability to accurately quantify biological age could help monitor and control healthy aging. Epigenetic clocks have emerged as promising tools for estimating biological age, yet they have been developed from heterogeneous bulk tissues, and are thus composites of two aging processes, one reflecting the change of cell-type composition with age and another reflecting the aging of individual cell-types. There is thus a need to dissect and quantify these two components of epigenetic clocks, and to develop epigenetic clocks that can yield biological age estimates at cell-type resolution. Here we demonstrate that in blood and brain, approximately 39% and 12% of an epigenetic clocks accuracy is driven by underlying shifts in lymphocyte and neuronal subsets, respectively. Using brain and liver tissue as prototypes, we build and validate neuron and hepatocyte specific DNA methylation clocks, and demonstrate that these cell-type specific clocks yield improved estimates of chronological age in the corresponding cell and tissue-types. We find that neuron and glia specific clocks display biological age acceleration in Alzheimers Disease with the effect being strongest for glia in the temporal lobe. Moreover, CpGs from these clocks display a small but significant overlap with the causal DamAge-clock, mapping to key genes implicated in neurodegeneration. The hepatocyte clock is found accelerated in liver under various pathological conditions. In contrast, non-cell-type specific clocks do not display biological age-acceleration, or only do so marginally. In summary, this work highlights the importance of dissecting epigenetic clocks and quantifying biological age at cell-type resolution.

bioinformatics↗

bioRxiv2024

A smartphone-based genetically recombinant whole-cell biosensor for highly sensitive monitoring of polychlorinated biphenyls (PCBs)

Polychlorinated biphenyls (PCBs) are highly carcinogenic and persistent pollutants commonly found in ecosystems. Their complex congeners pose a huge challenge to instrumental analysis and ELISA methods, which prefer single and known targets. To overcome this limitation, here we developed an Escherichia coli whole-cell biosensor (WCB) for simultaneously detecting multiple PCB congeners. In this sensor, PCBs were firstly converted into hydroxylated PCBs (OH-PCBs) by bphAB degradation circuits, which then serve as high-affinity targets of transcriptional factor HbpRCBP6-based sensing pathways for sensitive response through extensive chassis screening. The resulting biosensor BL21(DE3)/HbpRCBP6-bphAB shows the lowest detection limits for 2-CBP (2-chlorobiphenyl) to date and can recognize various PCB homologues, including 3-CBP, 4-CBP, 2,3-diCBP and 2,2-diCBP, with detection limits of 0.06-1 M. Further investigation of the docking structure and binding energy reveal that HbpRCBP6 has a stronger affinity for OH-PCBs than for PCBs, indicating that the conversion of PCB by BphAB enzymes is a key step to improve the sensitivity of WCB. Subsequently, we developed an immobilized hydrogel WCB and a smartphone-based detection procedure to facilitate real-time and user-friendly PCB detection. This study will not only advance the biomonitoring of PCB contaminants but also provide an innovative strategy for developing metabolic pathway-sensing proteins combined biosensor. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/601110v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@10772cdorg.highwire.dtl.DTLVardef@22699org.highwire.dtl.DTLVardef@1343c27org.highwire.dtl.DTLVardef@595859_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Divergent roles of SOX2 in human and mouse germ cell specification related to X-linked gene dosage effects

Human primordial germ cell-like cells (hPGCLCs) can be generated from pluripotent stem cells (PSCs) but the differentiation efficiency of female hPSCs is often lower than that of male hPSCs. Moreover, Klinefelter Syndrome (KS), a condition characterized by an extra X-chromosome in males, often presents the failure of germline specification and infertility. In this study, we investigate how X-linked gene dosage affects hPGCLCs specification potential in both healthy and diseased conditions. We reveal that the X-chromosome plays a multifaceted role in modulating hPGCLCs induction. The inhibitory effects on TGF-beta/Activin A and BMP pathways by escape genes IGSF1 and CHRDL1, respectively, are demonstrated by the increased yield of hPGCLCs with knockdown experiments. Importantly, our results identified the intriguing role of SOX2 that is upregulated by the escape gene USP9X in hPGCLCs specification, highlighting a species-specific difference from the mouse model. The elevated USP9X-SOX2 regulatory axis profoundly influences cellular metabolism, mitochondrial morphology, and progenitor competence, thereby affecting hPGCLCs induction. Furthermore, the inability to downregulate SOX2 and upregulate SOX17 in response to BMP signaling impedes downstream gene activation due to motif binding competition. These findings shed novel insights into the hPGC specification by elucidating the differential roles of SOX2 versus SOX17 between mice and humans, influenced by X-linked gene dosage effects. Additionally, our results offer potential applications for improving the induction and survival efficiency of hPGCLCs from hPSCs, facilitating disease modeling and mechanistic studies. HighlightsO_LIDownregulation of three X-linked genes, i.e. IGSF1, CHRDL1 and USP9X, enhanced the differentiation efficiency of hPGCLCs C_LIO_LISOX2 as a downstream of human-specific escape gene USP9X plays a multifacet role against hPGCLCs specification C_LIO_LIFailure to timely downregulate SOX2 and upregulate SOX17 interferes downstream gene activation likely due to motif binding competition C_LI

cell biology↗

bioRxiv2024

Platinum drug reprogramming of protein phosphorylation

Cisplatin is a DNA-targeting chemotherapeutic. Here we investigate how the cisplatin damaged gene loci are linked to specific protein-driven signalling pathways. Using forward chemical genetics methods, cisplatin damage to specific genes has been mapped in human lung cancer cells, a total of 16216 cisplatin-damaged genes (CDGs) with fold-enrichment > 1.5. Surprisingly, bioinformatics analysis demonstrates that cisplatin targets the majority of human protein kinase and phosphatase genes and involved in 300 core signalling pathways (-log p >4). The most associated key signalling pathways are sperm motility and protein kinase A. The highest related disease is cancer, and tissue toxicities related to CDGs are about hepato- and nephro- toxicities. Notably, cisplatin damaged 85% (440) of human protein kinase genes and 81% (110) of human protein phosphatase genes. This suggests that cisplatin acts as a multi-targeting protein-phosphorylation regulator, confirmed by a significant decrease in expression of a series of key protein kinase genes. These results reveal that cisplatin disrupts protein phosphorylation signalling genome-wide. Key points summarising the key messages of your articleA total of 16216 genes damaged by the clinical drug cisplatin in human lung cancer cells were identified using a forward chemical genetics method. Bioinformatics analysis revealed that cisplatin targets 85% of protein kinase and 81% of phosphatase genes. Cisplatin acts as a multi-targeting protein-phosphorylation regulator, disrupting protein phosphorylation signalling genome-wide. The disturbance of protein phosphorylation by cisplatin can be related to anticancer activity and tissue toxicities of the drug. These findings suggests novel strategies for rational design of next-generation anticancer metallodrugs involving specific targeting of protein phosphorylation.

cancer biology↗

bioRxiv2024

Transcriptomic Profile of Lin-Sca1+c-kit (LSK) cells in db/db mice with long-standing diabetes

The Lin-Sca1+c-Kit+ (LSK) fraction comprises multipotent hematopoietic stem cells (HSCs), vital to tissue homeostasis and vascular repair. While HSC homeostasis is impaired in diabetes, it is not known how chronic (>6 months) type 2 diabetes (T2D) alters the HSC transcriptome. Herein, we assessed the transcriptomic signature of HSCs in db/db mice employing mRNA and miRNA sequencing. We uncovered 2076 mRNAs and 35 miRNAs differentially expressed in db/db mice, including two novel miRNAs previously unreported in T2D. Further analysis of these transcripts showed a molecular shift with an increase in the pro-inflammatory cytokines and a decrease in anti-inflammatory cytokine expression. Also, pathway mapping unveiled inflammation and angiogenesis as one of the top pathways. These effects were reflected in bone marrow mobilopathy, retinal microglial inflammation, and neurovascular deficits in db/db mice. In conclusion, our study highlights that chronic diabetes alters HSCs at the transcriptomic level, thus potentially contributing to overall homeostasis and neurovascular deficits of diabetes, such as diabetic retinopathy. HighlightsO_LIBone marrow mobilopathy with long-standing diabetes C_LIO_LISwitch in LSK transcriptomic profile towards inflammation and angiogenesis C_LIO_LIDiscovered 35 miRNAs, including two novel miRNAs, miR-3968 and miR-1971 C_LIO_LILSK dysfunction reflected in inflammation and neurovascular deficits of the retina C_LI

cell biology↗

bioRxiv2023

Benchmarking Reverse Docking through AlphaFold2 Human Proteome

Predicting binding of a small molecule to the human proteome by reverse docking methods, we can predict the target interactions of drug compounds in the human body, as well as further evaluate their potential off-target effects or toxic side effects. In this study, we constructed 11 pipelines to evaluate and benchmark thoroughly the predictive capabilities of these reverse docking pipelines. The pipelines were built using site prediction tools (PointSite and SiteMap) based on the AF2 human proteome, docking programs (Glide and AutoDock Vina), and scoring functions (Glide, Autodock Vina, RTMScore, DeepRMSD, OnionNet-SFCT). The results show that pipeline glide_sfct (PS) exhibited the best target prediction ability and successfully predicted the similar proteins of native targets. This finding provides important clues for understanding the promiscuity between the drug ligand and the whole human proteome. In general, our study has the potential to increase the success rate and reduce the development timeline of drug discovery, thereby saving costs.

bioinformatics↗

bioRxiv2023

Targetable leukemia dependency on noncanonical PI3Kγ signaling

Phosphoinositide 3-kinase gamma (PI3K{gamma}) is implicated as a target to repolarize tumor-associated macrophages and promote anti-tumor immune responses in solid cancers. However, cancer cell-intrinsic roles of PI3K{gamma} are unclear. Here, by integrating unbiased genome-wide CRISPR interference screening with functional analyses across acute leukemias, we define a selective dependency on the PI3K{gamma} complex in a high-risk subset that includes myeloid, lymphoid, and dendritic lineages. This dependency is characterized by innate inflammatory signaling and activation of phosphoinositide 3-kinase regulatory subunit 5 (PIK3R5), which encodes a regulatory subunit of PI3K{gamma} and stabilizes the active enzymatic complex. Mechanistically, we identify p21 (RAC1) activated kinase 1 (PAK1) as a noncanonical substrate of PI3K{gamma} that mediates this cell-intrinsic dependency independently of Akt kinase. PI3K{gamma} inhibition dephosphorylates PAK1, activates a transcriptional network of NF{kappa}B-related tumor suppressor genes, and impairs mitochondrial oxidative phosphorylation. We find that treatment with the selective PI3K{gamma} inhibitor eganelisib is effective in leukemias with activated PIK3R5, either at baseline or by exogenous inflammatory stimulation. Notably, the combination of eganelisib and cytarabine prolongs survival over either agent alone, even in patient-derived leukemia xenografts with low baseline PIK3R5 expression, as residual leukemia cells after cytarabine treatment have elevated G protein-coupled purinergic receptor activity and PAK1 phosphorylation. Taken together, our study reveals a targetable dependency on PI3K{gamma}/PAK1 signaling that is amenable to near-term evaluation in patients with acute leukemia.

cancer biology↗

bioRxiv2023

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types

As the most abundant mRNA modification in mRNA, N6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the function and role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A-seq and RNA-seq samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called "m6A-express", we predicted m6A- regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A for cancer precision medicine for patients with different cancer types.

bioinformatics↗

bioRxiv2023

Modulation of Alzheimer's Disease Brain Pathology in Mice by Gut Bacterial Deletion: The Role of Il-17a and Microglial MyD88

Gut bacteria regulate brain pathology of Alzheimers disease (AD) patients and animal models; however, the underlying mechanism remains unclear. In this study, 3-month-old APP-transgenic female mice with and without knock-out of Il-17a gene, or haploinsufficiency of MyD88 in microglia were treated with antibiotics-supplemented or normal drinking water for 2 months. Antibiotic treatment eradicated gut bacteria, particularly in the phyla Bacteroidetes and Firmicutes, and reduced Il-17a-expressing CD4-positive T lymphocytes. Deletion of gut bacteria inhibited inflammatory activation in the brain and microglia, and reduced cerebral A{beta} levels in APP-transgenic mice, which was abolished by deficiency of Il-17a or haploinsufficiency of MyD88 in microglia. As possible mechanisms regulating A{beta} pathology, deletion of gut bacteria inhibited {beta}-secretase activity and increased the expression of Abcb1 and Lrp1 in the brain or at the blood-brain barrier, which were also reversed by the absence of Il-17a. Interestingly, a crossbreeding experiment between APP-transgenic mice and Il-17a knockout mice further showed that deficiency of Il-17a had already increased Abcb1 and Lrp1 expression at the blood-brain barrier. Thus, deletion of gut bacteria attenuates inflammatory activation and amyloid pathology in APP-transgenic mice via Il-17a and microglial MyD88-involved signalling pathways. Our study contributes to a better understanding of the gut-brain axis in AD pathophysiology.

neuroscience↗

bioRxiv2023

DualNetGO: A Dual Network Model for Protein Function Prediction via Effective Feature Selection

MotivationProtein-protein Interaction (PPI) networks are crucial for automatically annotating protein functions. As multiple PPI networks exist for the same set of proteins that capture properties from different aspects, it is a challenging task to effectively utilize these heterogeneous networks. Recently, several deep learning models have combined PPI networks from all evidence, or concatenated all graph embeddings for protein function prediction. However, the lack of a judicious selection procedure prevents the effective harness of information from different PPI networks, as these networks vary in densities, structures, and noise levels. Consequently, combining protein features indiscriminately could increase the noise level, leading to decreased model performance. ResultsWe develop DualNetGO, a dual network model comprised of a classifier and a selector, to predict protein functions by effectively selecting features from different sources including graph embeddings of PPI networks, protein domain and subcellular location information. Evaluation of DualNetGO on human and mouse datasets in comparison with other network-based models show at least 4.5%, 6.2% and 14.2% improvement on Fmax in BP, MF and CC Gene Ontology categories respectively for human, and 3.3%, 10.6% and 7.7% improvement on Fmax for mouse. We demonstrate the generalization capability of our model by training and testing on the CAFA3 data, and show its versatility by incorporating Esm2 embeddings. We further show that our model is insensitive to the choice of graph embedding method and is time- and memory-saving. These results demonstrate that combining a subset of features including PPI networks and protein attributes selected by our model is more effective in utilizing PPI network information than only using one kind of or concatenating graph embeddings from all kinds of PPI networks. Availability and implementationThe source code of DualNetGO and some of the experiment data are available at: https://github.com/georgedashen/DualNetGO. Contactluo@ust.hk, zchen190@connect.hkust-gz.edu.cn Supplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

Topologically associating domains can arise from stochastic folding of heterogeneous fluidlike chromatin

Topologically associating domains (TADs) are critical for gene regulation. Current views attribute TAD formation to cohesin-mediated extrusion and ignore the role of physical properties of in vivo chromatin. Here, we demonstrate that the two universal properties: chromatin fluidlike behavior and heterogeneity in DNA-packing density along chromatin, can drive TAD formation. We use DNA-accessibility data to parameterize DNA-packing density along chromatin and simulate stochastic folding of the heterogeneous chromatin in nucleus to yield a conformation ensemble. Such an ensemble can be cross-validated by Hi-C and FISH data. Furthermore, the stochastic folding model allows de novo prediction of the establishment and disappearance of key TADs during early T cell differentiation. Together, our work demonstrates that the intrinsic stochastic folding of fluidlike chromatin leads to the prevalence of TAD-like domains in single cells and their cell-to-cell variation, while the heterogeneity in DNA-packing density along chromatin mediates the emergence of TADs at ensemble-averaged level. In briefA study based on polymer simulation reveals that the two universal physical properties of in vivo chromatin fiber: chromatin fluidlike behavior and heterogeneity in DNA-packing density along chromatin play a vital role in TAD formation. HighlightsO_LIIntrinsic stochastic folding of fluidlike chromatin in nuclear space underlies the prevalence of TAD-like domains in single cells and their cell-to-cell variation C_LIO_LIHeterogeneity in DNA-packing density along chromatin causes the emergence of TADs at ensemble-averaged level C_LIO_LIThe disappearance and establishment of key TADs during early T cell differentiation can occur through a stochastic folding process alone, without the need of any cohesin-mediated chromatin extrusion C_LIO_LIThe stochastic folding model applies to diverse cell types and is thus able to de novo predict the dynamics of genome organization over time C_LI

genomics↗

bioRxiv2023

Microglia Regulate Sleep via Calcium-Dependent Modulation of Norepinephrine Transmission

Sleep interacts reciprocally with immune system activity, but its specific relationship with microglia - the resident immune cells in the brain - remains poorly understood. Here we show that microglia can regulate sleep through a mechanism involving Gi-coupled GPCRs, intracellular Ca2+ signaling, and suppression of norepinephrine transmission. Chemogenetic activation of microglia Gi signaling strongly promoted sleep, whereas pharmacological blockade of Gi-coupled P2Y12 receptors decreased sleep. Two-photon imaging showed that P2Y12/Gi activation elevated microglia intracellular Ca2+, and blockade of this Ca2+ elevation largely abolished the Gi-induced sleep increase. Microglia Ca2+ level also increased at natural wake-to-sleep transitions, caused partly by reduced norepinephrine. Furthermore, imaging of norepinephrine activity with its biosensor showed that microglia P2Y12/Gi activation significantly reduced norepinephrine, partly by increasing the adenosine concentration. Thus, microglia can regulate sleep through reciprocal interactions with norepinephrine transmission.

neuroscience↗

bioRxiv2023

COMSE: Analysis of Single-Cell RNA-seq Data Using Community Detection Based Feature Selection

Single-cell RNA sequencing enables studying cells individually, yet high gene dimensions and low cell numbers challenge the analysis. And only a subset of the genes detected are involved in the biological processes underlying cell-type specific functions. We present COMSE, an unsupervised feature selection framework using community detection to capture informative genes from scRNA-seq data. COMSE identified cell substates with high resolution, as demonstrated by its capacity in distinguishing cells at different stages of the cell cycle. Evaluations based on real and simulated scRNA-seq datasets showed COMSE outperformed methods even at high dropout rates in cell clustering. We also demonstrate that by identifying communities of genes associated with batch effects, COMSE differentiates biological differences from batch effects, thereby enabling integrated analysis of scRNA-seq datasets generated with different platforms.

bioinformatics↗

bioRxiv2023

Projectome-defined subtypes and modular intra-hypothalamic subnetworks of peptidergic neurons

The hypothalamus plays a vital role in coordinating essential neuroendocrine, autonomic, and somatomotor responses for survival and reproduction. While previous studies have explored population-level projections of hypothalamic neurons, the specific innervation patterns of individual hypothalamic axons remain unclear. To understand the organization of hypothalamic axon projections, we conducted a comprehensive reconstruction of single-cell projectomes from 7,180 mouse hypothalamic neurons expressing specific neuropeptides. Our analysis identified 31 distinct subtypes based on projectome-defined characteristics, with many exhibiting long-range axon collateral projections to multiple brain regions. Notably, these subtypes selectively targeted specific subdomains within downstream areas, either unilaterally or bilaterally. Furthermore, we observed that individual peptidergic neuronal types encompassed multiple projectome-defined subtypes, explaining their diverse functional roles. Additionally, by examining intra-hypothalamic axon projections, we uncovered six modular subnetworks characterized by enriched intramodular connections and distinct preferences for downstream targets. This modular organization of the intra-hypothalamic network likely contributes to the coordinated organization of hypothalamic outputs. In summary, our comprehensive projectome analysis reveals the organizational principles governing hypothalamic axon projections, providing a framework for understanding the neural circuit mechanisms underlying the diverse and coordinated functions of the hypothalamus.

neuroscience↗

bioRxiv2023

A meta-analysis of immune cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes

AbstractO_ST_ABSBackgroundC_ST_ABSChanges in cell-type composition of complex tissues are associated with a wide range of diseases, environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell-subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect these shifts in tissue composition. MethodsHere we derive a DNA methylation reference matrix for 12 immune cell-types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix and Stouffers method, we perform a meta-analysis encompassing 25,629 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes, including health outcomes. ResultsOur meta-analysis reveals many associations with age, sex, smoking and obesity, many of which we validate with single-cell RNA-sequencing. We discover that T-regulatory and naive T-cell subsets are higher in women compared to men, whilst the reverse is true for monocyte, natural killer, basophil and eosinophil fractions. In a large subset encompassing 5000 individuals we find associations with stress, exercise, sleep and health outcomes, revealing that naive T-cell and B-cell fractions are associated with a reduced risk of all-cause mortality independently of age, sex, race, smoking, obesity and alcohol consumption. We find that decreased natural killer cell counts are associated with smoking, obesity and stress levels, whilst an increased count correlates with exercise, sleep and a reduced risk of all-cause mortality. ConclusionsThis work derives and extensively validates a high resolution DNAm reference matrix for blood, and uses it to generate a comprehensive map of associations between immune cell fractions and common phenotypes, including health outcomes. AvailabilityThe 12 immune cell-type DNAm reference matrices for Illumina 850k and 450k beadarrays alongside tools for cell-type fraction estimation are freely available from our EpiDISH Bioconductor R-package http://www.bioconductor.org/packages/devel/bioc/html/EpiDISH.html

bioinformatics↗

bioRxiv2023

Common roles for serotonin in rats and humans for computations underlying flexible decision-making

Serotonin is critical for adapting behavior flexibly to meet changing environmental demands. Cognitive flexibility is important both for successful attainment of goals, as well as for social interactions, and is frequently impaired in neuropsychiatric disorders, including obsessive-compulsive disorder (OCD). However, a unifying mechanistic framework accounting for the role of serotonin in behavioral flexibility has remained elusive. Here, we demonstrate common effects of manipulating serotonin function across two species (rats and humans) on latent processes supporting choice behavior during probabilistic reversal learning using computational modelling. The findings support a role of serotonin in behavioral flexibility and plasticity, indicated, respectively, by increases or decreases in choice repetition ( stickiness) or reinforcement learning rates depending upon manipulations intended to increase or decrease serotonin function. More specifically, the rate at which expected value increased following reward and decreased following punishment (reward and punishment learning rates) was greatest after sub-chronic administration of the selective serotonin reuptake (SSRI) citalopram (5 mg/kg for 7 days followed by 10 mg/kg twice a day for 5 days) in rats. Conversely, humans given a single dose of an SSRI (20mg escitalopram), which can decrease post-synaptic serotonin signalling, and rats that received the neurotoxin 5,7-dihydroxytryptamine (5,7-DHT), which destroys forebrain serotonergic neurons, exhibited decreased reward learning rates. A basic perseverative tendency ( stickiness), or choice repetition irrespective of the outcome produced, was likewise increased in rats after the 12-day SSRI regimen and decreased after single dose SSRI in humans and 5,7-DHT in rats. These common effects of serotonergic manipulations on rats and humans - identified via computational modelling - suggest an evolutionarily conserved role for serotonin in plasticity and behavioral flexibility and have clinical relevance transdiagnostically for neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

Uncertainty in crop phenology simulations is driven primarily by parameter variability

It has become common to compare crop model results in multi-model simulation experiments. In general, one observes a large variability in such studies, which reduces the confidence one can have in such models. It is important to understand the causes of this variability as a first step toward reducing it. For a given data set, the variability in a multi-model study can arise from uncertainty in structure or in parameter values for a given structure. Previous studies have made assumptions about the origin of parameter uncertainty, and then quantified its contribution, generally finding that parameter uncertainty is less important than structure uncertainty. However, those studies do not take account of the full parameter variability in multi-model studies. Here we propose estimating parameter uncertainty based on open-call multi-model ensembles where the same structure is used by more than one modeling group. The variability in such a case is due to the full variability of parameters among modeling groups. Then structure and parameter contributions can be estimated sing random effects analysis of variance. Based on three multi-model studies for simulating wheat phenology, it is found that the contribution of parameter uncertainty to total uncertainty is, on average, more than twice as large as the uncertainty from structure. A second estimate, based on a comparison of two different calibration approaches for multiple models leads to a very similar result. We conclude that improvement of crop models requires as much attention to parameters as to model structure.

plant biology↗

bioRxiv2023

m6A Demethylase FTO Stabilizes LINK-A to Exert Oncogenic Roles via MCM3-Mediated Cell Cycle Progression and HIF-1α Activation

RNA N6-methyladenosine (m6A) modification, balanced by methyltransferases and demethylases, has recently been shown to play critical roles in multiple cancers. However, the mechanism by which m6A modification regulates long noncoding RNA (lncRNA) stability and function during cancer progression remains unclear. Here, we show that m6A demethylase fat mass and obesity-associated protein (FTO) removes the m6A modification on long intergenic noncoding RNA for kinase activation (LINK-A) and stabilizes it to promote cell proliferation and cytotoxic chemotherapy resistance in esophageal squamous cell carcinoma (ESCC). Mechanistically, LINK-A enhances the interaction between minichromosome maintenance complex component 3 (MCM3) and cyclin-dependent kinase 1 (CDK1) to promote MCM3 phosphorylation by CDK1. MCM3 is a subunit of the hexameric protein complex and its phosphorylation facilitates loading of the MCM complex onto chromatin, which promotes cell cycle progression and subsequent cell proliferation. Meanwhile, LINK-A prevents the interaction of MCM3 and hypoxia-inducible factor 1 (HIF-1), abrogates MCM3-mediated transcriptional repression of HIF-1, and promotes glycolysis and chemoresistance of cancer cells. These results elucidate a mechanism whereby FTO-stabilized LINK-A plays oncogenic roles and present the FTO/LINK-A/MCM3/HIF-1 axis as a promising therapeutic target for ESCC.

cancer biology↗