Biology subjects

Tan, T.

Publications and source records attributed to Tan, T..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Mitigation of Fetal Irradiation Injury from Mid-Gestation Total Body Radiation with Mitochondrial-Targeted GS-Nitroxide JP4-039

Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal irradiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal irradiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)- nitroxide radiation mitigator, JP4-039. Pregnant female C57BL/6NTac mice received 3 Gy total body ionizing irradiation (TBI) at mid-gestation embryonic day 13.5 (E13.5). Using novel time- and-motion-resolved 4D in utero magnetic resonance imaging (4D-uMRI), we found TBI caused extensive injury to the fetal brain that included cerebral hemorrhage, loss of cerebral tissue, and hydrocephalus with excessive accumulation of cerebrospinal fluid (CSF). Histopathology of the fetal mouse brain showed broken cerebral vessels and elevated apoptosis. Further use of novel 4D Oxy-wavelet MRI capable of probing in vivo mitochondrial function in intact brain revealed significant reduction of mitochondrial function in the fetal brain after 3Gy TBI. This was validated by ex vivo Oroboros mitochondrial respirometry. Maternal administration JP4-039 one day after TBI (E14.5), which can pass through the placental barrier, significantly reduced fetal brain radiation injury and improved fetal brain mitochondrial respiration. This also preserved cerebral brain tissue integrity and reduced cerebral hemorrhage and cell death. As JP4-039 administration did not change litter sizes or fetus viability, together these findings indicate JP4-039 can be deployed as a safe and effective mitigator of fetal radiation injury from mid-gestational in utero ionizing radiation exposure. One Sentence SummaryMitochondrial-targeted gramicidin S (GS)-nitroxide JP4-039 is safe and effective radiation mitigator for mid-gestational fetal irradiation injury.

developmental biology↗

bioRxiv2024

Deep learning-based Spatial Feature Extraction for Prognostic Prediction of Hepatocellular Carcinoma from Pathological Images

The spatial structures of various cell types in tumor tissues have been demonstrated to be able to provide useful information for the evaluation of the disease progression as well as the responsiveness to targeted therapies. Therefore, powered by machine-learning, several image segmentation methods have been developed to identify tumor-cells, stromal, lymphocytes, etc., in hematoxylin and eosin (H&E) stained pathological images. However, the quantitative and systematic characterization of the spatial structures of various cell types is still challenging. In this work, we first developed a robust procedure based on deep learning to precisely recognize cancer cells, stromal and lymphocytes in H&E-stained pathological images of hepatocellular carcinoma (HCC). In order to quantitatively characterize the composition and spatial arrangement of the tumor microenvironment, we then systematically constructed 109 spatial features based on locations of the 3 major types of cells in the H&E images. Interestingly, we discovered that the absolute values of several spatial features are significantly associated with patient overall survival in two independent patient cohorts, such as the cellular diversity around stromal cells (StrDiv), the average distance between stromal cells (StrDis), the coefficient of variation of the tumor-cell polygon area in the Voronoi diagram (TumCV), etc., based on univariate analysis. In addition, multivariate Cox regress analyses further demonstrated that StrDiv and StrDis are independent survival prognostic factors for HCC patient from The Cancer Genome Atlas Program (TCGA). Furthermore, we demonstrated that a combination analysis with cell spatial features, i.e. StrDiv or TumCV, and another important clinical feature, i.e. microvascular invasion (MVI), can further improve the efficacy of prognostic stratification for patients from the Beijing Hospital cohorts. In summary, the spatial features of tumor microenvironment enabled by the digital image analysis pipeline developed in this work can be effective in patient stratification, which holds the promise for its usage in predicting the therapeutic response of patients in the future.

bioinformatics↗

bioRxiv2024

Non-physiologic interaction of MG53 with insulin receptor and lack of evidence for MG53's role in controlling insulin-stimulated Akt phosphorylation in muscle, heart and liver tissues.

RationaleMG53s known function in facilitating tissue repair and anti-inflammation has broad applications to regenerative medicine. There is controversy regarding MG53s role in the development of type 2 diabetes mellitus (T2DM). ObjectiveThis study aims to address this controversy - whether MG53s myokine function contributes to inhibition of insulin signaling in muscle, heart, and liver tissues. Study DesignWe determined the binding affinity of the recombinant human MG53 (rhMG53) to the insulin receptor extracellular domain (IR-ECD) and found low affinity of interaction with Kd (>480 nM). Using cultured C2C12 myotubes and HepG2 cells, we found no effect of rhMG53 on insulin-stimulated Akt phosphorylation (p-Akt). We performed in vivo assay with C57BL/6J mice subjected to insulin stimulation (1 U/kg, intraperitoneal injection) and observed no effect of rhMG53 on insulin-stimulated p-Akt in muscle, heart and liver tissues. ConclusionOverall, our data suggest that rhMG53 can bind to the IR-ECD, however has a low likelihood of a physiologic role, as the Kd for binding is [~]10,000 higher than the physiologic level of MG53 present in the serum of rodents and humans ([~]10 pM). Our findings question the notion proposed by Xiao and colleagues - whether targeting circulating MG53 opens a new therapeutic avenue for T2DM and its complications.

physiology↗

bioRxiv2024

Immunogenicity of autologous and allogeneic human primary cholangiocyte organoids

Primary human cells cultured in 3D organoid format have great promise as potential regenerative cellular therapies, but their immunogenicity has not yet been fully characterized. In this study, we use in vitro co-cultures and in vivo humanized mouse experimental models to examine the human immune response to autologous and allogeneic primary cholangiocyte organoids (PCOs). Our data demonstrate that PCOs upregulate the expression of HLA-I and HLA-II in inflammatory conditions. The immune response to allogeneic PCOs is driven by both HLA-I and HLA-II and is substantially ameliorated by donor-recipient HLA matching. Autologous PCOs induce a low-level immune infiltration into the graft site, while allogeneic cells display evolving stages of immune rejection in vivo. Our findings have important implications for the design and clinical translation of autologous and allogeneic organoid cellular therapies. ONE-SENTENCE SUMMARYThe immune response to human primary cholangiocyte organoids is ameliorated by donor-recipient HLA matching.

immunology↗

bioRxiv2023

Pathogenic mechanisms underlying adverse neurodevelopmental outcome in congenital heart disease

Poor neurodevelopment is often observed with congenital heart disease (CHD), especially with mutations in chromatin modifiers. Here analysis of mice with hypoplastic left heart syndrome (HLHS) arising from mutations in Sin3A associated chromatin modifier Sap130, and adhesion protein Pcdha9, revealed neurodevelopmental and neurobehavioral deficits reminiscent of those in HLHS patients. Microcephaly was associated with impaired cortical neurogenesis, mitotic block, and increased apoptosis. Transcriptional profiling indicated dysregulated neurogenesis by REST, altered CREB signaling regulating memory and synaptic plasticity, and impaired neurovascular coupling modulating cerebral blood flow. Many neurodevelopmental/neurobehavioral disease pathways were recovered, including autism and cognitive impairment. These same pathways emerged from genome-wide DNA methylation and Sap130 chromatin immunoprecipitation sequencing analyses, suggesting epigenetic perturbation. Mice with Pcdha9 mutation or forebrain-specific Sap130 deletion without CHD showed learning/memory deficits and autism-like behavior. These novel findings provide mechanistic insights indicating the adverse neurodevelopment in HLHS may involve cell autonomous/nonautonomous defects and epigenetic dysregulation and suggest new avenues for therapy.

developmental biology↗

bioRxiv2023

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation

ObjectiveRecent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing self-supervised learning (SSL) techniques to leverage large IMU datasets to pre-train deep learning models, which can improve the accuracy and data efficiency of IMU-based GRF estimation. MethodsWe performed SSL by masking a random portion of the input IMU data and training a transformer model to reconstruct the masked portion. We systematically compared a series of masking ratios across three pre-training datasets that included real IMU data, synthetic IMU data, or a combination of the two. Finally, we built models that used pre-training and labeled data to estimate GRF during three prediction tasks: overground walking, treadmill walking, and drop landing. ResultsWhen using the same amount of labeled data, SSL pre-training significantly improved the accuracy of 3-axis GRF estimation during walking compared to baseline models trained by conventional supervised learning. Fine-tuning SSL model with 1-10% of walking data yielded comparable accuracy to training baseline model with 100% of walking data. The optimal masking ratio for SSL is 6.25-12.5%. ConclusionSSL leveraged large real and synthetic IMU datasets to increase the accuracy and data efficiency of deep-learning-based GRF estimation, reducing the need for labeled data. SignificanceThis work, with its open-source code and models, may unlock broader use cases of IMU-driven kinetic assessment by mitigating the scarcity of GRF measurements in practical applications.

bioengineering↗

bioRxiv2023

Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations

SummaryAdmixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic study of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. Availability and implementationAdmix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow.

genetics↗

bioRxiv2023

Quantification of circulating tumor DNA using deep learning

Quantification of circulating tumor DNA (ctDNA) levels in blood enables non-invasive surveillance of cancer progression. Fragle is an ultra-fast deep learning-based method for ctDNA quantification directly from cell-free DNA fragment length profiles. We developed Fragle using low-pass whole genome sequence (lpWGS) data from multiple cancer types and healthy control cohorts, demonstrating high accuracy, and improved lower limit of detection in independent cohorts as compared to existing tumor-naive methods. Uniquely, Fragle is also compatible with targeted sequencing data, exhibiting high accuracy across both research and commercial targeted gene panels. We used this method to study longitudinal plasma samples from colorectal cancer patients, identifying strong concordance of ctDNA dynamics and treatment response. Furthermore, prediction of minimal residual disease in resected lung cancer patients demonstrated significant risk stratification beyond a tumor-naive gene panel. Overall, Fragle is a versatile, fast, and accurate method for ctDNA quantification with potential for broad clinical utility.

bioinformatics↗

bioRxiv2023

Dissecting embryonic and extra-embryonic lineage crosstalk with stem cell co-culture

Faithful embryogenesis requires precise coordination between embryonic and extraembryonic tissues. Although stem cells from embryonic and extraembryonic origins have been generated for several mammalian species(Bogliotti et al., 2018; Choi et al., 2019; Cui et al., 2019; Evans and Kaufman, 1981; Kunath et al., 2005; Li et al., 2008; Martin, 1981; Okae et al., 2018; Tanaka et al., 1998; Thomson et al., 1998; Vandevoort et al., 2007; Vilarino et al., 2020; Yu et al., 2021b; Zhong et al., 2018), they are grown in different culture conditions with diverse media composition, which makes it difficult to study cross-lineage communication. Here, by using the same culture condition that activates FGF, TGF-{beta} and WNT signaling pathways, we derived stable embryonic stem cells (ESCs), extraembryonic endoderm stem cells (XENs) and trophoblast stem cells (TSCs) from all three founding tissues of mouse and cynomolgus monkey blastocysts. This allowed us to establish embryonic and extraembryonic stem cell co-cultures to dissect lineage crosstalk during early mammalian development. Co-cultures of ESCs and XENs uncovered a conserved and previously unrecognized growth inhibition of pluripotent cells by extraembryonic endoderm cells, which is in part mediated through extracellular matrix signaling. Our study unveils a more universal state of stem cell self-renewal stabilized by activation, as opposed to inhibition, of developmental signaling pathways. The embryonic and extraembryonic stem cell co-culture strategy developed here will open new avenues for creating more faithful embryo models and developing more developmentally relevant differentiation protocols.

developmental biology↗

bioRxiv2023

CRB3 navigates Rab11 trafficking vesicles to promote γTuRC assembly during ciliogenesis

The primary cilium plays important roles in regulating cell differentiation, signal transduction, and tissue organization. Dysfunction of the primary cilium can lead to ciliopathies and cancer. The formation and organization of the primary cilium are highly associated with cell polarity proteins, such as the apical polarity protein CRB3. However, the molecular mechanisms by which CRB3 regulates ciliogenesis and the location of CRB3 remain unknown. Here, we show that CRB3, as a navigator, regulates vesicle trafficking in {gamma}-TuRC assembly during ciliogenesis and cilium-related Hh and Wnt signaling pathways in tumorigenesis. Crb3 knockout mice display severe defects of the primary cilium in the mammary ductal lumen and renal tubule, while mammary epithelial-specific Crb3 knockout mice exhibit the promotion of ductal epithelial hyperplasia and tumorigenesis. CRB3 is essential for lumen formation and ciliary assembly in the mammary epithelium. We demonstrate that CRB3 localizes to the basal body and that CRB3 trafficking is mediated by Rab11-positive endosomes. Significantly, CRB3 interacts with Rab11 to navigate GCP6/Rab11 trafficking vesicles to CEP290, resulting in intact {gamma}-TuRC assembly. In addition, CRB3-depleted cells are unresponsive to the activation of the Hh signaling pathway, while CRB3 regulates the Wnt signaling pathway. Therefore, our studies reveal the molecular mechanisms by which CRB3 recognizes Rab11-positive endosomes to facilitate ciliogenesis, and regulates cilium-related signaling pathways in tumorigenesis.

cell biology↗

bioRxiv2022

Polygenic prediction across populations is influenced by ancestry, genetic architecture, and methodology

Polygenic risk scores (PRS) developed from multi-ancestry genome-wide association studies (GWAS), PRSmulti, hold promise for improving PRS accuracy and generalizability across populations. To establish best practices for leveraging the increasing diversity of genomic studies, we investigated how various factors affect the performance of PRSmulti compared to PRS constructed from single-ancestry GWAS (PRSsingle). Through extensive simulations and empirical analyses, we showed that PRSmulti overall outperformed PRSsingle in understudied populations, except when the understudied population represented a small proportion of the multi-ancestry GWAS. Notably, for traits with large-effect ancestry-enriched variants, such as mean corpuscular volume, using substantially fewer samples from Biobank Japan achieved comparable accuracies to a much larger European cohort. Furthermore, integrating PRS based on local ancestry-informed GWAS and large-scale European-based PRS improved predictive performance in understudied African populations, especially for less polygenic traits with large ancestry-enriched variants. Our work highlights the importance of diversifying genomic studies to achieve equitable PRS performance across ancestral populations and provides guidance for developing PRS from multiple studies.

genomics↗

bioRxiv2022

COVIDpro: Database for mining protein dysregulation in patients with COVID-19

BackgroundThe ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has limited treatment options partially due to our incomplete understanding of the molecular dysregulations of the COVID-19 patients. We aimed to generate a repository and data analysis tools to examine the modulated proteins underlying COVID-19 patients for the discovery of potential therapeutic targets and diagnostic biomarkers. MethodsWe built a web server containing proteomic expression data from COVID-19 patients with a toolset for user-friendly data analysis and visualization. The web resource covers expert-curated proteomic data from COVID-19 patients published before May 2022. The data were collected from ProteomeXchange and from select publications via PubMed searches and aggregated into a comprehensive dataset. Protein expression by disease subgroups across projects was compared by examining differentially expressed proteins. We also visualize differentially expressed pathways and proteins. Moreover, circulating proteins that differentiated severe cases were nominated as predictive biomarkers. FindingsWe built and maintain a web server COVIDpro (https://www.guomics.com/covidPro/) containing proteomics data generated by 41 original studies from 32 hospitals worldwide, with data from 3077 patients covering 19 types of clinical specimens, the majority from plasma and sera. 53 protein expression matrices were collected, for a total of 5434 samples and 14,403 unique proteins. Our analyses showed that the lipopolysaccharide-binding protein, as identified in the majority of the studies, was highly expressed in the blood samples of patients with severe disease. A panel of significantly dysregulated proteins was identified to separate patients with severe disease from non-severe disease. Classification of severe disease based on these proteomic signatures on five test sets reached a mean AUC of 0.87 and ACC of 0.80. InterpretationCOVIDpro is an online database with an integrated analysis toolkit. It is a unique and valuable resource for testing hypotheses and identifying proteins or pathways that could be targeted by new treatments of COVID-19 patients. FundingNational Key R&D Program of China: Key PDPM technologies (2021YFA1301602, 2021YFA1301601, 2021YFA1301603), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Hangzhou Agriculture and Society Advancement Program (20190101A04), National Natural Science Foundation of China (81972492) and National Science Fund for Young Scholars (21904107), National Resource for Network Biology (NRNB) from the National Institute of General Medical Sciences (NIGMS-P41 GM103504) Research in contextO_ST_ABSEvidence before this studyC_ST_ABSAlthough an increasing number of therapies against COVID-19 are being developed, they are still insufficient, especially with the rise of new variants of concern. This is partially due to our incomplete understanding of the diseases mechanisms. As data have been collected worldwide, several questions are now worth addressing via meta-analyses. Most COVID-19 drugs function by targeting or affecting proteins. Effectiveness and resistance to therapeutics can be effectively assessed via protein measurements. Empowered by mass spectrometry-based proteomics, protein expression has been characterized in a variety of patient specimens, including body fluids (e.g., serum, plasma, urea) and tissue (i.e., formalin-fixed and paraffin-embedded (FFPE)). We expert-curated proteomic expression data from COVID-19 patients published before May 2022, from the largest proteomic data repository ProteomeXhange as well as from literature search engines. Using this resource, a COVID-19 proteome meta-analysis could provide useful insights into the mechanisms of the disease and identify new potential drug targets. Added value of this studyWe integrated many published datasets from patients with COVID-19 from 11 nations, with over 3000 patients and more than 5434 proteome measurements. We collected these datasets in an online database, and generated a toolbox to easily explore, analyze, and visualize the data. Next, we used the database and its associated toolbox to identify new proteins of diagnostic and therapeutic value for COVID-19 treatment. In particular, we identified a set of significantly dysregulated proteins for distinguishing severe from non-severe patients using serum samples. Implications of all the available evidenceCOVIDpro will support the navigation and analysis of patterns of dysregulated proteins in various COVID-19 clinical specimens for identification and verification of protein biomarkers and potential therapeutic targets.

systems biology↗

bioRxiv2022

Large scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal crosstalk

Recent advances in human blastoids generated from naive pluripotent stem cells have opened a new avenue for modelling early human development and implantation. Despite the success, however, existing protocols have several limitations, e.g., the use of custom-built microwell arrays impedes wide adoption by the research community, and mass production of human blastoids is hampered by low-output or low-efficiency methods. To address these issues, here we developed an optimized protocol based on commercially available microwell plates, which enabled efficient generation of high-fidelity human blastoids at a large scale. Leveraging on the improved protocol, we identified MAPK. PI3K/AKT and mTOR signaling pathways were activated in both blastoids and blastocyst, and discovered endometrial stromal effects in promoting trophoblast cell survival, proliferation and syncytialization during extended co-culture with blastoids. Our optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, tractable, and ethical model for human blastocysts.

developmental biology↗

bioRxiv2022

Automated identification of aneuploid cells within the inner cell mass of an embryo using a numerical extraction of morphological signatures

STUDY QUESTIONCan artificial intelligence distinguish between euploid and aneuploid cells within the inner cell mass of mouse embryos using brightfield images? SUMMARY ANSWERA deep morphological signature (DMS) generated by deep learning followed by swarm intelligence and discriminative analysis can identify the ploidy state of inner cell mass (ICM) in the mouse blastocyst-stage embryo. WHAT IS KNOWN ALREADYThe presence of aneuploidy - a deviation from the expected number of chromosomes - is predicted to cause early pregnancy loss or congenital disorders. To date, available techniques to detect embryo aneuploidy in IVF clinics involve an invasive biopsy of trophectoderm cells or a non-invasive analysis of cell-free DNA from spent media. These approaches, however, are not specific to the ICM and will consequently not always give an accurate indication of the presence of aneuploid cells with known ploidy therein. STUDY DESIGN, SIZE, DURATIONThe effect of aneuploidy on the morphology of ICMs from mouse embryos was studied using images taken using a standard brightfield microscope. Aneuploidy was induced using the spindle assembly checkpoint inhibitor, reversine (n = 13 euploid and n = 9 aneuploid). The morphology of primary human fibroblast cells with known ploidy was also assessed. PARTICIPANTS/MATERIALS, SETTING, METHODSTwo models were applied to investigate whether the morphological details captured by brightfield microscopy could be used to identify aneuploidy. First, primary human fibroblasts with known karyotypes (two euploid and trisomy: 21, 18, 13, 15, 22, XXX and XXY) were imaged. An advanced methodology of deep learning followed by swarm intelligence and discriminative analysis was used to train a deep morphological signature (DMS). Testing of the DMS demonstrated that there are common cellular features across different forms of aneuploidy detectable by this approach. Second, the same approach was applied to ICM images from control and reversine treated embryos. Karyotype of ICMs was confirmed by mechanical dissection and whole genome sequencing. MAIN RESULTS AND THE ROLE OF CHANCEThe DMS for discriminating euploid and aneuploid fibroblasts had an area under the receiver operator characteristic curve (AUC-ROC) of 0.89. The presence of aneuploidy also had a strong impact on ICM morphology (AUC-ROC = 0.98). Aneuploid fibroblasts treated with reversine and projected onto the DMS space mapped with untreated aneuploid fibroblasts, supported that the DMS is sensitive to aneuploidy in the ICMs, and not a non-specific effect of the reversine treatment. Consistent findings in different contexts suggests that the role of chance low. LARGE SCALE DATAN/A LIMITATIONS, REASON FOR CAUTIONConfirmation of this approach in humans is necessary for translation. WIDER IMPLICATIONS OF THE FINDINGSThe application of deep learning followed by swarm intelligence and discriminative analysis for the development of a DMS to detect euploidy and aneuploidy in the ICM has high potential for clinical implementation as the only equipment it requires is a brightfield microscope, which are already present in any embryology laboratory. This makes it a low cost, a non-invasive approach compared to other types of pre-implantation genetic testing for aneuploidy. This study gives proof of concept for a novel strategy with the potential to enhance the treatment efficacy and prognosis capability for infertility patients. STUDY FUNDING/COMPETING INTEREST(S)K.R.D. is supported by a Mid-Career Fellowship from the Hospital Research Foundation (C-MCF-58-2019). This study was funded by the Australian Research Council Centre of Excellence for Nanoscale Biophotonics (CE140100003), the National Health and Medical Research Council (APP2003786) and an ARC Discovery Project (DP210102960). The authors declare that there is no conflict of interest.

bioinformatics↗

bioRxiv2022

Striatal Mu-Opioid Receptor Activation Triggers Direct-Pathway GABAergic Plasticity to Induce Negative Affect

Withdrawal from chronic opioid use often causes hypodopaminergic states and negative affect, which drives relapse. Direct-pathway medium spiny neurons (dMSNs) in the striatal patch compartment contain high levels of {micro}-opioid receptors (MORs). It remains unclear how chronic opioid exposure affects these MOR-expressing dMSNs and their striatopallidal and striatonigral outputs to induce negative emotions and relapse. Here, we report that MOR activation acutely suppressed GABAergic striatopallidal transmission in habenula-projecting globus pallidus neurons. Notably, repeated administrations of a MOR agonist (morphine or fentanyl) potentiated this GABAergic transmission. We also discovered that intravenous self-administration of fentanyl enhanced GABAergic striatonigral transmission and reduced the firing activity of midbrain dopaminergic neurons. Importantly, fentanyl withdrawal caused depression-like behaviors and promoted the reinstatement of fentanyl-seeking behaviors. These data suggest that chronic opioid use triggers GABAergic striatopallidal and striatonigral plasticity to induce a hypodopaminergic state, promoting negative emotions and leading to relapse. HighlightsO_LIRepeated administration of morphine potentiates IPSCdMSN{lozenge}GPh neurotransmission. C_LIO_LIRepeated administration of fentanyl potentiates IPSCdMSN{lozenge}SNc neurotransmission. C_LIO_LIFentanyl withdrawal induces negative emotional states, which drive relapse. C_LI

neuroscience↗

bioRxiv2021

Microtubule Lattice Spacing Governs Cohesive Envelope Formation of Tau Family Proteins

Tau is an intrinsically-disordered microtubule-associated protein (MAP) implicated in neurodegenerative disease. On microtubules, tau molecules segregate into two kinetically distinct phases, consisting of either independently diffusing molecules or interacting molecules that form cohesive "envelopes" around microtubules. Envelopes differentially regulate lattice accessibility for other MAPs, but the mechanism of envelope formation remains unclear. Here, we find that tau envelopes form cooperatively, locally altering the spacing of tubulin dimers within the microtubule lattice. Envelope formation compacted the underlying lattice, whereas lattice extension induced tau-envelope disassembly. Investigating other members of the tau-MAP family, we find MAP2 similarly forms envelopes governed by lattice-spacing, whereas MAP4 cannot. Envelopes differentially biased motor protein movement, suggesting that tau family members could spatially divide the microtubule surface into functionally distinct segments. We conclude that the interdependent allostery between lattice-spacing and cooperative envelope formation provides the molecular basis for spatial regulation of microtubule-based processes by tau and MAP2.

biophysics↗

bioRxiv2021

Monoclonal antibodies targeting surface exposed epitopes of Candida albicans cell wall proteins confer in vivo protection in an infection model

MAb based immunotherapies targeting systemic and deep-seated fungal infections are still in their early stages of development with currently no licensed antifungal mAbs available for patients at risk. The cell wall glycoproteins of Candida albicans are of particular interest as potential targets for therapeutic antibody generation due to their extracellular location and key involvement in fungal pathogenesis. Here we describe the generation of recombinant human antibodies specifically targeting two key cell wall proteins (CWPs) in C. albicans - Utr2 and Pga31. These antibodies were isolated from a phage display antibody library using peptide antigens representing the surface exposed regions of CWPs expressed at elevated levels during in vivo infection. Reformatted human-mouse chimeric mAbs preferentially recognised C. albicans hyphal forms compared to yeast cells and an increased binding was observed when the cells were grown in the presence of the antifungal agent caspofungin. In J774.1 macrophage interaction assays, mAb pre-treatment resulted in a faster engulfment of C. albicans cells suggesting a role of the CWP antibodies as opsonising agents during phagocyte recruitment. Finally, in a series of clinically predictive, mouse models of systemic candidiasis, our lead mAb achieved an improved survival (83%) and several log reduction of fungal burden in the kidneys, similar to levels achieved for the fungicidal drug caspofungin, and superior to any anti-Candida mAb therapeutic efficacy reported to date.

microbiology↗

bioRxiv2021

rRNA Biogenesis Regulates Mouse 2C-like State by 3D Structure Reorganization of Peri-Nucleolar Heterochromatin

Nucleolus is the organelle for ribosome biogenesis and for sensing various types of stress. Its role in regulating stem cell fate is unclear. Here, we present multiple lines of evidence that nucleolar stress induced by interfering rRNA biogenesis can drive 2-cell stage embryo-like (2C-like) transcriptional program and induce an expanded 2C-like cell population in mouse embryonic stem (mES) cells. Mechanistically, the nucleolar integrity mediated by rRNA biogenesis maintains the normal liquid-liquid phase separation (LLPS) of nucleolus and the formation of peri-nucleolar heterochromatin (PNH). Upon rRNA biogenesis defect, the natural LLPS of nucleolus is disrupted, causing dissociation of NCL/TRIM28 complex from PNH and changes of epigenetic states and reorganization of the 3D structure of PNH, which leads to Dux, a 2C program transcription factor gene, to be released from the PNH region and activation of 2C-like program. Correspondingly, embryos with rRNA biogenesis defect are incompatible to develop from 2-cell (2C) to 4-cell embryos, with delayed repression of 2C/ERV genes and a transcriptome skewed toward earlier cleavage embryo signatures. Our results highlight that rRNA-mediated nucleolar integrity and 3D structure reshaping of PNH compartment regulates the fate transition of mES cells to 2C-like cells, and that rRNA biogenesis is a critical regulator during the 2-cell-to-4-cell transition of murine pre-implantation embryo development.

cell biology↗