Biology subjects

Han, X.

Publications and source records attributed to Han, X..

At least 199 records · Page 11Linked to original sources

bioRxiv2022

SurvivalML: an integrative platform for the discovery and exploration of prognostic models in multi-center cancer cohorts

Advances in multi-omics and big-data technologies have led to numerous prognostic signatures aimed at improving current clinicopathological staging systems. Due to the lack of reproducibility and independent confirmation, few signatures have been translated into clinical routine. As high-quality datasets accumulate, identifying robust signatures across multiple independent cohorts becomes possible. Nonetheless, inaccurate data retrieval, different versions of genome annotations, disparate expression distributions, difficult data cleaning, inconsistent clinical information, algorithm selection, and parameter tuning have impeded model development and validation in multi-center datasets. Hence, for the first time, we introduced SurvivalML (https://rookieutopia.com/app_direct/SurvivalML/), a web application for helping develop and validate prognostic models across multi-center datasets. SurvivalML included 37,325 samples (253 eligible datasets) with both transcriptome data and survival information from 21 cancer types, which were renewedly and uniformly re-annotated, normalized, and cleaned. This application provided 10 survival machine-learning algorithms for flexibly training models via tuning essential parameters online and delivered four aspects for model evaluation, including Kaplan-Meier survival analysis, time-dependent ROC, calibration curve, and decision curve analysis. Overall, we believe that SurvivalML can serve as an attractive platform for model discovery from multi-center datasets.

bioinformatics↗

bioRxiv2022

A Robust, Compact and Diverse Population Code for Competing Sounds in Auditory Cortex

Cortical circuits encoding sensory information consist of populations of neurons, yet how information aggregates via pooling individual cells remains poorly understood. Such pooling may be particularly important in noisy settings where single neuron encoding is degraded. One example is the cocktail party problem, with competing sounds from multiple spatial locations. How populations of neurons in auditory cortex (ACx) code competing sounds have not been previously investigated. Here, we apply a novel information theoretic approach to estimate information in populations of neurons in ACx about competing sounds from multiple spatial locations, including both summed population (SP) and labeled line (LL) codes. We find that a small subset of neurons is sufficient to nearly maximize mutual information over different spatial configurations, with the LL code outperforming the SP code, and approaching information levels attained without noise. Moreover, with a LL code, units with diverse spatial responses, including both regular and narrow-spiking units, constitute the best pool. Finally, information in the population increases with spatial separation between target and masker, in correspondence with behavioral results on spatial release from masking in human and animals. Taken together, our results reveal that a compact and diverse population of neurons in ACx provide a robust code for competing sounds from different spatial locations.

neuroscience↗

bioRxiv2022

The autism spectrum disorder risk gene NEXMIF alters hippocampal CA1 cellular and network dynamics

Perturbations in autism spectrum disorder (ASD) risk genes disrupt neural circuit dynamics and ultimately lead to behavioral abnormalities. To understand how ASD-implicated genes influence network computation during behavior, we performed in vivo calcium imaging from hundreds of individual hippocampal CA1 neurons simultaneously in freely locomoting mice with total knockout of NEXMIF. NEXMIF is an ASD risk gene most highly expressed in the hippocampus, and NEXMIF knockout in mice creates a range of behavioral deficits, including impaired hippocampal-dependent memory. We found that NEXMIF knockout does not alter the overall excitability of individual neurons but exaggerates movement-mediated neuronal responses. At the network level, NEXMIF knockout creates over-synchronization of the CA1 circuit, quantified by pairwise correlation and network closeness centrality. These neuronal effects observed upon NEXMIF knockout highlight the network consequences of perturbations in ASD-implicated genes, which have broad implications for cognitive performance and other ASD-related behavioral disruptions.

neuroscience↗

bioRxiv2022

BEST: a web application for comprehensive biomarker exploration on large-scale data in solid tumors

SummaryData mining from RNA-seq or microarray data has become an essential part of cancer biomarker exploration. Certain existing web servers are valuable and broadly utilized, but the meta-analysis of multiple datasets is absent. Most web servers only contain tumor samples from the TCGA database with only one cohort for each cancer type, which also means that the analysis results mainly derived from a single cohort are thin and unstable. Indeed, consistent performance across multiple independent cohorts is the foundation for an excellent biomarker. Moreover, many analytical functions researchers require remain adequately unmet by these tools. Thus, we introduce BEST (Biomarker Exploration for Solid Tumors), a web application for comprehensive biomarker exploration on large-scale data in solid tumors. BEST includes more than 50,000 samples of 27 cancer types. To ensure the comparability of genes between different sequencing technologies and the legibility of clinical traits, we re-annotated transcriptome data based on the GRCh38 patch 13 sequences and unified the nomenclature of clinical traits. BEST delivers fast and customizable functions, including clinical association, survival analysis, enrichment analysis, cell infiltration, immunomodulator, immunotherapy, candidate agents, and genomic alteration. Together, our web server provides multiple cleaned-up independent datasets and diverse analysis functionalities, helping unleash the value of current data resources. It is freely available at https://rookieutopia.com/. The bigger pictureBioinformatics web servers enable researchers without computational programming skills to conduct various bioinformatics analyses. However, most web servers only contain tumor samples from the TCGA database with only one cohort for each cancer type, which also means that the analysis results mainly derived from a single cohort are thin and unstable. Thus, we introduce BEST (Biomarker Exploration for Solid Tumors), a web application for comprehensive biomarker exploration on large-scale data in solid tumors. BEST includes more than 50,000 samples of 27 cancer types that have been uniformly re-annotated based on the GRCh38 patch 13 sequences, which ensures the comparability of genes between different sequencing technologies. BEST also offers prevalent functions including clinical association, survival analysis, enrichment analysis, cell infiltration, immunomodulator, immunotherapy, candidate agents, and genomic alteration. Together, BEST provides a curated database and innovative analytical pipelines to explore cancer biomarkers at high resolution.

genomics↗

bioRxiv2022

Searching across-cohort relatives via encrypted genotype regression

Explicitly sharing individual level data in genomics studies has many merits comparing to sharing summary statistics, including more strict QCs, common statistical analyses, relative identification and improved statistical power in GWAS, but it is hampered by privacy or ethical constraints. In this study, we developed encG-reg, a regression approach that can detect relatives of various degrees based on encrypted genomic data, which is immune of ethical constraints. The encryption properties of encG-reg are based on the random matrix theory by masking the original genotypic matrix without sacrificing precision of individual-level genotype data. We established a connection between the dimension of a random matrix, which masked genotype matrices, and the required precision of a study for encrypted genotype data. encG-reg has false positive and false negative rates equivalent to sharing original individual level data, and is computationally efficient when searching relatives. We split the UK Biobank into their respective centers, and then encrypted the genotype data. We observed that the relatives estimated using encG-reg was equivalently accurate with the estimation by KING, which is a widely used software but requires original genotype data. In a more complex application, we launched a finely devised multi-center collaboration across 5 research institutes in China, covering 9 cohorts of 54,092 GWAS samples. encG-reg again identified true relatives existing across the cohorts with even different ethnic backgrounds and genotypic qualities. Our study clearly demonstrates that encrypted genomic data can be used for data sharing without loss of information or data sharing barrier. Author SummaryEstimating pairwise genetic relatedness within a single cohort is straightforward. However, in practice, related samples are often distributed across different cohorts, making it challenging to estimate inter-cohort relatedness. In this study, we propose a method called encrypted genotype regression (encG-reg), which provides an unbiased estimation of inter-cohort relatedness using encrypted genotypes. The genotype matrix of each cohort is masked by a random matrix, which acts similarly to a private key in a cryptographic scheme. This masking process produces encrypted genotypes, which are a projection of the original genotype matrix. We derive the expectation and particularly the sampling variance for encG-reg, the latter involves eighth-order moments calculation. encG-reg allows us to accurately identify relatedness across cohorts, even for large-scale biobank data. To demonstrate the efficacy of encG-reg, we verified it in a multi-ethnicity UK Biobank dataset comprising 485,158 samples. For this case, we successfully tracked down to the 1st-degree relatedness (such as full sibs and parent-offspring). Furthermore, we used encG-reg in a collaboration involving 9 Chinese cohorts, encompassing a total of 54,092 samples from 5 genomic centers. It is worth noting that if the number of effective markers is sufficient encG-reg has the potential to detect even more distant degrees of relatedness beyond what we demonstrated.

genetics↗

bioRxiv2022

St2cell: Reconstruction of in situ single-cell spatial transcriptomics by integrating high-resolution histological image.

Spatially resolved transcriptomics (SRT) has greatly expanded our understanding of the spatial patterns of gene expression in histological tissue sections. However, most currently available platforms could not provide in situ single-cell spatial transcriptomics, limiting their biological applications. Here, to in silico reconstruct SRT at the single-cell resolution, we propose St2cell which combines deep learning-based frameworks with a novel convex quadratic programming (CQP)-based model. St2cell can thoroughly leverage information in high-resolution (HR) histological images, enabling the accurate segmentation of in situ single cells and identification of their transcriptomics. Applying St2cell on various SRT datasets, we demonstrated the reliability of reconstructed transcriptomics. The single-cell resolution provided by our proposed method greatly promoted the detection of elaborate spatial architectures and further facilitated the integration with single-cell RNA-sequencing data. Moreover, in a breast cancer tissue, St2cell identified general spatial structures and co-occurrence patterns of cell types in the tumor microenvironment. St2cell is also computationally efficient and easily accessible, making it a promising tool for SRT studies.

bioinformatics↗

bioRxiv2022

Functional genomics of cattle through integration of multi-omics data

Functional annotation of the bovine genome was performed by characterizing the spectrum of RNA transcription using a multi-omics approach, combining long- and short-read transcript sequencing and orthogonal data to identify promoters and enhancers and to determine boundaries of open chromatin. A total number of 171,985 unique transcripts (50% protein-coding) representing 35,150 unique genes (64% protein-coding) were identified across tissues. Among them, 159,033 transcripts (92% of the total) were structurally validated by independent datasets such as PacBio Iso-seq, ONT-seq, de novo assembled transcripts from RNA-seq, or Ensembl and NCBI gene sets. In addition, all transcripts were supported by extensive independent data from different technologies such as WTTS-seq, RAMPAGE, ChIP-seq, and ATAC-seq. A large proportion of identified transcripts (69%) were novel, of which 87% were produced by known genes and 13% by novel genes. A median of two 5 untranslated regions was detected per gene, an increase from Ensembl and NCBI annotations (single). Around 50% of protein-coding genes in each tissue were bifunctional and transcribed both coding and noncoding isoforms. Furthermore, we identified 3,744 genes that functioned as non-coding genes in fetal tissues, but as protein coding genes in adult tissues. Our new bovine genome annotation extended more than 11,000 known gene borders compared to Ensembl or NCBI annotations. The resulting bovine transcriptome was integrated with publicly available QTL data to study tissue-tissue interconnection involved in different traits and construct the first bovine trait similarity network. These validated results show significant improvement over current bovine genome annotations.

bioinformatics↗

bioRxiv2022

Differential Inhibitory Responses to Temporal Features Enhance Cortical Coding of Dynamic Stimuli: A Network Model

Cortical circuits feature both excitatory and inhibitory cells that underlie the encoding of dynamic sensory stimuli, e.g., speech, music, odors, and natural scenes. While previous studies have shown that inhibition plays an important role in shaping the neural code, how excitatory and inhibitory cells coordinate to enhance encoding of temporally dynamic stimuli is not fully understood. Recent experimental recordings in mouse auditory cortex have shown that optogenetic suppression of parvalbumin neurons results in a decrease of neural discriminability of dynamic stimuli. Here, we present a multilayer model of a cortical circuit that mechanistically explains these results. The model is based on parvalbumin neurons which respond to both stimulus onsets and offsets, as observed experimentally, and incorporates characteristic shortterm synaptic plasticity profiles of excitatory and parvalbumin neurons. We reveal that by tuning the relative strengths of onset and offset inputs to parvalbumin neurons, the model generates different regimes of coding dominated by rapid firing rate modulations or spike timing. Moreover, the model replicates the experimentally observed reduction in neural discrimination performance during optogenetic suppression of parvalbumin neurons. These results suggest that distinct onset and offset inputs to parvalbumin neurons enhance cortical discriminability of dynamic stimuli by encoding distinct temporal features, enhancing temporal coding, and reducing cortical noise. New & NoteworthyHere we propose a model for the mechanisms that underlie neuron responses in the auditory cortex. This study focuses on single channel tuning of simple interactions between neurons. Using physiologically relevant parameters that underly parvalbumin and excitatory neurons, in the proposed artificial network, we show that we can recreate observed results in live studies.

neuroscience↗

bioRxiv2022

Gene interaction perturbation network deciphers a high-resolution taxonomy in colorectal cancer

Molecular subtypes of colorectal cancer (CRC) are currently identified via the snapshot transcriptional profiles, largely ignoring the dynamic changes of gene expressions. Conversely, biological networks remain relatively stable irrespective of time and condition. Here, we introduce an individual-specific gene interaction perturbation network-based (GIN) approach and identify six GIN subtypes (GINS1-6) with distinguishing features: (i) GINS1 (proliferative, 24%[~]34%), elevated proliferative activity, high tumor purity, immune-desert, PIK3CA mutations, and immunotherapeutic resistance; (ii) GINS2 (stromal-rich, 14%[~]22%), abundant fibroblasts, immune-suppressed, stem-cell-like, SMAD4 mutations, unfavorable prognosis, high potential of recurrence and metastasis, immunotherapeutic resistance, and sensitive to fluorouracil-based chemotherapy; (iii) GINS3 (KRAS-inactivated, 13%[~]20%), high tumor purity, immune-desert, activation of EGFR and ephrin receptors, chromosomal instability (CIN), fewer KRAS mutations, SMOC1 methylation, immunotherapeutic resistance, and sensitive to cetuximab and bevacizumab; (iv) GINS4 (mixed, 10%[~]19%), moderate level of stromal and immune activities, transit-amplifying-like, and TMEM106A methylation; (v) GINS5 (immune-activated, 12%[~]24%), stronger immune activation, plentiful tumor mutation and neoantigen burden, microsatellite instability and high CpG island methylator phenotype, BRAF mutations, favorable prognosis, and sensitive to immunotherapy and PARP inhibitors; (vi) GINS6, (metabolic, 5%[~]8%), accumulated fatty acids, enterocyte-like, and BMP activity. Overall, the novel high-resolution taxonomy derived from an interactome perspective could facilitate more effective management of CRC patients.

genetics↗

bioRxiv2022

Canonical Wnt signaling regulates soft palate development through mediating ciliary homeostasis

Craniofacial morphogenesis requires complex interactions among tissues, signaling pathways, secreted factors, and organelles. The details of these interactions remain elusive. In this study, we analyzed the molecular mechanisms and homeostatic cellular activities governing soft palate development to improve regenerative strategies for cleft palate patients. We have identified canonical Wnt signaling as a key signaling pathway primarily active in cranial neural crest (CNC)-derived mesenchymal cells surrounding soft palatal myogenic cells. Using Osr2-Cre;{beta}-cateninfl/fl mice, we further discovered that Wnt signaling is indispensable for mesenchymal cell proliferation and subsequently myogenesis through mediating ciliogenesis. Specifically, we identified that Wnt signaling directly regulates expression of the ciliary gene Ttll3 through {beta}-catenin/Tcf7l2 complex. Impaired ciliary disassembly leads to differentiation defects of mesenchymal cells and indirectly disrupts myogenesis through decreased expression of Dlk1, a mesenchymal cell-derived pro-myogenesis factor. Moreover, we found that restoring ciliary homeostasis rescues mesenchymal cell proliferation in Osr2-Cre;{beta}-cateninfl/fl samples. This study highlights the role of Wnt signaling in palatogenesis through controlling ciliary homeostasis, which establishes a new mechanism for Wnt-regulated craniofacial morphogenesis.

developmental biology↗

bioRxiv2022

AMPK is elevated in human cachectic muscle and prevents cancer-induced metabolic dysfunction in mice

BackgroundMetabolic dysfunction and cancer cachexia are associated with poor cancer prognosis, yet the molecular mechanisms causing cancer-induced metabolic dysfunction and cachexia remain to be defined. A key link between metabolic- and muscle mass-regulation is adenosine monophosphate-activated protein kinase (AMPK). As AMPK could be a potential treatment, it is important to determine the function for AMPK in cancer-associated metabolic dysfunction and cachexia. Here we determined the function of AMPK in cancer-associated metabolic dysfunction, insulin resistance, and cachexia. MethodsIn vastus lateralis muscle biopsies from pre-cachectic and cachectic patients with Non-Small-Cell Lung Carcinoma (NSCLC), AMPK signaling and expression were examined by immunoblotting. To investigate the role of muscle AMPK, male mice overexpressing a dominant-negative AMPK2 (kinase-dead) specifically in striated muscle (mAMPK-KD) were inoculated with Lewis Lung Carcinoma (LLC) cells. In a subsequent cohort, male LLC-tumor-bearing mice were treated with/without 5-Aminoimidazole-4-carboxamide ribonucleotide (AICAR) to activate AMPK for 13 days. Littermate mice were used as control. Metabolic phenotyping of mice was performed via indirect calorimetry, body composition analyses, glucose- and insulin tolerance tests, tissue-specific 2-deoxy- glucose (2-DG) uptake, and immunoblotting. ResultsIn muscle from patients with NSCLC, we found increased expression of AMPK subunits 1, 2, {beta}2, {gamma}1, and {gamma}3; ranging from +27% to +79% compared to healthy control subjects. AMPK subunit expression correlated with indices of cachexia, including cross sectional area and weight loss. Tumor-bearing mAMPK-KD mice presented increased fat loss as well as glucose and insulin intolerance. LLC in mAMPK-KD mice displayed lower insulin-stimulated 2-DG uptake in skeletal muscle (quadriceps; -35%, soleus; -49%, EDL; -48%) and the heart (-29%) compared to non-tumor-bearing mice. In skeletal muscle, mAMPK-KD abrogated the tumor-induced increase in phosphorylation of TBC1D4thr642. Additionally, protein expression of TBC1D4 (+26%), pyruvate dehydrogenase (PDH, +94%), and PDH-kinases (PDKs, +45% to +100%), and glycogen synthase (+48%) were increased in skeletal muscle of tumor-bearing mice in an AMPK-dependent manner. Lastly, chronic AICAR treatment elevated hexokinase-II protein expression and normalized phosphorylation of p70S6Kthr389 (mTORC1 substrate) and ACCser212 (AMPK substrate) and rescued the cancer-induced insulin intolerance. ConclusionsUpregulated protein expression of AMPK subunits observed in skeletal muscle of (pre)cachectic patients with non-small-cell lung carcinoma. This seemed protective inferred by AMPK-deficient tumor-bearing mice being highly prone to developing metabolic dysfunction, which included the AMPK-dependent regulation of several proteins involved in glucose metabolism. These observations highlight the potential for targeting AMPK to counter cancer-associated metabolic dysfunction and cachexia. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/495096v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@7ff169org.highwire.dtl.DTLVardef@1c249aeorg.highwire.dtl.DTLVardef@736350org.highwire.dtl.DTLVardef@17d2be2_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2022

Persistent Inflammatory Lipotoxicity Impedes Pancreatic β-cell Function in Diet-Induced Obese Mice Despite Correction of Glucotoxicity

Insulin resistance is a hallmark feature of Type 2 Diabetes (T2D), but the progression of the disease is closely linked to a deterioration in {beta}-cell mass and function. While the precise mechanisms of {beta}-cell failure are unclear, chronic hyperglycemia (glucotoxicity) and dyslipidemia (lipotoxicity) are considered contributing factors; however, the relative importance of these insults on {beta}-cell function remains controversial. To examine this, we dissociated glucotoxicity from lipotoxicity using a high-fat diet (HFD)-fed mouse model of T2D and the glucose-lowering SGLT2 inhibitor, canagliflozin (CANA). As expected, HFD-feeding impaired glucose tolerance and isolated islet function. However, despite improvements in glucose tolerance and indices of {beta}-cell insulin secretory function in vivo, CANA failed to restore isolated {beta}-cell function. Shotgun lipidomics analysis of isolated islets revealed that HFD-feeding induced glycerophospholipid remodeling with a persistent increase in arachidonic acid (20:4)-enriched molecular species. Further analysis revealed that lysophosphatidylcholine (LPC) was the predominant lipid class elevated in HFD islets following correction of glucotoxicity with CANA. In follow-up experiments, LPC stimulations acutely and dose-dependently impaired glucose-stimulated insulin secretion (GSIS) in isolated wild-type islets, mechanistically linking this lipid class to {beta}-cell dysfunction. Our findings indicate that persistent inflammatory lipotoxicity impedes {beta}-cell function in diet-induced obese (DIO) rodents even after normalization of hyperglycemia. If replicated in humans, these data suggest that interventions targeting lipotoxicity may be beneficial for the long-term protection of pancreatic {beta}-cell function in T2D.

physiology↗

bioRxiv2022

BEN: a generalizable Brain Extraction Net for multimodal MRI data from rodents, nonhuman primates, and humans

Accurate brain tissue extraction on magnetic resonance imaging (MRI) data is crucial for analyzing brain structure and function. While several conventional tools have been optimized to handle human brain data, there have been no generalizable methods to extract brain tissues for multimodal MRI data from rodents, nonhuman primates, and humans. Therefore, developing a flexible and generalizable method for extracting whole brain tissue across species would allow researchers to analyze and compare experiment results more efficiently. Here, we propose a domain-adaptive and semi-supervised deep neural network, named the Brain Extraction Net (BEN), to extract brain tissues across species, MRI modalities, and MR scanners. We have evaluated BEN on 18 independent datasets, including 783 rodent MRI scans, 246 nonhuman primate MRI scans, and 4,601 human MRI scans, covering five species, four modalities, and six MR scanners with various magnetic field strengths. Compared to conventional toolboxes, the superiority of BEN is illustrated by its robustness, accuracy, and generalizability. Our proposed method not only provides a generalized solution for extracting brain tissue across species but also significantly improves the accuracy of atlas registration, thereby benefiting the downstream processing tasks. As a novel fully automated deep-learning method, BEN is designed as an open-source software to enable high-throughput processing of neuroimaging data across species in preclinical and clinical applications.

neuroscience↗

bioRxiv2022

TGF-β signaling and Creb5 cooperatively regulate Fgf18 to control pharyngeal muscle development

The communication between myogenic cells and their surrounding connective tissues is indispensable for muscle morphogenesis. During late embryonic development in mice, myogenic progenitors migrate to discrete sites to form individual muscles. The detailed mechanism of this process remains unclear. Using levator veli palatini (LVP) development as a model, we systematically investigated how a distinct connective tissue subpopulation, perimysial fibroblasts, communcates with myogenic cells to regulate mouse pharyngeal myogenesis. Using single-cell RNAseq data analysis, we identified that TGF-{beta} signaling is a key regulator for the perimysial fibroblasts. Loss of TGF-{beta} signaling led to defects in perimysial fibroblasts and subsequently muscle formation in Osr2-Cre;Alk5fl/fl mice. In particular, a perimysial fibroblast-specific regulator, Creb5, interacts with TGF-{beta} signaling to enable specific activation of perimysial fibroblast-derived signals such as Fgf18. Moreover, Fgf18 supports pharyngeal muscle development in vivo and its exogenous expression can partially rescue myogenic cell numbers in Osr2-Cre;Alk5fl/fl samples, illustrating that TGF-{beta}-regulated Fgf18 signaling is required for LVP development. Collectively, our findings revealed the mechanism by which TGF-{beta} signaling achieves its specificity in defining the perimysial-to-myogenic signals for pharyngeal myogenesis.

developmental biology↗

bioRxiv2022

De novo lipogenesis fuels adipocyte autophagosome membrane dynamics

Autophagy is a homeostatic degradative process for cell components that enables stress resilience and can determine cellular fate and function. However, lipid sources for the rapid membrane expansions of autophagosomes, the workhorses of autophagy, are poorly understood. Here, we identify de novo lipogenesis (DNL) as a critical source of fatty acids (FA) to fuel autophagosome dynamics in adipocytes. Adipocyte fatty acid synthase (Fasn) deficiency markedly impairs autophagy, evident by autophagosome accumulation, and severely compromises degradation of the autophagic substrate p62. Autophagy dependence on FA produced by Fasn is not fully alleviated by exogenous FA in cultured adipocytes even though lipid droplet size is restored. Imaging studies reveal that Fasn colocalizes with nascent autophagosomes, while loss of Fasn decreases certain membrane phosphoinositides known to be required for autophagosome assembly. Together, our studies highlight a newly appreciated function for adipocyte DNL in autophagosome membrane formation and provide evidence that localized FA synthesis contributes to autophagosome dynamics.

molecular biology↗

bioRxiv2022

Comprehensive machine-learning survival framework develop a consensus model in large scale multi-center cohorts for pancreatic cancer

BackgroundAs the most aggressive tumor, the outcome of pancreatic cancer (PACA) has not improved observably over the last decade. Anatomy-based TNM staging does not exactly identify treatment-sensitive patients, and an ideal biomarker is urgently needed for precision medicine. MethodsA total of 1280 patients from 10 multi-center cohorts were enrolled. 10 machine-learning algorithms were transformed into 76 combinations, which were performed to construct an artificial intelligence-derived prognostic signature (AIDPS). The predictive performance, multi-omic alterations, immune landscape, and clinical significance of AIDPS were further explored. ResultsBased on 10 independent cohorts, we screened 32 consensus prognostic genes via univariate Cox regression. According to the criterion with the largest average C-index in the nine validation sets, we selected the optimal algorithm to construct the AIDPS. After incorporating several vital clinicopathological features and 86 published signatures, AIDPS exhibited robust and dramatically superior predictive capability. Moreover, in other prevalent digestive system tumors, the 9-gene AIDPS could still accurately stratify the prognosis. Of note, our AIDPS had important clinical implications for PACA, and patients with low AIDPS owned a dismal prognosis, relatively high frequency of mutations and copy number alterations, and denser immune cell infiltrates as well as were more sensitive to immunotherapy. Correspondingly, the high AIDPS group possessed dramatically prolonged survival, and panobinostat might be a potential agent for patients with high AIDPS. ConclusionsThe AIDPS could accurately predict the prognosis and immunotherapy efficacy of PACA, which might become an attractive tool to further guide the stratified management and individualized treatment. FundingThis study was supported by the National Natural Science Foundation of China (No. 81870457, 82172944).

bioinformatics↗

bioRxiv2022

Regulation of astrocyte lipid metabolism and ApoE secretion by the microglial oxysterol, 25-hydroxycholesterol

Neuroinflammation is a major hallmark of Alzheimers disease and several other neurological and psychiatric disorders and is often associated with dysregulated cholesterol metabolism. Relative to homeostatic microglia, activated microglia express higher levels of Ch25h, an enzyme that hydroxylates cholesterol to produce 25-hydroxycholesterol (25HC). 25HC is an oxysterol with interesting immune roles stemming from its ability to regulate cholesterol biosynthesis. Since astrocytes synthesize cholesterol in the brain and transport it to other cells via apolipoprotein E (ApoE)-containing lipoproteins, we hypothesized that secreted 25HC from microglia may influence lipid metabolism as well as extracellular ApoE derived from astrocytes. Here we show that astrocytes take up externally added 25HC and respond with altered lipid metabolism. 25HC increased extracellular levels of ApoE lipoprotein particles without altering Apoe mRNA expression, due to elevated Abca1 expression via activation of LXRs and decreased ApoE reuptake due to suppressed Ldlr expression via inhibition of SREBP. Astrocytes metabolized 25HC to limit its effects on lipid metabolism via Cyp7b1, an enzyme responsible for 7-hydroxylation of 25HC. Knockdown of Cyp7b1 expression with siRNA prolonged the effects of 25HC on astrocyte lipid metabolism. 25HC also suppressed Srebf2 expression to reduce cholesterol synthesis in astrocytes but did not affect fatty acid levels or the genes required for fatty acid synthesis. We further show that 25HC led to a doubling of the amount of cholesterol esters and their concomitant storage in lipid droplets. Our results suggest an important role for 25HC in regulating astrocyte lipid metabolism.

cell biology↗

bioRxiv2022

A cocktail containing two synergetic antibodies broadly neutralizes SARS-CoV-2 and its variants including Omicron BA.1 and BA.2

Neutralizing antibodies (NAbs) can prevent and treat infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, continuously emerging variants, such as Omicron, have significantly reduced the potency of most known NAbs. The selection of NAbs with broad neutralizing activities and the identification of conserved critical epitopes are still urgently needed. Here, we identified an extremely potent antibody (55A8) by single B-cell sorting from convalescent SARS-CoV-2-infected patients that recognized the receptor-binding domain (RBD) in the SARS-CoV-2 spike (S) protein. 55A8 could bind to wild-type SARS-CoV-2, Omicron BA.1 and Omicron BA.2 simultaneously with 58G6, a NAb previously identified by our group. Importantly, an antibody cocktail containing 55A8 and 58G6 (2-cocktail) showed synergetic neutralizing activity with a half-maximal inhibitory concentration (IC50) in the picomolar range in vitro and prophylactic efficacy in hamsters challenged with Omicron (BA.1) through intranasal delivery at an extraordinarily low dosage (25 g of each antibody daily) at 3 days post-infection. Structural analysis by cryo-electron microscopy (cryo-EM) revealed that 55A8 is a Class III NAb that recognizes a highly conserved epitope. It could block angiotensin-converting enzyme 2 (ACE2) binding to the RBD in the S protein trimer via steric hindrance. The epitopes in the RBD recognized by 55A8 and 58G6 were found to be different and complementary, which could explain the synergetic mechanism of these two NAbs. Our findings not only provide a potential antibody cocktail for clinical use against infection with current SARS-CoV-2 strains and future variants but also identify critical epitope information for the development of better antiviral agents.

immunology↗