Biology subjects

Chen, X.

Publications and source records attributed to Chen, X..

At least 775 records · Page 43Linked to original sources

bioRxiv2023

Pharmacologic inhibition of BAF chromatin remodeling complexes as a therapeutic approach to transcription factor-dependent cancers

The BRG/Brahma-associated factors (BAF or mSWI/SNF) family of chromatin remodeling complexes are critical regulators of gene expression and are major determinants of cancer and other diseases. Two paralog ATPases, SMARCA4 and SMARCA2 (BRG1 and BRM, respectively), provide the enzymatic activity required for chromatin remodeling. Here, we discover and characterize a novel series of compounds that potently and selectively inhibit SMARCA4/SMARCA2. Mutational and biochemical studies demonstrate that these inhibitors act through a unique mode of inhibition, distinct from reported SMARCA4/SMARCA2 inhibitors. Across a range of cancer cell lines, SMARCA4/SMARCA2 inhibition resulted in lineage-specific changes in chromatin accessibility at binding sites for key transcription factors (TFs). In uveal melanoma (UM), BAF inhibition resulted in loss of enhancer occupancy of SOX10 and MITF, two essential TFs, leading to down-regulation of the melanocytic gene expression program. In a mouse xenograft model of UM, SMARCA4/SMARCA2 inhibition was well tolerated and resulted in dose-dependent tumor regression correlating with pharmacodynamic modulation of BAF-target gene expression. These data provide the foundation for first-in-human studies of BAF ATPase inhibition as a novel therapeutic to treat TF-dependent cancers.

cancer biology↗

bioRxiv2023

GraffiTE: a Unified Framework to Analyze Transposable Element Insertion Polymorphisms using Genome-graphs

Transposable Elements are ubiquitous mobile DNA sequences evolving among their hosts genomes, generating insertion polymorphisms that contribute to genomic diversity. We present GraffiTE, a flexible pipeline to analyze polymorphic mobile elements. By integrating state-of-the-art structural variant detection algorithms and graph genomes, GraffiTE identifies polymorphic mobile elements from genomic assemblies and/or long-read sequencing data, and genotypes these variants using short or long read sets. Benchmarking on simulated and real datasets reports high precision and recall rates. GraffiTE is designed to allow non-expert users to perform comprehensive analyses, including in models with limited transposable element knowledge and is compatible with various sequencing technologies. GraffiTE is freely available at https://github.com/cgroza/GraffiTE. Here, we demonstrate the versatility of GraffiTE by analyzing human, Drosophila melanogaster, maize, and Cannabis sativa pangenome data. These analyses reveal the landscapes of polymorphic mobile elements and their frequency variations across individuals, strains, and cultivars.

bioinformatics↗

bioRxiv2023

Cell2Sentence: Teaching Large Language Models the Language of Biology

We introduce Cell2Sentence (C2S), a novel method to directly adapt large language models to a biological context, specifically single-cell transcriptomics. By transforming gene expression data into "cell sentences," C2S bridges the gap between natural language processing and biology. We demonstrate cell sentences enable the fine-tuning of language models for diverse tasks in biology, including cell generation, complex cell-type annotation, and direct data-driven text generation. Our experiments reveal that GPT-2, when fine-tuned with C2S, can generate biologically valid cells based on cell type inputs, and accurately predict cell types from cell sentences. This illustrates that language models, through C2S fine-tuning, can acquire a significant understanding of single-cell biology while maintaining robust text generation capabilities. C2S offers a flexible, accessible framework to integrate natural language processing with transcriptomics, utilizing existing models and libraries for a wide range of biological applications.

bioinformatics↗

bioRxiv2023

An explainable language model for antibody specificity prediction using curated influenza hemagglutinin antibodies

Despite decades of antibody research, it remains challenging to predict the specificity of an antibody solely based on its sequence. Two major obstacles are the lack of appropriate models and inaccessibility of datasets for model training. In this study, we curated a dataset of >5,000 influenza hemagglutinin (HA) antibodies by mining research publications and patents, which revealed many distinct sequence features between antibodies to HA head and stem domains. We then leveraged this dataset to develop a lightweight memory B cell language model (mBLM) for sequence-based antibody specificity prediction. Model explainability analysis showed that mBLM captured key sequence motifs of HA stem antibodies. Additionally, by applying mBLM to HA antibodies with unknown epitopes, we discovered and experimentally validated many HA stem antibodies. Overall, this study not only advances our molecular understanding of antibody response to influenza virus, but also provides an invaluable resource for applying deep learning to antibody research.

immunology↗

bioRxiv2023

OBIA: An Open Biomedical Imaging Archive

With the development of artificial intelligence (AI) technologies, biomedical imaging data play an important role in scientific research and clinical application, but the available resources are limited. Here we present Open Biomedical Imaging Archive (OBIA), a repository for archiving biomedical imaging and related clinical data. OBIA adopts five data objects (Collection, Individual, Study, Series, and Image) for data organization, accepts the submission of biomedical images of multiple modalities, organs, and diseases. In order to protect personal privacy, OBIA has formulated a unified de-identification and quality control process. In addition, OBIA provides friendly and intuitive web interface for data submission, browsing and retrieval, as well as image retrieval. As of September 2023, OBIA has housed data for a total of 937 individuals, 4136 studies, 24,701 series, and 1,938,309 images covering 9 modalities and 30 anatomical sites. Collectively, OBIA provides a reliable platform for biomedical imaging data management and offers free open access to all publicly available data to support research activities throughout the world. OBIA can be accessed at https://ngdc.cncb.ac.cn/obia.

bioinformatics↗

bioRxiv2023

Global brain activity and its coupling with cerebrospinal fluid flow is related to tau pathology

AO_SCPLOWBSTRACTC_SCPLOWAmyloid-{beta} (A{beta}) and tau deposition constitute Alzheimers disease (AD) neuropathology. Cortical tau deposits first in the entorhinal cortex and hippocampus and then propagates to neocortex in an A{beta}-dependent manner. Tau also tends to accumulate earlier in higher-order association cortex than in lower-order primary sensory-motor cortex. While previous research has examined the production and spread of tau, little attention has been paid to its clearance. Low-frequency (<0.1 Hz) global brain activity during the resting state is coupled with cerebrospinal fluid (CSF) flow and potentially reflects glymphatic clearance. Here we report that tau deposition in subjects with evaluated A{beta}, accompanied by cortical thinning and cognitive decline, is strongly associated with decreased coupling between CSF flow and global brain activity. Substantial modulation of global brain activity is also manifested as propagating waves of brain activation between higher- and lower-order regions, resembling tau spreading. Together, the findings suggest an important role of resting-state global brain activity in AD tau pathology. One Sentence SummaryResting-state global brain activity affects tau deposition through the potential involvement of a glymphatic clearance function.

neuroscience↗

bioRxiv2023

Early-stage neural processing reveals distinctive responses to saliency-differentiated colors in various types of color vision

Individuals with minority color vision phenotypes have been reported to exhibit enhanced color discrimination and color recognition, which deviate from predictions based on their receptoral sensitivities. However, the specific mechanisms underlying this enhanced sensitivity remain unclear. In this study, we examined the commonality and diversity of neural activity between typical and anomalous trichromats in response to differences in color saliency. Electroencephalography was recorded during an oddball task, in which participants discriminated each of two target stimuli, blue-green and red, from a green standard stimulus. The chromaticity of the stimulus was identical across participants, whereas the relationship of saliency between the target stimuli was expected to be reversed between color vision types. The spatiotemporal dynamics of event-related potentials (ERPs) were analyzed using cluster-based permutation tests. Typical trichromats demonstrated faster behavioral and neural responses to the more salient red target stimulus, with pronounced neural activity spreading from the occipital to the parietal regions in the comparison between the target stimuli. Anomalous trichromats also exhibited similar temporal patterns toward the more salient target stimulus when each target stimulus was compared with the green standard stimulus, indicating comparable processing toward saliency across color vision types. Although a similarity was observed, neither behavioral nor neural responses in anomalous trichromats reflected saliency contrast differences. In addition, a comparative analysis of ERPs between color vision types did not reveal any distinct differences in either target stimulus. Given the large variations in color sensitivity in individuals with anomalous trichromacy, further investigation is required to understand the detailed neural processing in individuals with various color vision types.

neuroscience↗

bioRxiv2023

Automated Bioinformatics Analysis via AutoBA

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle the bioinformatics analysis continues to grow. In response to this need, we introduce Automated Bioinformatics Analysis (AutoBA), an autonomous AI agent designed explicitly for fully automated multi-omic analyses based on large language models. AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step-by-step plans for various bioinformatics tasks. Through rigorous validation by expert bioinformaticians, AutoBAs robustness and adaptability are affirmed across a diverse range of omics analysis cases, including whole genome/exome sequencing (WGS/WES), chromatin immunoprecipitation assays with sequencing (ChIP-seq), RNA sequencing (RNA-seq), single-cell RNA-seq, spatial transcriptomics and so on. AutoBAs unique capacity to self-design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA offers multiple LLM backends, with options for both online and local usage, prioritizing data security and user privacy. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents an advanced and convenient tool, offering robustness and adaptability for conventional multi-omic analyses.

bioinformatics↗

bioRxiv2023

Epigenetic regulation of p63 blocks squamous-to-neuroendocrine transdifferentiation in esophageal development and malignancy

While cell fate determination and maintenance are important in establishing and preserving tissue identity and function during development, aberrant cell fate transition leads to cancer cell heterogeneity and resistance to treatment. Here, we report an unexpected role for the transcription factor p63 (Trp63/TP63) in the fate choice of squamous versus neuroendocrine lineage in esophageal development and malignancy. Deletion of p63 results in extensive neuroendocrine differentiation in the developing mouse esophagus and esophageal progenitors derived from human embryonic stem cells. In human esophageal neuroendocrine carcinoma (eNEC) cells, p63 is transcriptionally silenced by EZH2-mediated H3K27 trimethylation (H3K27me3). Upregulation of the major p63 isoform {Delta}Np63, through either ectopic expression or EZH2 inhibition, promotes squamous transdifferentiation of eNEC cells. Together these findings uncover p63 as a rheostat in coordinating the transition between squamous and neuroendocrine cell fates during esophageal development and tumor progression.

cell biology↗

bioRxiv2023

O-GlcNAcylation of YTHDF2 antagonizes ERK-dependent phosphorylation and inhibits lung carcinoma

The intracellular O-linked N-acetylglucosamine (O-GlcNAc) glycosylation mediates many signal transduction events and regulates tumorigenesis. Previously the RNA N6-methyladenosine (m6A) reader, YTH (YT521-B homology) domain 2 (YTHDF2), has been shown to be O-GlcNAcylated on Ser-263 during Hepatitis B virus (HBV) infection and promote HBV-related hepatocellular carcinoma. Herein we mapped YTHDF2 O-GlcNAcylation at Thr-49 via electron-transfer dissociation mass spectrometry under unperturbed conditions. We show that YTHDF2 Thr-49 O-GlcNAcylation antagonizes Extracellular-signal regulated kinase (ERK)-dependent phosphorylation at Ser-39 and promotes YTHDF2 degradation. The downstream signaling pathway of YTHDF2 in lung carcinoma are thus upregulated, which leads to the downregulation of c-Myc. We further used mouse xenograft models to show that YTHDF2-T49A mutants increased lung cancer mass and size. Our work reveals a key role of YTHDF2 O-GlcNAcylation in tumorigenesis and suggests that O-GlcNAcylation exerts distinct functions under different biological stress.

biochemistry↗

bioRxiv2023

Bacterial Sphingolipids Exacerbate Colitis by Inhibiting ILC3-derived IL-22 Production.

Commensal bacteria of the Bacteroidetes phylum are the primary producers of sphingolipids in the gut lumen. These lipids serve dual roles as bacterial virulence factors and regulators of the host mucosal immune system, including regulatory T cells and invariant natural killer T cells (iNKT). Sphingolipid composition is significantly altered in fecal samples of patients with inflammatory bowel disease (IBD). However, the specific mechanisms by which bacterial sphingolipids modulate mucosal homeostasis and regulate intestinal inflammation remain unclear. In this study, we investigated the impact of bacterial sphingolipids on intestinal inflammation by mono-colonizing mice with Bacteroides fragilis strains that either express or lack sphingolipids during DSS-induced colitis. We discovered that B. fragilis sphingolipids exacerbate intestinal inflammation. Mice mono-colonized with B. fragilis lacking sphingolipids exhibited less severe DSS-induced colitis. This amelioration of colitis was associated with increased production of interleukin-22 (IL-22) by innate lymphoid cell type 3 (ILC3). Consistent with the inhibitory effect of sphingolipids on IL-22 production, mice colonized with B. fragilis lacking sphingolipids showed enhanced epithelial STAT3 activity, intestinal cell proliferation, and antimicrobial peptide production following DSS treatment compared to those colonized with B. fragilis producing sphingolipids. Additionally, colitis severity in mice colonized with B. fragilis lacking sphingolipids was exacerbated upon IL-22 blockade. Furthermore, our study reveals that bacterial sphingolipids restrict epithelial IL-18 production following DSS treatment and interfere with IL-22 production by a subset of ILC3 cells expressing both the interleukin-18 receptor (IL-18R) and major histocompatibility complex class II (MHC II). These findings indicate that B. fragilis-derived sphingolipids exacerbate mucosal inflammation by impeding epithelial IL-18 expression, resulting in compromised production of IL-22 by ILC3 cells. HighlightsO_LIB. fragilis-derived sphingolipids exacerbate DSS-induced colitis in mono-colonized C57BL/6 mice. C_LIO_LIB. fragilis-derived sphingolipids constrain ILC3-derived IL-22, leading to reduced colonic epithelial cell proliferation and compromised barrier function. C_LIO_LIB. fragilis-derived sphingolipids restrict epithelial NLRC4 inflammasome activation and IL-18 secretion. C_LIO_LIB. fragilis-derived sphingolipids modulate IL-22 production by IL18R+ MHC II+ ILC3s. C_LI

immunology↗

bioRxiv2023

Targeting and Imaging Mitochondria with a Novel Cyanine-based Fluorescent Dye and Its Application to Whole Brain Imaging

In vivo, brain imaging poses several challenges due to the complexity of brain tissue and the requirements for effective and safe imaging. In this manuscript, we reported on developing a new fluorescent dye, Cy5-PEG2, that can selectively accumulate in mitochondria, allowing us to visualize these organelles in different cell lines. Its versatility makes it broadly applicable in various experimental conditions, including monitoring mitochondrial dynamics in living cells. Moreover, we demonstrated that the Cy5-PEG2 dye could penetrate the blood-brain barrier (BBB), making it a promising tool for in vivo brain imaging. We further examined the response of glial cells in the hippocampus and neocortex regions of the brain through biomarkers GFAP and Iba1 but found no significant increase in their expression levels. This indicates that Cy5-PEG2 dye had no noticeable adverse effects on the brains immune response or neuronal health. We anticipate such a mitochondria-targeting fluorescent dye can be used to facilitate the study of mitochondrial dynamics and function in the context of whole-brain physiology and disease progression. Further research into the safety and efficacy of this dye may be necessary.

neuroscience↗

bioRxiv2023

Antigenicity and infectivity characterization of SARS-CoV-2 BA.2.86

The recently identified SARS-CoV-2 variant, BA.2.86, which carries a substantial number of Spike mutations, has raised a global alarm. An immediate assessment of its antigenic properties and infectivity is necessary. Here, we reveal the distinct antigenicity of BA.2.86 compared with previous variants including XBB.1.5. BA.2.86 significantly evades convalescent plasma from XBB breakthrough infection (BTI) and reinfections. Key mutations that mediate the enhanced resistance include N450D, K356T, L452W, A484K, V483del, and V445H on the RBD, while BA.2.86s NTD mutations and E554K on SD1 also largely contribute. However, we found that BA.2.86 pseudovirus exhibits compromised efficiency of infecting HEK293T-hACE2 cells compared to XBB.1.5 and EG.5, which may be caused by K356T, V483del, and E554K, and could potentially limit BA.2.86s transmissibility. In sum, it appears that BA.2.86 has traded its infectivity for higher immune evasion during long-term host-viral evolution. Close attention should be paid to monitoring additional mutations that could improve BA.2.86s infectivity.

immunology↗

bioRxiv2023

AP profiling resolves co-translational folding pathway and chaperone interactions in vivo

Natural proteins have evolved to fold robustly along specific pathways. Folding begins during synthesis, guided by interactions of the nascent protein with the ribosome and molecular chaperones. However, the timing and progression of co-translational folding remain largely elusive, in part because the process is difficult to measure in the natural environment of the cytosol. We developed a high-throughput method to quantify co-translational folding in live cells that we term Arrest Peptide profiling (AP profiling). We employed AP profiling to delineate co-translational folding for a set of GTPase domains with very similar structures, defining how topology shapes folding pathways. Genetic ablation of major nascent chain-binding chaperones resulted in localized folding changes that suggest how functional redundancies among chaperones are achieved by distinct interactions with the nascent protein. Collectively, our studies provide a window into cellular folding pathways of complex proteins and pave the way for systematic studies on nascent protein folding at unprecedented resolution and throughput.

molecular biology↗

bioRxiv2023

Convergent evolution of SARS-CoV-2 XBB lineages on receptor-binding domain 455-456 enhances antibody evasion and ACE2 binding

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) XBB lineages have achieved dominance worldwide and keep on evolving. Convergent evolution of XBB lineages on the receptor-binding domain (RBD) L455F and F456L is observed, resulting in variants like EG.5, FL.1.5.1, XBB.1.5.70, and HK.3. Here, we show that neutralizing antibody (NAb) evasion drives the convergent evolution of F456L, while the epistatic shift caused by F456L enables the subsequent convergence of L455F through ACE2 binding enhancement and further immune evasion. L455F and F456L evade Class 1 NAbs, reducing the neutralization efficacy of XBB breakthrough infection (BTI) and reinfection convalescent plasma. Importantly, L455F single substitution significantly dampens receptor binding; however, the combination of L455F and F456L forms an adjacent residue flipping, which leads to enhanced NAbs resistance and ACE2 binding affinity. The perturbed receptor-binding mode leads to the exceptional ACE2 binding and NAb evasion, as revealed by structural analyses. Our results indicate the evolution flexibility contributed by epistasis cannot be underestimated, and the evolution potential of SARS-CoV-2 RBD remains high.

immunology↗

bioRxiv2023

PyHFO: Lightweight Deep Learning-poweredEnd-to-End High-Frequency Oscillations AnalysisApplication

In the context of epilepsy studies, intracranially-recorded interictal high-frequency oscillations (HFOs) in EEG signals are emerging as promising spatial neurophysiological biomarkers for epileptogenic zones. While significant efforts have been made in identifying and understanding these biomarkers, deep learning is carving novel avenues for biomarker detection and analysis. Yet, transitioning such methodologies to clinical environments is difficult due to the rigorous computational needs of processing EEG data via deep learning. This paper presents our development of an advanced end to end software platform, PyHFO, aimed at bridging this gap. PyHFO provides an integrated and user-friendly platform that includes time-efficient HFO detection algorithms such as short-term energy (STE) and Montreal Neurological Institute and Hospital (MNI) detectors and deep learning models for artifact and HFO with spike classification. This application functions seamlessly on conventional computer hardware. Our platform has been validated to adeptly handle datasets from 10-minute EEG recordings captured via grid/strip electrodes in 19 patients. Through implementation optimization, PyHFO achieves speeds up to 50 times faster than the standard HFO detection method. Users can either employ our pre-trained deep learning model for their analyses or use their EEG data to train their model. As such, PyHFO holds great promise for facilitating the use of advanced EEG data analysis tools in clinical practice and large-scale research collaborations.

neuroscience↗

bioRxiv2023

Population genomic analyses reveal extensive genomic regions within selective sweeps associated with adaptation and demographic history of a wheat fungal pathogen

Plant pathogens can quickly evolve in response to the changing host and environment, resulting in destructive epidemics. The fungus Puccinia striiformis f. sp. tritici (Pst), causing wheat stripe rust disease worldwide, is one such pathogen. In the arms race between pathogens and hosts, changes in host populations exerted continuous selective forces on the dynamics of pathogens. However, the footprints of these selection forces and the demography of Pst remain poorly explored, limited our understanding the evolutionary processes that shape the spread and evolution of pathogens. In this study, we revealed several features of worldwide Pst populations through population genomic analyses. There might be limited gene flow between Pst populations from China and other countries. A slower rate of linkage disequilibrium decay was detected comparing to rust fungi with known sexual reproduction. Furthermore, we detected extensive hard and soft sweeps associated with Pst adaptation. Genes within the selective sweeps were enriched in secreted proteins and effectors and showed functions related to pathogenicity or virulence, temperature tolerance, and fungicide resistance implying that Chinese Pst populations suffered positive selection pressures from host and abiotic factors. Moreover, demographic history indicated Pst populations experienced strong bottlenecks at the beginning of the wheat domestication around 10,000 years ago and during modern agriculture around 100 years ago, suggesting that the crop domestication and breeding programs could continuously contribute to the decline of pathogen effective population sizes. Our results provided insights into the evolution of the Pst genome and highlighted the role of modern agriculture on pathogen demography. Author SummaryWheat stripe rust, as a pathogen of wheat, is capable of inducing significant yield reduction on a global scale. Traditional epidemiological investigations have elucidated the causative agent behind this disease, the wheat stripe rust pathogen, as an organism exhibiting swift adaptive evolution in response to its environment. However, the precise mechanisms underpinning its adaptive strategies and the ensuing alterations in population dynamics remain relatively unexplored. In our research, we have undertaken an analysis encompassing wheat stripe rust samples throughout the world. Employing population genomics methods, we have sought to discern the genomic footprints corresponding to the adaptive process within the pathogen. These genomic footprints have illuminated the operation of positive selection pressures caused by both the host plant and the ecological context. Concurrently, it have provided insights into the population size that the wheat stripe rust pathogen has undergone over millennia. Notably, its change in population size revealed the demographic history associated with wheat domestication.

microbiology↗

bioRxiv2023

The evolution of autonomy from two cooperative specialists in the fluctuating environments

From microbes to humans, organisms perform numerous tasks for their survival, including food acquisition, migration, and reproduction. A complex biological task can be performed by either an autonomous organism or by cooperation among several specialized organisms. However, it remains unclear how autonomy and cooperation evolutionarily switch. For example, it remains unclear whether and how a group of cooperative specialists can evolve into an autonomous organism. Here, we address this question by experimentally evolving a mutualistic microbial consortium composed of two specialists that cooperatively degrade naphthalene. We observed that autonomous genotypes capable of performing the entire naphthalene degradation pathway evolved from two cooperative specialists and came to dominate the microbial community. This evolutionary transition was driven by the horizontal gene transfer between the two specialists. However, this evolution was exclusively observed to occur in the fluctuating environment supplied with either naphthalene or pyruvate, where mutualism and competition between the two specialists alternated. The naphthalene-supplied environment exerts selective pressure that favors the expansion of autonomous genotypes but was associated with both low cell density and low coexistence levels. In contrast, the pyruvate-supplying environment promoted the coexistence and cell density of the cooperative specialists, thereby increasing the likelihood of horizontal gene transfer. Using a mathematical model, we quantitatively demonstrate that environmental fluctuations facilitate the evolution of autonomy through HGT when the relative growth rate and carrying capacity of the cooperative specialists allow enhanced coexistence and higher cell density in the competitive environment. Together, our results demonstrate that mutualistic cooperation can evolve into autonomous organisms through direct genetic exchange under specific conditions, including the alternation of mutualism and competition in fluctuating environments in a manner frequently occurring in nature.

evolutionary biology↗