Biology subjects

Xie, L.

Publications and source records attributed to Xie, L..

At least 127 records · Page 7Linked to original sources

bioRxiv2023

Brd4-Nutm1 fusion gene initiates NUT carcinoma in vivo

Nut carcinoma (NC) is an aggressive cancer with no effective treatment. The majority (70%) of NUT carcinoma is associated with chromosome translocation events that lead to the formation of a BRD4::NUTM1 fusion gene. However, because the BRD4::NUTM1 gene is unequivocally cytotoxic when ectopically expressed in cell lines, questions remain on whether the fusion gene can initiate NC. Here, we report the first genetically engineered mouse model (GEMM) for NUT carcinoma recapitulating the human mutation. By stochastically inducing a chromosome translocation mirroring the human event, we demonstrated that the Brd4::Nutm1 fusion gene could induce aggressive carcinomas in mice. The tumors present histopathological and molecular features similar to human NC, with an enrichment of undifferentiated cells. Similar to the reports of human NC incidence, Brd4::Nutm1 can induce NC from a broad range of tissues, demonstrating that its oncogenic potential is not lineage-restricted. The consistent induction of tumors of squamous phenotypes, even from ductal epithelial and mesenchymal tissues, demonstrated a strong reprogramming activity of BRD4::NUTM1. The new mouse model provided a critical preclinical model for NC and opens new opportunities for understanding the oncogenic mechanism and developing new therapies.

cancer biology↗

bioRxiv2023

Seed size control via phloem end by callose deposition/degradation of β-1,3-glucanase

Seed formation is crucial for lives of plants as well as humans; however, the mechanisms governing seed size require further investigation. Here, we present a new mechanism to modify the seed size by the newly identified phloem end that support nutrient transport, at the chalazal end of the ovule, however, blocked by callose deposition. Callose is removed after central cell fertilization (open state), allowing nutrients to be transported to the seed. However, if fertilization fails, callose deposition persists (closed state), preventing the phloem end from transporting nutrients. {beta}-1,3-glucanase genes, including putative plasmodesmata-associated proteins (AtBG_ppap), were identified as regulators of callose removal. The Atbg_ppap mutant had the phloem end in the closed state and produced smaller seeds due to incomplete callose degradation. In contrast, the AtBG_ppap overexpression line produced larger seeds than the wild type due to continuous callose degradation, indicating that the phloem end regulates substance flow via callose deposition/degradation.

plant biology↗

bioRxiv2023

Introducing PandaNovo for practical large-scale de novo peptide sequencing

De novo peptide sequencing is a promising approach for novel peptide discovery. We use a novel concept of complementary spectra to enhance ion information and propose a de novo sequencing model{pi} -HelixNovo based on Transformer architecture.{pi} -HelixNovo outperforms other state-of-the-art models and enhances the taxonomic resolution of gut metaproteome, taking a significant step forward in de novo sequencing.

bioinformatics↗

bioRxiv2023

Deciphering Phage-Host Specificity Based on the Association of Phage Depolymerases and Bacterial Surface Glycan with Deep Learning

Phage tailspike proteins are depolymerases that target diverse bacterial surface glycans with high specificity, determining the host-specificity of numerous phages. To address the challenge of identifying tailspike proteins due to their sequence diversity, we developed SpikeHunter, an approach based on the ESM-2 protein language model. Using SpikeHunter, we successfully identified 231,965 tailspike proteins from a dataset comprising 8,434,494 prophages found within 165,365 genomes of five common pathogens. Among these proteins, 143,035 tailspike proteins displayed strong associations with serotypes. Moreover, we observed highly similar tailspike proteins in species that share closely related serotypes. We found extensive domain swapping in all five species, with the C-terminal domain being significantly associated with host serotype highlighting its role in host range determination. Our study presents a comprehensive cross-species analysis of tailspike protein to serotype associations, providing insights applicable to phage therapy and biotechnology.

bioinformatics↗

bioRxiv2023

AraENCODE: a comprehensive epigenomic database of Arabidopsis Thaliana

Arabidopsis (Arabidopsis thaliana) is a vital model organism in plant biology and genetics. In the last two decades, researchers have made significant progresses in characterizing the chromatin conformation and epigenomic information within the Arabidopsis genome. This information includes but is not limited to the higher structure of chromosomes, histone modification, DNA methylation, and chromatin accessibility. The results of these studies have provided an additional layer of information that complements the DNA sequence data. However, utilizing such knowledge poses a challenge for certain groups that lack bioinformatics analysts or adequate computing resources. A user-friendly and reproducible platform for accessing this information is urgently needed. In this study, we have developed a comprehensive epigenomic database for Arabidopsis (AraENCODE http://glab.hzau.edu.cn/AraENCODE), which comprises a total of 4,511 data libraries, including published chromatin conformation capture datasets (Hi-C, HiChIP), epigenomic datasets (ChIP-Seq, ATAC-Seq, FAIRE-Seq, MNase-Seq, DNase-Seq, BS-seq), and transcriptome data (RNA-Seq, miRNA-Seq). Furthermore, we have incorporated various existing resources, such as single nucleotide polymorphisms (SNPs), cis-regulatory modules, and multi-omics associations. We aim to provide a novel platform for investigating the regulation of epigenetic and chromatin interactions in Arabidopsis in relation to biological processes.

bioinformatics↗

bioRxiv2023

The TRIP6/LATS1 complex constitutes the tension sensor of α-catenin/vinculin at both bicellular and tricellular junctions

Cell-cell mechanotransduction regulates tissue development and homeostasis. -catenin, the core component of adherens junctions, functions as a tension sensor and transducer by recruiting vinculin and transducing the signals to influence cell behaviors. However, little is known about the components, distributions, and dynamics of the -catenin based tension sensors at the cell junctions. Here, we uncovered the TRIP6/LATS1 complex locates at the tension sites where -catenin/vinculin is at both the bicellular junctions (BCJs) and tricellular junctions (TCJs). Vinculin/TRIP6/LATS1 are prone to form as puncta in the cytoplasm without -catenin participation. Furthermore, the tension sensing complex distributed stronger at TCJs and exhibited a discontinuously button-like pattern on BCJs. The -catenin/vinculin BiFC-based mechanosensor further proved the discontinuous distribution of the tension at BCJs, and was more motile than the TCJs. In summary, our study revealed that TRIP6 and LATS1 are novel compositions of the tension sensor, together with the core complex of -catenin/vinculin, at both the BCJs and TCJs. This work gives insights and improvements in exploring the molecular mechanism that mediates cell-cell mechanotransduction at cell junctions.

cell biology↗

bioRxiv2023

Data Efficiency Semi-Supervised Meta-Learning Elucidates Understudied Interspecies Molecular Interactions

Many biological problems are understudied due to experimental limitations and human biases. Although deep learning is promising in accelerating scientific discovery, its power compromises when applied to problems with scarcely labeled data and data distribution shifts. We developed a semi-supervised meta learning framework Meta Model Agnostic Pseudo Label Learning (MMAPLE) to address these challenges by effectively exploring out-of-distribution (OOD) unlabeled data when transfer learning fails. The power of MMAPLE is demonstrated in multiple applications: predicting OOD drug-target interactions, hidden human metabolite-enzyme interactions, and understudied interspecies microbiome metabolite-human receptor interactions, where chemicals or proteins in unseen data are dramatically different from those in training data. MMAPLE achieves 11% to 242% improvement in the prediction-recall on multiple OOD benchmarks over baseline models. Using MMAPLE, we reveal novel interspecies metaboliteprotein interactions that are validated by bioactivity assays and fill in missing links in microbiome-human interactions. MMAPLE is a general framework to explore previously unrecognized biological domains beyond the reach of present experimental and computational techniques.

systems biology↗

bioRxiv2023

Engineering GliaTrap: a biodegradable non-swelling hydrogel with tuned release of CXCL12 to attract migrating glioblastoma cells

Glioblastoma is the most aggressive type of brain cancer with an average overall survival of 15-21 months after first diagnosis. The relapse is mainly caused by migrating glioblastoma cells that diffuse away from the tumor mass into the brain parenchyma and retain cancer stem cell (GSC) properties. Current therapeutic options are ineffective and inevitably result in relapse, indicating a high unmet medical need for innovative therapies in the treatment of invasive glioblastoma. To address this challenge, we propose a new therapeutic modality: GliaTrap, a biodegradable non-swelling, injectable hydrogel with sustained release of a chemoattractant for GSCs that lures and traps the migrating cells back to the tumor resection cavity. We developed a biodegradable and injectable hyaluronan/collagen II-based (HA/Col) hydrogel that does not swell in vivo. The hydrogel is embedded with CXCL12 loaded liposomes and is tuned for sustained release of CXCL12. The safety profile of liposome-embedded HA/Col hydrogel was determined in-vivo after stereotactic implantation in the mouse brain. The efficacy of GliaTrap to attract GSCs was determined ex vivo using a 3D tumor spheroid model and in-vivo using 3D light-sheet microscopy in orthotopic human glioblastoma xenografts. Our findings suggest that GliaTrap could represent a safe and efficacious new therapeutic approach for glioblastoma and potentially serve as a drug delivery platform to locally deliver tumor-killing agents. One Sentence SummaryGliaTrap is a biodegradable non-swelling hydrogel with tuned release of a chemoattractant to attract invading glioma cells and serve as delivery platform for local therapeutics.

cancer biology↗

bioRxiv2023

Experimental Factors Influence Diversity Metrics of the Gut Microbiome in Laboratory Mice

IntroductionAnimal models are regularly used to test the role of the gut microbiome in hypertension. Small-scale pre-clinical studies have investigated changes to the gut microbiome in the angiotensin II hypertensive model. However, the gut microbiome is influenced by internal and external factors not regularly considered in the study design. Once these factors are accounted for, it is unclear if microbiome signatures are reproduceable. We aimed to determine the influence of angiotensin II treatment on the gut microbiome using a large and diverse cohort of mice and to quantify the magnitude by which other factors contribute to microbiome variations. Methods and ResultsWe conducted a retrospective study to establish a diverse mouse cohort resembling large human studies. We sequenced the V4 region of the 16S rRNA gene from 538 samples across the gastrointestinal tract of 303 male and female C57BL/6J mice randomised into sham or angiotensin II treatment from different genotypes, diets, animal facilities, and age groups. Analysing over 17 million sequencing reads, we observed that angiotensin II treatment influenced -diversity (P=0.0137) and {beta}-diversity (i.e., composition of the microbiome, P<0.001). Bacterial abundance analysis revealed patterns consistent with a reduction in short-chain fatty acid-producers, microbial metabolites that lower blood pressure. Furthermore, animal facility, genotype, diet, age, sex, intestinal sampling site, and sequencing batch had significant effects on both - and {beta}-diversity (all P<0.001). Sampling site (6.8%) and diet (6%) had the largest impact on the microbiome, while angiotensin II and sex had the smallest effect (each 0.4%). ConclusionsOur large-scale data confirmed findings from small-scale studies that angiotensin II impacted the gut microbiome. However, this effect was modest relative to most of the other factors studied. Accounting for these factors in future pre-clinical hypertensive studies will increase the likelihood that microbiome findings are replicable and translatable.

microbiology↗

bioRxiv2023

GPR41/43 regulates blood pressure by improving gut epithelial barrier integrity to prevent TLR4 activation and renal inflammation

Fermentation of dietary fibre by the gut microbiota leads to the production of metabolites called short-chain fatty acids (SCFAs), which have emerged as potent regulators of immune, metabolic, and tissue barrier functions. More recently, a high fibre diet and SCFA supplementation were shown to lower blood pressure and be cardio-protective. SCFAs activate host signalling responses via the receptors GPR41 and GPR43, which have redundancy in their signalling pathways. Whether these receptors play a role in hypertension or mediate the cardio-protective effects of fibre remains unknown. Using an experimental model that lacks both GPR41 and GPR43, we show that lack of signalling via these receptors increases risk to high blood pressure and leads to cardiorenal fibrosis and hypertrophy. Moreover, we demonstrate that GPR41/43 signalling is essential in maintaining gut epithelial barrier, which prevents the translocation of the bacterial toxins lipopolysaccharides (LPS) from entering the peripheral circulation. In the absence of GPR41/43, this is accompanied by macrophage infiltration to the kidneys, resulting in pro-inflammatory cytokine production. Using an antagonist against the LPS receptor, TLR4, a potent pro-inflammatory signalling pathway, we were able to rescue the cardiovascular phenotype in GPR41/43 knockout mice. We also demonstrate that GPR41/43 are, at least partially, responsible for the blood pressure- lowering and cardio-protective effects of a high fibre diet; however, improvements of gut barrier integrity and macrophages in the kidney were independent of GPR41/43 signalling. Finally, using the UK Biobank, we provide translational evidence that variants associated with lower expression of both GPR41/43 are more prevalent in hypertensive patients. Our findings highlight that lack of SCFA-receptor signalling via both GPR41/43 increases risk of high blood pressure, suggesting these receptors could be targeted as a new treatment.

physiology↗

bioRxiv2023

A syntelog-based pan-genome provides insights into rice domestication and de-domestication

Asian rice is one of the worlds most widely cultivated crops. Large-scale resequencing analyses have been undertaken to explore the domestication and de-domestication genomic history of Asian rice, but the evolution of rice is still under debate. Here, we construct a syntelog-based rice pan-genome by integrating and merging 74 high-accuracy genomes based on long-read sequencing, encompassing all ecotypes and taxa of Oryza sativa and Oryza rufipogon. Analyses of syntelog groups illustrate subspecies divergence in gene presence-and-absence and haplotype composition and identify massive genomic regions putatively introgressed from ancient Geng/japonica to ancient Xian/indica or its wild ancestor, including almost all well-known domestication genes and a 4.5-Mb centromere-spanning block, supporting a single domestication event in rice. Genomic comparisons between weedy and cultivated rice highlight the contribution from wild introgression to the emergence of de-domestication syndromes in weedy rice. This work highlights the significance of inter-taxa introgression in shaping diversification and divergence in rice evolution and provides an exploratory attempt by utilizing the advantages of pan-genomes in evolutionary studies.

evolutionary biology↗

bioRxiv2023

Elucidation of Genome-wide Understudied Proteins targeted by PROTAC-induced degradation using Interpretable Machine Learning

Proteolysis-targeting chimeras (PROTACs) are hetero-bifunctional molecules. They induce the degradation of a target protein by recruiting an E3 ligase to the target. The PROTAC can inactivate disease-related genes that are considered as understudied, thus has a great potential to be a new type of therapy for the treatment of incurable diseases. However, only hundreds of proteins have been experimentally tested if they are amenable to the PROTACs. It remains elusive what other proteins can be targeted by the PROTAC in the entire human genome. For the first time, we have developed an interpretable machine learning model PrePROTAC, which is based on a transformer-based protein sequence descriptor and random forest classification to predict genome-wide PROTAC-induced targets degradable by CRBN, one of the E3 ligases. In the benchmark studies, PrePROTAC achieved ROC-AUC of 0.81, PR-AUC of 0.84, and over 40% sensitivity at a false positive rate of 0.05, respectively. Furthermore, we developed an embedding SHapley Additive exPlanations (eSHAP) method to identify positions in the protein structure, which play key roles in the PROTAC activity. The key residues identified were consistent with our existing knowledge. We applied PrePROTAC to identify more than 600 novel understudied proteins that are potentially degradable by CRBN, and proposed PROTAC compounds for three novel drug targets associated with Alzheimers disease. Author SummaryMany human diseases remain incurable because disease-causing genes cannot by selectively and effectively targeted by small molecules. Proteolysis-targeting chimera (PROTAC), an organic compound that binds to both a target and a degradation-mediating E3 ligase, has emerged as a promising approach to selectively target disease-driving genes that are not druggable by small molecules. Nevertheless, not all of proteins can be accommodated by E3 ligases, and be effectively degraded. Knowledge on the degradability of a protein will be crucial for the design of PROTACs. However, only hundreds of proteins have been experimentally tested if they are amenable to the PROTACs. It remains elusive what other proteins can be targeted by the PROTAC in the entire human genome. In this paper, we propose an intepretable machine learning model PrePROTAC that takes advantage of powerful protein language modeling. PrePROTAC achieves high accuracy when evaluated by an external dataset which comes from different gene families from the proteins in the training data, suggesting the generalizability of PrePROTAC. We apply PrePROTAC to the human genome, and identify more than 600 understudied proteins that are potentially responsive to the PROTAC. Furthermore, we design three PROTAC compounds for novel drug targets associated with Alzheimers disease.

bioinformatics↗

bioRxiv2023

Single-cell RNA sequencing to explore the immune process difference between Kawasaki disease and febrile patients

BackgroundKawasaki disease (KD) is an acute systemic vasculitis that can lead to acquired heart disease in children mostly from in developed countries. The previous research showed that B cells in KD patients underwent a profound change in both the cell numbers and types after intravenous immunoglobulin (IVIG) therapy. MethodsWe performed the single-cell RNA-sequencing for the peripheral blood mononuclear cells (PBMCs) from three febrile patients and three KD patients to investigate the possible mechanism underlying B cell developmental dysfunction in KD. A previously published single-cell sequencing KD dataset (GSE168732) was also utilized in study for sample size expansion and validation. The comprehensive single-cell data analyses were applied for our dataset and GSE168732 dataset including single-cell trajectory analysis. To validate the immune disorders in KD, we measured immune-related indicators from 28 KD and 28 febrile patients. ResultOverall single-cell expression profiles show that the biological processes of immunity, B cell activation pathway and their related biological entities are repressed in KD patients before IVIG treatment compared to febrile patient and KD patients after IVIG treatment. The differentially expressed gene analyses further demonstrate that B cell signaling pathway is downregulated in B cells and plasma blast cells of KD patients before treatment while cell cycle genes and MYC gene are upregulated in dendritic cells (DCs) and hematopoietic stem and progenitor cells (HSPCs) of KD patients before treatment. The biological process of immune response is upregulated in the HSPCs of KD patients before treatment in our dataset while the biological process of inflammatory response is upregulated in the HSPCs of KD patients before treatment in GSE168732 dataset. Single-cell trajectory analyses demonstrate that KD patients before treatment have a shortened developmental path in which B cells and T cells are failed to differentiate into separate lineages. HSPD1 and HSPE1 genes show an elevated expression level in the early cell development stage of KD patients before treatment accompanied with the repression of MYC, SPI1, MT2A and UBE2C genes. Our analyses of all B cells from KD patients before treatment show most of B cells are arrested in a transitional state with an ill developmental path compared with febrile patients and KD patients after treatment. The percentage and absolute value of CD8 T cells in KD were lower than those in febrile patients. The ratio of CD4/CD8 in KD was higher than it in febrile patients. The serum levels of IgG and IgM in KD were lower than those in febrile patients. ConclusionsOur results indicate that the immune premature HSPCs accompanied with the abnormal expression dynamics of cell cycle and SPI1 genes are the mechanism underlying B cell developmental dysfunction in KD patients. FundingThis work is jointly supported by National Natural Science Foundation of China (82170518) and the Shanghai Science and Technology Committee research Funding (22Y11909700) and Shanghai Jinshan District medical key specialty Funding (JSZK2023A04).

immunology↗

bioRxiv2023

Excess PrPC inhibits muscle cell differentiation via miRNA-enhanced liquid-liquid phase separation implicated in myopathy

The cellular prion protein (PrPC), a glycoprotein existing in membrane-bound and cytoplasmic forms, has functional importance in skeletal muscle, but the mechanism behind the phenomenon remains poorly understood. Here we report that PrPC is overexpressed and located in the cytoplasm of the skeletal muscle of six myopathy patients; cytoplasmic PrPC strongly inhibits skeletal muscle cell autophagy and blocks myoblast differentiation. PrPC selectively binds to a subset of miRNAs during myoblast differentiation, and the co-localization of PrPC with miR-214-3p was clearly observed in the skeletal muscle of six myopathy patients but not in that of four age-matched controls. We demonstrate that PrPC is overexpressed in skeletal muscle cells under pathological conditions and inhibits muscle cell differentiation via physically interacting with a subset of miRNAs to significantly inhibit autophagy-related protein 5-dependent autophagy, and selectively recruits these miRNAs into phase-separated condensates in living myoblasts, which in turn greatly enhances liquid-liquid phase separation (LLPS) of PrPC and results in the subsequent PrP aggregation and muscle bundle formation in myopathy patients characterized by incomplete muscle regeneration. Our findings show how excess PrPC can inhibit muscle cell differentiation via miRNA-enhanced LLPS implicated in myopathy.

biochemistry↗

bioRxiv2023

GABA-mediated inhibition in visual feedback neurons fine-tunes Drosophila male courtship

Vision is critical for the regulation of mating behaviors in many species. Here, we discovered that the Drosophila ortholog of human GABAA-receptor-associated protein (GABARAP) is required to fine-tune male courtship by modulating the activity of visual feedback neurons, lamina tangential cells (Lat). GABARAP is a ubiquitin-like protein that regulates cell-surface levels of GABAA receptors. Knocking down GABARAP or GABAA receptors in Lat neurons or hyperactivating them induces male courtship toward other males. Inhibiting Lat neurons, on the other hand, delays copulation by impairing the ability of males to follow females. Remarkably, the human ortholog of Drosophila GABARAP restores function in Lat neurons. Using in vivo two-photon imaging and optogenetics, we show that Lat neurons are functionally connected to neural circuits that mediate visually-guided courtship pursuits in males. Our work reveals a novel physiological role for GABARAP in fine-tuning the activity of a visual circuit that tracks a mating partner during courtship.

neuroscience↗

bioRxiv2023

Preclinical Basis of the Efficacy and Pharmacodynamics of Finotonlimab, a Humanized Anti-PD-1 Monoclonal Antibody with Potent Implications for Clinical Benefit

BackgroundThe antibodies of programmed cell death protein 1 (PD-1) and its ligand (PD-L1) have dramatically changed the treatment landscapes for patients with cancer. Clinical uses of PD-1 antibodies have greatly improved the overall survival and durable responses in patients across selected tumor types. MethodsWe describe the preclinical characterization of Finotonlimab, a humanized anti-PD-1 antibody, by head to head comparison with Nivolumab or Pembrolizumab. Herein, we characterized the in vitro and in vivo efficacy, PK, PD and Fc mediated effector function of Finotonlimab. The single-agent anti-tumor activity of Finotonlimab was evaluated using humanized mouse models and a human PBMC reconstituted mouse model. Furthermore, in cynomolgus monkeys, comparative PK measurements confirmed better PK profiles of Finotonlimab than that of Pembrolizumab and Nivolumab. ResultsOur data showed Finotonlimab bind to human PD-1 with significantly high affinity and effectively inhibited its interaction with its ligands, PD-L1 and PD-L2, and thus could effectively stimulate the human T cell functions in vitro and exhibited significant antitumor efficacy in vivo. In addition, Finotonlimab showed minimal impact on Fc receptor dependent effector cell activation, which may contribute to the killing of PD-1+ T cells. In cynomolgus monkeys, Finotonlimab exhibited a non-linear pharmacokinetics (PK) profile in a dose-dependent manner, and approximately 90% of consistent receptor occupancy period was observed at 168 h after a single administration of 1 mg/kg. Following a 13-week successive administration of Finotonlimab, a pharmacodynamics study indicated a sustained mean receptor occupancy of [≥] 93% of PD-1 molecules on circulating T cells in cynomolgus monkeys up to 8 weeks even at 3 mg/kg. ConclusionsTaken together, these preclinical data are encouraging and provide a basis for the efficacy and pharmacodynamics of Finotonlimab in clinical trials.

immunology↗

bioRxiv2022

Machine learning prediction of cancer cell metabolism from autofluorescence lifetime images

Metabolic reprogramming at a cellular level contributes to many diseases including cancer, yet few assays are capable of measuring metabolic pathway usage by individual cells within living samples. Here, we combine autofluorescence lifetime imaging with single-cell segmentation and machine-learning models to predict the metabolic pathway usage of cancer cells. The metabolic activities of MCF7 breast cancer cells and HepG2 liver cancer cells were controlled by growing the cells in culture media with specific substrates and metabolic inhibitors. Fluorescence lifetime images of two endogenous metabolic coenzymes, reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD), were acquired by a multi-photon fluorescence lifetime microscope and analyzed at the cellular level. Quantitative changes of NADH and FAD lifetime components were observed for cells using glycolysis, oxidative phosphorylation, and glutaminolysis. Conventional machine learning models trained with the autofluorescence features classified cells as dependent on glycolytic or oxidative metabolism with 90 - 92% accuracy. Furthermore, adapting convolutional neural networks to predict cancer cell metabolic perturbations from the autofluorescence lifetime images provided improved performance, 95% accuracy, over traditional models trained via extracted features. In summary, autofluorescence lifetime imaging combined with machine learning models can detect metabolic perturbations between glycolysis and oxidative metabolism of living samples at a cellular level, providing a label-free technology to study cellular metabolism and metabolic heterogeneity.

bioengineering↗

bioRxiv2022

SnapFISH: a computational pipeline to identify chromatin loops from multiplexed DNA FISH data

Multiplexed DNA fluorescence in situ hybridization (FISH) imaging technologies have been developed to map the folding of chromatin fibers at tens of nanometer and tens of kilobase resolution in single cells. However, computational methods to reliably identify chromatin loops from such imaging datasets are still lacking. Here we present a Single-Nucleus Analysis Pipeline for multiplexed DNA FISH (SnapFISH), to process the multiplexed DNA FISH data and identify chromatin loops. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH obtained comparable results of chromatin loops across datasets generated from diverse imaging technologies.

bioinformatics↗