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Biology subjects

Yuan, Y.

Publications and source records attributed to Yuan, Y..

At least 289 records · Page 16Linked to original sources

Transcranial Photobiomodulation with Near-Infrared Light from Childhood to Elderliness: Simulation of Dosimetry

SignificanceMajor depressive disorder (MDD) affects over 40 million US adults in their lifetimes. Transcranial photobiomodulation (t-PBM) has been shown to be effective in treating MDD, but the current treatment dosage does not account for anatomical head and brain changes due to aging. AimWe study effective t-PBM dosage and its variations across age groups using state-of-the-art Monte Caxrlo (MC) simulations and age-dependent brain atlases ranging between 5 to 85 years of age. ApproachAge-dependent brain models are derived from 18 MRI brain atlases. Two extracranial source positions, F3-F4 and Fp1-Fpz-Fp2 in the EEG 10-20 system, are simulated at five selected wavelengths and energy depositions at two MDD-relevant cortical regions - dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) - are quantified. ResultsAn overall decrease of energy deposition was found with increasing age. A strong negative correlation between the thickness of extra-cerebral tissues (ECT) and energy deposition, suggesting that increasing ECT thickness over age is primarily responsible for reduced energy delivery. The F3-F4 position appears to be more efficient in reaching dlPFC compared to treating vmPFC via the Fp1-Fpz-Fp2 position. ConclusionQuantitative simulations revealed age-dependent light delivery across the lifespan of human brains, suggesting the needs for personalized and age-adaptive t-PBM treatment planning.

biophysics↗

Variant-specific changes in persistent or resurgent Na+ current in SCN8A-EIEE13 iPSC-derived neurons

Missense variants in the voltage-gated sodium channel (VGSC) gene, SCN8A, are linked to early-infantile epileptic encephalopathy type 13 (EIEE13). EIEE13 patients exhibit a wide spectrum of intractable seizure types, severe developmental delay, movement disorders, and elevated risk of sudden unexpected death in epilepsy (SUDEP). The mechanisms by which SCN8A variants lead to epilepsy are poorly understood, although heterologous expression systems and mouse models have demonstrated altered sodium current (INa) properties. To investigate these mechanisms using a patient-specific model system, we generated induced pluripotent stem cells (iPSCs) from three patients with missense variants in SCN8A: p.R1872>L (P1); p.V1592>L (P2); and p.N1759>S (P3). Using small molecule differentiation into excitatory neurons, iPSC-derived neurons from all three patients displayed altered INa. P1 and P2 had elevated persistent INa, while P3 had increased resurgent INa compared to controls. Further analyses focused on one of the patients with increased persistent INa (P1) and the patient with increased resurgent INa (P3). Excitatory cortical neurons from both patients had prolonged action potential (AP) repolarization and shorter axon initial segment lengths compared to controls, the latter analyzed by immunostaining for ankyrin-G. Using doxycycline-inducible expression of the neuronal transcription factors Neurogenin 1 and 2 to synchronize differentiation of induced excitatory cortical-like neurons (iNeurons), we investigated network activity and response to pharmacotherapies. Both patient neurons and iNeurons displayed similar abnormalities in AP repolarization. Patient iNeurons showed increased burstiness that was sensitive to phenytoin, currently a standard treatment for EIEE patients, or riluzole, an FDA-approved drug used in amyotrophic lateral sclerosis and known to block persistent and resurgent INa, at pharmacologically relevant concentrations. Patch-clamp recordings showed that riluzole suppressed spontaneous firing and increased the AP firing threshold of patient-derived neurons to more depolarized potentials. Our results indicate that patient-specific neurons are useful for modeling EIEE13 and demonstrate SCN8A variant-specific mechanisms. Moreover, these findings suggest that patient-specific iPSC neuronal disease modeling offers a useful platform for discovering precision epilepsy therapies.

neuroscience↗

Characterization of the Intestinal Absorption of Morroniside from Cornus officinalis Sieb. et Zucc via a Caco-2 Cell Monolayer Model

Morroniside is biologically active polyphenols found in Cornus officinalis Sieb. et Zucc (CO) which exhibits a broad spectrum of pharmacological activities, such as protecting nerves, preventing diabetic liver damageand renal damage. However, little data is available regarding its mechanism ofintestinal absorption. Here, ahuman intestinal epithelial cell model Caco-2 cell in vitro cultured was applied to study on the absorption and transport of morroniside, the effects of time, donor concentration,pH, temperature and inhibitors,the absorption and transport of morroniside were investigated.The bidirectional permeability of morroniside from the apical (AP) to the basolateral (BL) side and in the revese direction was studied. When administrated was setat three tested concentrations (5, 25 and 100M), the P app value in AP-to-BL direction was ranged from 1.59 to 2.66x10 -6 cm/s. Inthe reverse direction, BL-to-AP, the value was ranged from 2.67to 4.10 x10 -6 cm/s.The data indicated that morroniside transport was both pH- and temperature- dependent. The morronisides permeability process affected bytreatment with various inhibitors, such as the multidrug resistance protein inhibitors MK571 and benzbromarone, the breast cancer resistance protein inhibitor apigenin.It can be found that the mechanisms of intestinal absorption of morroniside may involve multiple transport pathways like passive diffusion as well as efflux protein-mediated active transportespecially the multidrug resistance protein2 and breast cancer resistance protein.After CO was added, P app AB increased significantly by about 125.26%, it can therefore be assumed that some ingredients in the crude material promote morronisides absorption in the small intestine.

pharmacology and toxicology↗

GCNG: Graph convolutional networks for inferring cell-cell interactions

Several methods have been developed for inferring gene-gene interactions from expression data. To date, these methods mainly focused on intra-cellular interactions. The availability of high throughput spatial expression data opens the door to methods that can infer such interactions both within and between cells. However, the spatial data also raises several new challenges. These include issues related to the sparse, noisy expression vectors for each cell, the fact that several different cell types are often profiled, the definition of a neighborhood of cell and the relatively small number of extracellular interactions. To enable the identification of gene interactions between cells we extended a Graph Convolutional Neural network approach for Genes (GCNG). We encode the spatial information as a graph and use the network to combine it with the expression data using supervised training. Testing GCNG on spatial transcriptomics data we show that it improves upon prior methods suggested for this task and can propose novel pairs of extracellular interacting genes. Finally, we show that the output of GCNG can also be used for down-stream analysis including functional assignment. Supporting website with software and data: https://github.com/xiaoyeye/GCNG.

bioinformatics↗

Structural characterization of the N-terminal domain of the Dictyostelium discoideum mitochondrial calcium uniporter

The mitochondrial calcium uniporter (MCU) plays a critical role in the mitochondrial calcium uptake into the matrix. In metazoans, the uniporter is a tightly regulated multi-component system including the pore-forming subunit MCU and several regulators (MICU1, MICU2, EMRE). The calcium-conducting activity of metazoan MCU requires the single-transmembrane protein EMRE. Dictyostelium discoideum (Dd), however, developed a simplified uniporter for which the pore-forming MCU (DdMCU) alone is necessary and sufficient for calcium influx. Here, we report a crystal structure of the N-terminal domain (NTD) of DdMCU at 1.7 [A] resolution. The DdMCU-NTD contains four helices and two strands arranged in a fold that is completely different from the known structures of other MCU-NTD homologs. Biochemical and biophysical analyses of DdMCU-NTD in solution indicated that the domain exists as oligomers, most probably as a pentamer or hexamer. Mutagenesis showed that the acidic residues Asp60, Glu72 and Glu74, which appeared to mediate the parallel interface as observed in the crystal structure, participated in the self-assembly of DdMCU-NTD. Intriguingly, the oligomeric complex readily dissociated to lower-order oligomers in the presence of calcium. We propose that the calcium-triggered dissociation of NTD regulates the channel activity of DdMCU by a yet unknown mechanism.

biophysics↗

Nova proteins direct synaptic integration of somatostatin interneurons through activity-dependent alternative splicing

Somatostatin interneurons are the earliest born population of cortical inhibitory cells. They are crucial to support normal brain development and function; however, the mechanisms underlying their integration into nascent cortical circuitry are not well understood. In this study, we begin by demonstrating that the maturation of somatostatin interneurons is activity dependent. We then investigated the relationship between activity, alternative splicing and synapse formation within this population. Specifically, we discovered that the Nova family of RNA-binding proteins are activity-dependent and are essential for the maturation of somatostatin interneurons, as well as their afferent and efferent connectivity. Within this population, Nova2 preferentially mediates the alternative splicing of genes required for axonal formation and synaptic function independently from its effect on gene expression. Hence, our work demonstrates that the Nova family of proteins through alternative splicing are centrally involved in coupling developmental neuronal activity to cortical circuit formation.

neuroscience↗

Immune surveillance in clinical regression of pre-invasive squamous cell lung cancer

Before squamous cell lung cancer develops, pre-cancerous lesions can be found in the airways. From longitudinal monitoring, we know that only half of such lesions become cancer, whereas a third spontaneously regress. While recent studies have described the presence of an active immune response in high-grade lesions, the mechanisms underpinning clinical regression of pre-cancerous lesions remain unknown. Here, we show that host immune surveillance is strongly implicated in lesion regression. Using bronchoscopic biopsies from human subjects, we find that regressive carcinoma in-situ lesions harbour more infiltrating immune cells than those that progress to cancer. Moreover, molecular profiling of these lesions identifies potential immune escape mechanisms specifically in those that progress to cancer: antigen presentation is impaired by genomic and epigenetic changes, TGF-beta signalling is overactive, and the immunomodulator TNFSF9 is downregulated. Changes appear intrinsic to the CIS lesions as the adjacent stroma of progressive and regressive lesions are transcriptomically similar. This study identifies mechanisms by which pre-cancerous lesions evade immune detection during the earliest stages of carcinogenesis and forms a basis for new therapeutic strategies that treat or prevent early stage lung cancer.

cancer biology↗

Unmasking the tissue microecology of ductal carcinoma in situ with deep learning

Despite increasing evidence supporting the clinical relevance of tumour infiltrating lymphocytes (TILs) in invasive breast cancer, TIL spatial distribution pattern surrounding ductal carcinoma in situ (DCIS) and its association with progression is not well understood. To characterize the tissue microecology of DCIS, we designed and tested a new deep learning pipeline, UNMaSk (UNet-IM-Net-SCCNN), for the automated detection and simultaneous segmentation of DCIS ducts. This new method achieved the highest sensitivity and recall over cutting-edge deep learning networks in three patient cohorts, as well as the highest concordance with DCIS identification based on CK5 staining. Following automated DCIS detection, spatial tessellation centred at each DCIS duct created the boundary in which local ecology can be studied. Single cell identification and classification was performed with an existing deep learning method to map the distribution of TILs. In a dataset comprising grade 2-3 pure DCIS and DCIS adjacent to invasive cancer (adjacent DCIS), we found that pure DCIS cases had more TILs compared to adjacent DCIS. However, TILs co-localise significantly less with DCIS ducts in pure DCIS compared with adjacent DCIS, suggesting a more inflamed tissue ecology local to adjacent DCIS cases. Our experiments demonstrate that technological developments in deep convolutional neural networks and digital pathology can enable us to automate the identification of DCIS as well as to quantify the spatial relationship with TILs, providing a new way to study immune response and identify new markers of progression, thereby improving clinical management.

pathology↗

A portable and cost-effective microfluidic system for massively parallel single-cell transcriptome profiling

Single-cell technologies are becoming increasingly widespread and have been revolutionizing our understanding of cell identity, state, diversity and function. However, current platforms can be slow to apply to large-scale studies and resource-limited clinical arenas due to a variety of reasons including cost, infrastructure, sample quality and requirements. Here we report DNBelab C4 (C4), a negative pressure orchestrated, portable and cost-effective device that enables high-throughput single-cell transcriptional profiling. C4 system can efficiently allow discrimination of species-specific cells at high resolution and dissect tissue heterogeneity in different organs, such as murine lung and cerebral cortex. Finally, we show that the C4 system is comparable to existing platforms but has huge benefits in cost and portability and, as such, it will be of great interest for the wider scientific community.

genomics↗

Genome-wide quantitative trait loci mapping on Verticilliumw

Cotton Verticillium wilt (VW) is a devastating disease seriously affecting fiber yield and quality, and the most effective and economical prevention measure at present is selection and extension of Gossypium varieties harboring high resistant VW. However, multiple attempts to improve the VW resistance of the most widely cultivated Upland cotton have brought in little significant progress, and it seems necessary and urgent to develop Chromosome segment substitution lines (CSSLs) for merging the superior genes related with high yield and wide adaptation from G. hirsutum and VW resistance and excellent fiber quality from G. barbadense. In this study, 300 CSSLs were chosen from the developed BC5F3:5 CSSLs constructed by G. hirsutum CCRI36 and G. barbadense Hai1 to conduct quantitative trait locus (QTL) mapping on VW resistance, and a total of 53 QTLs relevant to VW disease index (DI) were identified together with the phenotypic data of 2 years investigations in two fields with two replications per year. All the QTLs were distributed on 20 chromosomes with phenotypic variation of 3.74-11.89%, of which 29 stable ones were consistent in at least two environments. Based on Meta-analysis on the 53 QTLs, 43 novel ones were identified, while 10 ones consistent to previously identified QTLs. Meanwhile, 32 QTL hotspot regions were detected, including 15 ones were novel. This study concentrates on QTL identification and screening hotspot region related with VW in the 300 CSSLs, which lay a solid platform not only for revealing the genetic and molecular mechanisms of VW resistance, but also for further fine mapping, gene cloning and molecular designing in breeding program for resistant cotton varieties.

plant biology↗

Pathway engineering in yeast for synthesizing the complex polyketide bikaverin

Fungal polyketides display remarkable structural diversity and bioactivity, and therefore the biosynthesis and engineering of this large class of molecules is therapeutically significant. Here, we successfully recoded, constructed and characterized the biosynthetic pathway of the formation of bikaverin, a tetracyclic polyketide with antibiotic, antifungal and anticancer properties, in S. cerevisiae. We used a green fluorescent protein (GFP) tagging strategy to identify the low expression of Bik1 (polyketide synthase) as the bottleneck step in the pathway, and a promoter exchange strategy to increase expression of Bik1 and bikaverin yield. To further increase product yield, we used an enzyme-fusion strategy to couple the monooxygenase (Bik2) and methyltransferase (Bik3) to efficiently channel intermediates between modifying enzymes, leading to a dramatic improvement of Bikaverin yield of nearly 60-fold. This study demonstrates that the biosynthesis of complex polyketides biosynthesis can be established and efficiently engineered in S. cerevisiae, highlighting the great potential for natural product synthesis and large-scale fermentation in yeast.

synthetic biology↗

Microtubule-mediated nuclear deformation drives the Epithelial-to-Mesenchymal Transition and breast cancer.

Morphology dictates how cells sense physical and soluble cues in their environment; thus contributing to fate decisions. The differentiation of epithelial cells into mesenchymal forms, or epithelial-mesenchymal plasticity (EMP), is essential for metazoan development and homeostasis. Here we show that the decision to engage EMP is coupled to cell morphology by cell-cell adhesions by microtubule and nuclear organization (MTNO). Using an integrative omic approach we identify Junctional Adhesion Molecule 3 (JAM3) as a new tumour suppressor in breast cancer patients. JAM3 depletion in epithelial cells alters MTNO and causes differentiation into mesenchymal forms. Soluble TGF{beta} also changes MTNO, and synergizes with JAM3 depletion to promote mesenchymal morphogenesis. Through systematic proteomic analysis we show that changes in MTNO lead to the upregulation of an inflammatory signalling network where YAP/TAZ, FOXO, IKK-NFKB, and JNK pathways are active; but where insulin signalling is suppressed. The actions of the MT-motor Kinesin-1 serve to both change MTNO and promote the upregulation of the core EMP network. Critically, the upregulation of the EMP network predicts the mesenchymal state across cancers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=137 HEIGHT=200 SRC="FIGDIR/small/689737v3_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@6ab6d1org.highwire.dtl.DTLVardef@8787borg.highwire.dtl.DTLVardef@1dff5dorg.highwire.dtl.DTLVardef@16856a1_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Ranking of Major Classes of Antibiotics for Activity against Stationary Phase Pseudomonas aeruginosa and Identification of Clinafloxacin + Cefuroxime + Gentamicin Drug Combination that Eradicates Persistent P. aeruginosa Infection in a Murine Cystic Fibrosis Model

Pseudomonas aeruginosa can cause serious persistent infections such as ventilator-associated pneumonia, sepsis, biofilm-related infections as in cystic fibrosis (CF) patients. Although CF lung infections can be treated with antibiotics, full clearance is difficult due to P. aeruginosa persistence. While antibiotic activity against growing P. aeruginosa is well documented, their activity against the non-growing persisters enriched in stationary phase cultures has not been well studied. Here, we systematically evaluated and ranked the six major classes of antibiotics, cell wall and cell membrane inhibitors, protein synthesis inhibitors, DNA synthesis inhibitors, RNA synthesis inhibitors, sulfa drugs, and nitrofurantoin, for their activity against both growing and persister forms of P. aeruginosa using colony forming count (CFU) and SYBR Green I/Propidium Iodide (PI) viability assay. Among the six major classes of antibiotics, cell wall and cell membrane inhibitors (Cefuroxime and Colistin), DNA synthesis inhibitors (Clinafloxacin) and sulfa drugs (Sulfamethoxazole) had good activity against stationary phase cells. In contrast, protein synthesis inhibitors (Gentamicin), RNA synthesis inhibitor (Rifampicin) and Nitrofurantoin had relatively poor activity against the stationary phase P. aeruginosa but relatively high activity against log phase P. aeruginosa. Clinafloxacin is the only single drug that could completely kill all (109 CFU) stationary phase cells in a 4 day drug exposure. The Cefuroxime + Gentamicin+ Clinafloxacin combination could kill all biofilm bacteria in 2 days whereas the clinically used drug combination Cefuroxime + Gentamicin + Colistin only partially killed the biofilm bacteria with 103 CFU remaining. In a murine persistent CF lung infection model, only Cefuroxime + Gentamicin+ Clinafloxacin cleared all bacteria in the infected lungs, whereas Clinafloxacin alone, or Cefuroxime + Clinafloxacin, or the current recommended drug combination Cefuroxime + Gentamicin, all failed to completely clear the bacterial load in the lungs. The complete sterilization of the bacterial load is a property of Clinafloxacin combination, as Cefuroxime + Gentamicin+ Levofloxacin combination was unable to clear the bacterial load in the lungs. Our findings demonstrate the importance of persister drug clinafloxacin, offer new therapeutic approaches for more effective treatment of persistent P. aeruginosa infections, and may have implications for treating other persistent infections.

microbiology↗

In vitro prototyping and rapid optimization of biosynthetic enzymes for cellular design

Microbial cell factories offer an attractive approach for production of biobased products. Unfortunately, designing, building, and optimizing biosynthetic pathways remains a complex challenge, especially for industrially-relevant, non-model organisms. To address this challenge, we describe a platform for in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (iPROBE). In iPROBE, cell lysates are enriched with biosynthetic enzymes by cell-free protein synthesis and then metabolic pathways are assembled in a mix-and-match fashion to assess pathway performance. We demonstrate iPROBE with two examples. First, we tested and ranked 54 different pathways for 3-hydroxybutyrate production, improving in vivo production in Clostridium by 20-fold to 14.63 {+/-} 0.48 g/L and identifying a new biosynthetic route to (S)-(+)-1,3-butanediol. Second, we used iPROBE and data-driven design to optimize a 6-step n-butanol pathway, increasing titers 4-fold across 205 pathways, and showed strong correlation between cell-free and cellular performance. We expect iPROBE to accelerate design-build-test cycles for industrial biotechnology.

synthetic biology↗

A Drug Combination Approach Targeting Both Growing Bacteria and Dormant Persisters Eradicate Persistent Staphylococcus aureus Biofilm Infection

Staphylococcus aureus can cause a variety of infections, many of which involve biofilm infections. Inside biofilms, growing and non-growing bacteria such as persisters co-exist, making it challenging to completely eradicate a persistent and recurrent infection with current treatments. Despite the clinical relevance, most of the current antibiotic treatments mainly kill the growing bacteria and have poor activity against non-growing persister bacteria and thus have limited effect on treating persistent infections including biofilm infections. We previously proposed a Yin-Yang model using a drug combination approach targeting both growing bacteria and persister bacteria for more effective clearance of persistent infections. Here, as a proof of principle, we showed that combining drugs that have high activity against growing forms, such as vancomycin or meropenem, with drugs that have robust anti-persister activity, such as clinafloxacin and oritavancin, could completely eradicate S. aureus biofilm bacteria in vitro. In contrast, single or two drugs including the current treatment for persistent S. aureus infection doxycycline plus rifampin failed to kill all biofilm bacteria in vitro. We then developed a chronic persistent skin infection mouse model with biofilm-seeded bacterial inocula demonstrating that biofilm bacteria caused more severe and persistent skin lesions than log phase S. aureus bacteria. More importantly, we found that the drug combination which eradicated biofilm bacteria in vitro is more efficacious than current treatments and completely eradicated S. aureus biofilm infection in mice. The complete eradication of biofilm bacteria is attributed to the unique high anti-persister activity of clinafloxacin, which could not be replaced by other fluoroquinolones such as moxifloxacin, levofloxacin or ciprofloxacin. Our study is the first to demonstrate that the combination of meropenem, daptomycin, plus clinafloxacin completely cleared the persistent infection, healed the lesions, and had less inflammation, while mice treated with doxycycline plus rifampin, the current clinically recommended treatment for chronic tissue infection, failed to do so. We also compared our persister drug combination with other approaches for treating persistent infections including gentamicin+fructose and ADEP4+rifampin in the S. aureus biofilm infection mouse model. Neither gentamicin+fructose nor ADEP4+rifampin could eradicate or cure the persistent biofilm infection in mice. In contrast, our drug combination regimen with persister drug clinafloxacin plus meropenem and daptomycin completely eradicated and cured the persistent biofilm infection in 7 days. An unexpected observation is that ADEP4 treatment group developed worsened skin lesions and caused more extensive pathology than the untreated control mice. Our study demonstrates an important treatment principle for persistent infections by targeting both growing and non-growing heterogeneous bacterial populations utilizing persister drugs for more effective eradication of persistent and biofilm infections. Our findings may have implications for improved treatment of many other persistent infections in general.

microbiology↗

Fractal dimension, occupancy and hotspot analyses of B cell spatial distribution predict clinical outcome in breast cancer

While the density of tumor-infiltrating lymphocytes (TILs) is now well known to correlate with clinical outcome, the clinical significance of spatial distribution of TILs is not well characterized. We have developed novel statistical techniques (including fractal dimension differences, a hotspot analysis, a box counting method that we call occupancy and a way to normalize cell density that we call thinning) to analyze the spatial distribution (at different length scales) of various types of TILs in triple negative breast tumors. Consistent with prior reports, the density of CD20+ B cells within tumors is not correlated with clinical outcome. However, we found that their spatial distribution differs significantly between good clinical outcome (no recurrence within at least 5 years of diagnosis) and poor clinical outcome (recurrence with 3 years of diagnosis). Furthermore, CD20+ B cells are more spatially dispersed in good outcome tumors and are more likely to infiltrate into cancer cell islands. Lastly, we found significant correlation between the spatial distributions of CD20+ B cells and CD8+ (cytotoxic) T cells (as well as CD3+ T cells), regardless of outcome. These results highlight the significance of the spatial distribution of TILs, especially B cells, within tumors.\n\nSignificance StatementImmune cells can fight cancer. For example, a patient has a good prognosis when a high density of killer T cells, a type of immune cell that can kill cancer cells, infiltrates into a tumor. However, there is no clear association between prognosis and the density of B cells, another type of immune cell, in a tumor. We developed several statistical techniques to go beyond cell density and look at the spatial distribution, i.e., the pattern or arrangement of immune cells, in tumors that have been removed from patients with triple negative breast cancer. We find that B cells and killer T cells tend to be more spread out in the tumors of patients whose cancer did not recur.

cancer biology↗

Circulating bacterial DNA as a tool towards non-invasive biomarkers for colorectal cancer and adenoma

ObjectiveThe gut microbiota is closely associated with colorectal neoplasia. While most metagenomics studies utilized fecal samples, circulating microbial DNA in colorectal neoplasia patients remained unexplored. This study aimed to characterize microbial DNA in plasma samples and build a machine learning model for colorectal neoplasia early detection.\n\nDesignWe performed whole genome sequencing of plasma samples from 25 colorectal cancer (CRC) patients, 10 colorectal adenoma (CRA) patients and 22 healthy controls (HC). Microbial DNA was obtained by removing the host genome and relative abundance was measured by mapping reads into microbial genomes. Significant biomarker species were identified in the discovery cohort and built into a random forest model, which was tested in the validation cohort.\n\nResultsIn the discovery cohort, there were 127 significant species between CRC patients and HC. Based on the random forest model, 28 species were selected from the discovery cohort (AUC=0.944) and yielded an AUC of 1 in the validation cohort. Interestingly, relative abundance of most biomarker species in CRA patients were between CRC patients and HC with a trend towards CRC patients. Furthermore, pathway enrichment analysis also showed similar pattern where CRA patients had intermediate relative abundance of significant pathways compared to CRC patients and HC. Finally, species network analysis revealed that CRC and HC displayed distinct patterns of species association.\n\nConclusionsWe demonstrated characteristic alteration of circulating bacterial DNA in colorectal neoplasia patients. The predictive model accurately distinguished CRC and CRA from HC, suggesting the utility of circulating bacterial biomarkers as a non-invasive tool for colorectal neoplasia screening and early diagnosis.

cancer biology↗

An ATAC-seq atlas of chromatin accessibility in mouse tissues

The Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) is a fundamental epigenomics approach and has been widely used in profiling the chromatin accessibility dynamics in multiple species. A comprehensive reference of ATAC-seq datasets for mammalian tissues is important for the understanding of regulatory specificity and developmental abnormality caused by genetic or environmental alterations. Here, we report an adult mouse ATAC-seq atlas by producing a total of 66 ATAC-seq profiles from 20 primary tissues of both male and female mice. The ATAC-seq read enrichment, fragment size distribution, and reproducibility between replicates demonstrated the high quality of the full dataset. We identified a total of 296,574 accessible elements, of which 26,916 showed tissue-specific accessibility. Further, we identified key transcription factors specific to distinct tissues and found that the enrichment of each motif reflects the developmental similarities across tissues. In summary, our study provides an important resource on the mouse epigenome and will be of great importance to various scientific disciplines such as development, cell reprogramming, and genetic disease.

genomics↗