Biology subjects

Meng, P.

Publications and source records attributed to Meng, P..

5 recordsLinked to original sources

bioRxiv2026

PPARγ brakes cytosolic DNA-induced macrophage inflammation by super-enhancer metabolic reprogramming

Cytoplasmic DNA sensing triggers intense innate immune responses that require tight regulation. PPAR{gamma} is a master metabolic regulator in macrophages, but its role in cytoplasmic DNA immunity remains unclear. Using poly(dA:dT) to mimic cytoplasmic DNA stimulation, we combined transcriptomics, epigenomics (PPAR{gamma}/H3K27ac ChIP-seq), and functional assays. Poly(dA:dT) induced a cytokine storm with MAPK activation and apoptosis/necrosis. PPAR{gamma} activation by rosiglitazone (RGZ) antagonized this response, reducing cell death and transcriptionally inhibiting MAPK genes (e.g., DUSP4/10). Mechanistically, PPAR{gamma} bound promoters/enhancers via PPRE motifs and distal intergenic regions, remodeling H3K27ac (reduced at inflammatory loci, increased at metabolic genes). RGZ induced de novo super-enhancers coupling PPAR metabolic programs (e.g., CPT2) with immune suppression by targeting TLR4, CEBPB, and PIM3. Thus, PPAR{gamma} acts as a brake in cytoplasmic DNA immunity, integrating metabolic reprogramming and inflammation suppression through a multi-level genomic/epigenetic program. This study highlights PPAR{gamma} as a key immune-metabolic integrator and therapeutic target for diseases driven by excessive cytoplasmic DNA sensing.

immunology↗

bioRxiv2026

Noninvasive tomography of tumor progression via dynamical changes of T-cells in surrounding microenvironment

Tumor progression is shaped by a continuous competition between malignant expansion and immune access within the surrounding microenvironment. Although spatial assays can reveal where T cells accumulate, most current approaches remain descriptive, treating immune organization as a static pattern and failing to infer the latent resistance structure that governs progression. Here we show that changes in peri-tumoral T-cell distribution can support noninvasive tomography of tumor progression. Using spatially resolved human breast tumor sections and controlled numerical experiments, we formulate immune-tumor interaction within a mean-field game framework in which T cells act as agents responding to a heterogeneous microenvironment while the tumor shapes an equivalent barrier field that restricts infiltration. This framework converts boundary enrichment, layered blocking and core penetration patterns into a constrained inference problem whose solution yields quantitative maps of immune exclusion, barrier strength and progression-associated internal states. Forward simulations show that barrier geometry reshapes immune-density equilibria, and inference experiments show that closely related barrier fields can be recovered from immune-density observations under controlled and tissue-shaped proxy settings. By linking observable T-cell redistribution to latent microenvironmental resistance, this approach establishes a route toward noninvasive, repeatable assessment of tumor progression without direct biopsy of the underlying barrier structure.

cancer biology↗

bioRxiv2021

GSA: An Independent Development Algorithm for Calling Copy Number and Detecting Homologous Recombination Deficiency (HRD) from Target Capture Sequencing

BackgroundThe gain or loss of large chromosomal regions or even whole chromosomes is termed as genomic scarring and can be observed as copy number variations resulting from the failure of DNA damage repair. ResultsIn this study, a new algorithm called Genomic Scar Analysis (GSA) has developed and validated to calculate homologous recombination deficiency (HRD) score. The two critical submodules were tree recursion (TR) segmentation and filtering, and the estimation and correction of the tumor purity and ploidy. Then, this study evaluated the rationality of segmentation and genotype identification by the GSA algorithm and compared with other two algorithms, PureCN and ASCAT, found that the segmentation result of GSA algorithm was more logical. In addition, the results indicated that the GSA algorithm had an excellent predictive effect on tumor purity and ploidy, if the tumor purity was more than 20%. Furtherly, this study evaluated the HRD scores and BRCA1/2 deficiency status of 195 clinical samples, and the results indicated that the accuracy was 0.98 (comparing with Affymetrix OncoScan assay) and the sensitivity was 95.2% (comparing with BRCA1/2 deficiency status), both were well-behaved. Finally, HRD scores and 16 genes mutations (TP53 and 15 HRR pathway genes) were analyzed in 17 cell lines, the results showed that there was higher frequency in HRR pathway genes in high HRD score samples. ConclusionsThis new algorithm, named as GSA, could effectively and accurately calculate the purity and ploidy of tumor samples through NGS data, and then reflect the degree of genomic instability and large-scale copy number variations of tumor samples.

bioinformatics↗

bioRxiv2020

Endosomal spatio-temporal modulation of the cortical RhoA zone conditions epithelial cell organization

At the basis of cell shape and behavior, actomyosin organization and force-generating property are widely studied, however very little is known about the regulation of the contractile network in space and time. Here we study the role of the epithelial-specific protein EpCAM, a contractility modulator, in cell shape and motility, and we show that it is required for the maturation of stress fibers and frontrear polarity acquisition at the single cell level. There, EpCAM ensures the remodeling of a transient active RhoA zone in the cortex of spreading epithelial cells. GTP-RhoA follows the endosomal pathway mediated by Rab35 and EHD1, where it co-evolves together with EpCAM. In fact, EpCAM balances GTP-RhoA turnover in order to tune actomyosin remodeling for cell shape, polarity and mechanical property acquisition. Impairment of GTP-RhoA endosomal trafficking either by EpCAM silencing or Rab35 / EHD1 mutant expression prevents correct myosin-II activity, stress fiber formation, and ultimately cell polarization. Collectively, this work shows that the coupling of EpCAM/RhoA co-trafficking to actomyosin rearrangement is critical for spreading, and advances our understanding of how biochemical and mechanical properties can be coupled for cell plasticity.

cell biology↗

bioRxiv2018

A computational protocol to characterize elusive Candidate Phyla Radiation bacteria in oral environments using metagenomic data

Several studies have documented the diversity and potential pathogenic associations of organisms in the human oral cavity. Although much progress has been made in understanding the complex bacterial community inhabiting the human oral cavity, our understanding of some microorganisms is less resolved due to a variety of reasons. One such little-understood group is the candidate phyla radiation (CPR), which is a recently identified, but highly abundant group of ultrasmall bacteria with reduced genomes and unusual ribosomes. Here, we present a computational protocol for the detection of CPR organisms from metagenomic data. Our approach relies on a self-constructed dataset comprising published CPR genomic sequences as a filter to identify CPR sequences from metagenomic sequencing data. After assembly and functional prediction, the taxonomic affiliation of CPR contigs can be identified through phylogenetic analysis with publically available 16S rRNA gene and ribosomal proteins, in addition to sequence similarity analyses (e.g., average nucleotide identity calculations and contig mapping). Using this protocol, we reconstructed two draft genomes of organisms within the TM7 superphylum, that had genome sizes of 0.594 Mb and 0.678 Mb. Among the predicted functional genes of the constructed genomes, a high percentage were related to signal transduction, cell motility, and cell envelope biogenesis, which could contribute to cellular morphological changes in response to environmental cues.\n\nImportanceCandidate phyla radiation (CPR) bacterial group is a recently identified, but highly diverse and abundant group of ultrasmall bacteria exhibiting reduced genomes and limited metabolic capacities. A number of studies have reported their potential pathogenic associations in multiple mucosal diseases including periodontitis, halitosis, and inflammatory bowel disease. However, CPR organisms are difficult to cultivate and are difficult to detect with PCR-based methods due to divergent genetic sequences. Thus, our understanding of CPR has lagged behind that of other bacterial component. Here, we used metagenomic approaches to overcome these previous barriers to CPR identification, and established a computational protocol for detection of CPR organisms from metagenomic samples. The protocol describe herein holds great promise for better understanding the potential biological functioning of CPR. Moreover, the pipeline could be applied to other organisms that are difficult to cultivate.

bioinformatics↗