Biology subjects

Hao, D.

Publications and source records attributed to Hao, D..

23 records · Page 2Linked to original sources

bioRxiv2020

Resolving the spatial and cellular architecture of lung adenocarcinoma by multi-region single-cell sequencing

Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing of 186,916 cells from 5 early-stage LUADs and 14 multi-region normal lung tissues of defined spatial proximities from the tumors. We show that cellular lineages, states, and transcriptomic features geospatially evolve across normal regions to LUADs. LUADs also exhibit pronounced intratumor cell heterogeneity within single sites and transcriptional lineage-plasticity programs. T regulatory cell phenotypes are increased in normal tissues with proximity to LUAD, in contrast to diminished signatures and fractions of cytotoxic CD8+ T cells, antigen-presenting macrophages and inflammatory dendritic cells. We further find that the LUAD ligand-receptor interactome harbors increased expression of epithelial CD24 which mediates pro-tumor phenotypes. These data provide a spatial atlas of LUAD evolution, and a resource for identification of targets for its treatment. Statement of significanceThe geospatial ecosystem of the peripheral lung and early-stage LUAD is not known. Our multi-region single-cell sequencing analyses unravel cell populations, states, and phenotypes in the spatial and ecological evolution of LUAD from the lung that comprise high-potential targets for early interception.

cancer biology↗

bioRxiv2020

Single-cell Characterization of Acute Myeloid Leukemia and its Microenvironment Following PD-1 Blockade Based Therapy

Acute myeloid leukemia (AML) and effector cells of immune checkpoint blockade (ICB) therapy co-reside in a complex bone marrow (BM) milieu. The interplay of tumor intrinsic and microenvironment (TME) mechanisms that influences the response to ICB-based therapies in AML have not been elucidated. Here we report our analyses of single cell RNA profiling of more than 127,000 BM cells from healthy donors and relapsed/refractory (R/R) AML patients at pre/post treatment with azacitidine/nivolumab, paired with single cell T cell receptor (TCR) repertoire profiles, to uncover factors impacting response and resistance. Loss of chromosome 7/7q conferred an immunosuppressive TME and was associated with resistance to ICB-based therapy in R/R AML. Our trajectory analysis revealed a continuum of CD8+ T cell phenotypes, characterized by differential expression of granzyme B (GZMB) and GZMK. GZMK expression defined a BM residing memory CD8+ T cell subset with stem-like properties likely an intermediary between naive and cytotoxic lymphocytes. Responses to ICB-based therapy were primarily driven by novel and expanded T cell clonotypes. Our findings support an adaptable T cell plasticity in response to PD-1 blockade in AML. Disentangling AML cells from their complex, immune-rich microenvironment revealed characteristics that shaped resistance to ICB-based therapy and could inform strategies to target AML vulnerabilities. SignificanceDetermining the cellular and molecular underpinnings of response and resistance to PD-1 blockade based therapy in AML can guide immune-based therapeutic strategies. Our results reveal AML intrinsic characteristics (chromosome 7/7q status and oxidative stressors) and tumor microenvironment to modulate responses to checkpoint blockers. CD8 cells exist in the bone marrow in a continuum with GZMK expression defining a memory, stem-like T cell population that could play a role in response to therapy.

cancer biology↗

bioRxiv2020

Deficiency in reverse cholesterol transport in mice augments sepsis

BackgroundSepsis claims over 215,000 lives and costs $16.7 billion per year in America alone. Recent studies revealed that HDL receptor scavenger receptor BI (SR-BI or Scarb1) plays a critical protective role in sepsis. Using Scarb1I179N mice, a mutant SR-BI mouse model with 90% depletion in hepatic SR-BI, we previously reported that the mutant mice are susceptible to cecal ligation and puncture (CLP)-induced sepsis. However, using a hypo-AlbCreSR-BIfl/fl mouse model, Hubys group showed that the liver-specific SR-BI KO mice are not more susceptible to CLP-induced sepsis. In this study, we generated a new floxed SR-BI mouse model to clarify the contribution of hepatic SR-BI in sepsis. SR-BI is known as a receptor that plays a key role in reverse cholesterol transport (RCT) by uptaking cholesterol to the liver. So, our established AlbCreSR-BIfl/fl mice (liver-specific SR-BI KO) is an RCT deficiency mice model that can be used to understand the mechanisms of RCT protecting against sepsis and may provide new insight into the pathogenesis of sepsis. Methods and ResultsWe generated SR-BIfl/fl mice by flanking exon 2. We bred the floxed mice with AlbCre mice to generate AlbCreSR-BIfl/fl mice (liver-specific SR-BI KO mice), then the mice were backcrossed to C57BL/6J for 10 generations. As shown in Fig 1, the liver SR-BI expression was normal in SR-BIfl/fl mice as compared to C57BL/6J (B6) mice, but completely depleted in AlbCreSR-BIfl/fl mice. Using this liver-specific SR-BI KO model, we observed that a deficiency in RCT rendered the mice highly susceptible to CLP-induced sepsis as shown by 80% and 14.3% survival of SR-BIfl/fl and AlbCreSR-BIfl/fl mice, respectively. We found aggravated inflammatory cytokine production, altered leukocyte recruitment and slightly increased in the blood and peritoneal bacteria. Moreover, we found RCT deficiency mice increased both free and total cholesterol levels in serum and showed severer hemolysis in AlbCreSR-BIfl/fl mice than SR-BIfl/fl mice during CLP-induced sepsis. Importantly, when we fed AlbCreSR-BIfl/fl mice with probucol to decrease the cholesterol level in serum before performing CLP, the survival rate of AlbCreSR-BIfl/fl mice improved to 88.9%. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/051250v1_fig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@80f819org.highwire.dtl.DTLVardef@12064dborg.highwire.dtl.DTLVardef@1bd8e72org.highwire.dtl.DTLVardef@1d30b5e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO Mice deficient in hepatic SR-BI are susceptible to CLP-induced septic death. A, PCR genotyping of AlbCreSR-BIfl/fl mice using tail DNA. B, Western blot analysis of SR-BI expression in the liver; C, survival analysis. AlbCreSR-BIfl/fl (n = 14) and SR-BIfl/fl mice (n = 10) were treated with CLP (23G needle, half ligation) and survival was observed for 7 days. The data were expressed as the percentage of mice surviving at indicated times, and survival was analyzed by Log-Rank x2 test. D, AlbCreSR-BIfl/fl and SR-BIfl/fl mice were treated with CLP for the indicated times, and kidney injury was assessed by measuring blood urea nitrogen (BUN) levels; and E, liver injury was assessed by measuring serum alanine aminotransferase (ALT) levels. n = 6 - 7 each group, mean {+/-} SEM. C_FIG ConclusionsDeficiency RCT resulting in abnormal metabolism of cholesterol and lipid metabolism is a risk factor in sepsis and maintain normal metabolism of cholesterol may provide a new insight for sepsis therapies.

molecular biology↗

bioRxiv2020

GeneDMRs: an R package for Gene-based Differentially Methylated Regions analysis

DNA methylation in gene or promoter or gene body could restrict/promote the gene transcription. Moreover, methylation in the gene regions along with CpG island regions could modulate the transcription to undetectable gene expression levels. Therefore, it is necessary to investigate the methylation levels within the gene, gene body, CpG island regions and their overlapped regions and then identify the gene-based differentially methylated regions (GeneDMRs). Here, R package GeneDMRs aims to facilitate computing gene based methylation rate using next generation sequencing (NGS)-based methylome data. The user-friendly R package GeneDMRs is presented to analyze the methylation levels in each gene/promoter/exon/intron/CpG island/CpG island shore or each overlapped region (e.g., gene-CpG island/promoter-CpG island/exon-CpG island/intron-CpG island/gene-CpG island shore/promoter-CpG island shore/exon-CpG island shore/intron-CpG island shore). Here, we used the public reduced representation bisulfite sequencing (RRBS) data of mouse (GSE62392) for evaluating software and found novel biologically significant results to supplement the previous research. The R package GeneDMRs can facilitate computing gene based methylation rate to interpret complex interplay between methylation levels and gene expression differences or similarities across physiological conditions or disease states.

bioinformatics↗

bioRxiv2017

ZmCOL3, a CCT-domain containing gene affects maize adaptation as a repressor and upstream of ZmCCT

Flowering time is a vital trait to control the adaptation of flowering plants to different environments. CCT-domain containing genes are considered to play an important role in plants flowering. Among 53 maize CCT family genes, 28 of them were located in the flowering time QTL regions and 16 genes were significant associated with flowering time based on candidate gene-based association mapping analysis. Furthermore, a CCT gene named as ZmCOL3 was validated to be a flowering repressor upstream of ZmCCT which is one of the key genes regulating maize flowering. The overexpressed ZmCOL3 could delay flowering time about 4 days whether in long day or short day conditions. The absent of one cytosine in 3UTR and the present of 551bp fragment in promoter regions are likely the causal polymorphisms which may contribute to the maize adaptation from tropical to temperate regions. ZmCOL3 could transactivate ZmCCT transcription or interfere circadian clock to inhibit flowering which was integrated in the modified model of maize photoperiod pathway.\n\nHighlightMaize CCT genes influence flowering time in different latitude environments and one of them named ZmCOL3 is a flowering time repressor which could transactivate ZmCCT transcription to delay flowering.

genetics↗