Abstract The identification of transcription factor binding sites and cis-regulatory motifs is a frontier whereupon the rules governing protein–DNA binding are being revealed. Here, we developed a new method (DEep Sequence and Shape mOtif or DESSO) for cis-regulatory motif prediction using deep neural networks and the binomial distribution model. DESSO outperformed existing tools, including DeepBind, in predicting motifs in 690 human ENCODE ChIP-sequencing datasets. Furthermore, the deep-learning framework of DESSO expanded motif discovery beyond the state-of-the-art by allowing the identification of known and new protein–protein–DNA tethering interactions in human transcription factors (TFs). Specifically, 61 putative tethering interactions were identified among the 100 TFs expressed in the K562 cell line. In this work, the power of DESSO was further expanded by integrating the detection of DNA shape features. We found that shape information has strong predictive power for TF–DNA binding and provides new putative shape motif information for human TFs. Thus, DESSO improves in the identification and structural analysis of TF binding sites, by integrating the complexities of DNA binding into a deep-learning framework.
Abstract 2-hydroxyglutarate (2HG) is a potent competitor of α-ketoglutarate (α-KG) and can inhibit multiple α-KG dependent dioxygenases that function on the epigenetic modifications. The accumulation of 2HG contributes to elevated risk of malignant tumors. 2HG carries an asymmetric carbon atom in its carbon backbone and differentiation between D-2-hydroxyglutarate (D-2HG) and L-2-hydroxyglutarate (L-2HG) is crucially important for accurate diagnosis of 2HG related diseases. Here we developed a strategy by chiral derivatization combined with liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) analysis for highly sensitive determination of D-2HG and L-2HG enantiomers. N -(p-toluenesulfonyl)-L-phenylalanyl chloride (TSPC) was used to derivatize 2HG. The formed diastereomers by TSPC labeling can efficiently improve the chromatographic separation of D-2HG and L-2HG. And derivatization by TSPC could also markedly increase the detection sensitivities by 291 and 346 folds for D-2HG and L-2HG, respectively. Using the developed method, we measured the contents of D-2HG and L-2HG in clear cell renal cell carcinoma (ccRCC) tissues. We observed 12.9 and 29.8 folds increase of D-2HG and L-2HG, respectively, in human ccRCC tissues compared to adjacent normal tissues. The developed chiral derivatization combined with LC-ESI-MS/MS analysis offers sensitive determination of D-2HG and L-2HG enantiomers, which benefits the precise diagnosis of 2HG related metabolic diseases.
Understanding how root systems modulate shoot system phenotypes is a fundamental question in plant biology and will be useful in developing resilient agricultural crops. Grafting is a common horticultural practice that joins the roots (rootstock) of one plant to the shoot (scion) of another, providing an excellent method for investigating how these two organ systems affect each other. In this study, we used the French-American hybrid grapevine 'Chambourcin' (Vitis L.) as a model to explore the rootstock-scion relationship. We examined leaf shape, ion concentrations, and gene expression in 'Chambourcin' grown ungrafted as well as grafted to three different rootstocks ('SO4', '1103P' and '3309C') across 2 years and three different irrigation treatments. We found that a significant amount of the variation in leaf shape could be explained by the interaction between rootstock and irrigation. For ion concentrations, the primary source of variation identified was the position of a leaf in a shoot, although rootstock and rootstock by irrigation interaction also explained a significant amount of variation for most ions. Lastly, we found rootstock-specific patterns of gene expression in grafted plants when compared to ungrafted vines. Thus, our work reveals the subtle and complex effect of grafting on 'Chambourcin' leaf morphology, ionomics, and gene expression.
<div>Abstract<p>Tumor hypoxia has been shown to predict poor patient outcomes in several cancer types, partially because it reduces radiation’s ability to kill cells. We hypothesized that some of the clinical effects of hypoxia could also be due to its impact on the tumor microbiome. Therefore, we examined the RNA sequencing data from the Oncology Research Information Exchange Network database of patients with colorectal cancer treated with radiotherapy. We identified microbial RNAs for each tumor and related them to the hypoxic gene expression scores calculated from host mRNA. Our analysis showed that the hypoxia expression score predicted poor patient outcomes and identified tumors enriched with certain microbes such as <i>Fusobacterium nucleatum</i>. The presence of other microbes, such as <i>Fusobacterium canifelinum</i>, predicted poor patient outcomes, suggesting a potential interaction between hypoxia, the microbiome, and radiation response. To experimentally investigate this concept, we implanted CT26 colorectal cancer cells into immune-competent BALB/c and immune-deficient athymic nude mice. After growth, in which tumors passively acquired microbes from the gastrointestinal tract, we harvested tumors, extracted nucleic acids, and sequenced host and microbial RNAs. We stratified tumors based on their hypoxia score and performed a metatranscriptomic analysis of microbial gene expression. In addition to hypoxia-tropic and -phobic microbial populations, analysis of microbial gene expression at the strain level showed expression differences based on the hypoxia score. Thus, hypoxia gene expression scores seem to associate with different microbial populations and elicit an adaptive transcriptional response in intratumoral microbes, potentially influencing clinical outcomes.</p>Significance:<p>Tumor hypoxia reduces radiotherapy efficacy. In this study, we explored whether some of the clinical effects of hypoxia could be due to interaction with the tumor microbiome. Hypoxic gene expression scores associated with certain microbes and elicited an adaptive transcriptional response in others that could contribute to poor clinical outcomes.</p></div>
<p>Demographic variables stratified by low and high hypoxia scores, showing no significant differences to be controlled for in the Cox proportional hazards model described in Figure 1D.</p>
<p>Cox proportional hazards model results for the interaction terms between hypoxia (binary, low or high) with microbe relative abundance in COADREAD tumors treated with radiotherapy.</p>
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