MAnorm2 for quantitatively comparing groups of ChIP-seq samples.

Eukaryotic gene transcription is regulated by a large cohort of chromatin-associated proteins, and inferring their differential binding sites between cellular contexts requires a rigorous comparison of the corresponding ChIP-seq data. We present MAnorm2, a new computational tool for quantitatively comparing groups of ChIP-seq samples. MAnorm2 uses a hierarchical strategy for normalization of ChIP-seq data and assesses within-group variability of ChIP-seq signals based on an empirical Bayes framework. In this framework, MAnorm2 allows for abundant differential ChIP-seq signals between groups of samples as well as very different global within-group variability between groups. Using a number of real ChIP-seq data sets, we observed that MAnorm2 clearly outperformed existing tools for differential ChIP-seq analysis, especially when the groups of samples being compared had distinct global within-group variability.

First Report of Aspergillus niger causing rot of Morchella sextelata in China.

As an important edible mushroom, morel mushroom (Morchella spp.) has been widely spread and cultivated in China. However, between 2022 and 2023, a rot disease with a natural incidence of 28% occurred in morel mushroom farms in the Qingpu district of Shanghai (N30°97', E121°06'), China. High temperatures (>20℃) and high humidity (>70%) provide conditions conducive to the spread of this disease. First, a small white mold-like symptoms appeared on the surface or the pinnacle of pileus. The tissues in the infected parts stop growing and developing.Then the lesion developed to encircle the pileus and spread gradually to the stipe, seriously affecting its yield and quality. The infected tissue of morel fruiting body at the edge of the lesions was isolated and cultivated on potato dextrose agar (PDA) at 28℃ in the dark. After 3 days, monospore cultures formed black cottony colonies. In order to reliably identify, isolates were transferred to Czapek Yeast Autolysate agar (CYA) (Samson et al, 2014). On CYA fungal colonies consisted of a white mycelium, covered by a layer of black conidiophores. Scanning electron microscope analysis revealed that mature mycelia produced conidiophores ended with numerous metula and phialides. The phialides showed the number of conidia bearing rounded spores, which coincides with previous research(Silva et al, 2020). To confirm the identity of the pathogen, the genomic fragments for the internal transcribed spacer (ITS), beta-microtubulin (BenA), calmodulin (CaM), and RNA polymerase II second largest subunit (RPB2) gene of the isolate were amplified by PCR (White et al. 1990; Glass et al. 1995; Hong et al. 2005; Liu et al. 1999). The resulting sequence was deposited in GenBank with accession OQ931346.1, OR393310, OR393311, and OR393312, respectively. PCR results and morphological observations indicated the isolated strain was a pure culture and the strain was designated as MOR02. Comparison results indicated that the sequences with accession numbers KF305756.1, MK450794.1, HQ285594.1, and HQ285594.1 have high identity with the molecular sequences of A. niger MOR02, which is 99%, 98%, 98%, 99%, respectively. Phylogenetic analysis with ITS and RBP2 genes of the isolated strain and 9 Aapergillus spp. strains were performed using MEGAX software with Neighbor-Joining (NJ) method. Based on the results of growth habits, morphological observations, and phylogenetic analysis, the pathogen was identified as A. niger. A spore suspension of the A. niger strain MOR02 (1 x107 conidia/mL) was inoculated back to healthy morel mushrooms. Five healthy fruit bodies of M. sextelata were injected, and another five healthy morels were treated with potato dextrose broth（PDB） medium as controls. Morels were incubated for 7 days at 20℃ and 85% to 90% relative humidity. The pathogen successfully infected the morel showing a similar white mold-like lesion as the natural occurrence disease. The controls remained healthy without any symptoms. The pathogen was reisolated from the affected lesions and identified as A. niger MOR02 based on its morphological characteristics and phylogenetic marker genes. To our knowledge, this is the first report of A. niger causing rot disease of M. sextelata. This study confirms that A. niger is the pathogenic fungus causing morel rot on the Qingpu farm in Shanghai. The disease occurs under conditions of high humidity and high-temperature conditions. Better production management is the most important to prevent the disease.

Strata temperatures and geothermal resource evaluation in the Dongpu Depression, Bohai Bay Basin, North China.

The development of geothermal resources in the Dongpu Depression can improve not only the economic benefits of the oilfield but also the ecological environment. Therefore, it is necessary to evaluate the geothermal resources in the region. Based on the heat flow, geothermal gradient and thermal properties, the temperatures and their distribution in different strata are calculated using geothermal methods, and the geothermal resource types of the Dongpu Depression are identified. The results show that the geothermal resources include low-temperature, medium-temperature and high-temperature geothermal resources in the Dongpu Depression. The Minghuazhen and Guantao Formations mainly include low-temperature and medium-temperature geothermal resources; the Dongying and Shahejie Formations include low-temperature, medium-temperature and high-temperature geothermal resources; the Ordovician rocks mainly include medium-temperature and high-temperature geothermal resources. The Minghuazhen, Guantao and Dongying Formations can form good geothermal reservoirs and are favorable layers for exploring low-temperature and medium-temperature geothermal resources. The geothermal reservoir of the Shahejie Formation is relatively poor, and the thermal reservoirs may be developed in the western slope zone and the central uplift. The Ordovician carbonate strata can provide thermal reservoirs for geothermal resources, and the Cenozoic bottom temperature is more than 150 °C except for most of the western gentle slope zone. In addition, for the same stratum, the geothermal temperatures in the southern Dongpu Depression are higher than those in the northern depression.

HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples.

Identifying genomic regions with hypervariable ChIP-seq or ATAC-seq signals across given samples is essential for large-scale epigenetic studies. In particular, the hypervariable regions across tumors from different patients indicate their heterogeneity and can contribute to revealing potential cancer subtypes and the associated epigenetic markers. We present HyperChIP as the first complete statistical tool for the task. HyperChIP uses scaled variances that account for the mean-variance dependence to rank genomic regions, and it increases the statistical power by diminishing the influence of true hypervariable regions on model fitting. A pan-cancer case study illustrates the practical utility of HyperChIP.

Nanodrugs Manipulating Endoplasmic Reticulum Stress for Highly Effective Antitumor Therapy.

Cancer is one of the leading causes of death worldwide due to high morbidity and mortality. Many attempts and efforts have been devoted to fighting cancer. Owing to the significant role of the endoplasmic reticulum (ER) in cell function, inducing ER stress can be promising for cancer treatment. However, the sustained activation of cytoprotective unfolded protein response (UPR) presents a tremendous obstacle for drugs in inducing unsolved ER stress in tumor cells, especially small-molecule drugs with poor bioavailability. Therefore, many emerging nanodrugs inducing and amplifying ER stress have been developed for efficient cancer treatment. More importantly, the novel discovery of ER stress in immunogenic cell death (ICD) makes it possible to repurpose antitumor drugs for immunotherapy through nanodrug-based strategies amplifying ER stress. Therefore, this mini-review aims to provide a comprehensive summary of the latest developments of the strategies underlying nanodrugs in the treatment of cancer via manipulating ER stress. Meanwhile, the prospects of ER stress-inducing nanodrugs for cancer treatment are systematically discussed, which provide a sound platform for novel therapeutic insights and inspiration for the design of nanodrugs in treating cancer.

Nanomedicine Strategies for Heating "Cold" Ovarian Cancer (OC): Next Evolution in Immunotherapy of OC.

Immunotherapy has revolutionized cancer treatment, dramatically improving survival rates of melanoma and lung cancer patients. Nevertheless, immunotherapy is almost ineffective against ovarian cancer (OC) due to its cold tumor immune microenvironment (TIM). Many traditional medications aimed at remodeling TIM are often associated with severe systemic toxicity, require frequent dosing, and show only modest clinical efficacy. In recent years, emerging nanomedicines have demonstrated extraordinary immunotherapeutic effects for OC by reversing the TIM because the physical and biochemical features of nanomedicines can all be harnessed to obtain optimal and expected tissue distribution and cellular uptake. However, nanomedicines are far from being widely explored in the field of OC immunotherapy due to the lack of appreciation for the professional barriers of nanomedicine and pathology, limiting the horizons of biomedical researchers and materials scientists. Herein, a typical cold tumor-OC is adopted as a paradigm to introduce the classification of TIM, the TIM characteristics of OC, and the advantages of nanomedicines for immunotherapy. Subsequently, current nanomedicines are comprehensively summarized through five general strategies to substantially enhance the efficacy of immunotherapy by heating the cold OC. Finally, the challenges and perspectives of this expanding field for improved development of clinical applications are also discussed.

Emerging early diagnostic methods for acute kidney injury.

Many factors such as trauma and COVID-19 cause acute kidney injury (AKI). Late AKI have a very high incidence and mortality rate. Early diagnosis of AKI provides a critical therapeutic time window for AKI treatment to prevent progression to chronic renal failure. However, the current clinical detection based on creatinine and urine output isn't effective in diagnosing early AKI. In recent years, the early diagnosis of AKI has made great progress with the advancement of information technology, nanotechnology, and biomedicine. These emerging methods are mainly divided into two aspects: First, predicting AKI through models construct by machine learning; Second, early diagnosis of AKI through detection of newly-discovered early biomarkers. Currently, these methods have shown great potential and become an attractive tool for the early diagnosis of AKI. Therefore, it is very important to discuss and summarize these methods for the early diagnosis of AKI. In this review, we first systematically summarize the application of machine learning in AKI prediction algorithms and specific scenarios. In addition, we introduce the key role of early biomarkers in the progress of AKI, and then comprehensively summarize the application of emerging detection technologies for early AKI. Finally, we discuss current challenges and prospects of machine learning and biomarker detection. The review is expected to provide new insights for early diagnosis of AKI, and provided important inspiration for the design of early diagnosis of other major diseases.

A systematic dissection of the epigenomic heterogeneity of lung adenocarcinoma reveals two different subclasses with distinct prognosis and core regulatory networks.

BACKGROUND: Lung adenocarcinoma (LUAD) is a highly malignant and heterogeneous tumor that involves various oncogenic genetic alterations. Epigenetic processes play important roles in lung cancer development. However, the variation in enhancer and super-enhancer landscapes of LUAD patients remains largely unknown. To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression. RESULTS: A high intertumoral epigenetic heterogeneity is observed across the LUAD H3K27ac profiles. We quantitatively model the intertumoral variability of H3K27ac levels at proximal gene promoters and distal enhancers and propose a new epigenetic classification of LUAD patients. Our classification defines two LUAD subgroups which are highly related to histological subtypes. Group II patients have significantly worse prognosis than group I, which is further confirmed in the public TCGA-LUAD cohort. Differential RNA-seq analysis between group I and group II groups reveals that those genes upregulated in group II group tend to promote cell proliferation and induce cell de-differentiation. We construct the gene co-expression networks and identify group-specific core regulators. Most of these core regulators are linked with group-specific regulatory elements, such as super-enhancers. We further show that CLU is regulated by 3 group I-specific core regulators and works as a novel tumor suppressor in LUAD. CONCLUSIONS: Our study systematically characterizes the epigenetic alterations during LUAD progression and provides a new classification model that is helpful for predicting patient prognosis.

MAP: model-based analysis of proteomic data to detect proteins with significant abundance changes.

Isotope-labeling-based mass spectrometry (MS) is widely used in quantitative proteomic studies. With this technique, the relative abundance of thousands of proteins can be efficiently profiled in parallel, greatly facilitating the detection of proteins differentially expressed across samples. However, this task remains computationally challenging. Here we present a new approach, termed Model-based Analysis of Proteomic data (MAP), for this task. Unlike many existing methods, MAP does not require technical replicates to model technical and systematic errors, and instead utilizes a novel step-by-step regression analysis to directly assess the significance of observed protein abundance changes. We applied MAP to compare the proteomic profiles of undifferentiated and differentiated mouse embryonic stem cells (mESCs), and found it has superior performance compared with existing tools in detecting proteins differentially expressed during mESC differentiation. A web-based application of MAP is provided for online data processing at http://bioinfo.sibs.ac.cn/shaolab/MAP.

The PRC2-binding long non-coding RNAs in human and mouse genomes are associated with predictive sequence features.

Recently, long non-coding RNAs (lncRNAs) have emerged as an important class of molecules involved in many cellular processes. One of their primary functions is to shape epigenetic landscape through interactions with chromatin modifying proteins. However, mechanisms contributing to the specificity of such interactions remain poorly understood. Here we took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features of these lncRNAs by developing a new computational pipeline for sequences composition analysis, in which each sequence is considered as a series of transitions between adjacent nucleotides. Through that, PRC2-binding lncRNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features, which can be utilized to distinguish them from the others with considerable accuracy. We further identified fragments of PRC2-binding lncRNAs that are enriched with these sequence features, and found they show strong PRC2-binding signals and are more highly conserved across species than the other parts, implying their functional importance.