Abstract
Background
Heat shock transcription factor1 (HSF1) was overexpressed to promote glutaminolysis and activate mTOR in colorectal cancer (CRC). Here, we investigated the mechanism for ...cancer-specific overexpression of HSF1.
Methods
HSF1 expression was analyzed by chromatin immunoprecipitation, qRT-PCR, immunohistochemistry staining and immunoblotting. HSF1 translation was explored by polysome profiling and nascent protein analysis. Biotin pulldown and m6A RNA immunoprecipitation were applied to investigate RNA/RNA interaction and m6A modification. The relevance of HSF1 to CRC was analyzed in APC
min/+
and APC
min/+
HSF1
+/−
mice.
Results
HSF1 expression and activity were reduced after the inhibition of WNT/β-catenin signaling by pyrvinium or β-catenin knockdown, but elevated upon its activation by lithium chloride (LiCl) or β-catenin overexpression. There are much less upregulated genes in HSF1-KO MEF treated with LiCl when compared with LiCl-treated WT MEF. HSF1 protein expression was positively correlated with β-catenin expression in cell lines and primary tissues. After β-catenin depletion, HSF1 mRNA translation was impaired, accompanied by the reduction of its m6A modification and the upregulation of miR455-3p, which can interact with 3′-UTR of HSF1 mRNA to repress its translation. Interestingly, inhibition of miR455-3p rescued β-catenin depletion-induced reduction of HSF1 m6A modification and METTL3 interaction. Both the size and number of tumors were significantly reduced in APC
min/+
mice when HSF1 was genetically knocked-out or chemically inhibited.
Conclusions
β-catenin suppresses miR455-3p generation to stimulate m6A modification and subsequent translation of HSF1 mRNA. HSF1 is important for β-catenin to promote CRC development. Targeting HSF1 could be a potential strategy for the intervention of β-catenin-driven cancers.
Pre-implantation embryo development is an intricate and precisely regulated process orchestrated by maternally inherited proteins and newly synthesized proteins following zygotic genome activation. ...Although genomic and transcriptomic studies have enriched our understanding of the genetic programs underlying this process, the protein expression landscape remains unexplored. Using quantitative mass spectrometry, we identified nearly 5,000 proteins from 8,000 mouse embryos of each stage (zygote, 2-cell, 4-cell, 8-cell, morula, and blastocyst). We found that protein expression in zygotes, morulas, and blastocysts is distinct from 2- to 8-cell embryos. Analysis of protein phosphorylation identified critical kinases and signal transduction pathways. We highlight key factors and their important roles in embryo development. Combined analysis of transcriptomic and proteomic data reveals coordinated control of RNA degradation, transcription, and translation and identifies previously undefined exon-junction-derived peptides. Our study provides an invaluable resource for further mechanistic studies and suggests core factors regulating pre-implantation embryo development.
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•Comprehensive quantitative proteomic study of mouse pre-implantation embryos•Phosphoproteomic analysis identified key kinases and important signaling pathways•Identified poorly studied key factors in early embryos and showed functional importance•Proteogenomic analysis identified previously undefined exon-junction-derived peptides
Proteomic analysis of pre-implantation embryos has not been explored for the minimal amount of material available. Gao et al. used a quantitative mass spectrometry strategy to elucidate the dynamic changes of the embryo proteome from the zygote to the blastocyst stage, which provides direct insight into the molecular details governing embryonic development.
Three TiO2 and Zn-Al-layered double hydroxide composites, denoted LDH-TiO2 composites, were prepared using the sol–gel method and characterized utilizing scanning and transmission electron microscopy ...with energy dispersive spectroscopy, ultraviolet–visible diffuse reflectance spectroscopy, X-ray diffraction, N2 adsorption–desorption, X-ray photoelectron spectroscopy, photocurrent, photoluminescence and electrochemical impedance spectroscopy techniques. The characterization results illustrated that TiO2 was attached onto the surface of LDH and the sizes of both TiO2 and LDH particles were in the nanoscale range. The combination of LDH and TiO2 promoted the photogenerated electron–hole transfer and separation. The removal abilities of the LDH-TiO2 composites for Cr(VI) were evaluated using the synergistic adsorption and photocatalytic method. The adsorption percentages of the three LDH-TiO2 composites for 20.0 mg/L Cr(VI) solutions ranged between 26% and 75%, and upon ultraviolet irradiation, the total removal percentages rapidly increased to approximately 100%. The removal efficiency for Cr(VI) depended on the TiO2 contents of the LDH-TiO2 composites. Increasing the TiO2 percentage resulted in decrease in the adsorption capacities and increase in the photocatalytic removal ratios. The kinetic and isothermal data well fitted the pseudo-second-order and Langmuir equations, respectively. The high removal efficiencies suggested that the composites were suitable for the treatment of Cr(VI)-containing wastewater.
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•The removal percentage of LDH-TiO2 composites for 20 mg/L Cr(VI) approached 100%.•The combination of Zn-Al-LDH and TiO2 promoted photoinduced charge transport.•Cr(VI) was removed using LDH-TiO2 via synergistic adsorption and photocatalysis.
A growing body of research indicates that microorganisms play a crucial role in human health. Imbalances in microbial communities are closely linked to human diseases, and identifying potential ...relationships between microbes and diseases can help elucidate the pathogenesis of diseases. However, traditional methods based on biological or clinical experiments are costly, so the use of computational models to predict potential microbe-disease associations is of great importance.
In this paper, we present a novel computational model called MLFLHMDA, which is based on a Multi-View Latent Feature Learning approach to predict Human potential Microbe-Disease Associations. Specifically, we compute Gaussian interaction profile kernel similarity between diseases and microbes based on the known microbe-disease associations from the Human Microbe-Disease Association Database and perform a preprocessing step on the resulting microbe-disease association matrix, namely, weighting K nearest known neighbors (WKNKN) to reduce the sparsity of the microbe-disease association matrix. To obtain unobserved associations in the microbe and disease views, we extract different latent features based on the geometrical structure of microbes and diseases, and project multi-modal latent features into a common subspace. Next, we introduce graph regularization to preserve the local manifold structure of Gaussian interaction profile kernel similarity and add
-norms to the projection matrix to ensure the interpretability and sparsity of the model.
The AUC values for global leave-one-out cross-validation and 5-fold cross validation implemented by MLFLHMDA are 0.9165 and 0.8942+/-0.0041, respectively, which perform better than other existing methods. In addition, case studies of different diseases have demonstrated the superiority of the predictive power of MLFLHMDA. The source code of our model and the data are available on https://github.com/LiangzheZhang/MLFLHMDA_master.
Statistics requantitates the central dogma Li, Jingyi Jessica; Biggin, Mark D
Science (American Association for the Advancement of Science),
03/2015, Letnik:
347, Številka:
6226
Journal Article
Recenzirano
Odprti dostop
Transcription, not translation, chiefly determines protein abundance in mammals
Also see Research Article by
Jovanovic
et al.
Mammalian proteins are expressed at ∼10
3
to 10
8
molecules per cell (
1
...). Differences between cell types, between normal and disease states, and between individuals are largely defined by changes in the abundance of proteins, which are in turn determined by rates of transcription, messenger RNA (mRNA) degradation, translation, and protein degradation. If the rates for one of these steps differ much more than the rates of the other three, that step would be dominant in defining the variation in protein expression. Over the past decade, system-wide studies have claimed that in animals, differences in translation rates predominate (
2
–
5
). On page 1112 of this issue, Jovanovic
et al.
(
6
), as well as recent studies by Battle
et al.
(
7
) and Li
et al.
(
1
), challenge this conclusion, suggesting that transcriptional control makes the larger contribution.
Objectives Syphilis is a globally prevalent sexually transmitted infection. This study aimed to elucidate the epidemiological characteristics of syphilis in China from 2004 to 2019. Methods Incidence ...data for syphilis across 31 provinces in mainland China were obtained from the Data Center of China Public Health Science for the period from 2004 to 2019. Epidemiological methods and the Chi-squared test were used to analyze the temporal, regional, and disease stage distributions of syphilis. Results In total, 5,527,399 syphilis cases were reported in China from 2004 to 2019, with an average annual prevalence of 25.7063 per 100,000 population and overall increasing trend. In terms of regional distribution, high-incidence provinces included Shanghai, Zhejiang, Fujian, Guangxi, Guangdong, Xinjiang, Ningxia, and Qinghai. The proportion of latent syphilis increased from 20.41% in 2004 to 82.95% in 2019, with an upward trend each year. Conclusions Syphilis incidence exhibited an overall increasing trend in China, and latent syphilis was predominant. Syphilis incidences considerably varied among regions, and syphilis was detected from coastal to inland provinces. Thus, syphilis prevention and control programs should be tailored according to the specific epidemiological characteristics of each region.
DiGeorge syndrome critical region 8 (DGCR8) is a critical component of the canonical microprocessor complex for microRNA biogenesis. However, the non-canonical functions of DGCR8 have not been ...studied. Here, we demonstrate that DGCR8 plays an important role in maintaining heterochromatin organization and attenuating aging. An N-terminal-truncated version of DGCR8 (DR8
) accelerated senescence in human mesenchymal stem cells (hMSCs) independent of its microRNA-processing activity. Further studies revealed that DGCR8 maintained heterochromatin organization by interacting with the nuclear envelope protein Lamin B1, and heterochromatin-associated proteins, KAP1 and HP1γ. Overexpression of any of these proteins, including DGCR8, reversed premature senescent phenotypes in DR8
hMSCs. Finally, DGCR8 was downregulated in pathologically and naturally aged hMSCs, whereas DGCR8 overexpression alleviated hMSC aging and mouse osteoarthritis. Taken together, these analyses uncovered a novel, microRNA processing-independent role in maintaining heterochromatin organization and attenuating senescence by DGCR8, thus representing a new therapeutic target for alleviating human aging-related disorders.
Photodiode-based (PD-based) visible light positioning (VLP) has become a research focus of indoor positioning technology, while the existing VLP models rarely consider the anti-interference and ...positioning time of that. In this paper, indoor real-time three-dimensional visible light positioning system using fingerprinting and extreme learning machine (ELM) is proposed to make the system achieve not only high positioning accuracy and elevated anti-interference but also well-behaved real-time ability. In contrast to the positioning system based on K-Nearest Neighbor or Support Vector Machine, the proposed system achieves the highest positioning accuracy and the state-of-the-art positioning speed. Furthermore, the visible light positioning kernel is proposed as a method to reduce the size of the fingerprint database and thus reduce the training time exponentially. Both the simulation and the experiment results show that the proposed system achieves real-time 3-D positioning with high anti-interference. Therefore, this scheme can be considered as one of the effective methods for indoor 3-D positioning.
A critical challenge in microbiome data analysis is the existence of many non-biological zeros, which distort taxon abundance distributions, complicate data analysis, and jeopardize the reliability ...of scientific discoveries. To address this issue, we propose the first imputation method for microbiome data-mbImpute-to identify and recover likely non-biological zeros by borrowing information jointly from similar samples, similar taxa, and optional metadata including sample covariates and taxon phylogeny. We demonstrate that mbImpute improves the power of identifying disease-related taxa from microbiome data of type 2 diabetes and colorectal cancer, and mbImpute preserves non-zero distributions of taxa abundances.
Hypoxia is a physiological stress that frequently occurs in solid tissues. Autophagy, a ubiquitous degradation/recycling system in eukaryotic cells, renders cells tolerant to multiple stressors. ...However, the mechanisms underlying autophagy initiation upon hypoxia remains unclear. Here we show that protein arginine methyltransferase 5 (PRMT5) catalyzes symmetrical dimethylation of the autophagy initiation protein ULK1 at arginine 170 (R170me2s), a modification removed by lysine demethylase 5C (KDM5C). Despite unchanged PRMT5-mediated methylation, low oxygen levels decrease KDM5C activity and cause accumulation of ULK1 R170me2s. Dimethylation of ULK1 promotes autophosphorylation at T180, a prerequisite for ULK1 activation, subsequently causing phosphorylation of Atg13 and Beclin 1, autophagosome formation, mitochondrial clearance and reduced oxygen consumption. Further, expression of a ULK1 R170K mutant impaired cell proliferation under hypoxia. This study identifies an oxygen-sensitive methylation of ULK1 with an important role in hypoxic stress adaptation by promoting autophagy induction.
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