Itaconate alleviates diet-induced obesity via activation of brown adipocyte thermogenesis.

Despite medical advances, there remains an unmet need for better treatment of obesity. Itaconate, a product of the decarboxylation of the tricarboxylic acid cycle intermediate cis-aconitate, plays a regulatory role in both metabolism and immunity. Here, we show that itaconate, as an endogenous compound, counteracts high-fat-diet (HFD)-induced obesity through leptin-independent mechanisms in three mouse models. Specifically, itaconate reduces weight gain, reverses hyperlipidemia, and improves glucose tolerance in HFD-fed mice. Additionally, itaconate enhances energy expenditure and the thermogenic capacity of brown adipose tissue (BAT). Unbiased proteomic analysis reveals that itaconate upregulates key proteins involved in fatty acid oxidation and represses the expression of lipogenic genes. Itaconate may provoke a major metabolic reprogramming by inducing fatty acid oxidation and suppression of fatty acid synthesis in BAT. These findings highlight itaconate as a potential activator of BAT-mediated thermogenesis and a promising candidate for anti-obesity therapy.

Dynamic Proteomic Changes in Tumor and Immune Organs Reveal Systemic Immune Response to Tumor Development.

In orthotopic mouse tumor models, tumor progression is a complex process, involving interactions among tumor cells, host cell-derived stromal cells, and immune cells. Much attention has been focused on the tumor and its tumor microenvironment, while the host's macroenvironment including immune organs in response to tumorigenesis is poorly understood. Here, we report a temporal proteomic analysis on a subcutaneous tumor and three immune organs (LN, MLN, and spleen) collected on Days 0, 3, 7, 10, 14, and 21 after inoculation of mouse forestomach cancer cells in a syngeneic mouse model. Bioinformatics analysis identified key biological processes during distinct tumor development phases, including an initial acute immune response, the attack by the host immune system, followed by the adaptive immune activation, and the build-up of extracellular matrix. Proteomic changes in LN and spleen largely recapitulated the dynamics of the immune response in the tumor, consistent with an acute defense response on D3, adaptive immune response on D10, and immune evasion by D21. In contrast, the immune response in MLN showed a gradual and sustained activation, suggesting a delayed response from a distal immune organ. Combined analyses of tumors and host immune organs allowed the identification of potential therapeutic targets. A proof-of-concept experiment demonstrated that significant growth reduction can be achieved by dual inhibition of MEK and DDR2. Together, our temporal proteomic dataset of tumors and immune organs provides a useful resource for understanding the interaction between tumors and the immune system and has the potential for identifying new therapeutic targets for cancer treatment.

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics.

BACKGROUND: Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories. RESULTS: Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics. CONCLUSION: Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

Dynamic proteomic change of tumor and immune organs in an immune-competent hepatocellular carcinoma mouse model.

Subcutaneous implantation of a human cancer cell line in immune-deficient mice (CDX) is a commonly used tool in preclinical studies for the assessment of potential anti-cancer drugs. As immunotherapy is transforming cancer treatment, tumor models in immunocompetent mice are necessary for us to understand the immune aspects of tumor biology. However, the systemic immune response to the implantation of cancer cells at proteome level is unclear. In this study, we characterized the dynamic proteomic changes of subcutaneous tumors and 5 immune organs (draining lymph node, mesenteric lymph node, spleen, thymus and marrow) at six time points after implantation using a Hepa1-6 derived allograft mouse model. Our data suggest that interaction of the implanted tumor cells with mouse immune system followed the trajectory of "tumor rejection" to "immune evasion" in that the tumor gained the ability to evade the immune system for growth. Furthermore, anti-PDL2 antibody was validated here as an optional immunotherapy strategy to inhibit the growth of Hepa1-6 subcutaneous tumors. These findings from our study provided valuable information for the understanding of tumor and immune interaction and shed light on the rational design for clinical cancer treatment and other preclinical experiments.

Dynamic EGFR interactomes reveal differential association of signaling modules with wildtype and Exon19-del EGFR in NSCLC cell lines.

Protein-protein interaction networks (PPIs) govern the majority of biological processes, but how oncogenic mutations impact these interactions and their functions at a network scale is poorly understood. Mutations of epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) is a pre-requisition for EGFR tyrosine kinase inhibitor (TKI) treatment. Identification of interaction partners that bind to mutated EGFR can help understand the mechanism of action and pathways that mediate drug resistance. In this study, we characterized the dynamic interaction network of a pair of EGFR wildtype and mutant NSCLC cell lines. We performed immunoprecipitation of endogenous EGFR at various time points following EGF treatment and analyzed the associated proteins by quantitative mass spectrometry. Our results showed that the core signaling modules and key downstream pathways are maintained in the mutant cell line, but receptor internalization and intracellular trafficking in the mutant is delayed. Furthermore, we identified mutant EGFR-associated proteins that could affect EGFR functions in lung adenocarcinoma. SIGNIFICANCE: We analyzed the dynamic EGFR interaction network in NSCLC cell lines expressing wild-type and mutant EGFR. By comparing the similarities and differences in the EGFR proteome, we gained a better understanding of EGFR signal transduction network, and identified new factors for further functional characterizations and clinical significance assessment.

Proteome-Wide Profiling of Readers for DNA Modification.

DNA modifications, represented by 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC), play important roles in epigenetic regulation of biological processes. The specific recognition of DNA modifications by the transcriptional protein machinery is thought to be a potential mechanism for epigenetic-driven gene regulation, and many modified DNA-specific binding proteins have been uncovered. However, the panoramic view of the roles of DNA modification readers at the proteome level remains largely unclear. Here, a recently developed concatenated tandem array of consensus transcription factor (TF) response elements (catTFREs) approach is employed to profile the binding activity of TFs at DNA modifications. Modified DNA-binding activity is quantified for 1039 TFs, representing 70% of the TFs in the human genome. Additionally, the modified DNA-binding activity of 600 TFs is monitored during the mouse brain development from the embryo to the adult stages. Readers of these DNA modifications are predicted, and the hierarchical networks between the transcriptional protein machinery and modified DNA are described. It is further demonstrated that ZNF24 and ZSCAN21 are potential readers of 5fC-modified DNA. This study provides a landscape of TF-DNA modification interactions that can be used to elucidate the epigenetic-related transcriptional regulation mechanisms under physiological conditions.

A Multi-Level Output-Based DBN Model for Fine Classification of Complex Geo-Environments Area Using Ziyuan-3 TMS Imagery.

Fine-scale land use and land cover (LULC) data in a mining area are helpful for the smart supervision of mining activities. However, the complex landscape of open-pit mining areas severely restricts the classification accuracy. Although deep learning (DL) algorithms have the ability to extract informative features, they require large amounts of sample data. As a result, the design of more interpretable DL models with lower sample demand is highly important. In this study, a novel multi-level output-based deep belief network (DBN-ML) model was developed based on Ziyuan-3 imagery, which was applied for fine classification in an open-pit mine area of Wuhan City. First, the last DBN layer was used to output fine-scale land cover types. Then, one of the front DBN layers outputted the first-level land cover types. The coarse classification was easier and fewer DBN layers were sufficient. Finally, these two losses were weighted to optimize the DBN-ML model. As the first-level class provided a larger amount of additional sample data with no extra cost, the multi-level output strategy enhanced the robustness of the DBN-ML model. The proposed model produces an overall accuracy of 95.10% and an F1-score of 95.07%, outperforming some other models.

Antibiotic resistance gene profiling in response to antibiotic usage and environmental factors in the surface water and groundwater of Honghu Lake, China.

There is an increasing concern that aquaculture has been implicated in the formation of antibiotic resistance gene (ARG) reservoirs; however, little is known about the consequences of their presence in groundwater. In this study, 22 antibiotics, including four acetylated metabolites, and 27 ARGs were analyzed in fish pond water, surface water, and groundwater of the Honghu Lake in China. Correlations between conventional parameters, ionic composition, antibiotic concentration, and relative abundance of ARGs in water samples were analyzed. Among the three different sources of water, total antibiotic levels were the highest in fish pond water and the lowest in groundwater, with moderate levels in lake water. In surface water, sulfonamides and their metabolites accounted for the highest antibiotic content, whereas tetracyclines were the most frequently found in groundwater samples. Despite the near-undetectable levels of antibiotics in groundwater, the relative abundance of ARGs in groundwater samples was even higher than that in surface waters. The magnitude and extent of ARG migration are likely to be dependent on local antibiotic contamination levels as well as on the local environmental and hydrogeological conditions, with the class 1 integrons (intI1) being essential for the dissemination of such ARGs. The effects of environmental parameters such as antibiotics, dissolved oxygen, HCO3-, and pH on ARGs were highly significant, reflecting the potential impact of these factors on the abundance of ARGs. Our findings thus highlight the need for improved control of the spread of ARGs in and from aquaculture environments.

A time-resolved multi-omic atlas of the developing mouse liver.

Liver organogenesis and development are composed of a series of complex, well-orchestrated events. Identifying key factors and pathways governing liver development will help elucidate the physiological and pathological processes including those of cancer. We conducted multidimensional omics measurements including protein, mRNA, and transcription factor (TF) DNA-binding activity for mouse liver tissues collected from embryonic day 12.5 (E12.5) to postnatal week 8 (W8), encompassing major developmental stages. These data sets reveal dynamic changes of core liver functions and canonical signaling pathways governing development at both mRNA and protein levels. The TF DNA-binding activity data set highlights the importance of TF activity in early embryonic development. A comparison between mouse liver development and human hepatocellular carcinoma (HCC) proteomic profiles reveal that more aggressive tumors are characterized with the activation of early embryonic development pathways, whereas less aggressive ones maintain liver function-related pathways that are elevated in the mature liver. This work offers a panoramic view of mouse liver development and provides a rich resource to explore in-depth functional characterization.

A region-resolved mucosa proteome of the human stomach.

The human gastric mucosa is the most active layer of the stomach wall, involved in food digestion, metabolic processes and gastric carcinogenesis. Anatomically, the human stomach is divided into seven regions, but the protein basis for cellular specialization is not well understood. Here we present a global analysis of protein profiles of 82 apparently normal mucosa samples obtained from living individuals by endoscopic stomach biopsy. We identify 6,258 high-confidence proteins and estimate the ranges of protein expression in the seven stomach regions, presenting a region-resolved proteome reference map of the near normal, human stomach. Furthermore, we measure mucosa protein profiles of tumor and tumor nearby tissues (TNT) from 58 gastric cancer patients, enabling comparisons between tumor, TNT, and normal tissue. These datasets provide a rich resource for the gastrointestinal tract research community to investigate the molecular basis for region-specific functions in mucosa physiology and pathology including gastric cancer.

[Effect of high fat diet on proteome in mice stomachs].

To explore the effect of high fat diet on proteome in mice stomachs, we constructed a model in which the mice were fed with high fat diet as the high fat diet (HFD) group or normal diet as the control (CTRL) group for 110 days. The stomachs were collected and divided into three regions (forestomach (F), corpus (C) and antrum (A)) for protein extraction and mass spectrometry analysis. Of all 9 307 identified proteins in two groups, 4 066 proteins (HFD: 3 832, CTRL: 3 654) were strictly identified by at least one unique peptide and identified twice in three replicates. Using gene ontology (GO) and interaction network analysis we analyzed differentially expressed proteins (fold change≥2) in two groups or between regions. In the whole stomach tissues, proteins up-regulated in HFD group mainly were associated with protein stabilization and protein transport. Differentially expressed proteins between regions showed that forestomach was related to the biological process of keratinization and actin assembly, while corpus and antrum mainly performed digestive function. Compared with forestomach, the corpus and antrum were more affected by the diet. Though there was no significant effect on the basic digestive function of the stomach, proteins that were involved in protein transport and lipid metabolism-related biological processes were significantly highly expressed in HFD group.

A time-resolved multi-omic atlas of the developing mouse stomach.

The mammalian stomach is structurally highly diverse and its organ functionality critically depends on a normal embryonic development. Although there have been several studies on the morphological changes during stomach development, a system-wide analysis of the underlying molecular changes is lacking. Here, we present a comprehensive, temporal proteome and transcriptome atlas of the mouse stomach at multiple developmental stages. Quantitative analysis of 12,108 gene products allows identifying three distinct phases based on changes in proteins and RNAs and the gain of stomach functions on a longitudinal time scale. The transcriptome indicates functionally important isoforms relevant to development and identifies several functionally unannotated novel splicing junction transcripts that we validate at the peptide level. Importantly, many proteins differentially expressed in stomach development are also significantly overexpressed in diffuse-type gastric cancer. Overall, our study provides a resource to understand stomach development and its connection to gastric cancer tumorigenesis.