New technologies enable single-cell transcriptome analysis, mapping genome-wide expression across the human body. Here, we present an extended analysis of protein-coding genes in all major human tissues and organs, combining single-cell and bulk transcriptomics. To enhance transcriptome depth, 31 tissues were analyzed using a pooling method, identifying 557 unique cell clusters, manually annotated by marker gene expression. Genes were classified by body-wide expression and validated through antibody-based profiling. All results are available in the updated open-access Single Cell Type section of the Human Protein Atlas for genome-wide exploration of genes, proteins, and their spatial distribution in cells.

Chronic liver disease poses significant challenges to healthcare systems, which frequently struggle to meet the needs of end-stage liver disease patients. Early detection and management are essential because liver damage and fibrosis are potentially reversible. However, the implementation of population-wide screenings is hindered by the asymptomatic nature of early chronic liver disease, along with the risks and costs associated with traditional diagnostics, such as liver biopsies. This study pioneers the development of innovative, minimally invasive methods capable of improving the outcomes of liver disease patients by identifying liver disease biomarkers using quantification methods with translational potential. A targeted mass spectrometry assay based on stable isotope standard protein epitope signature tags (SIS-PrESTs) was employed for the absolute quantification of 108 proteins in just two microliters of plasma. The plasma profiles were derived from patients of various liver disease stages and etiologies, including healthy controls. A set of potential biomarkers for stratifying liver fibrosis was identified through differential expression analysis and supervised machine learning. These findings offer promising alternatives for improved diagnostics and personalized treatment strategies in liver disease management. Moreover, our approach is fully compatible with existing technologies that facilitate the robust quantification of clinically relevant protein targets via minimally disruptive sampling methods.

Herbs are extensively utilized in Traditional Chinese Medicine (TCM) for lung and liver cancer treatment, but the mechanisms behind these herbs remain largely unknown. Here, high-throughput transcriptomic analysis technology was used to uncover molecular mechanisms of herbal treatment. Furthermore, we developed a compound recognition approach utilizing the LINCS L1000 database to identify potential treatment targets. Our results showed that among 14 herbs tested, Pulsatilla chinensis exhibited the strongest anticancer effects in A549 and Huh7 cells, followed by Bupleurum chinense, and Polyporus umbellatus. P. chinensis exerts its anticancer properties by downregulating cell cycle-related transcription factors, including E2F1 and TFDP1. Notably, the mechanisms of P. chinensis treatment differed between the two cell lines. In A549 cells, which possess wild-type p53, P. chinensis induced apoptosis through the regulation of the p53 pathway. In contrast, in Huh7 cells, which harbor mutant p53, the effect was mediated via the TNF-alpha/NF-kappa B signaling pathway. We also identified two drugs, AMG232 and Nutlin-3, that exhibited treatment effects similar to P. chinensis in A549 cells. Both drugs function as inhibitors of the MDM2-p53 interaction. Western blot analysis confirmed the alteration of the relevant proteins, aligning with our computational predictions. Furthermore, 23-hydroxybetulinic acid, a key active compound of P. chinensis, demonstrated the ability to inhibit the p53-MDM2 interaction by binding to the same pocket on the MDM2 protein.

Background Chronic liver disease due to alcohol-related liver disease and chronic viral hepatitis pose a substantial burden on healthcare systems. Chronic liver disease may predispose to hepatocellular carcinoma, for which therapeutic options are limited. This study aimed to explore the immune cell characteristics of the clinical conditions.Methods Explant liver samples were collected from 25 patients for bulk RNA sequencing and flow cytometry analysis. Immune cell populations were characterized by flow cytometry from isolated hepatic and peripheral mononuclear cells.Results Significant differences in immune cell characteristics were observed among patients with three clinical conditions. Viral hepatitis and peri-tumor samples exhibited higher hepatic B cell counts compared to alcohol-related liver disease. Additionally, chronic liver disease patients showed higher levels of CD57+ T cells, suggestive of T cell differentiation. Differential expression analysis identified several genes associated with immune regulation, including downregulation of CD27 and upregulation of granzyme B in ARLD, consistent with a highly differentiated phenotype. LAG3 and PDCD1 were upregulated in peri-tumor samples. The NK cell count was lower in peri-tumor liver specimens compared to ARLD, and an upregulation of TIGIT, an inhibitory marker, was observed in those peri-tumor specimens.Conclusion This study contributes to the understanding of immune dynamics in chronic liver disease among different etiologies. B lymphocytes are relatively reduced in alcohol-related liver disease compared to other groups, and T cells exhibit a more differentiated subtype. The peritumor microenvironment in HCC suggests a relatively diminished presence of NK cells and a potential tendency toward increased inhibitory characteristics.

Background/Objectives: Glioblastoma multiforme (GBM), an aggressive and deadly brain tumour, presents significant challenges in achieving effective treatment due to its resistance to current therapies and poor prognosis. This study aimed to synthesise and evaluate 23 novel analogues of 3,4-dihydroquinolin-2(1H)-one, designed to enhance druggability and solubility, and to investigate their potential as VEGFR2 inhibitors for GBM treatment. Methods: The synthesised compounds were analysed using in silico methods, including molecular docking and dynamics studies, to assess their interactions with key residues within the VEGFR2 binding pocket. In vitro evaluations were performed on U87-MG and U138-MG GBM cell lines using MTT assays to determine the IC50 values of the compounds. Results: Among the tested compounds, 4u (IC50 = 7.96 mu M), 4t (IC50 = 10.48 mu M), 4m (IC50 = 4.20 mu M), and 4q (IC50 = 8.00 mu M) demonstrated significant antiproliferative effects against both the U87-MG and U138-MG cell lines. These compounds exhibited markedly higher efficacy compared to temozolomide (TMZ), which showed IC50 values of 92.90 mu M and 93.09 mu M for U87-MG and U138-MG, respectively. Molecular docking and dynamics studies confirmed strong interactions between the compounds and VEGFR2 kinase, supporting their substantial anti-cancer activity. Conclusions: This study highlights the promising potential of 3,4-dihydroquinolin-2(1H)-one analogues, particularly 4m, 4q, 4t, and 4u, as VEGFR2-targeting therapeutic agents for GBM treatment. Further detailed research is warranted to validate and expand upon these findings.

In recent years, the overuse of antibiotics has led to the emergence of antimicrobial-resistant (AMR) bacteria. To evaluate the spread of AMR bacteria, the reservoir of AMR genes (resistome) has been identified in environmental samples, hospital environments, and human populations, but the functional role of AMR bacteria and their persistence within individuals has not been fully investigated. Here, we performed a strain-resolved in-depth analysis of the resistome changes by reconstructing a large number of metagenome-assembled genomes from the gut microbiome of an antibiotic-treated individual. Interestingly, we identified two bacterial populations with different resistome profiles: extensively acquired antimicrobial-resistant bacteria (EARB) and sporadically acquired antimicrobial-resistant bacteria, and found that EARB showed broader drug resistance and a significant functional role in shaping individual microbiome composition after antibiotic treatment. Our findings of AMR bacteria would provide a new avenue for controlling the spread of AMR bacteria in the human community.

Objectives: Sucrose-rich diets promote hepatic de novo lipogenesis (DNL) and steatosis through interactions with the gut microbiota. However, the role of sugar-microbiota dynamics in the absence of dietary fat remains unclear. This study aimed to investigate the effects of a high-sucrose, zero-fat diet (ZFD) on hepatic steatosis and host metabolism in conventionally raised (CONVR) and germ-free (GF) mice. Methods: CONVR and GF mice were fed a ZFD, and hepatic lipid accumulation, gene expression, and metabolite levels were analyzed. DNL activity was assessed by measuring malonyl-CoA levels, expression of key DNL enzymes, and activation of the transcription factor SREBP-1c. Metabolomic analyses of portal vein plasma identified microbiota-derived metabolites linked to hepatic steatosis. To further examine the role of SREBP-1c, its hepatic expression was knocked down using antisense oligonucleotides in CONVR ZFD-fed mice. Results: The gut microbiota was essential for sucrose-induced DNL and hepatic steatosis. In CONVR ZFD-fed mice, hepatic fat accumulation increased alongside elevated expression of genes encoding DNL enzymes, higher malonyl-CoA levels, and upregulation of SREBP-1c. Regardless of microbiota status, ZFD induced fatty acid elongase and desaturase gene expression and increased hepatic monounsaturated fatty acids. Metabolomic analyses identified microbiota-derived metabolites associated with hepatic steatosis. SREBP-1c knockdown in CONVR ZFD-fed mice reduced hepatic steatosis and suppressed fatty acid synthase expression. Conclusions: Sucrose-microbiota interactions and SREBP-1c are required for DNL and hepatic steatosis in the absence of dietary fat. These findings provide new insights into the complex interplay between diet, gut microbiota, and metabolic regulation.

Risk stratification using multi‐omics data deepens understanding of immunometabolism in successfully treated people with HIV (PWH) is inadequately explained. A personalized medicine approach integrating blood cell transcriptomics, plasma proteomics, and metabolomics is employed to identify the mechanisms of immunometabolic complications in prolonged treated PWH from the COCOMO cohort. Among the PWHs, 44% of PWH are at risk of experiencing immunometabolic complications identified using the network‐based patient stratification method. Utilizing advanced machine learning techniques and a Bayesian classifier, five plasma protein biomarkers; Tubulin Folding Cofactor B (TBCB), Gamma‐Glutamylcyclotransferase (GGCT), Taxilin Alpha (TXLNA), Pyridoxal Phosphate Binding Protein (PLPBP) and Large Tumor Suppressor Kinase 1 (LATS1) are identified as highly differentially abundant between healthy control (HC)‐like and immunometabolically at‐risk PWHs (all FDR<10 −10 ). The personalized metabolic models predict metabolic perturbations, revealing disruptions in central carbon metabolic fluxes and host tryptophan metabolism in at‐risk phenotype. Functional assays in primary cells and cortical forebrain organoids (FBOs) further validate this. Metabolic perturbations lead to persistent monocyte activation, thereby impairing their functions ex vivo . Furthermore, the chronic inflammatory plasma microenvironment contributes to synaptic dysregulation in FBOs. The endogenous plasma inflammatory microenvironment is responsible for chronic inflammation in treated immunometabolically complicated at‐risk PWH who have a higher risk of cardiovascular and neuropsychiatric disorders.

Chronic hepatic injury and inflammation from various causes can lead to fibrosis and cirrhosis, potentially predisposing to hepatocellular carcinoma. The molecular mechanisms underlying fibrosis and its progression remain incompletely understood. Using a proteo-transcriptomics approach, we analyze liver and plasma samples from 330 individuals, including 40 healthy individuals and 290 patients with histologically characterized fibrosis due to chronic viral infection, alcohol consumption, or metabolic dysfunction-associated steatotic liver disease. Our findings reveal dysregulated pathways related to extracellular matrix, immune response, inflammation, and metabolism in advanced fibrosis. We also identify 132 circulating proteins associated with advanced fibrosis, with neurofascin and growth differentiation factor 15 demonstrating superior predictive performance for advanced fibrosis(area under the receiver operating characteristic curve [AUROC] 0.89 [95% confidence interval (CI) 0.81–0.97]) compared to the fibrosis-4 model (AUROC 0.85 [95% CI 0.78–0.93]). These findings provide insights into fibrosis pathogenesis and highlight the potential for more accurate non-invasive diagnosis.

The human microbiome is increasingly recognized for its crucial role in the development and progression of neurodegenerative diseases. While the gut-brain axis has been extensively studied, the contribution of the oral microbiome and gut-oral tropism in neurodegeneration has been largely overlooked. Cognitive impairment (CI) is common in neurodegenerative diseases and develops on a spectrum. In Parkinson’s Disease (PD) patients, CI is one of the most common non-motor symptoms but its mechanistic development across the spectrum remains unclear, complicating early diagnosis of at-risk individuals. Here, we generated 228 shotgun metagenomics samples of the gut and oral microbiomes across PD patients with mild cognitive impairment (PD-MCI) or dementia (PDD), and a healthy cohort, to study the role of gut and oral microbiomes on CI in PD. In addition to revealing compositional and functional signatures, the role of pathobionts, and dysregulated metabolic pathways of the oral and gut microbiome in PD-MCI and PDD, we also revealed the importance of oral-gut translocation in increasing abundance of virulence factors in PD and CI. The oral-gut virulence was further integrated with saliva metaproteomics and demonstrated their potential role in dysfunction of host immunity and brain endothelial cells. Our findings highlight the significance of the oral-gut-brain axis and underscore its potential for discovering novel biomarkers for PD and CI.