PLAU promotes cell proliferation and migration of head and neck cancer via STAT3 signaling pathway.

It was reported that within the head and neck cancer (HNC) cell line CAL21 the epithelial-mesenchymal transition (EMT) and cell proliferation were promoted by Urokinase-Type Plasminogen Activator (PLAU) proteinase through TNFRSF12A. Additionally, in this paper HNC cell lines refer to Fadu and Tu686. A novel PLAU-STAT3 axis was found to be involved in HNC cell line proliferation and metastasis. PLAU expression in HNC samples was upregulated, besides, the elevated expression of PLAU was linked to the lower overall survival (OS) and disease-free survival (DFS). Ectopic PLAU expression promoted cell proliferation and migration, while PLAU knockdown exhibited opposite results. RNA-seq data identified the JAK-STAT signaling pathway, confirmed by western blotting. A recovery assay using S3I-201, a selective inhibitor of signal transducer and activator of transcription 3 (STAT3), indicated that PLAU promoted HNC cell line progression via STAT3 signaling in vitro. The oncogenic role of PLAU in HNC tumor growth in vivo was confirmed using xenograft models. In summary, we identified the tumorigenic PLAU function in the HNC progress. PLAU may represent a potential prognostic biomarker of HNC and the PLAU-STAT3 pathway might be considered a therapeutic target of HNC.

SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging.

Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional single-cell resolution platform for targeted spatial proteomics. However, the precision of subsequent clinical analysis is constrained by imaging noise and resolution. Here, we propose SpiDe-Sr, a super-resolution network embedded with a denoising module for IMC spatial resolution enhancement. SpiDe-Sr effectively resists noise and improves resolution by 4 times. We demonstrate SpiDe-Sr respectively with cells, mouse and human tissues, resulting 18.95%/27.27%/21.16% increase in peak signal-to-noise ratio and 15.95%/31.63%/15.52% increase in cell extraction accuracy. We further apply SpiDe-Sr to study the tumor microenvironment of a 20-patient clinical breast cancer cohort with 269,556 single cells, and discover the invasion of Gram-negative bacteria is positively correlated with carcinogenesis markers and negatively correlated with immunological markers. Additionally, SpiDe-Sr is also compatible with fluorescence microscopy imaging, suggesting SpiDe-Sr an alternative tool for microscopy image super-resolution.

Single-Cell Study Unveils Lead Lifespan in Blood Cell Populations Follows a Universal Lognormal Distribution with Individual Skewness.

Lead is a widespread environmental hazard that can adversely affect multiple biological functions. Blood cells are the initial targets that face lead exposure. However, a systematic assessment of lead dynamics in blood cells at single-cell resolution is still absent. Herein, C57BL/6 mice were fed with lead-contaminated food. Peripheral blood was harvested at different days. Extracted red blood cells and leukocytes were stained with 19 metal-conjugated antibodies and analyzed by mass cytometry. We quantified the time-lapse lead levels in 12 major blood cell subpopulations and established the distribution of lead heterogeneity. Our results show that the lead levels in all major blood cell subtypes follow lognormal distributions but with distinctively individual skewness. The lognormal distribution suggests a multiplicative accumulation of lead with stochastic turnover of cells, which allows us to estimate the lead lifespan of different blood cell populations by calculating the distribution skewness. These findings suggest that lead accumulation by single blood cells follows a stochastic multiplicative process.

Identification and Characterization of CD8+ CD27+ CXCR3- T Cell Dysregulation and Progression-Associated Biomarkers in Systemic Lupus Erythematosus.

Systemic Lupus Erythematosus (SLE) etiopathogenesis highlights the contributions of overproduction of CD4+ T cells and loss of immune tolerance. However, the involvement of CD8+ T cells in SLE pathology and disease progression remains unclear. Here, the comprehensive immune cell dysregulation in total 263 clinical peripheral blood samples composed of active SLE (aSLE), remission SLE (rSLE) and healthy controls (HCs) is investigated via mass cytometry, flow cytometry and single-cell RNA sequencing. This is observed that CD8+ CD27+ CXCR3- T cells are increased in rSLE compare to aSLE. Meanwhile, the effector function of CD8+ CD27+ CXCR3- T cells are overactive in aSLE compare to HCs and rSLE, and are positively associated with clinical SLE activity. In addition, the response of peripheral blood mononuclear cells (PBMCs) is monitored to interleukin-2 stimulation in aSLE and rSLE to construct dynamic network biomarker (DNB) model. It is demonstrated that DNB score-related parameters can faithfully predict the remission of aSLE and the flares of rSLE. The abundance and functional dysregulation of CD8+ CD27+ CXCR3- T cells can be potential biomarkers for SLE prognosis and concomitant diagnosis. The DNB score with accurate prediction to SLE disease progression can provide clinical treatment suggestions especially for drug dosage determination.

Platinum-Chimeric Carrier Cells for Ultratrace Cell Analysis in Mass Cytometry.

Mass cytometry by time-of-flight (CyTOF), a high-dimensional single-cell analysis platform, detects up to 50 biomarkers at single-cell resolution. However, CyTOF analysis of biological samples with a minimal number of available cells or rare cell subsets remains a major technical challenge due to the extensive loss of cells during cell recovery, staining, and acquisition. Here, we introduce a platinum-chimeric carrier cell strategy for mass cytometry profiling of ultratrace cell samples. Cisplatin can rapidly enter broken plasma membranes of dead cells and form a chimeric interaction with cellular proteins, peptides, and amino acids. Thus, 198Pt-cisplatin is adopted to tag carrier cells in the pretreatment stage. We investigated 8 cell lines that are commonly accessible in laboratories for their potential as carrier cells to preserve rare target cells for CyTOF analysis. We designed a panel of 35 protein biomarkers to evaluate the comprehensive single-cell subtype classification capability with or without the carrier cell strategy. We further demonstrated the detection and analysis of as few as 1 × 104 immune cells using our method. The proposed method thus allows CyTOF analysis on precious clinical samples with less abundant cells.

Effect of Paxlovid on Tacrolimus Concentration in Perioperative Kidney Transplant Patients Infected With COVID-19: A Case Report.

Paxlovid, as a new drug, received emergency approval for the treatment of COVID-19 in China; there is very little experience with kidney transplantation patients taking tacrolimus with perioperative COVID-19 infection. We discontinued tacrolimus on the day of using Paxlovid, and we chose to frequently monitor the concentration of tacrolimus and creatinine early in the course of treatment by enzyme multiplied immunoassay technique (EMIT) and liquid chromatography-mass spectrometry (LC-MS/MS). The results show varying degrees of elevation of creatinine levels in 3 patients, and EMIT may overestimate the true concentration of tacrolimus metabolites compared with LC-MS/MS. All the data comply with the Helsinki Congress and the Declaration of Istanbul.

Precise Identification and Profiling of Surface Proteins of Ultra Rare Tumor Specific Extracellular Vesicle with Dynamic Quantitative Plasmonic Imaging.

Specific detection of tumor-derived EVs (tEVs) in plasma is complicated by nontumor EVs and non-EV particles. To accurately identify tEVs and profile their surface protein expression at single tEV resolution directly with clinical plasma is still an unmet need. Here, we present a Dynamic Immunoassay for Single tEV surface protein Profiling (DISEP), a kinetic assay based on surface plasmon resonance microscopy (SPRM) for specific single tEV profiling. DISEP adopts a pair of low-affinity oligonucleotide probes to respectively label EV surface proteins and functionalize an SPRM biosensor interface. tEVs labeled with the oligonucleotide probes possess distinctive binding kinetics from nonspecific particles in plasma, which permits accurate digital plasmonic counting of single EVs. We demonstrate DISEP for recognizing target EVs among 350-fold background plasma particles with high sensitivity (4677 EVs per µL). Clinical plasma samples were analyzed to discriminate between pancreatic cancer patients (n = 40) and healthy donors (n = 45). With a panel of biomarker signatures (EpCAM, HER2, and GPC1), DISEP only requires 10 µL primary sample from each donor to classify tumor patients with an area under the curve of 0.98. DISEP provides a highly specific EV detection and surface protein profiling strategy for early cancer diagnosis.

Genetic characteristics of classical astroviruses in Shenzhen, China, 2016-2019.

Human astrovirus (HAstV) is a single-stranded, positive-sense RNA virus and is the leading cause of viral gastroenteritis. However, despite its prevalence, astroviruses still remain one of the least studied enteroviruses. In this study, we sequenced 11 classical astrovirus strains from clinical samples collected in Shenzhen, China from 2016 to 2019, analyzed their genetic characteristics, and deposited them into GenBank. We conducted phylogenetic analysis using IQ-TREE software, with references to astrovirus sequences worldwide. The phylogeographic analysis was performed using the Bayesian Evolutionary Analysis Sampling Trees program, through Bayesian Markov Chain Monte Carlo sampling. We also conducted recombination analysis with the Recombination Detection Program. The newly sequenced strains were categorized as HAstV genotype 1, which is the predominant genotype in Shenzhen. Phylogeographic reconstruction indicated that HAstV-1 may have migrated from the United States to China, followed by frequent transmission between China and Japan. The recombination analysis revealed recombination events within and across genotypes, and identified a recombination-prone region that produced relatively uniform recombination breakpoints and fragment lengths. The genetic analysis of HAstV strains in Shenzhen addresses the current lack of astrovirus data in the region of Shenzhen and provides key insights to the evolution and transmission of astroviruses worldwide. These findings highlight the importance of improving surveillance of astroviruses.

Multiplex Protein Profiling by Low-Signal-Loss Single-Cell Western Blotting with Fluorescent-Quenching Aptamers.

Single-cell western blotting (scWB) is a prevalent technique for high-resolution protein analysis on low-abundance cell samples. However, the extensive signal loss during repeated antibody stripping precludes multiplex protein detection. Herein, we introduce Fluorescent-quenching Aptamer-based Single-cell Western Blotting (FAS-WB) for multiplex protein detection at single-cell resolution. The minimal size of aptamer probes allows rapid in-gel penetration, diffusion, and elution. Meanwhile, the fluorophore-tagged aptamers, coordinated with complementary quenching strands, avoid the massive signal loss conventionally caused by antibody stripping during repeated staining. Such a strategy also facilitates multiplex protein analysis with a limited number of fluorescent tags. We demonstrated FAS-WB for co-imaging four biomarker proteins (EpCAM, PTK7, HER2, CA125) at single-cell resolution with lower signal loss and enhanced signal-to-noise ratio compared to conventional antibody-based scWB. Being more time-saving (less than 25 min per cycle) and economical (1/1000 cost of conventional antibody probes), FAS-WB offers a highly efficient platform for profiling multiplex proteins at single-cell resolution.

Evaluating the effect of SARS-CoV-2 spike mutations with a linear doubly robust learner.

Driven by various mutations on the viral Spike protein, diverse variants of SARS-CoV-2 have emerged and prevailed repeatedly, significantly prolonging the pandemic. This phenomenon necessitates the identification of key Spike mutations for fitness enhancement. To address the need, this manuscript formulates a well-defined framework of causal inference methods for evaluating and identifying key Spike mutations to the viral fitness of SARS-CoV-2. In the context of large-scale genomes of SARS-CoV-2, it estimates the statistical contribution of mutations to viral fitness across lineages and therefore identifies important mutations. Further, identified key mutations are validated by computational methods to possess functional effects, including Spike stability, receptor-binding affinity, and potential for immune escape. Based on the effect score of each mutation, individual key fitness-enhancing mutations such as D614G and T478K are identified and studied. From individual mutations to protein domains, this paper recognizes key protein regions on the Spike protein, including the receptor-binding domain and the N-terminal domain. This research even makes further efforts to investigate viral fitness via mutational effect scores, allowing us to compute the fitness score of different SARS-CoV-2 strains and predict their transmission capacity based solely on their viral sequence. This prediction of viral fitness has been validated using BA.2.12.1, which is not used for regression training but well fits the prediction. To the best of our knowledge, this is the first research to apply causal inference models to mutational analysis on large-scale genomes of SARS-CoV-2. Our findings produce innovative and systematic insights into SARS-CoV-2 and promotes functional studies of its key mutations, serving as reliable guidance about mutations of interest.

A Meta-Analysis of the Influence on Inflammatory Factors in Type 2 Diabetes among Middle-Aged and Elderly Patients by Various Exercise Modalities.

The purpose of this study was to investigate the effects of various exercise modalities on inflammatory factors in middle-aged and elderly patients with type 2 diabetes (MEPT2D), as lifestyle changes, such as physical activity and dietary modifications, are considered important in the prevention of type 2 diabetes. For the study methodology, Pubmed, CNKI, EBSCO, Wanfang Data, and Web of Science were selected for the search. The methodological quality of the included studies was assessed by the Cochrane Risk of Bias (ROB) tool, and statistically analyzed using the RevMan 5.4.1 analysis software, which included 18 investigations involving 853 study subjects. Meta-analysis findings indicated that aerobic training (AT), resistance training (RT), combined training (CT), and high-intensity interval training (HIIT) showed significant reductions in CRP, TNF-α, IL-6, and IL-10 levels in MEPT2D. Among them, HIIT was superior to other training modalities in reducing TNF-α levels, while CT was superior to AT, RT, and HIIT in decreasing IL-6, IL-10, and CRP in MEPT2D. Meanwhile, RT had limited effects in reducing CRP and TNF-α levels in MEPT2D. However, HIIT had no significant effect on IL-6 and IL-10 in MEPT2D. In conclusion, long-term regular AT, RT, CT, and HIIT all contributed to the reduction of inflammatory status (CRP, TNF-α, IL-6, and IL-10) in MEPT2D, while CT (for CRP, IL-6, and IL-10) and HIIT (for TNF-α) represent the best approaches to counteract the inflammatory response in MEPT2D.

Role of LONP2 in head and neck squamous cell carcinoma.

Lon Peptidase 2, Peroxisomal (LONP2) is a peptidase in peroxisomes that selectively degrades oxidatively damaged proteins in cells and is upregulated in several cancers. In this study, we found both the mRNA and protein level of LONP2 was upregulated in head and neck squamous cell carcinoma (HNSCC) samples. Ectopic overexpressed LONP2 enhanced HNSCC cell growth and migration. Nevertheless, LONP2 silencing suppressed tumor growth in vitro and in vivo. It was also indicated that knockdown of LONP2 also impaired the cell cycle progression and improved apoptosis rate of HNSCC cells. The results of RNA sequencing showed that plastin 3 (PLS3) was heavily downregulated after LONP2 silencing. PLS3 is an actin-bundling protein that functions as an oncogene in several cancers. Furthermore, knockdown of PLS3 inhibited the cell proliferation induced by LONP2 overexpression. In conclusion, we identified an oncogenic effect of LONP2 on cell proliferation and migration in HNSCC via positively regulating the expression of PLS3.

Comparative genomics reveals new insights into the evolution of the IncA and IncC family of plasmids.

Incompatibility groups IncA and IncC plasmids are of great concern due to their ability to disseminate antibiotic resistance in bacteria via conjugative transfer. A deep understanding of their genomic structures and evolutionary characteristics is of great significance for improving our knowledge about its multidrug-resistance evolution and dissemination. However, current knowledge of their backbone structure, features of core functional modules and the characteristics of variable regions is based on a few plasmids, which highlights the need for a comprehensive systematic study. The present study thoroughly compared and analysed 678 IncA and IncC plasmid genomes. We found that their core functional genes were occasionally deficient and sometimes existed as multiple functional copies/multiple families, which resulted in much diversity. The phylogeny of 13 core functional genes corresponded well to the plasmid subtypes. The conjugative transfer system gained diverse complexity and exhibited many previously unnoticed types with multiple combinations. The insertion of mobile genetic elements (MGEs) in plasmids varied between types and was present in 4 insertion spots in different types of plasmids with certain types of transposons, integrons and insertion sequences. The impact of gene duplication, deletion, the insertion of MGEs, genome rearrangement and recombination resulted in the complex dynamic variable backbone of IncA and IncC plasmids. And IncA and IncC plasmids were more complex than their closest relative SXT/R391 integrative conjugative elements (ICEs), which included nearly all of the diversity of SXT/R391 in key systems. Our work demonstrated a global and systematic view of the IncA and IncC plasmids and provides many new insights into their genome evolution.

HTLV-1 infection of donor-derived T cells might promote acute graft-versus-host disease following liver transplantation.

Acute graft versus host disease (aGVHD) is a rare, but severe complication of liver transplantation (LT). It is caused by the activation of donor immune cells in the graft against the host shortly after transplantation, but the contributing pathogenic factors remain unclear. Here we show that human T cell lymphotropic virus type I (HTLV-1) infection of donor T cells is highly associated with aGVHD following LT. The presence of HTLV-1 in peripheral blood and tissue samples from a discovery cohort of 7 aGVHD patients and 17 control patients is assessed with hybridization probes (TargetSeq), mass cytometry (CyTOF), and multiplex immunohistology (IMC). All 7 of our aGVHD patients display detectable HTLV-1 Tax signals by IMC. We identify donor-derived cells based on a Y chromosome-specific genetic marker, EIF1AY. Thus, we confirm the presence of CD4+Tax+EIF1AY+ T cells and Tax+CD68+EIF1AY+ antigen-presenting cells, indicating HTLV-1 infection of donor immune cells. In an independent cohort of 400 patients, we verify that HTLV-1 prevalence correlates with aGVHD incidence, while none of the control viruses shows significant associations. Our findings thus provide new insights into the aetio-pathology of liver-transplantation-associated aGVHD and raise the possibility of preventing aGVHD prior to transplantation.

Uncover diagnostic immunity/hypoxia/ferroptosis/epithelial mesenchymal transformation-related CCR5, CD86, CD8A, ITGAM, and PTPRC in kidney transplantation patients with allograft rejection.

The aim of this study was to identify predictive immunity/hypoxia/ferroptosis/epithelial mesenchymal transformation (EMT)-related biomarkers, pathways and new drugs in allograft rejection in kidney transplant patients. First, gene expression data were downloaded followed by identification of differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis. Second, diagnostic model was construction based on key genes, followed by correlation analysis between immune/hypoxia/ferroptosis/EMT and key diagnostic genes. Finally, drug prediction of diagnostic key genes was carried out. Five diagnostic genes were further identified, including CCR5, CD86, CD8A, ITGAM, and PTPRC, which were positively correlated with allograft rejection after the kidney transplant. Highly infiltrated immune cells, highly expression of hypoxia-related genes and activated status of EMT were significantly positively correlated with five diagnostic genes. Interestingly, suppressors of ferroptosis (SOFs) and drivers of ferroptosis (DOFs) showed a complex regulatory relationship between ferroptosis and five diagnostic genes. CD86, CCR5, and ITGAM were respectively drug target of ABATACEPT, MARAVIROC, and CLARITHROMYCIN. PTPRC was drug target of both PREDNISONE and EPOETIN BETA. In conclusion, the study could be useful in understanding changes in the microenvironment within transplantation, which may promote or sustain the development of allograft rejection after kidney transplantation.

A Standardized Framework for Better Understanding of Phenotypic Differences within Bacterial Phyla Based on Protein Domain.

We propose a standardized framework to classify target species based on their protein domains, which can be utilized in different contexts, like eukaryotes and prokaryotes. In this study, by applying the framework to the bacterial kingdom as an implementation example and comparing the results with the current taxonomy standards at the phylum level, we came to the conclusion that the sequence of domains rather than the content of domains in a protein and the presence of one domain rather than the number of occurrences of one domain play more important roles in deciding bacterial phenotypes as well as matching the current taxonomy. In addition, the comparison also helps us to better focus on the species that conflict with the current phylum category, as well as to further investigate their phenotypic or genotypic differences. IMPORTANCE A 3-step framework was designed which can be applied to clustering species based on their protein domains, and different candidate models are proposed in each step for better adaptation of various scenarios. We show its implementation for the bacterial kingdom as an example, which helps us to find the most appropriate model combination that will best reflect the relationship between domains and phenotypes in this context. In addition, identifying species that are distant in the results but should be closely related phylogenetically can help us to focus on the mismatch for better understanding of their key phenotypic or genotypic differences.

Identification of gene biomarkers with expression profiles in patients with allergic rhinitis.

BACKGROUND: Allergic rhinitis (AR) is an upper respiratory tract inflammation disease caused by IgE-mediated reactions against inhaled allergens. The incidence of AR is significantly increasing throughout the world. Hence, more specific, and sensitive gene biomarkers and understanding the underlying pathways are necessary to further explore the AR pathogenesis. OBJECTIVE: To identify gene biomarkers in nasal mucosa and in blood from AR patients which could be used in AR diagnosis. METHODS: The gene expression profiles of GSE43523 from nasal epithelial cells and GSE75011 from Th2-enriched CD4+ T cells in blood were downloaded from the Gene Expression Omnibus database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and protein-protein interaction (PPI) network analysis were conducted to investigate the functional changes of genes. The receiver operating characteristic (ROC) curves were used to assess the diagnostic values of the hub genes. Real-time quantitative PCR (RT-qPCR) was performed to validate the hub genes. RESULTS: Significant differentially enriched gene signatures in AR patients were identified in nasal epithelial cells (n-DEGs) and in blood (t-DEGs). Signatures associated with axoneme, extracellular matrix, collagen fibril organization, cell motility, calcium ion binding, and so on were more enriched in n-DEGs, whereas signatures associated with TNF signaling pathway, detoxification of inorganic compound, and cellular response to corticotropin-releasing hormone stimulus were enriched in t-DEGs. In addition, we identified 8 hub genes and 14 hub genes from n-DEGs and t-DEGs, respectively. The combination of POSTN in nasal mucosa and PENK and CDC25A in blood was constructed with a good AR predicting performance. The area under the curve (AUC) of the ROC curve of 3 hub genes' combination was 0.98 for AR diagnosis. CONCLUSION: This study utilized gene expression profiles and RT-qPCR validation on nasal mucosa and blood from AR patients to investigate the potential biomarkers for AR diagnosis.

Predicting the recurrence of chronic rhinosinusitis with nasal polyps using nasal microbiota.

BACKGROUND: Recent studies have revealed that the nasal microbiota in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) is profoundly altered and is correlated with systemic inflammation. However, little is known regarding whether the microbiota can be utilized to predict nasal polyp recurrence. This study is aimed to determine whether altered nasal microbiota constituents could be used as biomarkers to predict CRSwNP recurrence. METHODS: Nasal microbiota constituents were quantified and characterized using bacterial 16S ribosomal RNA gene sequencing. Selected features for least absolute shrinkage and selection operator regression-based predictors were the nasal microbiota community composition and CRSwNP patient clinical characteristics. The primary outcome was recurrence, which was determined post-admission. RESULTS: By distinguishing recurrence-associated nasal microbiota taxa and exploiting the distinct nasal microbiota abundance between patients with recurrent and non-recurrent CRSwNP, we developed a predictive classifier for the diagnosis of nasal polyps' recurrence with 91.4% accuracy. CONCLUSIONS: Key taxonomical features of the nasal microbiome could predict recurrence in CRSwNP patients. The nasal microbiome is an understudied source of clinical variation in CRSwNP and represents a novel therapeutic target for future prevention and treatment.