To gain insight into how an adjuvant impacts vaccination responses, we use systems immunology to study human H5N1 influenza vaccination with or without the adjuvant AS03, longitudinally assessing 14 time points including multiple time points within the first day after prime and boost. We develop an unsupervised computational framework to discover high-dimensional response patterns, which uncover adjuvant- and immunogenicity-associated early response dynamics, including some that differ post prime versus boost. With or without adjuvant, some vaccine-induced transcriptional patterns persist to at least 100 days after initial vaccination. Single-cell profiling of surface proteins, transcriptomes, and chromatin accessibility implicates transcription factors in the erythroblast-transformation-specific (ETS) family as shaping these long-lasting signatures, primarily in classical monocytes but also in CD8+ naive-like T cells. These cell-type-specific signatures are elevated at baseline in high-antibody responders in an independent vaccination cohort, suggesting that antigen-agnostic baseline immune states can be modulated by vaccine antigens alone to enhance future responses.

BACKGROUND: Osteoarthritis (OA) is a disabling and highly prevalent condition affecting millions worldwide. Recently discovered, disulfidptosis represents a novel form of cell death induced by the excessive accumulation of cystine. Despite its significance, a systematic exploration of disulfidptosis-related genes (DRGs) in OA is lacking.
METHODS: This study utilized three OA-related datasets and DRGs. Differentially expressed (DE)-DRGs were derived by intersecting the differentially expressed genes (DEGs) from GSE114007 with DRGs. Feature genes underwent screening through three machine learning algorithms. High diagnostic value genes were identified using the receiver operating characteristic curve. Hub genes were confirmed through expression validation. These hub genes were then employed to construct a nomogram and conduct enrichment, immune, and correlation analyses. An additional validation of hub genes was performed through in vitro cell experiments.
RESULTS: SLC3A2 and PDLIM1 were designated as hub genes, displaying excellent diagnostic performance. PDLIM1 exhibited low expression in early chondrocyte differentiation, rising significantly in the late stage, while SLC3A2 showed high overall expression, declining in the late differentiation stage. Cellular experiments corroborated the correlation of SLC3A2 and PDLIM1 with chondrocyte inflammation.
CONCLUSIONS: Two hub genes, SLC3A2 and PDLIM1, were identified in relation to disulfidptosis, providing potential directions for diagnosing and treating OA.

UNASSIGNED: Analyzing the local microenvironment of tumor cells can provide significant insights into their complex interactions with their cellular surroundings, including immune cells. By quantifying the prevalence and distances of certain immune cells in the vicinity of tumor cells through a neighborhood analysis, patterns may emerge that indicate specific associations between cell populations. Such analyses can reveal important aspects of tumor-immune dynamics, which may inform therapeutic strategies. This method enables an in-depth exploration of spatial interactions among different cell types, which is crucial for research in oncology, immunology, and developmental biology.
UNASSIGNED: We introduce an R Markdown script called SNAQ™ (Single-cell Spatial Neighborhood Analysis and Quantification), which conducts a neighborhood analysis on immunofluorescent images without the need for extensive coding knowledge. As a demonstration, SNAQ™ was used to analyze images of pancreatic ductal adenocarcinoma. Samples stained for DAPI, PanCK, CD68, and PD-L1 were segmented and classified using QuPath. The resulting CSV files were exported into RStudio for further analysis and visualization using SNAQ™. Visualizations include plots revealing the cellular composition of neighborhoods around multiple cell types within a customizable radius. Additionally, the analysis includes measuring the distances between cells of certain types relative to others across multiple regions of interest.
UNASSIGNED: The R Markdown files that comprise the SNAQ™ algorithm and the input data from this paper are freely available on the web at https://github.com/AryehSilver1/SNAQ.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through in vitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration in vitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

Entamoeba nuttalli is genetically the closest to Entamoeba histolytica, the causative agent of human amebiasis, and its natural host is Macaca species. A unique E. nuttalli specific surface protein (PTORS) containing 42 repeats of octapeptide was identified by comparative genomic analysis of Entamoeba species. We aimed to elucidate the function of this protein. When trophozoites from various E. nuttalli strains were examined by immunofluorescence microscopy and flow cytometry using a PTORS-specific monoclonal antibody, only a limited proportion of trophozoites were stained, indicating that the protein was not commonly expressed in all E. nuttalli trophozoite. The proportion of trophozoites expressing PTORS increased after passage in hamster livers, suggesting that the protein functions in the virulence of trophozoites in the liver tissue. Single-cell analysis revealed that in the cluster including trophozoites with PTORS gene expression, genes of virulence-related proteins were also upregulated. Trophozoites of E. histolytica transfected with PTORS showed enhanced adherence and subsequent phagocytic activity towards human Jurkat cells, independent of the lectin. E. histolytica trophozoites expressing PTORS formed larger liver abscesses in hamsters. These results demonstrate that PTORS is a novel virulence factor in Entamoeba species.

Measurable residual disease (MRD) is detected in approximately a quarter of AML chemotherapy responders, serving as a predictor for relapse and shorter survival. Immunological control of residual disease is suggested to prevent relapse, but the mechanisms involved are not fully understood. We present a peripheral blood single cell immune profiling by mass cytometry using a 42-antibody panel with particular emphasis on markers of cellular immune response. Six healthy donors were compared with four AML patients with MRD (MRD+) in first complete remission (CR1MRD+). Three of four patients demonstrated a favorable genetic risk profile, while the fourth patient had an unfavorable risk profile (complex karyotype, TP53-mutation) and a high level of MRD. Unsupervised clustering using self-organizing maps and dimensional reduction analysis was performed for visualization and analysis of immune cell subsets. CD57+ natural killer (NK)-cell subsets were found to be less abundant in patients than in healthy donors. Both T and NK cells demonstrated elevated expression of activity and maturation markers (CD44, granzyme B, and phosho-STAT5 Y694) in patients. Although mass cytometry remains an expensive method with limited scalability, our data suggest the utility for employing a 42-plex profiling for cellular immune surveillance in whole blood, and possibly as a biomarker platform in future clinical trials. The findings encourage further investigations of single cell immune profiling in CR1MRD+ AML-patients.

Tripos is a large dinoflagellate genus widely distributed in the world\'s oceans. Morphology-based species identification is inconclusive due to high morphological intraspecific variability. Metabarcoding analysis has been demonstrated to be effective for species identification and tracking their spatiotemporal dynamics. However, accumulating evidence suggests high levels of intragenomic variations (IGVs) are common in many algae, leading to concerns about overinterpretation of molecular diversity in metabarcoding studies. In this project, we evaluated and compared IGVs in Tripos species by conducting the first high-throughput sequencing (HTS) of 18S rDNA V4 of Tripos single cells. High numbers of haplotypes (19-172) were identified in each of the 30 Tripos cells. Each cell contained one dominant haplotype with high relative abundance and many haplotypes with lower abundances. Thus, the presence of multiple minor haplotypes substantially overestimate the molecular diversity identified in metabarcoding analysis, which encompass not only interspecific and intraspecific diversities, but high levels of IGVs.

Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data. TACIT uses unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integrating TACIT-identified cell types with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discovered under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

Electronic communication in natural systems makes use, inter alia, of molecular transmission, where electron transfer occurs within networks of redox reactions, which play a vital role in many physiological systems. In view of the limited understanding of redox signaling, we developed an approach and an electrochemical-optical lab-on-a-chip to observe cellular responses in localized redox environments. The developed fluidic micro-system uses electrogenetic bacteria in which a cellular response is activated to electrically and chemically induced stimulations. Specifically, controlled environments for the cells are created by using microelectrodes to generate spatiotemporal redox gradients. The in-situ cellular responses at both single-cell and population levels are monitored by optical microscopy. The elicited electrogenetic fluorescence intensities after 210 min in response to electrochemical and chemical activation were 1.3 × 108±0.30 × 108 arbitrary units (A.U.) and 1.2 × 108±0.30 × 108 A.U. per cell population, respectively, and 1.05 ± 0.01 A.U. and 1.05 ± 0.01 A.U. per-cell, respectively. We demonstrated that redox molecules\' mass transfer between the electrode and cells - and not the applied electrical field - activated the electrogenetic cells. Specifically, we found an oriented amplified electrogenetic response on the charged electrodes\' downstream side, which was determined by the location of the stimulating electrodes and the flow profile. We then focused on the cellular responses and observed distinct subpopulations that were attributed to electrochemical rather than chemical stimulation, with the distance between the cells and the stimulating electrode being the main determinant. These observations provide a comprehensive understanding of the mechanisms by which diffusible redox mediators serve as electron shuttles, imposing context and activating electrogenetic responses.

Isolation of tumor-specific T cells and their antigen receptors (TCRs) from malignant pleural effusions (MPE) may facilitate the development of TCR-transduced adoptive cellular immunotherapy products for advanced lung cancer patients. However, the characteristics and markers of tumor-specific T-cells in MPE are largely undefined. To this end, to establish the phenotypes and antigen specificities of CD8+ T cells, we performed single-cell RNA and TCR sequencing of samples from three advanced lung cancer patients. Dimensionality reduction on a total of 4,983 CD8+ T cells revealed 10 clusters including naïve, memory, and exhausted phenotypes. We focused particularly on exhausted T cell clusters and tested their TCR reactivity against neoantigens predicted from autologous cancer cell lines. Four different TCRs specific for the same neoantigen and one orphan TCR specific for the autologous cell line were identified from one of the patients. Differential gene expression analysis in tumor-specific T cells relative to the other T cells identified CXCL13, as a candidate gene expressed by tumor-specific T cells. In addition to expressing CXCL13, tumor-specific T cells were present in a higher proportion of T cells co-expressing PDCD1(PD-1)/TNFRSF9(4-1BB). Furthermore, flow cytometric analyses in advanced lung cancer patients with MPE documented that those with high PD-1/4-1BB expression have a better prognosis in the subset of 57 adenocarcinoma patients (p = .039). These data suggest that PD-1/4-1BB co-expression might identify tumor-specific CD8+ T cells in MPE, which are associated with patients\' prognosis. (233 words).