Journal: Microorganisms

Article Title: Outer Membrane Vesicles Attenuate Klebsiella pneumoniae Infection Injury by Affecting Macrophage Polarisation and Helper T Cell Differentiation

doi: 10.3390/microorganisms13122849

Figure Lengend Snippet: An analysis of transcriptome data derived from mice immunized with K. pneumoniae _OMVs. ( A ) A Venn diagram illustrating the co-expressed genes between the K. pneumoniae _OMVs and control groups. ( B ) A volcano plot depicting the DEGs. ( C ) A clustering heat map of the significant DEGs. ( D ) A bar graph representing the GO enrichment of the DEGs. ( E ) Summary plot of KEGG classification of DEGs. An online tool for data analysis and visualization, https://www.bioinformatics.com.cn (last viewed on 10 December 2024), created the heatmap .

Article Snippet: RNA-seq data analysis: The Norwood Biomedical Reference Transcriptome Cloud Analysis platform ( https://magic.novogene.com/customer/main#/homeNew (accessed on 29 May 2025)) was used to analyze differentially expressed genes (DEGs).

Techniques: Derivative Assay, Control

Journal: bioRxiv

Article Title: Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas

doi: 10.1101/2025.03.10.642376

Figure Lengend Snippet: Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole transcriptome probe set using GeoMx (Bruker).

Article Snippet: Due to the limited data on the functional role and significance of MDSCs in TB infected lung tissues, we used an unbiased spatial whole transcriptome analysis (WTA) platform (GeoMx, Bruker, Inc) integrated with single-cell immunophenotyping via highly multiplexed tissue cyclic immunofluorescence (CyCIF) to initiate this study of human TB.

Techniques: Fluorescence, Staining

Journal: Frontiers in Plant Science

Article Title: Combination of transcriptomic, biochemical, and physiological analyses reveals sugar metabolism in Camellia drupifera fruit at different developmental stages

doi: 10.3389/fpls.2024.1424284

Figure Lengend Snippet: DEGs from transcriptome sequencing across four fruit developmental stages in C. drupifera . (A) Summary of DEGS in all combinations of developmental stage comparisons; (B) PCA from July to October. Samples from the same development stage were grouped together within the same circle; The Venn diagram illustrates the DEGs between Jul. vs Aug., Jul. vs Sep., and Jul. vs Oct. (C) All DEGs; (D) Up-regulated DEGs; (E) Down- regulated DEGs.

Article Snippet: Furthermore, transcriptome sequencing, quality assessment, transcriptome assembly, functional annotation of Unigenes, and differential gene expression analysis were conducted using a no-reference genome transcriptome analysis platform provided by Beijing Biomarker Technologies Co., Ltd.

Techniques: Sequencing

Journal: Frontiers in Plant Science

Article Title: Combination of transcriptomic, biochemical, and physiological analyses reveals sugar metabolism in Camellia drupifera fruit at different developmental stages

doi: 10.3389/fpls.2024.1424284

Figure Lengend Snippet: Clusters of total genes and EuKaryotic Orthologous Group (KOG) annotations of profiles. (A) All genes were clustered based on their FPKM data with an FDR ≤ 0.05. Profile numbers, p-values, and gene numbers are in the upper left corner, lower left corner, and upper right corner; (B) Six clusters were obtained by short time-series expression miner (STEM) software, analyzing gene expression profiles. The y-axis of each cluster indicates the log2FC value. KOG analysis utilized a p-value ≤ 0.05 and a minimum fold change of two. The y−axis of each KOG analysis represents the number of genes.

Article Snippet: Furthermore, transcriptome sequencing, quality assessment, transcriptome assembly, functional annotation of Unigenes, and differential gene expression analysis were conducted using a no-reference genome transcriptome analysis platform provided by Beijing Biomarker Technologies Co., Ltd.

Techniques: Expressing, Software, Gene Expression