Immune activation during Paenibacillus brain infection in African infants with frequent cytomegalovirus co-infection

Abstract

Inflammation during neonatal brain infections leads to significant secondary sequelae such as hydrocephalus, which often follows neonatal sepsis in the developing world. In 100 African hydrocephalic infants we identified the biological pathways that account for this response. The dominant bacterial pathogen was a Paenibacillus species, with frequent cytomegalovirus co-infection. A proteogenomic strategy was employed to confirm host immune response to Paenibacillus and to define the interplay within the host immune response network. Immune activation emphasized neuroinflammation, oxidative stress reaction, and extracellular matrix organization. The innate immune system response included neutrophil activity, signaling via IL-4, IL-12, IL-13, interferon, and Jak/STAT pathways. Platelet-activating factors and factors involved with microbe recognition such as Class I MHC antigen-presenting complex were also increased. Evidence suggests that dysregulated neuroinflammation propagates inflammatory hydrocephalus, and these pathways are potential targets for adjunctive treatments to reduce the hazards of neuroinflammation and risk of hydrocephalus following neonatal sepsis.

Keywords: Immunology; Proteomics; Transcriptomics.

Graphical abstract

Figure 1

Schematic of proteogenomics experimental and data analysis workflow Output data from concurrent proteomics and RNA-seq on the same samples were preprocessed, normalized, batch-controlled, and explored independently. Differentially expressed transcriptomic and proteomic data were integrated following dimension reduction and feature selection. Gene ontology enrichment was evaluated and common reactome pathways were visualized to identify prominent molecular pathways implicated in the pathophysiology of postinfectious hydrocephalus. Adapted from “PTMScan Workflow,” by BioRender.com (2021). Retrieved from https://app.biorender.com/biorender-templates.

Figure 2

Proteomic profile of infants with postinfectious hydrocephalus (PIH) and those without (NPIH), based on 16s rRNA-determined Paenibacillus spp. status (A) Multidimensional scaling of normalized protein abundances demonstrating clustering of Paenibacillus spp.-positive (Paeni-positive) infants from the remaining groups. The abscissa and ordinate of the scatterplot of individual participants represent the first and second components, respectively. Each oval (not drawn to scale) encircles majority of patients belonging to the color-matched group, with blue as infants in the NPIH group, red as Paeni-negative PIH infants, and green as Paeni-positive infants. (B) Volcano plot demonstrating differential expression of genes between Paeni-positive and Paeni-negative infants. Adjustment for cytomegalovirus status did not change the differential expressions between groups. The vertical lines crossing the positive and negative abscissae demarcate fold changes of 1 and -1, respectively, and the horizontal dashed line crosses the ordinate at the alpha significance level of 0.05. Each point represents a differentially expressed protein, and those with an absolute fold change greater than 1 that met the significance level (red points) were selected for gene set enrichment analyses. Genes with enrichment below the statistically significant threshold are displayed in gray. (C) Gene ontology analyses of differentially expressed proteins of infants based on 16s rRNA-determined Paenibacillus spp. status. There was enrichment for functions associated with neuroinflammation, extracellular matrix structure, and cell-cell adhesion among Paeni-positive infants compared with Paeni-negative infants. The abscissae (ratio) of the dot plots correspond to the number of proteins per total number of proteins, and the size of each circle reflects the relative number of proteins expressed that are enriched for the corresponding function (ordinates).

Figure 3

Transcriptomic profile of infants with postinfectious hydrocephalus (PIH) and those without (NPIH), based on 16s rRNA-determined Paenibacillus spp. status (A) Multidimensional scaling of normalized gene expression demonstrating clustering of Paenibacillus spp.-positive (Paeni-positive) infants from the remaining groups. The abscissa and ordinate of the scatterplot of individual participants represent the first and second components, respectively. Each oval (not drawn to scale) encircles the majority of patients belonging to the color-matched group, with blue as infants in the NPIH group, red as Paeni-negative PIH infants, and green as Paeni-positive infants. (B) Heatmap of the 500 most differentially expressed genes between the Paeni-positive and Paeni-negative infants, with the dendrogram demonstrating hierarchical clustering on Euclidean distance of gene identified in infants based on Paenibacillus spp. status. (C) Gene ontology analyses of differentially expressed genes of infants based on 16s rRNA-determined Paenibacillus spp. status. There was enrichment for functions associated with neuroinflammation, extracellular matrix structure, and cell-cell adhesion among Paeni-positive infants compared with Paeni-negative infants. The abscissae (ratio) of the dot plots correspond to the number of proteins per total number of proteins, and the size of each circle reflects the relative number of proteins expressed that are enriched for the corresponding function (ordinates).

Figure 4

Role of CMV co-infection (A) An interactome of the 64 genes that were differentially expressed based on CMV status, enriched for functions related to host response to virus. (B) Principal-component analysis plot demonstrating that using RNA abundance of all genes was not able to cluster samples by CMV status. The abscissa and ordinate of the scatterplot of individual participants represent the first and second components, respectively. (C) Volcano plot demonstrating there are no differentially expressed proteins based on CMV status alone (blue points) that had a fold change greater than 1 or met statistical significance criteria. Genes with enrichment below the statistically significant threshold are displayed in gray. Differential expression of proteins based on Paenibacillus spp. status was similar with or without adjusting for CMV status (Figure 2).

Figure 5

Weighted correlation network analysis (WGCNA) and single-cell RNA deconvolution (A) Gene modules within RNA-seq data for PIH and NPIH cohorts identified by WGCNA. Module 1 positively correlated with CSF cell count and negatively with Paenibacillus spp. status and was enriched for host immune responses, including leukocyte and neutrophil functions. (B) Module 2 was positively correlated with Paenibacillus spp. status, but the associated genes had no specific functional enrichment. (C) Deconvolution of bulk RNA data into immune cell populations expressed on a scale of 0 to 1 that is calculated for each patient. There was hierarchical clustering of a mixture of NPIH and PIH samples with a hematologic predominance, and PIH-only samples with T helper and NK cell populations.

Figure 6

Proteogenomic integration of proteins and genes expressed in RNA-seq and/or proteomics among infants with postinfectious and non-postinfectious hydrocephalus stratified by cerebrospinal fluid 16s rRNA Paenibacillus spp. status (A) Alluvial plot demonstrating the most prominent gene ontological (GO) functions and interactions for PIH pathophysiology between Paenibacillus spp.-positive and Paenibacillus spp.-negative infants. Each ontological clustering occupies a column in the diagram and is horizontally connected to preceding and succeeding significance clustering by stream fields, representing similar gene involvement. Each stacked bar is color-coded based on the assay being assessed, with red representing RNA-seq data, purple for proteomics, and green for genes common to both RNA-seq and proteomics. The ordinate shows the number of genes represented in each cluster. (B) Box and whisker plot of the 33 genes that were differentially expressed based on Paenibacillus spp. status. Counts (ordinate) of each gene (abscissa) are shown for each group, with blue representing NPIH, red for Paeni-negative PIH, and green for Paeni-positive PIH infants.

Figure 7

Pathway analysis of 33 genes that were differentially expressed in both RNA-seq and proteomics among infants with postinfectious and non-postinfectious hydrocephalus stratified by cerebrospinal fluid 16s rRNA Paenibacillus spp. status Corresponding pairs of upregulated (red boxes) and downregulated (green boxes) proteins (blue columns) and genes (purple columns) in the Paenibacillus spp.-positive group that were identified with proteomics and RNA-seq, respectively, are listed on the abscissa. The 33 common genes demonstrated predominant involvement of the immune system, particularly the innate system and those associated with neutrophil-mediated activity, interleukins, interferon, and the Janus kinase/signal transducers and activators of transcription (JAK-STAT) pathway (ordinate). Differential expression was defined as log₂ fold change of >1 or < -1 at an alpha significance level of 0.05.