Early transcriptomic response of innate immune cells to subcutaneous BCG vaccination of mice

Abstract

Objectives

Current data suggests that Bacille Calmette-Guerin (BCG) vaccination contributes to nonspecific enhancement of resistance to various infections. Thus, BCG vaccination induces both specific immunity against mycobacteria and non-specific “trained immunity” against various pathogens. To understand the fundamental mechanisms of “trained” immunity, studies of transcriptome changes occurring during BCG vaccination in innate immunity cells, as well as in their precursors, are necessary. Furthermore, this data possesses important significance for practical applications associated with the development of recombinant BCG strains aimed to enhance innate immunity against diverse infectious agents.

Data description

We performed RNA sequencing of innate immune cells derived from murine bone marrow and spleen three days after subcutaneous BCG vaccination. Using fluorescence-activated cell sorting we obtained three cell populations for each mouse from both control and BCG vaccinated groups: bone marrow monocytes and neutrophils and splenic NK-cells. Then double-indexed cDNA libraries for Illumina sequencing from the collected samples were prepared, the resulting cDNA library mix was subjected to NovaSeq 6000 sequencing. This paper describes the collection of 24 RNA sequencing samples comprising 4 sets of immune cell populations obtained from subcutaneously BCG-vaccinated and control mice

Objective

The increasing amount of data from epidemiological and immunological studies indicates that, in addition to the target specific effects against particular diseases, vaccines might exhibit off-target heterologous effects on other unrelated pathogens [1, 2]. Research and randomized clinical trials (reviewed in [3]) demonstrate that the use of Bacillus Calmette-Guérin (BCG) contributes to increased resistance not only to tuberculosis but also to other diseases, resulting in a reduction in mortality from these conditions [3,4,5,6,7]. This effect is characteristic of other vaccines as well, and it is primarily associated with the training of innate immune cells (to form “trained immunity” [8]), that occurs during the primary infection or vaccination [9,10,11]. Subsequently, these trained cells provide protection against secondary infection through mechanisms independent of adaptive T and B cell responses [9]. Moreover, evidence suggest that “trained” innate immune cells may exhibit enhanced antiviral and anticancer activity [5, 12, 13]. In vitro and in vivo experiments demonstrated that the exposure of different types of cells to BCG led to the acquirement of characteristic features of “trained” cells by monocytes, macrophages, natural killers, neutrophils, and eosinophils [14]. It was also demonstrated that BCG vaccination induces epigenetic reprogramming of hematopoietic stem cells in the bone marrow, leading to subsequent transcriptional and functional changes, resulting in the emergence of “trained” myeloid cells such as monocytes and neutrophils [10, 15]. These observations explain the mechanism behind the prolonged presence of “trained” immune cells in the bloodstream after vaccination. In order to understand the fundamental mechanisms of “trained” immunity, studies of transcriptome changes occurring during BCG vaccination in innate immunity cells, as well as in their precursors, are necessary. Furthermore, this data possesses important significance for practical applications associated with the development of recombinant BCG strains aimed to enhance innate immunity against diverse infectious agents (viruses, bacteria, fungi).

Data description

C57Bl/6J mice were subcutaneously vaccinated with 106 CFU of Mycobacterium bovis/BCG, mice in the control group were subcutaneously injected with PBS. Three days after BCG administration, vaccinated and control animals were sacrificed under isoflurane anesthesia, by exsanguination and subsequent cervical dislocation, after which spleen and bone marrow were collected. Obtained cell suspensions from spleen and bone marrow were stained with antibody panel, containing conjugated antibodies against CD45-PerCP/Cy5.5, CD11b-FITC, NK1.1-PE, Ly6G-APC, and Ly6C-APC/Cyanine. Next, cell population analysis and fluorescence-activated cell sorting (FACS) were performed. Three cellular populations, Monocytes CD45 + CD11b + Ly6C+, Neutrophils CD45 + CD11b + Ly6G+, NK-cells CD45 + CD11b-NK1.1 + for each mouse from both control and BCG vaccinated groups were collected by FACS. As a result, 300,000 neutrophils, 50,000 monocytes and 50,000 NK cells for each mouse from both groups were isolated. Moreover, 1 million of total unsorted bone marrow cells from each mouse were collected to reveal common changes for all immune cells. All obtained cell populations were further used for total RNA extraction. The RNA quality was assessed via agarose gel electrophoresis using Agilent TapeStation 4200 System. The total RNA was further depleted from rRNA and used for directed double-indexed RNA-seq library preparation. Finally, the resulting 24 individually indexed RNA-seq libraries (3 × Bone Marrow-Control, 3 × Bone Marrow-BCG, 3 × Neutrophils-Control, 3 × Neutrophils-BCG, 3 × Monocytes-Control, 3 × Monocytes-BCG, 3 × NK-Control, 3 × NK-BCG) were mixed in equimolar amounts, the final mixture was analyzed with Agilent TapeStation system. The median fragment length of the pooled fragments was 357 b.p., distributed between 200 and 700 b.p. (Table 1)

The resulting RNA-seq library mixture was further subjected to NovaSeq 6000 (Illumina) sequencing. Overall, 1,418,200,000 double-end 150 b.p. reads were obtained. The fastq files were analyzed with FASTQC tool [16], the resulting report indicated acceptable sequencing quality for all 24 samples. The mean amount of paired-end reads per library was 57 million. The reads were further aligned to murine reference genome (GRCm38/mm10) via HISAT2 [16] tool. The successfully aligned reads were then counted with featureCount tool [17] (GENCODE vM23, GRCm38.p6 was used as the reference transcriptome, FeatureCount table accessible onhttps://identifiers.org/geo:GSE261448 [18]).

Table 1 Overview of data files/data sets

Limitations

This study is limited by the small sample size, and technical issues resulting in batch effects further reducing the statistical power. The experimental design takes every care to obtain the maximum possible amount of information using the minimum number of animals to be conducted in accordance with national and international standards regulating the use of experimental animals for scientific purposes.