CUT&RUN sequencing on wildtype HSCs, MPP3s, GMPs, and macrophages with four weeks M. avium infection
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE277899 | GEO | 2025/12/01
REPOSITORIES: GEO
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Project description:Purpose: To evaluate whether methylation changes occuring upon M. avium infection correlate with transcriptional alterations in trained HSCs, we reisolated CD45.2 untrained vs. trained HSCs (LK CD150+CD48–) from transplanted mice one-month after M. avium challenge to generate bulk RNA-Seq libraries. We compared both libraries to a library from HSCs of WT donor mice following primary M. avium infection. This comparison revealed changes in global transcription in trained HSCs after M. avium challenge compared to primary infection, with the untrained set serving as the irradiation and transplant control. Methods: 10,000-50,000 HSCs (CD45.1/CD45.2 KL CD150+ CD48-) into HBSS from naive or 1-month infected WT/transplanted mice (n=10-12 per group). DNA and RNA were isolated with the NucleoSpin ® RNA Plus XS kit (Macherey Nagel). RNA-seq libraries were prepared using SMARTer® Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara Bio Usa). Illumina NovaSeq SP was used for sequencing with a paired-end sequencing length of 10bp. Samples were sequenced at Admera Health using an Illumina HiSeq 2x150 at sequencing depth of ~40 million reads. FASTQ files were preprocessed using HTS stream (https://github.com/ibest/HTStream) and the clean FASTQ file were aligned using STAR. Differential expression (DE) analysis of gene expression was performed using Limma-Voom. False discovery rate (FDR)<0.05 was considered statistically significant. Further analysis was completed using Illumina Basespace packages and programs (deSeq2) We performed gene ontology analysis for differentially expressed genes with q value of <0.05. Gene set enrichment analysis (GSEA, Broad Institute and UC San Diego) was completed using normalized gene counts as previously described ((Subramanian et al., 2005). Results were visualized using Tidyverse packages in R. Comparison of differentially expressed gene lists and generation of Venn diagrams were generated using the GeneVenn webtool. Biological process and molecular function gene ontology analysis of differentially expressed genes found in bulk RNA-seq datasets were completed using GENEONTOLOGY of the Mus musculus database (Ashburner et al., 2000; Gene Ontology, 2021). Results:The gene expression profile of M. avium-challenged untrained HSCs was compared to that of control infected animals . Next, the gene expression profile of trained HSCs was compared to the same untransplanted controls to detect transcriptional changes potentiated by training. This analysis revealed many more genes (670) upregulated upon secondary infection in the trained population compared to untrained (255). GO analysis of the trained HSPC gene signature showed that there was an enrichment in pathways related to G protein-coupled receptor signaling, cellular adhesion, cell differentiation, immunity, and autophagy . Strikingly, gene set enrichment analysis (GSEA) of the genes uniquely upregulated upon infectious challenge in the trained HSPCs aligned with enhanced metabolism — glycolysis, oxidative phosphorylation, and fatty acid metabolism — genes that are reportedly rewired in macrophages in other trained immunity models (Figure 4C). Pathways related to transcription and translation were also upregulated in trained HSPCs (Supplemental Figure 4C). On the other hand, untrained HSPCs primarily upregulated chemokine responses and immune response pathways, as we previously reported. Together, these analyses reveal trained versus untrained HSPCs have differing responses to infection at 1 month post-challenge compared to untransplanted controls. When directly comparing untrained versus trained gene expression, those with a primary infectious exposure (untrained HSPCs) upregulated immune response pathways while trained cells upregulated metabolic pathway genes. We speculate that relatively lower immune response pathways in trained HSPCs may reflect greater control of infection in the host, enabling the cells to prioritize other cellular pathways. Conclusions: Upregulation of metabolism and gene regulation pathways in trained HSPCs that have been rechallenged with M. avium may reflect greater control of infection and improved immunity within the host compared to untrained controls.
2023-08-02 | GSE197294 | GEO
Project description:Once entering the cell, M. avium subsp.paratuberculosis is known to survive harsh microenvironments, especially those inside activated macrophages. To improve our understanding of M. avium subsp.paratuberculosis pathogenesis, we examined the phagosome maturation associated with transcriptional responses of M. avium subsp.paratuberculosis during macrophage infection. Monitoring cellular markers, only live M. avium subsp.paratuberculosis bacilli were able to prevent phagosome maturation and reduce its acidification. On the transcriptional level, over 300 of M. avium subsp.paratuberculosis genes were significantly, differentially regulated in both naïve and IFN-γ-activated macrophages. These genes include the sigma factor H (sigH) that was shown to be important during persistent infection in M. tuberculosis.
2013-01-22 | GSE43645 | GEO
Project description:Mycobacterium avium is one of the prominent disease causing bacteria in humans. It causes lymphadenitis, chronic pulmonary and extrapulmonary and disseminated infections in adults, children and immunocompromised humans. M. avium has ~4,500 predicted gene models, out of which not all are identified at proteomic level. Proteomic database search followed by proteogenomic analysis helps in the correction of gene models, identification of novel exons/genes, variant proteins. As part of this study, we performed proteomic analysis of M. avium cultures by data-dependent acquisition (DDA) and data-independent acquisition (DIA) method followed by proteogenomic analysis of M. avium proteomic data. M. avium culture was subjected to proteomic sample preparation. The resulting peptides were acquired in 120min DDA (12 bRPLC) and DIA method using EASY nLC 1200 liquid chromatogram system coupled to Orbitrap Fusion Tribrid mass spectrometer. The resulting DDA raw files were searched sequentially against the M. avium proteome database, Mycobacterium tuberculosis H37Rv and Ra proteome database (Mtb), M. avium genome six-frame translated proteome and variant proteins database, respectively. The database search result was converted into a spectral library and used for DIA data search for the validation of GSSPs and variant peptides. The database search of M. avium DDA has resulted in the identification of 2,954 M. avium proteins, 128 Mtb proteins, 174 GSSPs (M. avium genome six-frame translated proteome) and 795 SNPs corresponding to 612 proteins (variant proteins database), respectively. The M. avium proteome database search has covered 62.09% of the proteome with the identification of 2,954 proteins out of 4,757 proteins in the database. From the manual categorization of 174 GSSPs, we observed 23 N-terminal extensions, 142 pseudogene coding peptides and one each novel exon and short peptide, respectively.
2023-03-17 | PXD032067 | Pride
Project description:We focused on how Mycobacterium avium subsp. paratuberculosis influences the subsequent host response to investigate the host immunopathology accompanying the host anti-mycobacterial immune response during Mycobacterium avium subsp. paratuberculosis infection in spleen of mice.
2014-10-31 | GSE62836 | GEO
Project description:purpose: Chronic inflammation induced by Mycobacterium avium infection (timepoint= 1 month) results in transcriptomic changes within the HSC population subset upon bulk RNA-seq, particularly in pathways involved in the immune response, interferon gamma signaling (Th1 immune response) pathway, stat signaling, and antigen processing and presentation. We have also shown that chronic inflammation results in a myeloid differentiation bias of HSPCs. We hypothesize that these transcriptomic changes induced by chronic inflammation may be specific to a certain subset of HSPCs and could be passed on to specific terminally differentiated subsets. To investigate this hypothesis, we performed scRNA-seq using the 10x genomics platform to test the transcriptomic differences induced upon infection in HSC, progenitor, myeloid, and lymphoid cell populations along with heterogeneity observed within the HSC population. methods: CD45.2 mice were infected with 2 x 10^6 CFU M. avium for one month prior to bone marrow harvesting. One month post infection, experimental mice were euthanized and infection was confirmed by measuring splenic weight and size. WBM from the hips, tibias, and femurs of each mouse was extracted through crushing with a mortar and pestle. The suspension was then RBC lysed and CD117 (c-kit)+ and cKit- cells were separated using a manual magnetic separation system (Miltenyi). Experimental samples were stained with desired antibodies (listed in key resources table) and sorted using a BD FACS Aria cell sorter. The following cell types were isolated according to the following phenotypic definitions (please see file phenotypic_definitions.txt). The cellular purity and count of each sample was confirmed prior to pooling for submission to the BCM Single Cell Core. Depending on the rarity of the isolated population, 20,000-50,000 sorted cells were combined to a concentration of ~7200 cells/uL. Samples were loaded into the Chromium controller system and generated 3’ 10x scRNAseq barcoded libraries for each sample. Prior to sequencing, quality control of the libraries was completed using a Bioanalyzer (Agilent, Santa Clara, CA) and Nanodrop system. Samples were sequenced on a NovaSeq at a sequencing depth of 300M reads at the BCM Genomic and RNA Profiling (GARP) core. After sequencing, fastq files for each sample were generated (R1, R2, and I1 files) to demultiplex the data using the CellRanger pipeline results: scRNA-seq studies revealed that training led to a bimodal distribution of gene expression, with a subset showing activation of immunity-related genes. This gene signature was propagated to innate immune cells but was not conserved in B cells, indicating specific patterns of gene signature inheritance. M. avium training also led to the emergence of an “activated” HSC subpopulation, indicating subsets of HSCs are more responsive to training conclusions: Transcriptomic signatures induced by M. avium exposure, particularly in IFNg response genes, are heterogeneous and are propagated in a myeloid biased manner
2023-07-30 | GSE197407 | GEO
Project description:We focused on how Mycobacterium avium subsp. paratuberculosis influences the subsequent host response to investigate the host immunopathology accompanying the host anti-mycobacterial immune response during Mycobacterium avium subsp. paratuberculosis infection in spleen of mice. We analyzed altered transcription in the spleen of mice at 3, 6, and 12 weeks following Mycobacterium avium subsp. paratuberculosis infection.
2014-10-31 | E-GEOD-62836 | biostudies-arrayexpress
Project description:Deep sequencing was implemented to study the transcriptional landscape of Mycobacterium avium TMC724. High-resolution transcriptome analysis identified the transcription start points for 652 genes. One third of these coincided with the start codons and therefore belong to leaderless transcripts, whereas the rest of the transcripts had 5' UTRs with the mean length of 83 nt. In addition, the 5' UTRs of 6 genes contained SAM-IV and Ykok types of riboswitches. 87 antisense RNAs and 9 intergenic small RNAs were mapped. Four of the revealed intergenic small RNAs, including igMAV_1034-1035 expressed at a very high level, have no homologs in M. tuberculosis, whilst M. avium lacks several intergenic sRNAs present in M. tuberculosis. Among those, MTS479 and MTS1338 are of special interest due to their possible implication in pathogenesis. Elucidation of differences in the repertoire of intergenic sRNAs between the two mycobacterial species may improve our understanding of mycobacterial diseases pathogenesis. Transcriptional profile of Mycobacterium avium TMC724, grown at 37M-BM-0C in Dubos broth until mid-logarithmic growth phase
2013-04-23 | E-GEOD-46281 | biostudies-arrayexpress
Project description:Prunus avium subsp. avium RNAseq
| PRJNA863395 | ENA
Project description:Background: Mycobacterium avium complex (MAC) bacteria cause opportunistic infections in humans. Treatment yields cure rates of 60% and is comprised of a macrolide, a rifamycin and ethambutol; and in severe cases amikacin. Mechanisms of antibiotic tolerance remain mostly unknown. To elucidate these mechanisms, we studied the transcriptomic response to antibiotics and investigated the contribution of efflux and amikacin modification to susceptibility. Methods: M. avium was subjected to subinhibitory concentrations of clarithromycin, amikacin, ethambutol and rifampicin followed by RNA sequencing. Based thereupon, we characterized M. avium efflux pumps and performed time-kill kinetic analysis using each antibiotic in combination with the efflux pump inhibitors (EPIs) berberine, verapamil and CCCP to study the role of efflux on susceptibility. Finally, we studied the modification of amikacin by M. avium using metabolomic analysis. Results: Changes in respiratory state and changes in ribosome binding and protein folding likely contribute to clarithromycin and amikacin tolerance, respectively. No clear drug-specific mechanisms of tolerance are found for ethambutol and rifampicin. Of the EPIs, only berberine increased the susceptibility to rifampicin and clarithromycin. Finally, we show that M. avium, in contrast to M. abscessus, is not able to modify amikacin. Conclusion: M. avium likely relies on a combination of drug-specific and generic mechanisms of antibiotic tolerance including changes in respiratory and metabolic state in addition to drug efflux and target modification. Efflux inhibition can increase susceptibility but this effect is EPI and antibiotic specific. Finally, the lack of amikacin modifying activity in M. avium is important for its activity.
2024-01-01 | GSE213116 | GEO
Project description:A comparative genomic approach was used to identify large sequence polymorphisms among Mycobacterium avium isolates obtained from a variety of host species. DNA microarrays were used as a platform for comparing mycobacteria field isolates with the sequenced bovine isolate Mycobacterium avium subsp. paratuberculosis (Map) K10. ORFs were classified as present or divergent based on the relative fluorescent intensities of the experimental samples compared to Map K10 DNA. Map isolates cultured from cattle, bison, sheep, goat, avian, and human sources were hybridized to the Map microarray. Three large deletions were observed in the genomes of four Map isolates obtained from sheep and four clusters of ORFs homologous to sequences in the Mycobacterium avium subsp. avium (Maa) 104 genome were identified as being present in these isolates. One of these clusters encodes glycopeptidolipid biosynthesis enzymes. One of the Map sheep isolates had a genome profile similar to a group of Mycobacterium avium subsp. silvaticum (Mas) isolates which included four independent laboratory stocks of the organism traditionally identified as Maa strain 18. Genome diversity in Map appears to be mostly restricted to large sequence polymorphisms that are often associated with mobile genetic elements. Keywords: Comparative genomic hybridization
2007-04-27 | GSE7622 | GEO