-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
-
Cosmetic Ingredient
- Water Treatment Chemical
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
Written | Edited by Xue Yue | Xi Mycobacterium tuberculosis Mtb infection kills 1.
5 million people every year
.
However, the response of the human immune system to Mtb has not been fully elucidated, hindering the development of host-directed therapies
.
Mycobacterium tuberculosis is inhaled into the lungs and engulfed by macrophages, triggering an immune response and forming granulomas
.
Granuloma is a dynamic spatial structure composed of macrophages, granulocytes, lymphocytes and fibroblasts
.
Granulomas isolate infection sites from uninvolved lung tissue on the one hand to limit transmission, and on the other hand, tolerance pathways upregulated at granuloma sites limit Mycobacterium tuberculosis clearance
.
The composition of granulomas is highly variable
.
Even in a single individual, infection can lead to granulomas with different histological features
.
Each granuloma changes independently over time
.
In nonhuman primate infection models, there are more than ten granulomas per individual individual, and each granuloma varies widely in inflammatory characteristics, size, and bacterial ecology
.
Recently, Michael Angelo's team from Stanford University published an article entitled The immunoregulatory landscape of human tuberculosis granulomas in Nature Immunology, mapping the immune regulatory network of human tuberculosis granulomas
.
The authors first examined immune cell composition in human binding granulomas
.
Tissue samples were obtained from paraffin-embedded samples of treated patients
.
Paraffin-embedded samples were obtained from excised tissue from advanced tuberculosis in South Africa; lung tissue from fatal tuberculosis and autopsy of patients in the United States
.
Sample collection sites include the lungs, pleural cavity, lymph nodes, vertebrae, and endometrium
.
The authors performed MIBI-TOF imaging of the samples for antibodies including markers of immune and non-immune cell lineages and markers of immune activity, including lymphocytes, macrophages, granulocytes, and epithelial cells
.
After labeling, in order to extract information about individual cells, the authors performed phenotype analysis on each image using FlowSOM
.
The results showed that T cells and myeloid cells predominated in granulomas
.
Through different markers, myeloid cells can be differentiated into macrophages, DCs and monocytes
.
The authors also calculated that γδT cells accounted for 0.
1%, CD209+DC 0.
2%, and Treg 1%
.
This suggests that the method can identify cell populations that are less abundant
.
Consistent with previous reports, active granulomas showed increased blood vessels and endothelial cells accounted for 3.
7%
.
The proportions of fibroblasts and epithelial cells vary by lesion
.
The authors classified 94% of the detected, approximately 39,709 single cells into 19 cell populations
.
The authors carefully analyzed the relationship between 19 cell populations and TB disease status and found that a comprehensive cell census can reveal different types of granulomas, mainly determined by the frequency of immune cells
.
The authors next analyzed the association of spatial structure and function in granulomas
.
The authors performed a spatial enrichment analysis to quantify how often the two markers appeared together
.
Spatial analysis revealed a feature that could not be identified at the level of global analysis, namely the presence of spatially cooperating cellular responses in granulomas
.
For example, some granulomas exhibit a fibrotic wound-healing response, and in these sites CD163+M2-like macrophages are spatially distributed close to fibroblasts
.
By evaluating immune activity markers such as PD-L1 IDO1, the authors found that myeloid cells in granulomas play an immunosuppressive role, while the activation of lymphocytes distributed in granulomas is sporadic
.
Finally, the authors analyzed the peripheral blood transcriptional profiles of healthy individuals and tuberculosis patients to analyze immune activation in peripheral blood
.
The authors found that the immune status of granulomas and peripheral blood were synchronized and correlated with tuberculosis infection
.
In this study, we performed analysis of cellular composition, mapping of spatial distribution, and exploration of immune regulatory pathways in granulomas following Mycobacterium tuberculosis infection, and established a link between granulomas and peripheral immune responses, for the development of host-oriented immune responses.
Therapy provides the basics of immunology
.
Original link: https://doi.
org/10.
1038/s41590-021-01121-x Publisher: 11th reprint notice [Original article] BioArt original article, welcome to forward and share personally, reprint is prohibited without permission, all published articles The copyright of the work is owned by BioArt
.
BioArt reserves all legal rights and violators will be held accountable
.
5 million people every year
.
However, the response of the human immune system to Mtb has not been fully elucidated, hindering the development of host-directed therapies
.
Mycobacterium tuberculosis is inhaled into the lungs and engulfed by macrophages, triggering an immune response and forming granulomas
.
Granuloma is a dynamic spatial structure composed of macrophages, granulocytes, lymphocytes and fibroblasts
.
Granulomas isolate infection sites from uninvolved lung tissue on the one hand to limit transmission, and on the other hand, tolerance pathways upregulated at granuloma sites limit Mycobacterium tuberculosis clearance
.
The composition of granulomas is highly variable
.
Even in a single individual, infection can lead to granulomas with different histological features
.
Each granuloma changes independently over time
.
In nonhuman primate infection models, there are more than ten granulomas per individual individual, and each granuloma varies widely in inflammatory characteristics, size, and bacterial ecology
.
Recently, Michael Angelo's team from Stanford University published an article entitled The immunoregulatory landscape of human tuberculosis granulomas in Nature Immunology, mapping the immune regulatory network of human tuberculosis granulomas
.
The authors first examined immune cell composition in human binding granulomas
.
Tissue samples were obtained from paraffin-embedded samples of treated patients
.
Paraffin-embedded samples were obtained from excised tissue from advanced tuberculosis in South Africa; lung tissue from fatal tuberculosis and autopsy of patients in the United States
.
Sample collection sites include the lungs, pleural cavity, lymph nodes, vertebrae, and endometrium
.
The authors performed MIBI-TOF imaging of the samples for antibodies including markers of immune and non-immune cell lineages and markers of immune activity, including lymphocytes, macrophages, granulocytes, and epithelial cells
.
After labeling, in order to extract information about individual cells, the authors performed phenotype analysis on each image using FlowSOM
.
The results showed that T cells and myeloid cells predominated in granulomas
.
Through different markers, myeloid cells can be differentiated into macrophages, DCs and monocytes
.
The authors also calculated that γδT cells accounted for 0.
1%, CD209+DC 0.
2%, and Treg 1%
.
This suggests that the method can identify cell populations that are less abundant
.
Consistent with previous reports, active granulomas showed increased blood vessels and endothelial cells accounted for 3.
7%
.
The proportions of fibroblasts and epithelial cells vary by lesion
.
The authors classified 94% of the detected, approximately 39,709 single cells into 19 cell populations
.
The authors carefully analyzed the relationship between 19 cell populations and TB disease status and found that a comprehensive cell census can reveal different types of granulomas, mainly determined by the frequency of immune cells
.
The authors next analyzed the association of spatial structure and function in granulomas
.
The authors performed a spatial enrichment analysis to quantify how often the two markers appeared together
.
Spatial analysis revealed a feature that could not be identified at the level of global analysis, namely the presence of spatially cooperating cellular responses in granulomas
.
For example, some granulomas exhibit a fibrotic wound-healing response, and in these sites CD163+M2-like macrophages are spatially distributed close to fibroblasts
.
By evaluating immune activity markers such as PD-L1 IDO1, the authors found that myeloid cells in granulomas play an immunosuppressive role, while the activation of lymphocytes distributed in granulomas is sporadic
.
Finally, the authors analyzed the peripheral blood transcriptional profiles of healthy individuals and tuberculosis patients to analyze immune activation in peripheral blood
.
The authors found that the immune status of granulomas and peripheral blood were synchronized and correlated with tuberculosis infection
.
In this study, we performed analysis of cellular composition, mapping of spatial distribution, and exploration of immune regulatory pathways in granulomas following Mycobacterium tuberculosis infection, and established a link between granulomas and peripheral immune responses, for the development of host-oriented immune responses.
Therapy provides the basics of immunology
.
Original link: https://doi.
org/10.
1038/s41590-021-01121-x Publisher: 11th reprint notice [Original article] BioArt original article, welcome to forward and share personally, reprint is prohibited without permission, all published articles The copyright of the work is owned by BioArt
.
BioArt reserves all legal rights and violators will be held accountable
.
