Limits...
Functional Characteristics of the Gut Microbiome in C57BL/6 Mice Differentially Susceptible to Plasmodium yoelii

View Article: PubMed Central - PubMed

ABSTRACT

C57BL/6 mice are widely used for in vivo studies of immune function and metabolism in mammals. In a previous study, it was observed that when C57BL/6 mice purchased from different vendors were infected with Plasmodium yoelii, a causative agent of murine malaria, they exhibited both differential immune responses and significantly different parasite burdens: these patterns were reproducible when gut contents were transplanted into gnotobiotic mice. To gain insight into the mechanism of resistance, we removed whole ceca from mice purchased from two vendors, Taconic Biosciences (low parasitemia) and Charles River Laboratories (high parasitemia), to determine the combined host and microflora metabolome and metatranscriptome. With the exception of two Charles River samples, we observed ≥90% similarity in overall bacterial gene expression within vendors and ≤80% similarity between vendors. In total 33 bacterial genes were differentially expressed in Charles River mice (p-value < 0.05) relative to the mice purchased from Taconic. Included among these, fliC, ureABC, and six members of the nuo gene family were overrepresented in microbiomes susceptible to more severe malaria. Moreover, 38 mouse genes were differentially expressed in these purported genetically identical mice. Differentially expressed genes included basigin, a cell surface receptor required for P. falciparum invasion of red blood cells. Differences in metabolite pools were detected, though their relevance to malaria infection, microbial community activity, or host response is not yet understood. Our data have provided new targets that may connect gut microbial activity to malaria resistance and susceptibility phenotypes in the C57BL/6 model organism.

No MeSH data available.


Non-metric multidimensional scaling of Bray-Curtis similarity matrix comparing overall abundances of bacterially derived transcripts. Blue points represent samples isolated from Taconic Biosciences mice. Red points represent samples isolated from Charles River Laboratories mice. Ellipses represent lines of 80, 85, and 90% similarity between samples. Asterisks designate two Charles River samples addressed in text.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC5037233&req=5

Figure 3: Non-metric multidimensional scaling of Bray-Curtis similarity matrix comparing overall abundances of bacterially derived transcripts. Blue points represent samples isolated from Taconic Biosciences mice. Red points represent samples isolated from Charles River Laboratories mice. Ellipses represent lines of 80, 85, and 90% similarity between samples. Asterisks designate two Charles River samples addressed in text.

Mentions: Non-metric multidimensional scaling plot of Bray–Curtis dissimilarity analysis is represented in Figure 3. Sample Taconic 6 was left out of this analysis due to significant dissimilarity caused by methodology that skews the plot. Overall bacterial transcript abundances in the 5 Taconic and 6 Charles River samples are at least 80% similar Figure 3. With the exception of two Charles River samples (designated by asterisks in Figure 3), mouse groups cluster with at least 85% similarity and as high as 98%. These two samples more closely resemble expression profiles of the Taconic gut communities. As mice from these two substrains are so closely related, some overlap within the internal variation of the mouse groups was to be expected. However, ANOSIM analysis comparing overall expression of bacterially derived transcripts determined that community expression between mouse groups was statistically different (p = 0.048).


Functional Characteristics of the Gut Microbiome in C57BL/6 Mice Differentially Susceptible to Plasmodium yoelii
Non-metric multidimensional scaling of Bray-Curtis similarity matrix comparing overall abundances of bacterially derived transcripts. Blue points represent samples isolated from Taconic Biosciences mice. Red points represent samples isolated from Charles River Laboratories mice. Ellipses represent lines of 80, 85, and 90% similarity between samples. Asterisks designate two Charles River samples addressed in text.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5037233&req=5

Figure 3: Non-metric multidimensional scaling of Bray-Curtis similarity matrix comparing overall abundances of bacterially derived transcripts. Blue points represent samples isolated from Taconic Biosciences mice. Red points represent samples isolated from Charles River Laboratories mice. Ellipses represent lines of 80, 85, and 90% similarity between samples. Asterisks designate two Charles River samples addressed in text.
Mentions: Non-metric multidimensional scaling plot of Bray–Curtis dissimilarity analysis is represented in Figure 3. Sample Taconic 6 was left out of this analysis due to significant dissimilarity caused by methodology that skews the plot. Overall bacterial transcript abundances in the 5 Taconic and 6 Charles River samples are at least 80% similar Figure 3. With the exception of two Charles River samples (designated by asterisks in Figure 3), mouse groups cluster with at least 85% similarity and as high as 98%. These two samples more closely resemble expression profiles of the Taconic gut communities. As mice from these two substrains are so closely related, some overlap within the internal variation of the mouse groups was to be expected. However, ANOSIM analysis comparing overall expression of bacterially derived transcripts determined that community expression between mouse groups was statistically different (p = 0.048).

View Article: PubMed Central - PubMed

ABSTRACT

C57BL/6 mice are widely used for in vivo studies of immune function and metabolism in mammals. In a previous study, it was observed that when C57BL/6 mice purchased from different vendors were infected with Plasmodium yoelii, a causative agent of murine malaria, they exhibited both differential immune responses and significantly different parasite burdens: these patterns were reproducible when gut contents were transplanted into gnotobiotic mice. To gain insight into the mechanism of resistance, we removed whole ceca from mice purchased from two vendors, Taconic Biosciences (low parasitemia) and Charles River Laboratories (high parasitemia), to determine the combined host and microflora metabolome and metatranscriptome. With the exception of two Charles River samples, we observed ≥90% similarity in overall bacterial gene expression within vendors and ≤80% similarity between vendors. In total 33 bacterial genes were differentially expressed in Charles River mice (p-value < 0.05) relative to the mice purchased from Taconic. Included among these, fliC, ureABC, and six members of the nuo gene family were overrepresented in microbiomes susceptible to more severe malaria. Moreover, 38 mouse genes were differentially expressed in these purported genetically identical mice. Differentially expressed genes included basigin, a cell surface receptor required for P. falciparum invasion of red blood cells. Differences in metabolite pools were detected, though their relevance to malaria infection, microbial community activity, or host response is not yet understood. Our data have provided new targets that may connect gut microbial activity to malaria resistance and susceptibility phenotypes in the C57BL/6 model organism.

No MeSH data available.