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The Features of Fecal and Ileal Mucosa-Associated Microbiota in Dairy Calves during Early Infection with Mycobacterium avium Subspecies paratuberculosis.

Derakhshani H, De Buck J, Mortier R, Barkema HW, Krause DO, Khafipour E - Front Microbiol (2016)

Bottom Line: Current diagnostic tests for Johne's disease (JD), a chronic granulomatous inflammation of the gastrointestinal tract of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), lack the sensitivity to identify infected animals at early (asymptomatic) stages of the disease.Moreover, based on reconstructed metagenomes (PICRUSt) of ileal MAM, functional pathways associated with MAP infection were inferred.Enrichment of lysine and histidine metabolism pathways, and underrepresentation of glutathione metabolism and leucine and isoleucine degradation pathways in MAP-infected calves suggested potential contributions of ileal MAM in development of intestinal inflammation.

View Article: PubMed Central - PubMed

Affiliation: Department of Animal Science, University of Manitoba Winnipeg, MB, Canada.

ABSTRACT
Current diagnostic tests for Johne's disease (JD), a chronic granulomatous inflammation of the gastrointestinal tract of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), lack the sensitivity to identify infected animals at early (asymptomatic) stages of the disease. The objective was to determine the pattern of MAP-associated dysbiosis of intestinal microbiota as a potential biomarker for early detection of infected cattle. To that end, genomic DNA was extracted from ileal mucosa and fecal samples collected from 28 MAP-positive and five control calves. High-throughput Illumina sequencing of the V4 hypervariable region of the 16S rRNA gene was used for community profiling of ileal mucosa-associated (MAM) or fecal microbiota. The PERMANOVA analysis of unweighted UniFrac distances revealed distinct clustering of ileal MAM (P = 0.049) and fecal microbiota (P = 0.068) in MAP-infected vs. control cattle. Microbiota profile of MAP-infected animals was further investigated by linear discriminant analysis effective size (LEfSe); several bacterial taxa within the phylum Proteobacteria were overrepresented in ileal MAM of control calves. Moreover, based on reconstructed metagenomes (PICRUSt) of ileal MAM, functional pathways associated with MAP infection were inferred. Enrichment of lysine and histidine metabolism pathways, and underrepresentation of glutathione metabolism and leucine and isoleucine degradation pathways in MAP-infected calves suggested potential contributions of ileal MAM in development of intestinal inflammation. Finally, simultaneous overrepresentation of families Planococcaceae and Paraprevotellaceae, as well as underrepresentation of genera Faecalibacterium and Akkermansia in the fecal microbiota of infected cattle, served as potential biomarker for identifying infected cattle during subclinical stages of JD. Collectively, based on compositional and functional shifts in intestinal microbiota of infected cattle, we inferred that this dynamic network of microorganisms had an active role in intestinal homeostasis.

No MeSH data available.


Related in: MedlinePlus

Principal coordinates analysis (PCoA) of unweighted UniFrac distances. Between community diversity was tested for impact of MAP infection on clustering patterns of microbiota in (A) feces (P = 0.068), and (B) ileal mucosa (P = 0.049). Triangles represent samples belonging to calves that were included in the first year of the infection trial, whereas circles represent samples that belong to the second year. Green and red indicate samples obtained from control and MAP-infected calves, respectively. The impact of MAP infection and sampling year on the clustering pattern of microbial communities were tested using PERMANOVA (implemented in PRIMER-6 software). PERMDIS test was performed to test the  hypothesis of homogeneity of dispersions. P < 0.05 were considered significant.
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Figure 3: Principal coordinates analysis (PCoA) of unweighted UniFrac distances. Between community diversity was tested for impact of MAP infection on clustering patterns of microbiota in (A) feces (P = 0.068), and (B) ileal mucosa (P = 0.049). Triangles represent samples belonging to calves that were included in the first year of the infection trial, whereas circles represent samples that belong to the second year. Green and red indicate samples obtained from control and MAP-infected calves, respectively. The impact of MAP infection and sampling year on the clustering pattern of microbial communities were tested using PERMANOVA (implemented in PRIMER-6 software). PERMDIS test was performed to test the hypothesis of homogeneity of dispersions. P < 0.05 were considered significant.

Mentions: Within community diversity (α-diversity) was calculated using QIIME default scripts. Even depths of 12,000 and 16,000 sequences per sample were used for calculation of Chao1 richness and Shannon and Simpson diversity indices for the ileal MAM and fecal microbiota of MAP-infected and control, respectively (Figure 2). Alpha-diversity indices were also calculated according to the inflammation status (comparison between non-inflamed calves and inflamed ones—calves with minimum score of 1 for both macroscopic lesions and histologic scores), dose or age of infection (Table S1). To compare microbiota composition between samples, β-diversity was measured by calculating phylogenetic-based unweighted UniFrac distances (Lozupone and Knight, 2005). Principal coordinate analysis (PCoA) was applied on resulting distance matrices to generate two-dimensional plots using default settings of the PRIMER-6 (Figure 3; Warwick and Clarke, 2006). Finally, open source software PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states; Langille et al., 2013) was used to predict functional genes of the classified members of ileal MAM (resulting from reference-based OTU picking against Greengenes database). Predicted genes were then hierarchically clustered and categorized under KEGG (Kanehisa and Goto, 2000) orthologs (KOs) and pathways (level 1–3; Table S2).


The Features of Fecal and Ileal Mucosa-Associated Microbiota in Dairy Calves during Early Infection with Mycobacterium avium Subspecies paratuberculosis.

Derakhshani H, De Buck J, Mortier R, Barkema HW, Krause DO, Khafipour E - Front Microbiol (2016)

Principal coordinates analysis (PCoA) of unweighted UniFrac distances. Between community diversity was tested for impact of MAP infection on clustering patterns of microbiota in (A) feces (P = 0.068), and (B) ileal mucosa (P = 0.049). Triangles represent samples belonging to calves that were included in the first year of the infection trial, whereas circles represent samples that belong to the second year. Green and red indicate samples obtained from control and MAP-infected calves, respectively. The impact of MAP infection and sampling year on the clustering pattern of microbial communities were tested using PERMANOVA (implemented in PRIMER-6 software). PERMDIS test was performed to test the  hypothesis of homogeneity of dispersions. P < 0.05 were considered significant.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4814471&req=5

Figure 3: Principal coordinates analysis (PCoA) of unweighted UniFrac distances. Between community diversity was tested for impact of MAP infection on clustering patterns of microbiota in (A) feces (P = 0.068), and (B) ileal mucosa (P = 0.049). Triangles represent samples belonging to calves that were included in the first year of the infection trial, whereas circles represent samples that belong to the second year. Green and red indicate samples obtained from control and MAP-infected calves, respectively. The impact of MAP infection and sampling year on the clustering pattern of microbial communities were tested using PERMANOVA (implemented in PRIMER-6 software). PERMDIS test was performed to test the hypothesis of homogeneity of dispersions. P < 0.05 were considered significant.
Mentions: Within community diversity (α-diversity) was calculated using QIIME default scripts. Even depths of 12,000 and 16,000 sequences per sample were used for calculation of Chao1 richness and Shannon and Simpson diversity indices for the ileal MAM and fecal microbiota of MAP-infected and control, respectively (Figure 2). Alpha-diversity indices were also calculated according to the inflammation status (comparison between non-inflamed calves and inflamed ones—calves with minimum score of 1 for both macroscopic lesions and histologic scores), dose or age of infection (Table S1). To compare microbiota composition between samples, β-diversity was measured by calculating phylogenetic-based unweighted UniFrac distances (Lozupone and Knight, 2005). Principal coordinate analysis (PCoA) was applied on resulting distance matrices to generate two-dimensional plots using default settings of the PRIMER-6 (Figure 3; Warwick and Clarke, 2006). Finally, open source software PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states; Langille et al., 2013) was used to predict functional genes of the classified members of ileal MAM (resulting from reference-based OTU picking against Greengenes database). Predicted genes were then hierarchically clustered and categorized under KEGG (Kanehisa and Goto, 2000) orthologs (KOs) and pathways (level 1–3; Table S2).

Bottom Line: Current diagnostic tests for Johne's disease (JD), a chronic granulomatous inflammation of the gastrointestinal tract of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), lack the sensitivity to identify infected animals at early (asymptomatic) stages of the disease.Moreover, based on reconstructed metagenomes (PICRUSt) of ileal MAM, functional pathways associated with MAP infection were inferred.Enrichment of lysine and histidine metabolism pathways, and underrepresentation of glutathione metabolism and leucine and isoleucine degradation pathways in MAP-infected calves suggested potential contributions of ileal MAM in development of intestinal inflammation.

View Article: PubMed Central - PubMed

Affiliation: Department of Animal Science, University of Manitoba Winnipeg, MB, Canada.

ABSTRACT
Current diagnostic tests for Johne's disease (JD), a chronic granulomatous inflammation of the gastrointestinal tract of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), lack the sensitivity to identify infected animals at early (asymptomatic) stages of the disease. The objective was to determine the pattern of MAP-associated dysbiosis of intestinal microbiota as a potential biomarker for early detection of infected cattle. To that end, genomic DNA was extracted from ileal mucosa and fecal samples collected from 28 MAP-positive and five control calves. High-throughput Illumina sequencing of the V4 hypervariable region of the 16S rRNA gene was used for community profiling of ileal mucosa-associated (MAM) or fecal microbiota. The PERMANOVA analysis of unweighted UniFrac distances revealed distinct clustering of ileal MAM (P = 0.049) and fecal microbiota (P = 0.068) in MAP-infected vs. control cattle. Microbiota profile of MAP-infected animals was further investigated by linear discriminant analysis effective size (LEfSe); several bacterial taxa within the phylum Proteobacteria were overrepresented in ileal MAM of control calves. Moreover, based on reconstructed metagenomes (PICRUSt) of ileal MAM, functional pathways associated with MAP infection were inferred. Enrichment of lysine and histidine metabolism pathways, and underrepresentation of glutathione metabolism and leucine and isoleucine degradation pathways in MAP-infected calves suggested potential contributions of ileal MAM in development of intestinal inflammation. Finally, simultaneous overrepresentation of families Planococcaceae and Paraprevotellaceae, as well as underrepresentation of genera Faecalibacterium and Akkermansia in the fecal microbiota of infected cattle, served as potential biomarker for identifying infected cattle during subclinical stages of JD. Collectively, based on compositional and functional shifts in intestinal microbiota of infected cattle, we inferred that this dynamic network of microorganisms had an active role in intestinal homeostasis.

No MeSH data available.


Related in: MedlinePlus