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Impact of Helminth Infections and Nutritional Constraints on the Small Intestine Microbiota

Cattadori, Isabella M., Sebastian, Aswathy, Hao, Han, Katani, Robab, Albert, Istvan, Eilertson, Kirsten E., Kapur, Vivek, Pathak, Ashutosh, Mitchell, Susan·2016·PLOS ONE
DOI 10.1371/journal.pone.0159770PMC PMC4954658
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Figures

Fig 1 Abundance and alpha diversity of the duodenum microbiota. Abundance and diversity by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C) at the 3 taxonomic levels (time points pooled together). The mean, 25–75% percentiles, maximum and minimum and outliers from the Shannon diversity index are reported. Diversity is significantly lower in I than in CC or C groups. The number of taxa is similar among treatments.
Fig 1 Abundance and alpha diversity of the duodenum microbiota. Abundance and diversity by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C) at the 3 taxonomic levels (time points pooled together). The mean, 25–75% percentiles, maximum and minimum and outliers from the Shannon diversity index are reported. Diversity is significantly lower in I than in CC or C groups. The number of taxa is similar among treatments.CC BY · PubMed Central
Fig 2 Relative microbiota abundance by animal. Abundance at the 3 taxonomic levels in the four treatments (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C). Only the taxa with a relative abundance greater than 1% at each taxonomic level are presented. The white space that adds up to 100% abundance should be interpreted as 'other' taxa.
Fig 2 Relative microbiota abundance by animal. Abundance at the 3 taxonomic levels in the four treatments (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C). Only the taxa with a relative abundance greater than 1% at each taxonomic level are presented. The white space that adds up to 100% abundance should be interpreted as 'other' taxa.CC BY · PubMed Central
Fig 3 Expression of cytokine, transcription factor and function genes in the duodenal mucosa. Mean values (2-ΔΔct±s.e.) by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C) and sampling time (day post initial infection). Data have been standardized by the housekeeping gene HPRT and the mean values from the baseline animals sampled at day 0. Most of the variables show significant differences among treatments but not sampling time, higher values are observed in the I and IC groups.
Fig 3 Expression of cytokine, transcription factor and function genes in the duodenal mucosa. Mean values (2-ΔΔct±s.e.) by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C) and sampling time (day post initial infection). Data have been standardized by the housekeeping gene HPRT and the mean values from the baseline animals sampled at day 0. Most of the variables show significant differences among treatments but not sampling time, higher values are observed in the I and IC groups.CC BY · PubMed Central
Fig 4 Antibody IgA from the duodenal mucus. Mean (±s.e.) Optical Density (O.D.) for the species-specific (left y-axis, full cycle) and the total (right y-axis, full square) IgA by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C) and sampling time (days post initial infection). Both specific and total IgA are higher in I and IC than in CC or C.
Fig 4 Antibody IgA from the duodenal mucus. Mean (±s.e.) Optical Density (O.D.) for the species-specific (left y-axis, full cycle) and the total (right y-axis, full square) IgA by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC and Control: C) and sampling time (days post initial infection). Both specific and total IgA are higher in I and IC than in CC or C.CC BY · PubMed Central
Fig 5 Relationships between microbiota and immune response. Spearman rank correlations grouping animals by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC, and Control: C) and using only the bacteria that showed a between-individual coefficient of variation (CV) greater than 150. Negative relationships are in grades of blue while positive relationships are in grades of red; a correlation coefficient quantifies each grade, null correlations (0) are depicted in white; significant correlations (p<0.05) are highlighted with a star. Significant correlations are more common in the Infect group than the remaining treatments.
Fig 5 Relationships between microbiota and immune response. Spearman rank correlations grouping animals by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC, and Control: C) and using only the bacteria that showed a between-individual coefficient of variation (CV) greater than 150. Negative relationships are in grades of blue while positive relationships are in grades of red; a correlation coefficient quantifies each grade, null correlations (0) are depicted in white; significant correlations (p<0.05) are highlighted with a star. Significant correlations are more common in the Infect group than the remaining treatments.CC BY · PubMed Central
Fig 6 Relationships between microbiota and T. retortaeformis abundance. Spearman rank correlations grouping animals by treatment (Infect -I, Infect+Collar -IC), or treatment and time point, and: Panel A- the bacteria families with CV>150 or Panel B- the functions at the KEGG pathway module 2 that exhibited a coefficient of variation CV among individuals greater than 70,000. Additional details on the color-coding of the correlations are reported in Fig 5, while the activities related to the KEGG function IDs are listed in Fig 7. No significant correlations are detected, except in two cases.
Fig 6 Relationships between microbiota and T. retortaeformis abundance. Spearman rank correlations grouping animals by treatment (Infect -I, Infect+Collar -IC), or treatment and time point, and: Panel A- the bacteria families with CV>150 or Panel B- the functions at the KEGG pathway module 2 that exhibited a coefficient of variation CV among individuals greater than 70,000. Additional details on the color-coding of the correlations are reported in Fig 5, while the activities related to the KEGG function IDs are listed in Fig 7. No significant correlations are detected, except in two cases.CC BY · PubMed Central
Fig 7 Relative abundance of gene functionality in the duodenum by animal. Data are presented by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC, and Control: C) at the KEGG pathway level 2. Only the functions with a relative abundance greater than 1% were displayed. The white space that adds up to 100% abundance should be considered as 'other' functions. The following function IDs and related activities were selected: CellProc1 = Cellular Processes: Cell Motility; CellProc2 = Cellular Processes: Transport and Catabolism; EnvInfo1 = Environmental Information: Processing Membrane Transport; EnvInfo2 = Environmental Information: Processing Signal Transduction; GenInfo1 = Genetic Information: Processing Folding Sorting and Degradation; GenInfo2 = Genetic Information: Processing Replication and Repair; GenInfo3 = Genetic Information: Processing Transcription; GenInfo4 = Genetic Information: Processing Translation; Metab1 = Metabolism: Amino Acid Metabolism; Metab2 = Metabolism: Biosynthesis of Other Secondary Metabolites; Metab3 = Metabolism: Carbohydrate Metabolism; Metab4 = Metabolism: Energy Metabolism; Metab5 = Metabolism: Enzyme Families; Metab6 = Metabolism: Glycan Biosynthesis and Metabolism; Metab7 = Metabolism: Lipid Metabolism; Metab8 = Metabolism: Metabolism of Cofactors and Vitamins; Metab9 = Metabolism: Metabolism of Other Amino Acids; Metab10 = Metabolism: Metabolism of Terpenoids and Polyketides; Metab11 = Metabolism: Nucleotide Metabolism; Metab12 = Metabolism: Xenobiotics Biodegradation and Metabolism.
Fig 7 Relative abundance of gene functionality in the duodenum by animal. Data are presented by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC, and Control: C) at the KEGG pathway level 2. Only the functions with a relative abundance greater than 1% were displayed. The white space that adds up to 100% abundance should be considered as 'other' functions. The following function IDs and related activities were selected: CellProc1 = Cellular Processes: Cell Motility; CellProc2 = Cellular Processes: Transport and Catabolism; EnvInfo1 = Environmental Information: Processing Membrane Transport; EnvInfo2 = Environmental Information: Processing Signal Transduction; GenInfo1 = Genetic Information: Processing Folding Sorting and Degradation; GenInfo2 = Genetic Information: Processing Replication and Repair; GenInfo3 = Genetic Information: Processing Transcription; GenInfo4 = Genetic Information: Processing Translation; Metab1 = Metabolism: Amino Acid Metabolism; Metab2 = Metabolism: Biosynthesis of Other Secondary Metabolites; Metab3 = Metabolism: Carbohydrate Metabolism; Metab4 = Metabolism: Energy Metabolism; Metab5 = Metabolism: Enzyme Families; Metab6 = Metabolism: Glycan Biosynthesis and Metabolism; Metab7 = Metabolism: Lipid Metabolism; Metab8 = Metabolism: Metabolism of Cofactors and Vitamins; Metab9 = Metabolism: Metabolism of Other Amino Acids; Metab10 = Metabolism: Metabolism of Terpenoids and Polyketides; Metab11 = Metabolism: Nucleotide Metabolism; Metab12 = Metabolism: Xenobiotics Biodegradation and Metabolism.CC BY · PubMed Central
Fig 8 Relationships between gene functionality and immune response. Spearman rank correlations grouping animals by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC, and Control: C) and using the KEGG pathway level 2 functions with a CV>70,000. Additional details are reported in Figs 5 and 7. Significant correlations are mainly observed with a type 1 response.
Fig 8 Relationships between gene functionality and immune response. Spearman rank correlations grouping animals by treatment (Infect: I, Infect+Collar: IC, Control+Collar: CC, and Control: C) and using the KEGG pathway level 2 functions with a CV>70,000. Additional details are reported in Figs 5 and 7. Significant correlations are mainly observed with a type 1 response.CC BY · PubMed Central

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Metadata

Authors
Cattadori, I. M., Sebastian, A., Hao, H., Katani, R., Albert, I., Eilertson, K. E., Kapur, V., Pathak, A., & Mitchell, S.
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2016-07-20
Volume
11
Issue
7
Pages
e0159770
ISSN
1932-6203
DOI
10.1371/journal.pone.0159770
PMC
PMC4954658
Cited by
52
References
5
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
The Pennsylvania Department of Health Tobacco Cure Funds and The Pennsylvania State University Huck Institutes of the Life Sciences SEED grant

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