Pro A ABCA9 ALYREF ATIC CCDC28A CDC6 CDC7 CDCA7 CMIP DPP10 Acidaminococcus Bilophila Butyricimonas Christensenellaceae Clostridium Fusobacterium Haemophilus Oscillospira Pseudomonas Ruminococcaceae Sutterella Veillonella B TAT ZNHITE ABCAS GINS2 CCDC28A PAICS CDCA7 Butyricimonas Biloph GINS1 EIF3J GONT4 TMEM97 DPP10 PTGFA LOR1 Haemophilus Clostridium Acidaminococcus UCP3 FAM1118 Veillonella 0.75 MCM4 KIRREL3 MON1 ZC3H12A TFAM TEX10 UNG Christenseng ceas CDC6 Ruminococcaceae DUOX2 DUOXA2 0.5 IF3J Pseudomonas LCN2 Fusobacterium DUOXA2 ATIC LAPPAC MUCSAC FAM 118 CDCT RPLP2 CMIP FAM120C TRHDE DUOX2 TICAM1 GCNT4 Oscillospira HELLS NUDCD1 GINS1 FAM120C GINS2 0.25 NUDT14 NAPSA GSTO1 HELLS C rho=-0.675,q=0.083 rho -0.772.q=0.04 ILDR1 KIRREL3 LCN2 LRPPRC MCM4 MDN1 MRPL17 MUC5AC DUOX2 NAPSA NUDCD1 NUDT14 PAICS PPP1R14B PTGFR RPLP2 SESN3 TAT TBX10 TFAM TICAM1 TMEM97 TRHDE UCP3 -0.25 -0.5 -0.75 ZNHIT6 2.00 1.75 Christensenellaceae rho 0.759,q=0.045 UNG ZC3H12A ZNHIT6 B -1 DUOXA2 LCN2 Ruminococcaceae rho-0.698.q=0.082 0.0 -5.0 -25 Butyricimonas -75-50 -25 Veillonella 6.0 Fig. 3 Interactions between genes associated with colorectal cancer and gut mucosal microbes. a Correlation plot depicting gene-microbe correlations. Color and size of the squares indicate the magnitude of the correlation, asterisks indicate significance of correlation (* indicates q value <0.05 and indicates q value <0.1). b Network visualizing significant gene-microbe correlations (solid edges, q value <0.1) and significant microbe-microbe correlations (dashed edges, SparCC IRI>=0.1 and p value <0.05). Blue edges indicate positive correlation and red edges indicate negative correlation. Edge thickness represents the strength of the correlation. c Scatterplots depicting pattern of grouping by cystic fibrosis (red) and healthy (blue) samples in a few representative gene-microbe correlations, where the strength of correlation (Spearman rho) and significance (q) is indicated at the top of each plot and dashed edges represent microbe-microbe correla- tions. This subnetwork of microbe-microbe correlations depicts correlated abundance changes in the microbiome as a function of their presence (Fig. 3b, dashed edges). For instance, Bilophila and Butyricimonas are both de- pleted in CF (q value <0.05), and the abundance of the two genera is also correlated across individuals (SparCC R-05 pseudo p value=0.04) On the other hand solid edges), microbial nodes have more edges on aver- age compared to genes, where Christensenellaceae and Clostridium formed distinct hubs in the network. This potentially implies that these microbes and their path- ways are shared across multiple GI cancer-associated genes. Of note, Bilophila, Clostridium, and Pseudomonas are mostly negatively correlated with Gl cancer genes, while Haemophilus Oscillasnina Veillonella Eusobacter

Pro A ABCA9 ALYREF ATIC CCDC28A CDC6 CDC7 CDCA7 CMIP DPP10 Acidaminococcus Bilophila Butyricimonas Christensenellaceae Clostridium Fusobacterium Haemophilus Oscillospira Pseudomonas Ruminococcaceae Sutterella Veillonella B TAT ZNHITE ABCAS GINS2 CCDC28A PAICS CDCA7 Butyricimonas Biloph GINS1 EIF3J GONT4 TMEM97 DPP10 PTGFA LOR1 Haemophilus Clostridium Acidaminococcus UCP3 FAM1118 Veillonella 0.75 MCM4 KIRREL3 MON1 ZC3H12A TFAM TEX10 UNG Christenseng ceas CDC6 Ruminococcaceae DUOX2 DUOXA2 0.5 IF3J Pseudomonas LCN2 Fusobacterium DUOXA2 ATIC LAPPAC MUCSAC FAM 118 CDCT RPLP2 CMIP FAM120C TRHDE DUOX2 TICAM1 GCNT4 Oscillospira HELLS NUDCD1 GINS1 FAM120C GINS2 0.25 NUDT14 NAPSA GSTO1 HELLS C rho=-0.675,q=0.083 rho -0.772.q=0.04 ILDR1 KIRREL3 LCN2 LRPPRC MCM4 MDN1 MRPL17 MUC5AC DUOX2 NAPSA NUDCD1 NUDT14 PAICS PPP1R14B PTGFR RPLP2 SESN3 TAT TBX10 TFAM TICAM1 TMEM97 TRHDE UCP3 -0.25 -0.5 -0.75 ZNHIT6 2.00 1.75 Christensenellaceae rho 0.759,q=0.045 UNG ZC3H12A ZNHIT6 B -1 DUOXA2 LCN2 Ruminococcaceae rho-0.698.q=0.082 0.0 -5.0 -25 Butyricimonas -75-50 -25 Veillonella 6.0 Fig. 3 Interactions between genes associated with colorectal cancer and gut mucosal microbes. a Correlation plot depicting gene-microbe correlations. Color and size of the squares indicate the magnitude of the correlation, asterisks indicate significance of correlation (* indicates q value <0.05 and indicates q value <0.1). b Network visualizing significant gene-microbe correlations (solid edges, q value <0.1) and significant microbe-microbe correlations (dashed edges, SparCC IRI>=0.1 and p value <0.05). Blue edges indicate positive correlation and red edges indicate negative correlation. Edge thickness represents the strength of the correlation. c Scatterplots depicting pattern of grouping by cystic fibrosis (red) and healthy (blue) samples in a few representative gene-microbe correlations, where the strength of correlation (Spearman rho) and significance (q) is indicated at the top of each plot and dashed edges represent microbe-microbe correla- tions. This subnetwork of microbe-microbe correlations depicts correlated abundance changes in the microbiome as a function of their presence (Fig. 3b, dashed edges). For instance, Bilophila and Butyricimonas are both de- pleted in CF (q value <0.05), and the abundance of the two genera is also correlated across individuals (SparCC R-05 pseudo p value=0.04) On the other hand solid edges), microbial nodes have more edges on aver- age compared to genes, where Christensenellaceae and Clostridium formed distinct hubs in the network. This potentially implies that these microbes and their path- ways are shared across multiple GI cancer-associated genes. Of note, Bilophila, Clostridium, and Pseudomonas are mostly negatively correlated with Gl cancer genes, while Haemophilus Oscillasnina Veillonella Eusobacter

Biology: The Unity and Diversity of Life (MindTap Course List)

15th Edition

ISBN:9781337408332

Author:Cecie Starr, Ralph Taggart, Christine Evers, Lisa Starr

Publisher:Cecie Starr, Ralph Taggart, Christine Evers, Lisa Starr

Chapter21: Protists- The Simplest Eukaryotes

Section: Chapter Questions

Problem 9SQ

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