Ncri Poster
1
www.virtualpathology.leeds.ac.uk [email protected] www.youtube.com/ LeedsPathology @LeedsPathology Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds Methods • FFPE blocks were created from six anonymised frozen faecal samples. • The V4 (240 base pair product) and V6 (98 base pair product) regions of the 16S rRNA gene were amplified in FFPE samples. • For frozen samples (including from 57 further samples) regions V2, V3, V5, V7/V8 were also amplified. • Libraries were prepared from PCR product and samples submiTed for NGS using an Illumina MiSeq. • QIIME soZware was used for analysis. The different bacterial phylum and genera present were collated for each sample group. Alpha (within sample) and beta (between sample) diversity were calculated. s Investigating the faecal microbiome in formalin fixed paraffin embedded (FFPE) material Introduction • The microbiome describes ‘the ecological community of commensal, symbio^c and pathogenic microorganisms that share our body space’ (1). • Altered faecal microbiomes are present in a range of gastrointes^nal pathologies but their exact role in disease is not yet known (2,3). • Currently research into the microbiome makes use of fresh or frozen samples. • One poten^al method for rapidly expanding and diversifying research is the retrospec^ve study of formalin fixed paraffin embedded (FFPE) samples that contain faecal bacterial popula^ons. To inves)gate the feasibility of typing the microbiome in FFPE faecal samples and analyse how microbiome analysis varied when targe)ng different variable regions. Ivan Jobling, Morag Taylor, Caroline Young, Henry Wood, Phil Quirke Section of Pathology & Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds Conclusions • This is the first study to apply NGS technology to FFPE faecal material. • We have successfully produced microbiome data from FFPE material comparable to that from frozen samples. • When targe)ng the V6 region there is a closer correla)on between frozen and FFPE samples than when targe)ng V4. We hypothesise that this is due to the shorter V6 region being less affected by DNA fragmenta)on. • Microbiome analysis in frozen material is significantly affected by the variable region of the 16s rRNA gene targeted. • It is clear that choice of material and variable region is important in microbiome studies and further research is needed to standardise best prac)se when studying the gut microbiome. Results Aim References 1. Lederberg J, McCray AT. 'Ome sweet 'omics - A genealogical treasury of words. Scientist. 2001 Apr 2;15(7):8. PubMed PMID: WOS: 000168167400002. 2. Greenblum S, Turnbaugh PJ, Borenstein E. Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease. Proceedings of the National Academy of Sciences of the United States of America. 2012 Jan 10;109(2):594-9. PubMed PMID: 22184244. Pubmed Central PMCID: 3258644. 3. Chang JY, Antonopoulos DA, Kalra A, Tonelli A, Khalife WT, Schmidt TM, et al. Decreased diversity of the feacal microbiome in recurrent Clostridium difficile-associated diarrhea. The Journal of infectious diseases. 2008 Feb 1;197(3):435-8. PubMed PMID: 18199029. PC1 7% Figure 2. Frozen and FFPE taxonomy bar graph. Graph showing the rela^ve abundances of bacteria at genera level. This shows that FFPE and frozen results for each individual correlate. However, a significant difference in beta diversity between FFPE and frozen samples was found. Results correlated beTer between FFPE and frozen when targe^ng V6 compared to V4. Seven out of forty nega^ve controls were contaminated. These are dis^nguishable on this graph from each other and the faecal samples. It is possible to successfully amplify the 16S rRNA gene from FFPE faecal material. Targe)ng the shorter V6 region of the 16S rRNA gene gives closer results between FFPE and frozen samples than when targe)ng the V4 region. Figure 3. Alpha diversity. Rarefac^on chart showing the difference in within sample diversity between FFPE and frozen samples against sequences per sample. There is a significant difference between V4 FFPE and frozen samples (p = 0.05) but not V6. Figure 4. Taxonomy area graphs. Area graphs showing the rela^ve abundances of bacteria at phylum and genera level according to variable region of 16S rRNA gene targeted. The listed phyla varied in abundance significantly dependent on region targeted (p = < 0.002). Figure 1. Gel electrophoresis. Gel showing amplifica^on of the V6 region of the 16S rRNA gene in FFPE and frozen faecal samples. Reference ladders contain DNA strands 50 base pairs (bp) apart in size. Nega^ve and posi^ve controls shown. Figure shows that it is possible to successfully amplify the 16S rRNA gene from FFPE faecal material. 50 bp ladder 50 bp ladder 50 bp ladder 50 bp ladder Phylum Genera Phylum with abundance over 1% V4 frozen samples 1-6 V4 FFPE samples 1-6 V6 FFPE samples 1-6 V6 Frozen samples 1-6 V6 Negative controls (4/20 produced libraries) V4 Negative controls (3/20 produced libraries) V2 V3 V4 V5 V6 V7/V8 Phylum Genera Phyla listed had significantly different abundance dependent on variable region of 16S rRNA gene targeted. Figure 5. Alpha diversity of frozen samples according to variable region targeted. Graph shows significant differences between all variable regions targeted with shorter regions detec^ng less diversity (p < 0.001). Data from frozen samples varied significantly based on the varible region targeted. Longer regions tended to detect a higher level of alpha diversity.
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Can we investigate the microbiome in formalin-fixed paraffin-embedded (FFPE) specimens.
Transcript of Ncri Poster
www.virtualpathology.leeds.ac.uk [email protected]
www.youtube.com/LeedsPathology @LeedsPathology
Section of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds
Methods
• FFPE blocks were created from six anonymised frozen faecal samples.
• The V4 (240 base pair product) and V6 (98 base pair product) regions of the 16S rRNA gene were amplified in FFPE samples.
• For frozen samples (including from 57 further samples) regions V2, V3, V5, V7/V8 were also amplified.
• Libraries were prepared from PCR product and samples submiTed for NGS using an Illumina MiSeq.
• QIIME soZware was used for analysis. The different bacterial phylum and genera present were collated for each sample group. Alpha (within sample) and beta (between sample) diversity were calculated. s
Investigating the faecal microbiome in formalin fixed paraffin embedded (FFPE) material
Introduction
• The microbiome describes ‘the e c o l o g i c a l c o mm u n i t y o f c ommen s a l , s ymb i o ^ c a n d pathogenic microorganisms that share our body space’ (1).
• Altered faecal microbiomes are present in a range of gastrointes^nal pathologies but their exact role in disease is not yet known (2,3).
• Current ly research in to the microbiome makes use of fresh or frozen samples.
• One poten^al method for rapidly expanding and diversifying research is the retrospec^ve study of formalin fixed paraffin embedded (FFPE) samples that contain faecal bacterial popula^ons.
To inves)gate the feasibility of typing the microbiome in FFPE faecal samples and analyse how microbiome analysis varied when targe)ng different variable regions.
Ivan Jobling, Morag Taylor, Caroline Young, Henry Wood, Phil Quirke
Section of Pathology & Tumour Biology, Leeds Institute of Cancer and Pathology, University of Leeds
Conclusions
• This is the first study to apply NGS technology to FFPE faecal material.
• We have successfully produced microbiome data from FFPE material comparable to that from frozen samples.
• When targe)ng the V6 region there is a closer correla)on between frozen and FFPE samples than when targe)ng V4. We hypothesise that this is due to the shorter V6 region being less affected by DNA fragmenta)on.
• Microbiome analysis in frozen material is significantly affected by the variable region of the 16s rRNA gene targeted.
• It is clear that choice of material and variable region is important in microbiome studies and further research is needed to standardise best prac)se when studying the gut microbiome.
Results
Aim
References
1. Lederberg J, McCray AT. 'Ome sweet 'omics - A genealogical treasury of words. Scientist. 2001 Apr 2;15(7):8. PubMed PMID: WOS:000168167400002.
2. Greenblum S, Turnbaugh PJ, Borenstein E. Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease. Proceedings of the National Academy of Sciences of the United States of America. 2012 Jan 10;109(2):594-9. PubMed PMID: 22184244. Pubmed Central PMCID: 3258644.
3. Chang JY, Antonopoulos DA, Kalra A, Tonelli A, Khalife WT, Schmidt TM, et al. Decreased diversity of the feacal microbiome in recurrent Clostridium difficile-associated diarrhea. The Journal of infectious diseases. 2008 Feb 1;197(3):435-8. PubMed PMID: 18199029.
PC1 7%
Figure 2. Frozen and FFPE taxonomy bar graph. Graph showing the rela^ve abundances of bacteria at genera level. This shows that FFPE and frozen results for each individual correlate. However, a significant difference in beta diversity between FFPE and frozen samples was found. Results correlated beTer between FFPE and frozen when targe^ng V6 compared to V4. Seven out of forty nega^ve controls were contaminated. These are dis^nguishable on this graph from each other and the faecal samples.
It is possible to successfully amplify the 16S rRNA gene from FFPE faecal material.
Targe)ng the shorter V6 region of the 16S rRNA gene gives closer results between FFPE and frozen samples than when targe)ng the V4 region.
Figure 3. Alpha diversity. Rarefac^on chart showing the difference in within sample diversity between FFPE and frozen samples against sequences per sample. There is a significant difference between V4 FFPE and frozen samples (p = 0.05) but not V6.
Figure 4. Taxonomy area graphs. Area graphs showing the rela^ve abundances of bacteria at phylum and genera level according to variable region of 16S rRNA gene targeted. The listed phyla varied in abundance significantly dependent on region targeted (p = < 0.002).
Figure 1. Gel electrophoresis. Gel showing amplifica^on of the V6 region of the 16S rRNA gene in FFPE and frozen faecal samples. Reference ladders contain DNA strands 50 base pairs (bp) apart in size. Nega^ve and posi^ve controls shown. Figure shows that it is possible to successfully amplify the 16S rRNA gene from FFPE faecal material.
Phylum
Genera
Sample source (faecal or negative control)
Samples 1-6 Samples 1-6 Samples 1-6 Samples 1-6
Negative controls :Nc1 (Agar), N7 (95% ethanol) and N14 (tap water).
Negative controls :Nc1 (Agar), N2 (formalin) and N9 (ethanol) and N12 (xylene).
50 bp ladder
50 bp ladder
50 bp ladder
50 bp ladder
Phylum
Genera
Phylum with abundance over 1%
V4 frozen samples 1-6 V4 FFPE samples 1-6 V6 FFPE samples 1-6 V6 Frozen samples 1-6 V6 Negative
controls (4/20
produced
libraries)
V4
Negative
controls
(3/20
produced
libraries)
Taxonomy summary
V2 V3 V4 V5 V6 V7/V8
Legend
Figure 1. Taxonomy area graphs. Area graphs showing the relative abundances of bacteria at phylum level and genera level. Legend contains all phylum shown to vary significantly based on variable region targeted. Many species in the legend are not
Phylum
Genera
Taxonomy summary
V2 V3 V4 V5 V6 V7/V8
Legend
Figure 1. Taxonomy area graphs. Area graphs showing the relative abundances of bacteria at phylum level and genera level. Legend contains all phylum shown to vary significantly based on variable region targeted. Many species in the legend are not
Phylum
Genera
Phyla listed had significantly different abundance dependent on variable region of 16S rRNA gene targeted.
Figure 5. Alpha diversity of frozen samples according to variable region targeted. Graph shows significant differences between all variable regions targeted with shorter regions detec^ng less diversity (p < 0.001).
Data from frozen samples varied significantly based on the varible region targeted. Longer regions tended to detect a higher level of alpha diversity.
