Table of Content
I.Project Summary
II.Workflow Checklist
III.NGS Sequencing Results
IV.Complete Report Download
V.Raw Sequence Data Download
VI.Analysis - DADA2 Read Processing
 Sample Meta Info
 Read Count by Sample
VII.Analysis - Read Taxonomy Assignment
 Taxonomy Barplots
VIII.Analysis - Alpha Diversity
IX.Analysis - Beta Diversity
X.Analysis - Differential Abundance
 ANCOM Result
 LEfSe Result
XI.Analysis - Heatmap Profile
XII.Analysis - Network Association
XIII.Disclaimer

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FOMC Service Report

16S rRNA Gene V1V3 Amplicon Sequencing

Version V1.43

Version History

The Forsyth Institute, Cambridge, MA, USA
April 05, 2024

Project ID: FOMC16078

I. Project Summary

Project FOMC16078 services include NGS sequencing of the V1V3 region of the 16S rRNA gene amplicons from the samples. First and foremost, please download this report, as well as the sequence raw data from the download links provided below. These links will expire after 60 days. We cannot guarantee the availability of your data after 60 days.

Full Bioinformatics analysis service was requested. We provide many analyses, starting from the raw sequence quality and noise filtering, pair reads merging, as well as chimera filtering for the sequences, using the DADA2 denosing algorithm and pipeline.

We also provide many downstream analyses such as taxonomy assignment, alpha and beta diversity analyses, and differential abundance analysis.

For taxonomy assignment, most informative would be the taxonomy barplots. We provide an interactive barplots to show the relative abundance of microbes at different taxonomy levels (from Phylum to species) that you can choose.

If you specify which groups of samples you want to compare for differential abundance, we provide both ANCOM and LEfSe differential abundance analysis.

 

II. Workflow Checklist

☑1.Sample Received
☑2.Sample Quality Evaluated
☑3.Sample Prepared for Sequencing
☑4.Next-Gen Sequencing
☑5.Sequence Quality Check
☑6.Absolute Abundance
☑7.Report and Raw Sequence Data Available for Download
☑8.Bioinformatics Analysis - Reads Processing (DADA2 Quality Trimming, Denoising, Paired Reads Merging)
☑9.Bioinformatics Analysis - Reads Taxonomy Assignment
☑10.Bioinformatics Analysis - Alpha Diversity Analysis
☑11.Bioinformatics Analysis - Beta Diversity Analysis
☑12.Bioinformatics Analysis - Differential Abundance Analysis
☑13.Bioinformatics Analysis - Heatmap Profile
☑14.Bioinformatics Analysis - Network Association
 

III. NGS Sequencing

The samples were processed and analyzed with the ZymoBIOMICS® Service: Targeted Metagenomic Sequencing (Zymo Research, Irvine, CA).

DNA Extraction: If DNA extraction was performed, one of three different DNA extraction kits was used depending on the sample type and sample volume and were used according to the manufacturer’s instructions, unless otherwise stated. The kit used in this project is marked below:

☐ZymoBIOMICS® DNA Miniprep Kit (Zymo Research, Irvine, CA)
☐ZymoBIOMICS® DNA Microprep Kit (Zymo Research, Irvine, CA)
☐ZymoBIOMICS®-96 MagBead DNA Kit (Zymo Research, Irvine, CA)
☑N/A (DNA Extraction Not Performed)
Elution Volume: 50µL
Additional Notes: NA

Targeted Library Preparation: The DNA samples were prepared for targeted sequencing with the Quick-16S™ NGS Library Prep Kit (Zymo Research, Irvine, CA). These primers were custom designed by Zymo Research to provide the best coverage of the 16S gene while maintaining high sensitivity. The primer sets used in this project are marked below:

☐Quick-16S™ Primer Set V1-V2 (Zymo Research, Irvine, CA)
☑Quick-16S™ Primer Set V1-V3 (Zymo Research, Irvine, CA)
☐Quick-16S™ Primer Set V3-V4 (Zymo Research, Irvine, CA)
☐Quick-16S™ Primer Set V4 (Zymo Research, Irvine, CA)
☐Quick-16S™ Primer Set V6-V8 (Zymo Research, Irvine, CA)
☐Other: NA
Additional Notes: NA

The sequencing library was prepared using an innovative library preparation process in which PCR reactions were performed in real-time PCR machines to control cycles and therefore limit PCR chimera formation. The final PCR products were quantified with qPCR fluorescence readings and pooled together based on equal molarity. The final pooled library was cleaned up with the Select-a-Size DNA Clean & Concentrator™ (Zymo Research, Irvine, CA), then quantified with TapeStation® (Agilent Technologies, Santa Clara, CA) and Qubit® (Thermo Fisher Scientific, Waltham, WA).

Control Samples: The ZymoBIOMICS® Microbial Community Standard (Zymo Research, Irvine, CA) was used as a positive control for each DNA extraction, if performed. The ZymoBIOMICS® Microbial Community DNA Standard (Zymo Research, Irvine, CA) was used as a positive control for each targeted library preparation. Negative controls (i.e. blank extraction control, blank library preparation control) were included to assess the level of bioburden carried by the wet-lab process.

Sequencing: The final library was sequenced on Illumina® MiSeq™ with a V3 reagent kit (600 cycles). The sequencing was performed with 10% PhiX spike-in.

Absolute Abundance Quantification*: A quantitative real-time PCR was set up with a standard curve. The standard curve was made with plasmid DNA containing one copy of the 16S gene and one copy of the fungal ITS2 region prepared in 10-fold serial dilutions. The primers used were the same as those used in Targeted Library Preparation. The equation generated by the plasmid DNA standard curve was used to calculate the number of gene copies in the reaction for each sample. The PCR input volume (2 µl) was used to calculate the number of gene copies per microliter in each DNA sample.
The number of genome copies per microliter DNA sample was calculated by dividing the gene copy number by an assumed number of gene copies per genome. The value used for 16S copies per genome is 4. The value used for ITS copies per genome is 200. The amount of DNA per microliter DNA sample was calculated using an assumed genome size of 4.64 x 106 bp, the genome size of Escherichia coli, for 16S samples, or an assumed genome size of 1.20 x 107 bp, the genome size of Saccharomyces cerevisiae, for ITS samples. This calculation is shown below:

Calculated Total DNA = Calculated Total Genome Copies × Assumed Genome Size (4.64 × 106 bp) ×
Average Molecular Weight of a DNA bp (660 g/mole/bp) ÷ Avogadro’s Number (6.022 x 1023/mole)


* Absolute Abundance Quantification is only available for 16S and ITS analyses.

The absolute abundance standard curve data can be viewed in Excel here:

The absolute abundance standard curve is shown below:

Absolute Abundance Standard Curve

 

IV. Complete Report Download

The complete report of your project, including all links in this report, can be downloaded by clicking the link provided below. The downloaded file is a compressed ZIP file and once unzipped, open the file “REPORT.html” (may only shown as "REPORT" in your computer) by double clicking it. Your default web browser will open it and you will see the exact content of this report.

Please download and save the file to your computer storage device. The download link will expire after 60 days upon your receiving of this report.

Complete report download link:

To view the report, please follow the following steps:
1.Download the .zip file from the report link above.
2.Extract all the contents of the downloaded .zip file to your desktop.
3.Open the extracted folder and find the "REPORT.html" (may shown as only "REPORT").
4.Open (double-clicking) the REPORT.html file. Your default browser will open the top age of the complete report. Within the report, there are links to view all the analyses performed for the project.

 

V. Raw Sequence Data Download

The raw NGS sequence data is available for download with the link provided below. The data is a compressed ZIP file and can be unzipped to individual sequence files. Since this is a pair-end sequencing, each of your samples is represented by two sequence files, one for READ 1, with the file extension “*_R1.fastq.gz”, another READ 2, with the file extension “*_R1.fastq.gz”. The files are in FASTQ format and are compressed. FASTQ format is a text-based data format for storing both a biological sequence and its corresponding quality scores. Most sequence analysis software will be able to open them. The Sample IDs associated with the R1 and R2 fastq files are listed in the table below:



Sample IDOriginal Sample IDRead 1 File NameRead 2 File Name


F16078.S10original sample ID herezr16078_10V1V3_R1.fastq.gzzr16078_10V1V3_R2.fastq.gz


F16078.S11original sample ID herezr16078_11V1V3_R1.fastq.gzzr16078_11V1V3_R2.fastq.gz


F16078.S12original sample ID herezr16078_12V1V3_R1.fastq.gzzr16078_12V1V3_R2.fastq.gz


F16078.S13original sample ID herezr16078_13V1V3_R1.fastq.gzzr16078_13V1V3_R2.fastq.gz


F16078.S14original sample ID herezr16078_14V1V3_R1.fastq.gzzr16078_14V1V3_R2.fastq.gz


F16078.S15original sample ID herezr16078_15V1V3_R1.fastq.gzzr16078_15V1V3_R2.fastq.gz


F16078.S16original sample ID herezr16078_16V1V3_R1.fastq.gzzr16078_16V1V3_R2.fastq.gz


F16078.S17original sample ID herezr16078_17V1V3_R1.fastq.gzzr16078_17V1V3_R2.fastq.gz


F16078.S18original sample ID herezr16078_18V1V3_R1.fastq.gzzr16078_18V1V3_R2.fastq.gz


F16078.S01original sample ID herezr16078_1V1V3_R1.fastq.gzzr16078_1V1V3_R2.fastq.gz


F16078.S02original sample ID herezr16078_2V1V3_R1.fastq.gzzr16078_2V1V3_R2.fastq.gz


F16078.S03original sample ID herezr16078_3V1V3_R1.fastq.gzzr16078_3V1V3_R2.fastq.gz


F16078.S04original sample ID herezr16078_4V1V3_R1.fastq.gzzr16078_4V1V3_R2.fastq.gz


F16078.S05original sample ID herezr16078_5V1V3_R1.fastq.gzzr16078_5V1V3_R2.fastq.gz


F16078.S06original sample ID herezr16078_6V1V3_R1.fastq.gzzr16078_6V1V3_R2.fastq.gz


F16078.S07original sample ID herezr16078_7V1V3_R1.fastq.gzzr16078_7V1V3_R2.fastq.gz


F16078.S08original sample ID herezr16078_8V1V3_R1.fastq.gzzr16078_8V1V3_R2.fastq.gz


F16078.S09original sample ID herezr16078_9V1V3_R1.fastq.gzzr16078_9V1V3_R2.fastq.gz

Please download and save the file to your computer storage device. The download link will expire after 60 days upon your receiving of this report.

Raw sequence data download link:

 

VI. Analysis - DADA2 Read Processing

What is DADA2?

DADA2 is a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. DADA2 identified more real variants and output fewer spurious sequences than other methods.

DADA2’s advantage is that it uses more of the data. The DADA2 error model incorporates quality information, which is ignored by all other methods after filtering. The DADA2 error model incorporates quantitative abundances, whereas most other methods use abundance ranks if they use abundance at all. The DADA2 error model identifies the differences between sequences, eg. A->C, whereas other methods merely count the mismatches. DADA2 can parameterize its error model from the data itself, rather than relying on previous datasets that may or may not reflect the PCR and sequencing protocols used in your study.

DADA2 Publication: Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016 Jul;13(7):581-3. doi: 10.1038/nmeth.3869. Epub 2016 May 23. PMID: 27214047; PMCID: PMC4927377.

DADA2 Software Package is available as an R package at : https://benjjneb.github.io/dada2/index.html

Analysis Procedures:

DADA2 pipeline includes several tools for read quality control, including quality filtering, trimming, denoising, pair merging and chimera filtering. Below are the major processing steps of DADA2:

Step 1. Read trimming based on sequence quality The quality of NGS Illumina sequences often decreases toward the end of the reads. DADA2 allows to trim off the poor quality read ends in order to improve the error model building and pair mergicing performance.

Step 2. Learn the Error Rates The DADA2 algorithm makes use of a parametric error model (err) and every amplicon dataset has a different set of error rates. The learnErrors method learns this error model from the data, by alternating estimation of the error rates and inference of sample composition until they converge on a jointly consistent solution. As in many machine-learning problems, the algorithm must begin with an initial guess, for which the maximum possible error rates in this data are used (the error rates if only the most abundant sequence is correct and all the rest are errors).

Step 3. Infer amplicon sequence variants (ASVs) based on the error model built in previous step. This step is also called sequence "denoising". The outcome of this step is a list of ASVs that are the equivalent of oligonucleotides.

Step 4. Merge paired reads. If the sequencing products are read pairs, DADA2 will merge the R1 and R2 ASVs into single sequences. Merging is performed by aligning the denoised forward reads with the reverse-complement of the corresponding denoised reverse reads, and then constructing the merged “contig” sequences. By default, merged sequences are only output if the forward and reverse reads overlap by at least 12 bases, and are identical to each other in the overlap region (but these conditions can be changed via function arguments).

Step 5. Remove chimera. The core dada method corrects substitution and indel errors, but chimeras remain. Fortunately, the accuracy of sequence variants after denoising makes identifying chimeric ASVs simpler than when dealing with fuzzy OTUs. Chimeric sequences are identified if they can be exactly reconstructed by combining a left-segment and a right-segment from two more abundant “parent” sequences. The frequency of chimeric sequences varies substantially from dataset to dataset, and depends on on factors including experimental procedures and sample complexity.

Results

1. Read Quality Plots NGS sequence analaysis starts with visualizing the quality of the sequencing. Below are the quality plots of the first sample for the R1 and R2 reads separately. In gray-scale is a heat map of the frequency of each quality score at each base position. The mean quality score at each position is shown by the green line, and the quartiles of the quality score distribution by the orange lines. The forward reads are usually of better quality. It is a common practice to trim the last few nucleotides to avoid less well-controlled errors that can arise there. The trimming affects the downstream steps including error model building, merging and chimera calling. FOMC uses an empirical approach to test many combinations of different trim length in order to achieve best final amplicon sequence variants (ASVs), see the next section “Optimal trim length for ASVs”.

Quality plots for all samples:

2. Optimal trim length for ASVs The final number of merged and chimera-filtered ASVs depends on the quality filtering (hence trimming) in the very beginning of the DADA2 pipeline. In order to achieve highest number of ASVs, an empirical approach was used -

  1. Create a random subset of each sample consisting of 5,000 R1 and 5,000 R2 (to reduce computation time)
  2. Trim 10 bases at a time from the ends of both R1 and R2 up to 50 bases
  3. For each combination of trimmed length (e.g., 300x300, 300x290, 290x290 etc), the trimmed reads are subject to the entire DADA2 pipeline for chimera-filtered merged ASVs
  4. The combination with highest percentage of the input reads becoming final ASVs is selected for the complete set of data

Below is the result of such operation, showing ASV percentages of total reads for all trimming combinations (1st Column = R1 lengths in bases; 1st Row = R2 lengths in bases):

R1/R2281271261251241231
32160.89%62.22%62.91%64.02%64.66%59.45%
31160.78%62.27%62.97%63.48%59.55%42.20%
30160.93%62.34%62.47%58.39%42.27%14.24%
29161.12%61.88%57.50%40.87%14.57%9.01%
28160.89%56.96%40.75%13.83%8.95%5.40%
27156.27%41.23%13.74%8.41%5.27%2.46%

Based on the above result, the trim length combination of R1 = 321 bases and R2 = 241 bases (highlighted red above), was chosen for generating final ASVs for all sequences. This combination generated highest number of merged non-chimeric ASVs and was used for downstream analyses, if requested.

3. Error plots from learning the error rates After DADA2 building the error model for the set of data, it is always worthwhile, as a sanity check if nothing else, to visualize the estimated error rates. The error rates for each possible transition (A→C, A→G, …) are shown below. Points are the observed error rates for each consensus quality score. The black line shows the estimated error rates after convergence of the machine-learning algorithm. The red line shows the error rates expected under the nominal definition of the Q-score. The ideal result would be the estimated error rates (black line) are a good fit to the observed rates (points), and the error rates drop with increased quality as expected.

Forward Read R1 Error Plot


Reverse Read R2 Error Plot

The PDF version of these plots are available here:

 

4. DADA2 Result Summary The table below shows the summary of the DADA2 analysis, tracking paired read counts of each samples for all the steps during DADA2 denoising process - including end-trimming (filtered), denoising (denoisedF, denoisedF), pair merging (merged) and chimera removal (nonchim).

Sample IDF16078.S01F16078.S02F16078.S03F16078.S04F16078.S05F16078.S06F16078.S07F16078.S08F16078.S09F16078.S10F16078.S11F16078.S12F16078.S13F16078.S14F16078.S15F16078.S16F16078.S17F16078.S18Row SumPercentage
input124,633141,915119,656130,359125,545163,233143,048141,366140,052137,477154,971161,172141,660160,679157,251107,784156,995195,3952,603,191100.00%
filtered98,856112,41695,589103,12999,671130,176113,385111,943111,194109,119123,179128,101112,482127,121124,84885,398124,605155,6712,066,88379.40%
denoisedF97,249110,95694,103101,85798,271128,435111,828110,554109,713107,643122,703127,341111,656125,948123,86784,597123,603155,0712,045,39578.57%
denoisedR96,541110,01393,426100,99597,437127,358111,045109,685109,204106,819121,633126,163110,741125,272122,86183,966122,605153,9732,029,73777.97%
merged88,942100,93586,13694,45190,182117,453103,179102,021101,64998,193119,261119,811104,593115,219112,83079,961117,361151,2481,903,42573.12%
nonchim82,57589,88777,87787,19381,123106,68694,81194,07794,43491,695111,805111,72595,382100,42196,50071,234104,396142,7841,734,60566.63%

This table can be downloaded as an Excel table below:

 

5. DADA2 Amplicon Sequence Variants (ASVs). A total of 3479 unique merged and chimera-free ASV sequences were identified, and their corresponding read counts for each sample are available in the "ASV Read Count Table" with rows for the ASV sequences and columns for sample. This read count table can be used for microbial profile comparison among different samples and the sequences provided in the table can be used to taxonomy assignment.

 

The table can be downloaded from this link:

 
 

Sample Meta Information

Download Sample Meta Information
#SampleIDSample NameGroup
F16078.S01Human Microbiome1.Day 0.1Probiotics 1 Day 0
F16078.S02Human Microbiome1.Day 0.2Probiotics 1 Day 0
F16078.S03Human Microbiome1.Day 0.3Probiotics 1 Day 0
F16078.S04Human Microbiome1.Day 0.4Probiotics 1 Day 0
F16078.S05Human Microbiome1.Day 0.5Probiotics 1 Day 0
F16078.S06Human Microbiome2.Day 0.1Probiotics 2 Day 0
F16078.S07Human Microbiome2.Day 0.2Probiotics 2 Day 0
F16078.S08Human Microbiome2.Day 0.3Probiotics 2 Day 0
F16078.S09Human Microbiome2.Day 0.4Probiotics 2 Day 0
F16078.S10Human Microbiome2.Day 0.5Probiotics 2 Day 0
F16078.S11PM1.Day 14.1Probiotics 1 Day 14 + Microbiome
F16078.S12PM1.Day 14.2Probiotics 1 Day 14 Probiotics Only
F16078.S13PM1.Day 14.3Probiotics 1 Day 14 Probiotics Only
F16078.S14PM2.Day 15.1Probiotics 2 Day 15 + Microbiome
F16078.S15PM2.Day 15.2Probiotics 2 Day 15 + Microbiome
F16078.S16PM2.Day 15.3Day 15 Microbiome Only
F16078.S17PM2.Day 15.4Day 15 Microbiome Only
F16078.S18PMT.Day 0.1PMT.Day 0.1
 
 

ASV Read Counts by Samples

#Sample IDRead Count
F16078.S1671,234
F16078.S0377,877
F16078.S0581,123
F16078.S0182,575
F16078.S0487,193
F16078.S0289,887
F16078.S1091,695
F16078.S0894,077
F16078.S0994,434
F16078.S0794,811
F16078.S1395,382
F16078.S1596,500
F16078.S14100,421
F16078.S17104,396
F16078.S06106,686
F16078.S12111,725
F16078.S11111,805
F16078.S18142,784
 
 
 

VII. Analysis - Read Taxonomy Assignment

Read Taxonomy Assignment - Methods

 

The species-level, open-reference 16S rRNA NGS reads taxonomy assignment pipeline

Version 20210310
 

1. Raw sequences reads in FASTA format were BLASTN-searched against a combined set of 16S rRNA reference sequences. It consists of MOMD (version 0.1), the HOMD (version 15.2 http://www.homd.org/index.php?name=seqDownload&file&type=R ), HOMD 16S rRNA RefSeq Extended Version 1.1 (EXT), GreenGene Gold (GG) (http://greengenes.lbl.gov/Download/Sequence_Data/Fasta_data_files/gold_strains_gg16S_aligned.fasta.gz) , and the NCBI 16S rRNA reference sequence set (https://ftp.ncbi.nlm.nih.gov/blast/db/16S_ribosomal_RNA.tar.gz). These sequences were screened and combined to remove short sequences (<1000nt), chimera, duplicated and sub-sequences, as well as sequences with poor taxonomy annotation (e.g., without species information). This process resulted in 1,015 from HOMD V15.22, 495 from EXT, 3,940 from GG and 18,044 from NCBI, a total of 25,120 sequences. Altogether these sequence represent a total of 15,601 oral and non-oral microbial species.

The NCBI BLASTN version 2.7.1+ (Zhang et al, 2000) was used with the default parameters. Reads with ≥ 98% sequence identity to the matched reference and ≥ 90% alignment length (i.e., ≥ 90% of the read length that was aligned to the reference and was used to calculate the sequence percent identity) were classified based on the taxonomy of the reference sequence with highest sequence identity. If a read matched with reference sequences representing more than one species with equal percent identity and alignment length, it was subject to chimera checking with USEARCH program version v8.1.1861 (Edgar 2010). Non-chimeric reads with multi-species best hits were considered valid and were assigned with a unique species notation (e.g., spp) denoting unresolvable multiple species.

2. Unassigned reads (i.e., reads with < 98% identity or < 90% alignment length) were pooled together and reads < 200 bases were removed. The remaining reads were subject to the de novo operational taxonomy unit (OTU) calling and chimera checking using the USEARCH program version v8.1.1861 (Edgar 2010). The de novo OTU calling and chimera checking was done using 98% as the sequence identity cutoff, i.e., the species-level OTU. The output of this step produced species-level de novo clustered OTUs with 98% identity. Representative reads from each of the OTUs/species were then BLASTN-searched against the same reference sequence set again to determine the closest species for these potential novel species. These potential novel species were pooled together with the reads that were signed to specie-level in the previous step, for down-stream analyses.

Reference:
Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010 Oct 1;26(19):2460-1. doi: 10.1093/bioinformatics/btq461. Epub 2010 Aug 12. PubMed PMID: 20709691.

3. Designations used in the taxonomy:

	1) Taxonomy levels are indicated by these prefixes:
	
	   k__: domain/kingdom
	   p__: phylum
	   c__: class
	   o__: order
	   f__: family
	   g__: genus  
	   s__: species
	
	   Example: 
	
	   k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Blautia;s__faecis
		
	2) Unique level identified – known species:
	   
	   k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__hominis
	
	   The above example shows some reads match to a single species (all levels are unique)
	
	3) Non-unique level identified – known species:

	   k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__multispecies_spp123_3
	   
	   The above example “s__multispecies_spp123_3” indicates certain reads equally match to 3 species of the 
	   genus Roseburia; the “spp123” is a temporally assigned species ID.
	
	   k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__multigenus;s__multispecies_spp234_5
	   
	   The above example indicates certain reads match equally to 5 different species, which belong to multiple genera.; 
	   the “spp234” is a temporally assigned species ID.
	
	4) Unique level identified – unknown species, potential novel species:
	   
	   k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__ hominis_nov_97%
	   
	   The above example indicates that some reads have no match to any of the reference sequences with 
	   sequence identity ≥ 98% and percent coverage (alignment length)  ≥ 98% as well. However this groups 
	   of reads (actually the representative read from a de novo  OTU) has 96% percent identity to 
	   Roseburia hominis, thus this is a potential novel species, closest to Roseburia hominis. 
	   (But they are not the same species).
	
	5) Multiple level identified – unknown species, potential novel species:
	   k__Bacteria;p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Roseburia;s__ multispecies_sppn123_3_nov_96%
	
	   The above example indicates that some reads have no match to any of the reference sequences 
	   with sequence identity ≥ 98% and percent coverage (alignment length)  ≥ 98% as well. 
	   However this groups of reads (actually the representative read from a de novo  OTU) 
	   has 96% percent identity equally to 3 species in Roseburia. Thus this is no single 
	   closest species, instead this group of reads match equally to multiple species at 96%. 
	   Since they have passed chimera check so they represent a novel species. “sppn123” is a 
	   temporary ID for this potential novel species.

 
4. The taxonomy assignment algorithm is illustrated in this flow char below:
 
 
 
 

Read Taxonomy Assignment - Result Summary *

CodeCategoryMPC=0% (>=1 read)MPC=0.01%(>=173 reads)
ATotal reads1,734,6051,734,605
BTotal assigned reads1,730,6101,730,610
CAssigned reads in species with read count < MPC010,999
DAssigned reads in samples with read count < 50000
ETotal samples1818
FSamples with reads >= 5001818
GSamples with reads < 50000
HTotal assigned reads used for analysis (B-C-D)1,730,6101,719,611
IReads assigned to single species1,622,5061,615,995
JReads assigned to multiple species64,40063,798
KReads assigned to novel species43,70439,818
LTotal number of species696329
MNumber of single species394279
NNumber of multi-species2211
ONumber of novel species28039
PTotal unassigned reads3,9953,995
QChimeric reads332332
RReads without BLASTN hits675675
SOthers: short, low quality, singletons, etc.2,9882,988
A=B+P=C+D+H+Q+R+S
E=F+G
B=C+D+H
H=I+J+K
L=M+N+O
P=Q+R+S
* MPC = Minimal percent (of all assigned reads) read count per species, species with read count < MPC were removed.
* Samples with reads < 500 were removed from downstream analyses.
* The assignment result from MPC=0.1% was used in the downstream analyses.
 
 
 

Read Taxonomy Assignment - ASV Species-Level Read Counts Table

This table shows the read counts for each sample (columns) and each species identified based on the ASV sequences. The downstream analyses were based on this table.
SPIDTaxonomyF16078.S01F16078.S02F16078.S03F16078.S04F16078.S05F16078.S06F16078.S07F16078.S08F16078.S09F16078.S10F16078.S11F16078.S12F16078.S13F16078.S14F16078.S15F16078.S16F16078.S17F16078.S18
SP10Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sputigena27128712212427514112111717620503000000
SP100Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Bergeyella;sp. HMT3224794574316254677112012316786001000000
SP101Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;marshii1002032000656302147171400
SP102Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT33200100921598911218800000000
SP103Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sputigena10771026964186410224683674755063104218966488460
SP104Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;ochracea229285321323243343300000000
SP105Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;oralis_subsp._tigurinus_clade_07025944421528338717126036849587060888116472498574378556340
SP106Bacteria;Firmicutes;Negativicutes;Veillonellales;Veillonellaceae;Megasphaera;micronuciformis2752301544965415810700000000
SP107Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;cristatus_clade_578448822408998504134621561502117412462214371119131516409478880
SP108Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;sp. HMT3591383270596851450321424347700000000
SP11Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT4172342058678150365660567118549600000000
SP110Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT896121028103030139224846346800000000
SP111Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;gingivalis6300029181016352364579013694622251711231039400
SP112Bacteria;Firmicutes;Negativicutes;Veillonellales;Veillonellaceae;Dialister;invisus260731882502188373323554393695120104306721250
SP113Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Oribacterium;sp. HMT07822917011716319612018218925321900000000
SP114Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;granulosa28023842284925983270183170369207000000
SP115Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT137000803101851651399900000000
SP116Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp. HMT45822643110155110142112110797000000000
SP117Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;aphrophilus12024184138580556014000180000
SP118Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT525172103220516106561854441500000000
SP119Bacteria;Actinobacteria;Coriobacteriia;Coriobacteriales;Coriobacteriaceae;Slackia;exigua144229564110433297369633302943622984130
SP12Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-7];[Eubacterium]_yurii_subsps._yurii_&_margaretiae2392831922902472091481532151880155741213163712617740
SP120Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Stomatobaculum;longum64906577791131051181375600000000
SP121Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;periodonticum4652202253883041272006747113303014604930390
SP122Bacteria;Actinobacteria;Coriobacteriia;Coriobacteriales;Atopobiaceae;Olsenella;uli10115291862212386600492110120
SP123Bacteria;Firmicutes;Bacilli;Bacillales;Gemellaceae;Gemella;morbillorum287745862620392936202352190618671779148502752878507996417920
SP124Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp. HMT51230502617272400025725275382281281553150
SP125Bacteria;Actinobacteria;Actinobacteria;Propionibacteriales;Propionibacteriaceae;Arachnia;propionica4794042913032798597981627104771400000060
SP126Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;orale0000000080000543953460
SP127Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp. HMT314331827152612352871545400000000
SP129Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Schaalia;sp. HMT180152296150293247346255254271188013251277073710
SP13Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp. HMT317150757893913566992962186418601740173700000010
SP130Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp. HMT4231633280831253230292824182678350433262743076948025031760216829450
SP131Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;salivarius53808459112199141320134135203954562430158222480
SP132Bacteria;Firmicutes;Clostridia;Eubacteriales;Lachnospiraceae;Lachnospiraceae_[G-8];bacterium HMT500258001664340018097641522151632640
SP133Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;rava20827023452232402000000000
SP135Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT17060904474174252203139216300090800
SP136Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;gracilis45914828031227179255755753951400000000
SP137Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;sp. HMT23899112824787238615200000000
SP138Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT169383275151210377460356509456395000140000
SP139Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT17527229630425822653415118629819300000000
SP14Bacteria;Bacteroidetes;Bacteroidetes_[C-1];Bacteroidetes_[O-1];Bacteroidetes_[F-1];Bacteroidetes_[G-5];bacterium HMT511835336455178127525011190102100000
SP140Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;oralis1180220217412185186315921508190514711565013951584907612488777966840
SP141Bacteria;Proteobacteria;Betaproteobacteria;Burkholderiales;Comamonadaceae;Ottowia;sp. HMT894341923423113527210713981063055866350214959990
SP142Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;forsythia6933407432113315405451035123101841141242241673760
SP144Bacteria;Actinobacteria;Coriobacteriia;Coriobacteriales;Atopobiaceae;Olsenella;sp. HMT80721231020926530180370663873377000000000
SP145Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;hofstadii15915398415847840940532429300000000
SP146Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;serpentiformis1016979909816913325616721700000000
SP148Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;trevisanii251631121592462321439900000000
SP149Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;endodontalis349428260340323507309293218263168212710726166741080
SP15Bacteria;Bacteroidetes;Bacteroidetes_[C-1];Bacteroidetes_[O-1];Bacteroidetes_[F-1];Bacteroidetes_[G-3];bacterium HMT43600000000000061600000
SP154Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;oris807358645177436614348632823508189270175197900
SP155Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT44256571512663612501300000000
SP156Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;sp. HMT2311672631143222356490253414000000000
SP158Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;oulorum5019461720534957766800000000
SP159Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT14900500322133021000392735240
SP160Bacteria;Actinobacteria;Coriobacteriia;Coriobacteriales;Atopobiaceae;Lancefieldella;parvula33497242401144257936962721283027390
SP161Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;infantis_clade_431311316229310093000000000
SP162Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;fastidiosum2371771573222103052611381264980181371320120
SP164Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Solobacterium;moorei12620583166163196899621115424821587195214461029162710830
SP165Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-1];bacterium HMT348503815768838544410226208157242001200000
SP166Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT13462590574000311000000000
SP167Bacteria;Firmicutes;Clostridia;Eubacteriales;Peptostreptococcaceae;Peptoanaerobacter;[Eubacterium] yurii2833422073602025770861423101349131700000
SP169Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;artemidis593284224630719220323411500000000
SP17Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;pasteri703601528340464953103986574349200020260
SP171Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;australis1311972051273198081251404700000000
SP172Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp. HMT30024213320813795227197245358242001011817817600
SP174Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Catonella;sp. HMT4511256253246272172823700000000
SP175Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp. HMT4726222705335162135322199870000111100
SP176Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;wadei12496112569946982290480442500000000
SP177Bacteria;Firmicutes;Mollicutes;Mycoplasmatales;Mycoplasmataceae;Mycoplasma;faucium003001004323614200000000
SP178Bacteria;Bacteroidetes;Bacteroidetes_[C-1];Bacteroidetes_[O-1];Bacteroidetes_[F-1];Bacteroidetes_[G-3];bacterium HMT28000315011106109033084166168108840
SP179Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;noxia2821122128815133535731338217000000000
SP18Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;catoniae97410868521125771398378456332221021829920210
SP180Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Johnsonella;sp. HMT16667113501103938592932910800000000
SP181Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Stomatobaculum;sp. HMT0971351439016693000027001200000
SP183Bacteria;Firmicutes;Clostridia;Negativicutes;Veillonellaceae;Veillonella;rogosae516462619473040682800080000
SP184Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;denticola5682072661232283051941872132580261400000
SP185Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Eikenella;corrodens321108229185173753508900348615027286957511050
SP187Bacteria;Gracilibacteria_(GN02);Gracilibacteria_(GN02)_[C-2];Gracilibacteria_(GN02)_[O-2];Gracilibacteria_(GN02)_[F-2];Gracilibacteria_(GN02)_[G-2];bacterium HMT873000002039721470250851141122270
SP189Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;johnsonii119236122115144982785100962643400220000
SP19Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;melaninogenica134754496229477612225415821022400000000
SP190Bacteria;Firmicutes;Bacilli;Lactobacillales;Aerococcaceae;Abiotrophia;defectiva244455257337426542445498512382090554013290
SP191Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;chosunense28846748849862367468465766548505967118260162111760
SP192Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;oralis_subsp._dentisani_clade_05834843564666333066969178655540702252566405185608050
SP193Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT2217305035115451675500000000
SP194Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;micans13273113287993120296125100000000
SP195Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Mitsuokella;sp. HMT521281919160745157973600000000
SP197Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;sp. HMT23059632518420009000000000
SP198Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Schaalia;odontolytica247398294371384308227246251188014027818350
SP2Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp. HMT2782700330114951639912729141200000
SP20Bacteria;Firmicutes;Clostridia;Negativicutes;Veillonellaceae;Veillonella;dispar8297534481188611912672401491824195201991570
SP202Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Johnsonella;ignava1321341201131271235037716400000000
SP205Bacteria;Actinobacteria;Actinomycetia;Micrococcales;Micrococcaceae;Rothia;aeria51551059251152951165991964356700464000
SP206Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-6];[Eubacterium]_nodatum603336141912290102654700000000
SP208Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidaceae;Bacteroides;heparinolyticus000000300003038182518251590150414430
SP209Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;oris55487229129110807714533100000000
SP21Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;loescheii20628014173109922100000000
SP211Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Haemophilus;sputorum1903381500026501838735300000
SP212Bacteria;Firmicutes;Bacilli;Bacillales;Gemellaceae;Gemella;sanguinis1401871611902114635311483700000000
SP214Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Parvimonas;micra8841322865893846148477610289451534461551443202132292510
SP215Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT892412763222110503815900000000
SP216Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT3267440511414818015452830719200300000
SP217Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;mitis46761655360765412913920415715200000000
SP218Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-1];bacterium HMT349611899424435442537141158239142001700000
SP221Bacteria;Firmicutes;Bacilli;Bacillales;Gemellaceae;Gemella;bergeri400912003021900000000
SP222Bacteria;Firmicutes;Clostridia;Eubacteriales;Lachnospiraceae;Lachnospiraceae_[G-3];bacterium HMT100519101945998769856548357452582305000000
SP228Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Bergeyella;sp. HMT90012313787138108453148496401213285318310
SP229Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;massiliensis29135322624239596173491389572900000000
SP23Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;sp. HMT3602101261441119956555834033470201032391321231542060
SP230Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Schaalia;sp. HMT877467146878130440326824226600000000
SP231Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;oralis230387193979294901401630141129161622180
SP233Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidaceae;Bacteroidaceae_[G-1];bacterium HMT272000003810131623061211314422250
SP234Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Filifactor;alocis26019211713567822356275170292154145510651193291532600
SP237Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT336135214132143108767610780360421020000
SP239Bacteria;Synergistetes;Synergistia;Synergistales;Synergistaceae;Fretibacterium;sp. HMT36200000179220173000000000
SP24Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT9023033386728784847572404000000
SP240Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-1];bacterium HMT3461125213011811732135177676764244776300600000
SP241Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;saburreum25818919720318023731635833225400000000
SP242Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;sp. HMT808128173759312177768510122400000000
SP243Bacteria;Firmicutes;Negativicutes;Veillonellales;Veillonellaceae;Veillonellaceae_[G-1];bacterium HMT155334330703121141352300000000
SP244Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp. HMT949400131132411545290231700000
SP245Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT1711121697611012017115511714213600000000
SP246Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Mogibacterium;timidum3938321014128624910310900000000
SP247Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Schaalia;cardiffensis07740743143500032066242399629140
SP25Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT2121789133118011439326647142930500400000
SP250Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;sp. HMT258751158787574096000000000
SP251Bacteria;Firmicutes;Clostridia;Eubacteriales;Lachnospiraceae;Lachnospiraceae_[G-7];bacterium HMT163300000001311183281600000
SP252Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;constellatus1471841991951485932084113402950103142921251161220
SP254Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT498803366292712916717739612400000000
SP255Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Schaalia;sp. HMT1789715414921212040935654431528400004400
SP256Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcus;stomatis2964463584053992491391941581947312012198374569576385238600
SP259Bacteria;Firmicutes;Negativicutes;Veillonellales;Veillonellaceae;Anaeroglobus;geminatus185188242597376629200000000
SP26Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;segnis842673527853523526531016901391982643535714800
SP261Bacteria;Proteobacteria;Gammaproteobacteria;Cardiobacteriales;Cardiobacteriaceae;Cardiobacterium;hominis2358015523917615722328428418000000000
SP262Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp. HMT06441809747716083287985797917723741696126709372406122591615750
SP263Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Schaalia;georgiae75166361201148710220114912800000000
SP264Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;hwasookii2661958318619338640541000015300240
SP265Bacteria;Firmicutes;Bacilli;Bacillales;Gemellaceae;Gemella;haemolysans710123277413091108806370746401109846660
SP266Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;israelii15016273424418522228645900000000
SP267Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-5];[Eubacterium]_saphenum0004073821210513516300000000
SP268Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT223130737949799183120795800000000
SP269Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;buccae2301700500019391325093064604092092180
SP27Bacteria;Actinobacteria;Coriobacteriia;Coriobacteriales;Atopobiaceae;Lancefieldella;rimae4953375548382661962603004400
SP270Bacteria;Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Ruminococcaceae_[G-2];bacterium HMT08525183844361255756820321146184819200
SP271Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;anginosus164250152331314212730344002472381085384900
SP272Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp. HMT51355233823296794019380241700000
SP273Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;hongkongensis606064149684252581275200000000
SP274Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-3];bacterium HMT351568444856202301616027221900230
SP277Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-1];bacterium HMT95739356558744546587927941910433214121100
SP278Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacterales;Yersiniaceae;Serratia;marcescens00000000000008645335010413137440
SP28Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;flava1222910035559431082604705551046787075807468560
SP280Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Schaalia;meyeri6611494587930467110848000000000
SP281Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;pleuritidis1216373296961813086879300000000
SP282Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-1];bacterium HMT869968898971031074172845200000000
SP283Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT41242293588369480618057061200000
SP284Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-1];[Eubacterium]_infirmum7016156203158414524531044991165101810788636926110
SP286Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;subflava0000037956831057829206573936193699242322700
SP287Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-2];Saccharibacteria_(TM7)_[G-5];bacterium HMT3562895032763594317412732323100000000
SP289Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;gordonii49579966475269520521740251620732156024019228663539100918400
SP29Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacterales;Enterobacteriaceae;Enterobacter;cloacae0000000000329511635317301162490612247648327
SP294Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;flavescens14561109118141123102151132510760188558010259100
SP295Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-4];bacterium HMT35523206747310001000793741135267651090
SP296Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;sicca000003683821912082090002142182912870
SP297Bacteria;Proteobacteria;Gammaproteobacteria;Cardiobacteriales;Cardiobacteriaceae;Cardiobacterium;valvarum20688199321201334396574338378001150000
SP298Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;sp. HMT473117508526688172126854600000000
SP3Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;nucleatum_subsp._animalis7805857631018108124033212515834802170410000
SP30Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;gingivalis26416424537322735030342531732000000000
SP301Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-6];bacterium HMT870377376383511392261030172900000000
SP302Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;gingivalis524170316724124345072300028080
SP305Bacteria;Proteobacteria;Betaproteobacteria;Burkholderiales;Comamonadaceae;Delftia;lacustris00000000000456000000
SP307Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp. HMT47590831093479481930284500000000
SP308Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Mogibacterium;diversum1472162101582551401111442008700000000
SP31Bacteria;Firmicutes;Clostridia;Clostridiales;Peptococcaceae;Peptococcus;sp. HMT1686773836571825342484000000400
SP310Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Parvimonas;sp. HMT110250515314247332287514315811700000000
SP312Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;sp. HMT2476510165130560000000000000
SP313Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Peptidiphaga;gingivicola124591617511343821122716922400000000
SP314Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp. HMT2770004826202720221473292510000
SP317Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-2];bacterium HMT35087139791261374981255270000000000
SP32Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;tannerae82723561323945611551553917994107401821442419130
SP320Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT920001109311229261601650211300
SP322Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Pseudoleptotrichia;goodfellowii421232022491251662200000000
SP324Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-4];bacterium HMT369132187671066998642235760270294345231190
SP329Bacteria;Firmicutes;Clostridia;Eubacteriales;Lachnospiraceae;Butyrivibrio;sp. HMT0800000015162260000351239490
SP33Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;oralis25936914524556469165579364819440
SP330Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;oralis_subsp._tigurinus_clade_071117638125652532298397853120172073321514265343193090
SP332Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Peptidiphaga;sp. HMT18310171512912112794098774630062345124600000000
SP333Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Peptoniphilaceae_[G-1];bacterium HMT11316000021334382522000201022100
SP334Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sp. HMT05618729942717026113099189147181010450500
SP337Bacteria;Absconditabacteria_(SR1);Absconditabacteria_(SR1)_[C-1];Absconditabacteria_(SR1)_[O-1];Absconditabacteria_(SR1)_[F-1];Absconditabacteria_(SR1)_[G-1];bacterium HMT8741158611895698095104828600400000
SP338Bacteria;Firmicutes;Bacilli;Bacillales;Paenibacillaceae;Paenibacillus;naphthalenovorans00000000000000000374
SP34Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidales_[F-2];Bacteroidales_[G-2];bacterium HMT2746133065466925209371741932100825364148211912312441011570
SP340Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;pallens23017011753231623600000000
SP342Bacteria;Chloroflexi;Anaerolineae;Anaerolineales;Anaerolineaceae;Anaerolineae_[G-1];bacterium HMT43948060755433364900482117270
SP343Bacteria;Firmicutes;Clostridia;Clostridiales;Ruminococcaceae;Ruminococcaceae_[G-1];bacterium HMT0752111531359512721710524822915900300000
SP345Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;lecithinolyticum130170223651431212719164400000000
SP347Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;concisus1222848417415718216116213400000000
SP348Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;parasanguinis_clade_411111207841371490069500000000
SP349Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sinensis31274718949533463562901463832051842480
SP35Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT39288490865757056197683895976297400006000
SP356Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT33811279548233174440342200000000
SP357Bacteria;Actinobacteria;Actinobacteria;Propionibacteriales;Propionibacteriaceae;Arachnia;rubra5139141731236190120705000000000
SP358Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;endodontalis105717611694149160219141104010000000
SP359Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-9];[Eubacterium]_brachy694894803825616420401216251344066371115250
SP36Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;nigrescens121954584120262116909691207208510650185166117152123890
SP360Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT219104576910376302839332803000000
SP361Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;cristatus79167110216125021063004933442300170
SP365Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Parvimonas;sp. HMT39300000000000006468891550
SP366Bacteria;Actinobacteria;Actinomycetia;Micrococcales;Micrococcaceae;Rothia;dentocariosa73369054963482494477979798381400500050
SP368Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT41414125371182428523231821300000000
SP37Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Centipeda;periodontii954378471408212387987290190137123717200
SP370Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-8];bacterium HMT95522342915193749193500323616211000
SP374Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Alloscardovia;omnicolens0007000000386312500000
SP376Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;koreensis000006591566841000505554420
SP379Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-2];bacterium HMT09144282223310060095837232918200
SP38Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;naeslundii26815933423723517342092182720251706000029600
SP382Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Bifidobacterium;longum0000000000184421536430000
SP384Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;intermedius24633742834633315870252195175061460000
SP387Bacteria;Firmicutes;Clostridia;Eubacteriales;Peptostreptococcaceae;Peptoanaerobacter;stomatis6813561715910015806734856481130
SP389Bacteria;Actinobacteria;Actinomycetia;Micrococcales;Micrococcaceae;Rothia;mucilaginosa163147103246160351520119500000000
SP393Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Kingella;oralis190501145313322922640028825500000000
SP394Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT4482682098791825147697295549318000000000
SP395Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;perflava2704006320014541800000000
SP4Bacteria;Firmicutes;Clostridia;Clostridiales;Peptococcaceae;Peptococcus;sp. HMT16787227103179643214955628903002000
SP40Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT22510641158101454997032645250363348000000000
SP403Bacteria;Firmicutes;Erysipelotrichia;Erysipelotrichales;Erysipelotrichaceae;Bulleidia;extructa37312472112201210005553610100
SP41Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT86420411112987637864150606900000500
SP42Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;sp. HMT2033573623083633703139141418446200000000
SP44Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;sp. HMT286155131145109102118125142727400000000
SP45Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;elongata3863530313120763374084646369331063287244923733016271395960
SP46Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;maltophilum831159380871621486722523818288131192641490
SP47Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;saccharolytica11850118120101135152121841320524313816578420
SP48Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;baroniae190000000006146830500000
SP49Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;infelix145361083210723534325627231902031413062201231100
SP5Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;sp. HMT2375197205113564222267860873400000000
SP50Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;sp. HMT91270301291302432412000000000
SP51Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;dentalis186421605484916238001280100500000000
SP53Bacteria;Firmicutes;Clostridia;Negativicutes;Veillonellaceae;Veillonella;atypica90524124033241001883511932958210
SP54Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;nucleatum_subsp._vincentii13431004554613590538751197496397016601232101784020
SP55Bacteria;Actinobacteria;Actinomycetia;Corynebacteriales;Corynebacteriaceae;Corynebacterium;durum207122143127134126811407411800003000
SP56Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp. HMT284474039312413000400020000
SP57Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;sp. HMT21526614421523019634241029828018570040000
SP58Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;downii83413691162121411091156125210397891126087578531414326152817820
SP59Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;dianae113601173082136113144862770141906000
SP6Bacteria;Actinobacteria;Actinomycetia;Corynebacteriales;Corynebacteriaceae;Corynebacterium;matruchotii193612299967627632648424824132451385400000000
SP60Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;denticola253324151229157709211177192181422047261318130
SP61Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;veroralis122252419327912221800000000
SP63Bacteria;Firmicutes;Clostridia;Negativicutes;Veillonellaceae;Veillonella;parvula36211363335636495058811901070884277153613322084265275712120
SP64Bacteria;Proteobacteria;Betaproteobacteria;Burkholderiales;Burkholderiaceae;Lautropia;mirabilis507173452186367871108913507298561120223202341461731960
SP65Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Alloprevotella;sp. HMT9142701160243033293000000000
SP66Bacteria;Firmicutes;Mollicutes;Mycoplasmatales;Mycoplasmataceae;Mycoplasma;salivarium514511232734841761750808113250
SP69Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;flueggei2591819195544564115600000080
SP7Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;nucleatum583173604133525442283623402719292967243021662443289451560
SP70Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;umeaense325212221215207346226190194153052380250480
SP71Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;leadbetteri63746972280961660581066377761108000000
SP72Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Haemophilus;parainfluenzae54716251147668969986655196774202501760220150
SP73Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Kingella;denitrificans1071000526449742700000000
SP74Bacteria;Proteobacteria;Betaproteobacteria;Neisseriales;Neisseriaceae;Neisseria;mucosa0000015006544340001650750340
SP76Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Catonella;morbi51455732524440074651547152854613553164121103661070
SP77Bacteria;Absconditabacteria_(SR1);Absconditabacteria_(SR1)_[C-1];Absconditabacteria_(SR1)_[O-1];Absconditabacteria_(SR1)_[F-1];Absconditabacteria_(SR1)_[G-1];bacterium HMT34511211261627651403652350220010000
SP78Bacteria;Proteobacteria;Deltaproteobacteria;Desulfobacterales;Desulfobulbaceae;Desulfobulbus;sp. HMT0411206010420362111202302000724640
SP8Bacteria;Firmicutes;Negativicutes;Veillonellales;Veillonellaceae;Veillonellaceae_[G-1];bacterium HMT1502830166531105423700000000
SP82Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;buccalis11071728113191710791674183417611221110700000600
SP83Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;maculosa764664377010852781171090013222512140
SP84Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;nanceiensis391843949800121000000000
SP85Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;sp. HMT898471815141064731049072080156112851510
SP86Bacteria;Fusobacteria;Fusobacteriia;Fusobacteriales;Leptotrichiaceae;Leptotrichia;shahii2734381781642394161074699626270200000000
SP87Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;sp. HMT204522362436478479829939583200000000
SP88Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT897943258514921189857041730853100000000
SP9Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;showae3021401511311872693421772012502017255620371057116584811560
SP90Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT1383516431510361561259084801018942410
SP91Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp. HMT4432851400293633431000000000
SP92Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;intermedia377457377825741000661439135259444439884030203423990
SP93Bacteria;Absconditabacteria_(SR1);Absconditabacteria_(SR1)_[C-1];Absconditabacteria_(SR1)_[O-1];Absconditabacteria_(SR1)_[F-1];Absconditabacteria_(SR1)_[G-1];bacterium HMT8757546635041561726331700000000
SP95Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sanguinis10891338160219812030237817122237180118340315308120375669610940
SP96Bacteria;Firmicutes;Bacilli;Lactobacillales;Carnobacteriaceae;Granulicatella;adiacens23963496274226552704112011341524129586812869518429473429115335060
SP97Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacterales;Enterobacteriaceae;Enterobacter;cancerogenus00002000006212029834318033048961163447693799
SP98Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;socranskii3063311913812743512991662635850599356115187971250
SP99Bacteria;Gracilibacteria_(GN02);Gracilibacteria_(GN02)_[C-1];Gracilibacteria_(GN02)_[O-1];Gracilibacteria_(GN02)_[F-1];Gracilibacteria_(GN02)_[G-1];bacterium HMT87285113729599113437382300000000
SPN105Bacteria;Firmicutes;Clostridia;Eubacteriales;Lachnospiraceae;Lacrimispora;xylanolytica_nov_88.613%285757389797537346269302279952010800000
SPN108Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;sp. HMT284 nov_97.746%44244137936133339334625320216200000000
SPN109Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT892 nov_97.041%2910181211910418708476269850
SPN112Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;sp. HMT863 nov_97.890%615959792701500600000000
SPN113Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;noxia_nov_97.835%49854016343551211700000000
SPN114Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-1];bacterium HMT957 nov_97.550%72327172038257111401916181110160
SPN115Bacteria;Proteobacteria;Betaproteobacteria;Rhodocyclales;Rhodocyclaceae;Propionivibrio;dicarboxylicus_nov_93.802%266291815603825292200000000
SPN117Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;aphrophilus_nov_97.347%20101844738205900000000
SPN118Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;gingivalis_nov_97.899%00000423851714900000000
SPN119Bacteria;Actinobacteria;Actinomycetia;Propionibacteriales;Propionibacteriaceae;Brooklawnia;cerclae_nov_97.291%000002920372312800000000
SPN120Bacteria;Spirochaetes;Spirochaetia;Spirochaetales;Treponemataceae;Treponema;sp. HMT927 nov_91.411%818007332542561800000000
SPN121Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Catonella;sp. HMT451 nov_95.178%00000000000046823419200
SPN122Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp. HMT305 nov_93.456%137131370000013041026772001200
SPN123Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;sp. HMT175 nov_97.551%212424524800013000000000
SPN134Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;israelii_nov_96.838%1714173219570320313432308000110000
SPN153Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;sanguinis_nov_97.782%170613436480145317344134000514841850
SPN155Bacteria;Actinobacteria;Actinomycetia;Corynebacteriales;Corynebacteriaceae;Corynebacterium;matruchotii_nov_97.755%11849875154861526616120300000000
SPN165Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;gingivalis_nov_96.218%413053633830334437517128400000000
SPN177Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Peptidiphaga;gingivicola_nov_96.920%253230259287157362543713400000000
SPN190Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;forsythia_nov_97.308%000000050001061191681582363610
SPN195Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;naeslundii_nov_96.755%471186679137151908311310700000000
SPN20Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Bacteroidaceae;Bacteroides;heparinolyticus_nov_94.877%0000000000000210103157730
SPN206Bacteria;Saccharibacteria_(TM7);Saccharibacteria_(TM7)_[C-1];Saccharibacteria_(TM7)_[O-1];Saccharibacteria_(TM7)_[F-1];Saccharibacteria_(TM7)_[G-3];bacterium HMT351 nov_93.028%39112841400000496160274912190
SPN217Bacteria;Proteobacteria;Gammaproteobacteria;Pseudomonadales;Moraxellaceae;Moraxella;oblonga_nov_93.776%000002161612557714200000000
SPN228Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Centipeda;periodontii_nov_97.436%57276644112407831200207132341925120
SPN239Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Centipeda;periodontii_nov_97.441%17479205377705649200070000
SPN250Bacteria;Bacteroidota;Bacteroidia;Bacteroidales;Rikenellaceae;Acetobacteroides;hydrogenigenes_nov_81.120%00000798000000000000
SPN30Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT936 nov_97.030%584450286200000018011600000
SPN40Bacteria;Firmicutes;Clostridia;Eubacteriales;Lachnospiraceae;Lachnospiraceae_[G-8];bacterium HMT500 nov_97.895%000001135536444508887180070
SPN43Bacteria;Actinobacteria;Actinomycetia;Actinomycetales;Actinomycetaceae;Actinomyces;viscosus_nov_97.955%0000017017328127014500000000
SPN49Bacteria;Proteobacteria;Gammaproteobacteria;Cardiobacteriales;Cardiobacteriaceae;Cardiobacterium;hominis_nov_97.095%7825604688182877421300000000
SPN54Bacteria;Firmicutes;Clostridia;Clostridiales;Peptoniphilaceae;Parvimonas;micra_nov_97.474%2529432926000000006150921180
SPN66Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;flueggei_nov_97.624%18021006967474816600000000
SPN76Bacteria;Firmicutes;Negativicutes;Selenomonadales;Selenomonadaceae;Selenomonas;sp. HMT137 nov_95.842%1712170857751142610800000000
SPN8Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Bergeyella;zoohelcum_nov_93.004%0000011663619196644058495103900
SPN88Bacteria;Bacteroidetes;Flavobacteriia;Flavobacteriales;Flavobacteriaceae;Capnocytophaga;gingivalis_nov_90.546%112447744960504500000000
SPN99Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;catoniae_nov_97.746%001300585772915400000000
SPP1Bacteria;Proteobacteria;Gammaproteobacteria;Pasteurellales;Pasteurellaceae;Aggregatibacter;multispecies_spp1_20000020026928518820600000040
SPP10Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;multispecies_spp10_21751851971862018621621501800000000
SPP11Bacteria;Firmicutes;Clostridia;Negativicutes;Veillonellaceae;Veillonella;multispecies_spp11_218855132003175015962320210228922796233310633097371671556730245035100
SPP15Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacterales;Yersiniaceae;Serratia;multispecies_spp15_200000000000001472569167721470
SPP17Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;multispecies_spp17_25034119433830393171000000000
SPP18Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Lachnoanaerobaculum;multispecies_spp18_24111027186137041014130221135110
SPP19Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae_[XI];Peptostreptococcaceae_[XI][G-4];multispecies_spp19_25443050503300038047373562000
SPP2Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae_[XIV];Stomatobaculum;multispecies_spp2_205139624900000010000000
SPP21Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;multispecies_spp21_2471299462934507158142288274315014006713538670
SPP5Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Tannerella;multispecies_spp5_217915412716613716024921716611500000000
SPP6Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;multispecies_spp6_30131325120020154000000000
SPPN10Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;multispecies_sppn10_3_nov_97.845%15122326121365420221337411800000000
SPPN16Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;multispecies_sppn16_2_nov_97.536%18096821881160000000000000
 
 
Download OTU Tables at Different Taxonomy Levels
PhylumCount*: Relative**: CLR***:
ClassCount*: Relative**: CLR***:
OrderCount*: Relative**: CLR***:
FamilyCount*: Relative**: CLR***:
GenusCount*: Relative**: CLR***:
SpeciesCount*: Relative**: CLR***:
* Read count
** Relative abundance (count/total sample count)
*** Centered log ratio transformed abundance
;
 
The species listed in the table has full taxonomy and a dynamically assigned species ID specific to this report. When some reads match with the reference sequences of more than one species equally (i.e., same percent identiy and alignmnet coverage), they can't be assigned to a particular species. Instead, they are assigned to multiple species with the species notaton "s__multispecies_spp2_2". In this notation, spp2 is the dynamic ID assigned to these reads that hit multiple sequences and the "_2" at the end of the notation means there are two species in the spp2.

You can look up which species are included in the multi-species assignment, in this table below:
 
 
 
 
Another type of notation is "s__multispecies_sppn2_2", in which the "n" in the sppn2 means it's a potential novel species because all the reads in this species have < 98% idenity to any of the reference sequences. They were grouped together based on de novo OTU clustering at 98% identity cutoff. And then a representative sequence was chosed to BLASTN search against the reference database to find the closest match (but will still be < 98%). This representative sequence also matched equally to more than one species, hence the "spp" was given in the label.
 
 

Taxonomy Bar Plots for All Samples

 
 

Taxonomy Bar Plots for Individual Comparison Groups

 
 
Comparison No.Comparison NameFamiliesGeneraSpecies
Comparison 1Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 2Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 3Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 4Probiotics 2 Day 0 vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
Comparison 5Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 6Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
 
 

VIII. Analysis - Alpha Diversity

 

In ecology, alpha diversity (α-diversity) is the mean species diversity in sites or habitats at a local scale. The term was introduced by R. H. Whittaker[1][2] together with the terms beta diversity (β-diversity) and gamma diversity (γ-diversity). Whittaker's idea was that the total species diversity in a landscape (gamma diversity) is determined by two different things, the mean species diversity in sites or habitats at a more local scale (alpha diversity) and the differentiation among those habitats (beta diversity).


References:
Whittaker, R. H. (1960) Vegetation of the Siskiyou Mountains, Oregon and California. Ecological Monographs, 30, 279–338. doi:10.2307/1943563
Whittaker, R. H. (1972). Evolution and Measurement of Species Diversity. Taxon, 21, 213-251. doi:10.2307/1218190

 

Alpha Diversity Analysis by Rarefaction

Diversity measures are affected by the sampling depth. Rarefaction is a technique to assess species richness from the results of sampling. Rarefaction allows the calculation of species richness for a given number of individual samples, based on the construction of so-called rarefaction curves. This curve is a plot of the number of species as a function of the number of samples. Rarefaction curves generally grow rapidly at first, as the most common species are found, but the curves plateau as only the rarest species remain to be sampled.


References:
Willis AD. Rarefaction, Alpha Diversity, and Statistics. Front Microbiol. 2019 Oct 23;10:2407. doi: 10.3389/fmicb.2019.02407. PMID: 31708888; PMCID: PMC6819366.

 
 
 

Boxplot of Alpha-diversity Indices

The two main factors taken into account when measuring diversity are richness and evenness. Richness is a measure of the number of different kinds of organisms present in a particular area. Evenness compares the similarity of the population size of each of the species present. There are many different ways to measure the richness and evenness. These measurements are called "estimators" or "indices". Below is a diversity of 3 commonly used indices showing the values for all the samples (dots) and in groups (boxes).

 
Alpha Diversity Box Plots for All Groups
 
 
 
 
 
 
 
Alpha Diversity Box Plots for Individual Comparisons
 
Comparison 1Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomeView in PDFView in SVG
Comparison 2Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyView in PDFView in SVG
Comparison 3Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomeView in PDFView in SVG
Comparison 4Probiotics 2 Day 0 vs Day 15 Microbiome OnlyView in PDFView in SVG
Comparison 5Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyView in PDFView in SVG
Comparison 6Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyView in PDFView in SVG
 
 
 

Group Significance of Alpha-diversity Indices

To test whether the alpha diversity among different comparison groups are different statistically, we use the Kruskal Wallis H test provided the "alpha-group-significance" fucntion in the QIIME 2 "diversity" package. Kruskal Wallis H test is the non-parametric alternative to the One Way ANOVA. Non-parametric means that the test doesn’t assume your data comes from a particular distribution. The H test is used when the assumptions for ANOVA aren’t met (like the assumption of normality). It is sometimes called the one-way ANOVA on ranks, as the ranks of the data values are used in the test rather than the actual data points. The H test determines whether the medians of two or more groups are different.

Below are the Kruskal Wallis H test results for each comparison based on three different alpha diversity measures: 1) Observed species (features), 2) Shannon index, and 3) Simpson index.

 
 
Comparison 1.Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomeObserved FeaturesShannon IndexSimpson Index
Comparison 2.Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyObserved FeaturesShannon IndexSimpson Index
Comparison 3.Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomeObserved FeaturesShannon IndexSimpson Index
Comparison 4.Probiotics 2 Day 0 vs Day 15 Microbiome OnlyObserved FeaturesShannon IndexSimpson Index
Comparison 5.Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyObserved FeaturesShannon IndexSimpson Index
Comparison 6.Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyObserved FeaturesShannon IndexSimpson Index
 
 

IX. Analysis - Beta Diversity

 

NMDS and PCoA Plots

Beta diversity compares the similarity (or dissimilarity) of microbial profiles between different groups of samples. There are many different similarity/dissimilarity metrics. In general, they can be quantitative (using sequence abundance, e.g., Bray-Curtis or weighted UniFrac) or binary (considering only presence-absence of sequences, e.g., binary Jaccard or unweighted UniFrac). They can be even based on phylogeny (e.g., UniFrac metrics) or not (non-UniFrac metrics, such as Bray-Curtis, etc.).

For microbiome studies, species profiles of samples can be compared with the Bray-Curtis dissimilarity, which is based on the count data type. The pair-wise Bray-Curtis dissimilarity matrix of all samples can then be subject to either multi-dimensional scaling (MDS, also known as PCoA) or non-metric MDS (NMDS).

MDS/PCoA is a scaling or ordination method that starts with a matrix of similarities or dissimilarities between a set of samples and aims to produce a low-dimensional graphical plot of the data in such a way that distances between points in the plot are close to original dissimilarities.

NMDS is similar to MDS, however it does not use the dissimilarities data, instead it converts them into the ranks and use these ranks in the calculation.

In our beta diversity analysis, Bray-Curtis dissimilarity matrix was first calculated and then plotted by the PCoA and NMDS separately. Below are beta diveristy results for all groups together:

 
 
NMDS and PCoA Plots for All Groups
 
 
 
 
 

The above PCoA and NMDS plots are based on count data. The count data can also be transformed into centered log ratio (CLR) for each species. The CLR data is no longer count data and cannot be used in Bray-Curtis dissimilarity calculation. Instead CLR can be compared with Euclidean distances. When CLR data are compared by Euclidean distance, the distance is also called Aitchison distance.

Below are the NMDS and PCoA plots of the Aitchison distances of the samples:

 
 
 
 
 
 
 
NMDS and PCoA Plots for Individual Comparisons
 
 
Comparison No.Comparison NameNMDAPCoA
Bray-CurtisCLR EuclideanBray-CurtisCLR Euclidean
Comparison 1Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomePDFSVGPDFSVGPDFSVGPDFSVG
Comparison 2Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVGPDFSVG
Comparison 3Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomePDFSVGPDFSVGPDFSVGPDFSVG
Comparison 4Probiotics 2 Day 0 vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVGPDFSVG
Comparison 5Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVGPDFSVG
Comparison 6Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVGPDFSVG
 
 
 
 
 

Interactive 3D PCoA Plots - Bray-Curtis Dissimilarity

 
 
 

Interactive 3D PCoA Plots - Euclidean Distance

 
 
 

Interactive 3D PCoA Plots - Correlation Coefficients

 
 
 

Group Significance of Beta-diversity Indices

To test whether the between-group dissimilarities are significantly greater than the within-group dissimilarities, the "beta-group-significance" function provided in the QIIME 2 "diversity" package was used with PERMANOVA (permutational multivariate analysis of variance) as the group significant testing method.

Three beta diversity matrics were used: 1) Bray–Curtis dissimilarity 2) Correlation coefficient matrix , and 3) Aitchison distance (Euclidean distance between clr-transformed compositions).

 
 
Comparison 1.Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomeBray–CurtisCorrelationAitchison
Comparison 2.Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyBray–CurtisCorrelationAitchison
Comparison 3.Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomeBray–CurtisCorrelationAitchison
Comparison 4.Probiotics 2 Day 0 vs Day 15 Microbiome OnlyBray–CurtisCorrelationAitchison
Comparison 5.Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyBray–CurtisCorrelationAitchison
Comparison 6.Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyBray–CurtisCorrelationAitchison
 
 
 

X. Analysis - Differential Abundance

16S rRNA next generation sequencing (NGS) generates a fixed number of reads that reflect the proportion of different species in a sample, i.e., the relative abundance of species, instead of the absolute abundance. In Mathematics, measurements involving probabilities, proportions, percentages, and ppm can all be thought of as compositional data. This makes the microbiome read count data “compositional” (Gloor et al, 2017). In general, compositional data represent parts of a whole which only carry relative information (http://www.compositionaldata.com/).

The problem of microbiome data being compositional arises when comparing two groups of samples for identifying “differentially abundant” species. A species with the same absolute abundance between two conditions, its relative abundances in the two conditions (e.g., percent abundance) can become different if the relative abundance of other species change greatly. This problem can lead to incorrect conclusion in terms of differential abundance for microbial species in the samples.

When studying differential abundance (DA), the current better approach is to transform the read count data into log ratio data. The ratios are calculated between read counts of all species in a sample to a “reference” count (e.g., mean read count of the sample). The log ratio data allow the detection of DA species without being affected by percentage bias mentioned above

In this report, a compositional DA analysis tool “ANCOM” (analysis of composition of microbiomes) was used. ANCOM transforms the count data into log-ratios and thus is more suitable for comparing the composition of microbiomes in two or more populations. "ANCOM" generates a table of features with W-statistics and whether the null hypothesis is rejected. The “W” is the W-statistic, or number of features that a single feature is tested to be significantly different against. Hence the higher the "W" the more statistical sifgnificant that a feature/species is differentially abundant.


References:

Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ. Microbiome Datasets Are Compositional: And This Is Not Optional. Front Microbiol. 2017 Nov 15;8:2224. doi: 10.3389/fmicb.2017.02224. PMID: 29187837; PMCID: PMC5695134.

Mandal S, Van Treuren W, White RA, Eggesbø M, Knight R, Peddada SD. Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis. 2015 May 29;26:27663. doi: 10.3402/mehd.v26.27663. PMID: 26028277; PMCID: PMC4450248.

Lin H, Peddada SD. Analysis of compositions of microbiomes with bias correction. Nat Commun. 2020 Jul 14;11(1):3514. doi: 10.1038/s41467-020-17041-7. PMID: 32665548; PMCID: PMC7360769.

 
 

ANCOM Differential Abundance Analysis

 
ANCOM Results for Individual Comparisons
Comparison No.Comparison Name
Comparison 1.Probiotics 1 Day 0 vs Probiotics 1 Day 14 + Microbiome
Comparison 2.Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics Only
Comparison 3.Probiotics 2 Day 0 vs Probiotics 2 Day 15 + Microbiome
Comparison 4.Probiotics 2 Day 0 vs Day 15 Microbiome Only
Comparison 5.Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics Only
Comparison 6.Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome Only
 
 

ANCOM-BC2 Differential Abundance Analysis

 

Starting with version V1.2, we include the results of ANCOM-BC (Analysis of Compositions of Microbiomes with Bias Correction) (Lin and Peddada 2020). ANCOM-BC is an updated version of "ANCOM" that:
(a) provides statistically valid test with appropriate p-values,
(b) provides confidence intervals for differential abundance of each taxon,
(c) controls the False Discovery Rate (FDR),
(d) maintains adequate power, and
(e) is computationally simple to implement.

The bias correction (BC) addresses a challenging problem of the bias introduced by differences in the sampling fractions across samples. This bias has been a major hurdle in performing DA analysis of microbiome data. ANCOM-BC estimates the unknown sampling fractions and corrects the bias induced by their differences among samples. The absolute abundance data are modeled using a linear regression framework.

Starting with version V1.43, ANCOM-BC2 is used instead of ANCOM-BC, So that multiple pairwise directional test can be performed (if there are more than two gorups in a comparison). When performing pairwise directional test, the mixed directional false discover rate (mdFDR) is taken into account. The mdFDR is the combination of false discovery rate due to multiple testing, multiple pairwise comparisons, and directional tests within each pairwise comparison. The mdFDR is adopted from (Guo, Sarkar, and Peddada 2010; Grandhi, Guo, and Peddada 2016). For more detail explanation and additional features of ANCOM-BC2 please see author's documentation.

References:

Lin H, Peddada SD. Analysis of compositions of microbiomes with bias correction. Nat Commun. 2020 Jul 14;11(1):3514. doi: 10.1038/s41467-020-17041-7. PMID: 32665548; PMCID: PMC7360769.

Guo W, Sarkar SK, Peddada SD. Controlling false discoveries in multidimensional directional decisions, with applications to gene expression data on ordered categories. Biometrics. 2010 Jun;66(2):485-92. doi: 10.1111/j.1541-0420.2009.01292.x. Epub 2009 Jul 23. PMID: 19645703; PMCID: PMC2895927.

Grandhi A, Guo W, Peddada SD. A multiple testing procedure for multi-dimensional pairwise comparisons with application to gene expression studies. BMC Bioinformatics. 2016 Feb 25;17:104. doi: 10.1186/s12859-016-0937-5. PMID: 26917217; PMCID: PMC4768411.

 
 
ANCOM-BC Results for Individual Comparisons
 
Comparison No.Comparison Name
Comparison 1.Probiotics 1 Day 0 vs Probiotics 1 Day 14 + Microbiome
Comparison 2.Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics Only
Comparison 3.Probiotics 2 Day 0 vs Probiotics 2 Day 15 + Microbiome
Comparison 4.Probiotics 2 Day 0 vs Day 15 Microbiome Only
Comparison 5.Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics Only
Comparison 6.Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome Only
 
 
 

LEfSe - Linear Discriminant Analysis Effect Size

LEfSe (Linear Discriminant Analysis Effect Size) is an alternative method to find "organisms, genes, or pathways that consistently explain the differences between two or more microbial communities" (Segata et al., 2011). Specifically, LEfSe uses rank-based Kruskal-Wallis (KW) sum-rank test to detect features with significant differential (relative) abundance with respect to the class of interest. Since it is rank-based, instead of proportional based, the differential species identified among the comparison groups is less biased (than percent abundance based).

Reference:

Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011 Jun 24;12(6):R60. doi: 10.1186/gb-2011-12-6-r60. PMID: 21702898; PMCID: PMC3218848.

 
Probiotics 1 Day 0 vs Probiotics 1 Day 14 + Microbiome
 
 
 
 
 
 
 
LEfSe Results for All Comparisons
 
Comparison No.Comparison Name
Comparison 1.Probiotics 1 Day 0 vs Probiotics 1 Day 14 + Microbiome
Comparison 2.Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics Only
Comparison 3.Probiotics 2 Day 0 vs Probiotics 2 Day 15 + Microbiome
Comparison 4.Probiotics 2 Day 0 vs Day 15 Microbiome Only
Comparison 5.Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics Only
Comparison 6.Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome Only
 
 

XI. Analysis - Heatmap Profile

 

Species vs Sample Abundance Heatmap for All Samples

 
 
 

Heatmaps for Individual Comparisons

 
A) Two-way clustering - clustered on both columns (Samples) and rows (organism)
Comparison No.Comparison NameFamily LevelGenus LevelSpecies Level
Comparison 1Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 2Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 3Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 4Probiotics 2 Day 0 vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
Comparison 5Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 6Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
 
 
B) One-way clustering - clustered on rows (organism) only
Comparison No.Comparison NameFamily LevelGenus LevelSpecies Level
Comparison 1Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 2Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 3Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 4Probiotics 2 Day 0 vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
Comparison 5Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 6Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
 
 
C) No clustering
Comparison No.Comparison NameFamily LevelGenus LevelSpecies Level
Comparison 1Probiotics 1 Day 0 vs Probiotics 1 Day 14 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 2Probiotics 1 Day 0 vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 3Probiotics 2 Day 0 vs Probiotics 2 Day 15 + MicrobiomePDFSVGPDFSVGPDFSVG
Comparison 4Probiotics 2 Day 0 vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
Comparison 5Probiotics 1 Day 14 + Microbiome vs Probiotics 1 Day 14 Probiotics OnlyPDFSVGPDFSVGPDFSVG
Comparison 6Probiotics 2 Day 15 + Microbiome vs Day 15 Microbiome OnlyPDFSVGPDFSVGPDFSVG
 
 

XII. Analysis - Network Association

To analyze the co-occurrence or co-exclusion between microbial species among different samples, network correlation analysis tools are usually used for this purpose. However, microbiome count data are compositional. If count data are normalized to the total number of counts in the sample, the data become not independent and traditional statistical metrics (e.g., correlation) for the detection of specie-species relationships can lead to spurious results. In addition, sequencing-based studies typically measure hundreds of OTUs (species) on few samples; thus, inference of OTU-OTU association networks is severely under-powered. Here we use SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference), a statistical method for the inference of microbial ecological networks from amplicon sequencing datasets that addresses both of these issues (Kurtz et al., 2015). SPIEC-EASI combines data transformations developed for compositional data analysis with a graphical model inference framework that assumes the underlying ecological association network is sparse. SPIEC-EASI provides two algorithms for network inferencing – 1) Meinshausen-Bühlmann's neighborhood selection (MB method) and inverse covariance selection (GLASSO method, i.e., graphical least absolute shrinkage and selection operator). This is fundamentally distinct from SparCC, which essentially estimate pairwise correlations. In addition to these two methods, we provide the results of a third method - SparCC (Sparse Correlations for Compositional Data)(Friedman & Alm 2012), which is also a method for inferring correlations from compositional data. SparCC estimates the linear Pearson correlations between the log-transformed components.


References:

Kurtz ZD, Müller CL, Miraldi ER, Littman DR, Blaser MJ, Bonneau RA. Sparse and compositionally robust inference of microbial ecological networks. PLoS Comput Biol. 2015 May 7;11(5):e1004226. doi: 10.1371/journal.pcbi.1004226. PMID: 25950956; PMCID: PMC4423992.

Friedman J, Alm EJ. Inferring correlation networks from genomic survey data. PLoS Comput Biol. 2012;8(9):e1002687. doi: 10.1371/journal.pcbi.1002687. Epub 2012 Sep 20. PMID: 23028285; PMCID: PMC3447976.

 

SPIEC-EASI Network Inference by Neighborhood Selection (MB Method)

 
 

 

Association Network Inference by SparCC

 
 

 
 

XIII. Disclaimer

The results of this analysis are for research purpose only. They are not intended to diagnose, treat, cure, or prevent any disease. Forsyth and FOMC are not responsible for use of information provided in this report outside the research area.

 
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