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A Patient driven study

Discussion in 'General ME/CFS News' started by LHCTom, Jan 30, 2016.

  1. LHCTom


    I've been disgnosed with CFS/ME by 2 top West Coast doctors. I've investigated many aspects of my illness and have an interrest in finding a group of well defined CFS/ME patients who would like to get together and perform a microbiome study using ubiome.com. They are only able to detect bacteria with their 16s highthruput sequencing and not virus's nor parasites, fungi etc..


    But I have had the experience that the abtibiotic Bactrim dramatically pushes my arthritis-like pain into remission for some number of months. At first I thought this might be an indicator of an infection that was being supressed by the Bactrim. I have had other symptoms go into remission due to other abtibiotics over the years including Falgyl, Ceftin and others. But I have recently been exploring whether the antibiotic effect was via modifying and or supressing my gut microbiome bacteria. I'm currently pursuing avenues to investigate my guts role which included funding part of a CFS/ME study of 20 men and 20 women using the latest metabolomics tools. They identify about 700 chosen metabolites in human blood of CFS/ME patients and age matched controls. The results were stunning but clearly showed gut flora dysbiosis ( imbalance) combined with a permeable intestinal wall and significant allergic markers and macromolecules being leaked from the gut to the blood innapropriately.

    I'm in the process of both repeating the metabolomics after antibiotics have caused remmision and repeating my ubiome.com 16s gut sequencing to investigate the changes in my microbiome and try and correlate the 2. The beauty behind the umbiome.com sequencing is it can be done very inexpensively. I bought 5 kits for $399 or $79 per sequncing. So I can make changes in my diet or utilize antibiotics carefully to modify my symptoms and easily see what changes ocurred for $79 each time. I have learned to upload their Taxonomy JSON file and convert it to Excel and then use features like filtering to look at the the resolved species, genus, Family, Order, Class, Phylum, Kingdom.

    Its fairly easy to convert the JSON Taxonomy File to Excel here: https://json-csv.com/

    Once its in the Excel format its easy to look at what is in your gut. My step is I'm learning the bioinformatics language R which would allow me to analyze multiple files of mine or of mine and others. It provides all the statistical analysis and allows one to access most online biology databases.

    So I'm curious if anyone has already done the ubiome.com 16s sequencing or if I paid for it, would you give me access to the data for analyzing multiple CFS/ME patients.

    Just curious. To do simple study of 20 people would cost $399x5= about $2000. That's cheap and if there are statistical similarities bewteen patients, it could then be correlated with the metabolomics once its available to anyone.

    An example of the Taxonomy JSON File

    {"ubiome_bacteriacounts": [
    {"count": 70216, "count_norm": 1000000, "parent": 0, "tax_rank": "root", "tax_color": null, "avg": null, "taxon": 1, "tax_name": "root"},

    {"count": 70216, "count_norm": 1000000, "parent": 131567, "tax_rank": "superkingdom", "tax_color": null, "avg": null, "taxon": 2, "tax_name": "Bacteria"},

    {"count": 3191, "count_norm": 45445, "parent": 1760, "tax_rank": "subclass", "tax_color": null, "avg": null, "taxon": 84998, "tax_name": "Coriobacteridae"},

    {"count": 37, "count_norm": 526, "parent": 85005, "tax_rank": "family", "tax_color": null, "avg": null, "taxon": 2049, "tax_name": "Actinomycetaceae"},

    {"count": 64, "count_norm": 911, "parent": 216572, "tax_rank": "genus", "tax_color": null, "avg": null, "taxon": 459786, "tax_name": "Oscillibacter"},

    {"count": 26, "count_norm": 370, "parent": 206389, "tax_rank": "family", "tax_color": null, "avg": null, "taxon": 75787, "tax_name": "Rhodocyclaceae"},

    <cut out>

    {"count": 9429, "count_norm": 134285, "parent": 171551, "tax_rank": "genus", "tax_color": null, "avg": null, "taxon": 375288, "tax_name": "Parabacteroides"}, {"count": 34, "count_norm": 484, "parent": 186803, "tax_rank": "genus", "tax_color": null, "avg": null, "taxon": 437755,
    Thinktank and leela like this.
  2. Thinktank

    Thinktank Senior Member

    I've just received my results from Ubiome so i'm in.
    I also have results from Redlabs MSA test (PCR DNA) to compare.

    My results after 2 years of intravenous and oral antibiotics for lyme disease:

    Ubiome 8/1/2016:
    Bacteroidetes me: 42.77%
    Bacteroidetes group average: 36.65%

    Firmicutes me: 41.04%
    Firmicutes group average: 56.48%

    Verrucomicrobia me: 15.49%
    Verrucomicrobia group average: 2.07%

    Proteobacteria me: 0.48%
    Proteobacteria group average: 3.31%

    Actinobacteria me: 0.23%
    Actinobacteria group average: 2.48%

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