A reader emails as shown below. The deep vein thrombosis (DVT) aspect interest me because it is typically associated with inherited coagulation defects (an interest that I have), although actual DVT has not been an interest (when I flew regularly, I was prescribed heparin and took it with piracetam (good for my specific defect).
On 15 July 2021 I uploaded my first Thryve sample to your website. Prior to that sample I had a few Ubiome samples from a few years ago. Thryve seems to detect many more bacteria than Ubiome. My results seem particularly unusual with numerous rare bacteria unfortunately. My main symptoms have always been constipation, food allergies and 2 episodes of DVT whereby I remain on anticoag therapy to avoid further recurrences. Bacteroides Vulgatus seems to be significantly high in all of my test results, both Ubiome and Thryve. I wonder whether this could be the ‘root cause’ given that the numbers of it are so much higher than any other bacteria.
What is known about DVT and Microbiome?
After a while searching PubMed, I finally found a 2020 article. Of special interest is Staphylococcus aureus which appears to have a significant role with ME/CFS [2016 Post] and may account for the high percentage of hypercoagulation seen there.
” Many known bacteria, such as Helicobacter pylori, Chlamydia pneumoniae, Mycoplasma pneumoniae, Haemophilus influenzae, Streptococcus pneumoniae, Staphylococcus aureus, and Escherichia coli, causing infections may increase the risk of thrombotic complications through platelet activation or may lead to an inflammatory reaction involving the fibrinolytic system.” Microbial Modulation of Coagulation Disorders in Venous Thromboembolism [2020]
A fuller list from the full article (Citing 2019) is, below
Staphylococcus aureus,
Streptococcus pyogenes
Pseudomonas aeruginosa,
Escherichia coli,
Klebsiella pneumoniae,
Chlamydia pneumoniae,
Helicobacter pylori,
Haemophilus influenzae
Looking at samples over three year, we have a strong candidate for causing DVT, Haemophilus parainfluenzae. It is consistently very high. Blank indicated no reported value.
Using the Nat.Library of Medicine filter for constipation and relaxing to include high and low 12%, we came up with only a very short list of candidates. Using Kaltoft-Moldrup bounds, nothing was selected.
One study found Haemophilus influenzae associated with GI issues [2004]
As for allergies, “Streptococcus pneumoniae, Haemophilus influenzae and Moraxella catarrhalis are often involved in respiratory infections associated with wheezing, but there is no evidence for their active role in asthma pathogenesis or exacerbation. ” [2009]
Running Advance Suggestions “as Is”
The key items selected reflects our analysis above:
KEGG Suggested Probiotics
The numbers are low, indicating no major issues. None of the suggestions are known to increase (or decrease) our focus. For supplements, it is similar
beta-alanine
NADH
Bottom Line
The primary question from the user appears to be answered. I would suggest fixing the Haemophilus parainfluenzae in isolation from the other two issues. Those two issues resolution will likely tend towards the use of probiotics — which are counter indicated with Haemophilus parainfluenzae. You have to prioritize issues and be careful not to send mix messages to the microbiome.
As always, review and consult with your medical professional before implementing
A reader sent me this email (actually another one did too). The issue was fixed but not in the obvious way:
BUG: Checking and “Add elected items…”
This was actually a coding error, the checkbox should not be there. To do what the user intended:
Now to pick bacteria for KEGG Vectors
Below is the revised page fixing the problem. Notice the RED RECTANGLE
Clicking this will take you to the page listing the bacteria for this item, example below
On this page the checkboxes work. You see all of the bacteria associated that you have and thus can target the specific one (likely Brochothrix thermosphacta that is running well above the top of the normal range) that is causing the KEGG Vector (Product, Enzyme, Module) to be of concern.
While working on the last long COVID post, another Long COVID person contacted me. He was definitely frustrated (in the same way that I have seen people with ME/CFS be frustrated over the last decades).
I’ve literally consulted with over 7 doctors (internist, hematologist, endocrinologist, ENT, GI specialist, cardiologist, & neurologist) over 3 weeks period and still have 4 consultations to go! All those doctors did is to request for more bloodwork and scans and then tell me that it’s all in my head (using smooth words) and send me home!
Long Haul Covid Patient
Recap on the Literature
The Microbiome and COVID have strong relationships. The microbiome prior to COVID impacts the severity. The severity of the symptoms correlates with the microbiome changes. This leads naturally to Long COVID being a continuation of this theme.
A new study used fecal samples were collected at least 38 days following diagnosis. By common belief, the patients are fully recovered — except their microbiome are not! What is the difference? It depends on where COVID presentation.
positive detection of SARS-COV-2 RNA from the respiratory tract, defined as respiratory positive (RP)
failure to detect in the respiratory tract, but had covid, is negative
They found changes in “13 phyla, 18 classes, 44 orders, 88 families, 234 genera, 1 phylum, 1 class, and 1 order were significant”. To put it simply, look at the changes below — they are NOT minor but major shifts!
My ongoing long haul symptoms: – Vertigo/lightheadedness. Can’t maintain proper balance and head feels heavy 🙁 I was walking into furniture in my home! It’s difficult to drive a car or even fast walk or go down the stairs. I feel as if my head is heavy and will fall. – Mood swings/anhedonia. No more feeling of happiness or pleasure. Low serotonin? Low dopamine? – Brain fog/memory loss/loss of concentration. I’m back to work and it has been extremely difficult to get tasks done. – Occasional blood in stool. Ulcers? Never had GI bleeding in my life! – Early evening fatigue. Feel extremely tired past 8pm. I also wake up super early (5-6am) and can’t go back to sleep. – Blurry vision during night. – Slight shakiness/tremors in hands and legs. Low iron? Low dopamine? – Low libido/sex drive despite getting morning erections.
In his own words
Pro Forma Analysis
I am going to do the same process as with the other Long COVID person. First, we have two lists of bacteria available, the number of studies are few but slowly increasing.
The earlier sample had just 7 out of range, the latest sample increased to 16, implying the microbiome is drifting further away from normal. Comparing samples, we found the following concerningly high on both samples:
Three items were out of range, one in common with the other Long COVID but in the opposite direction a-Galactosidase was high, and the other was low.
KEGG Bacteria Products Out of Range
The earlier sample had 9 out of range, the latest sample has 145!! Another indication of shifting further away from normal 🙁
KEGG Modules Out of Range
Just one in each sample, nothing in common.
KEGG Enzymes Out of Range
The earlier sample had 8 out of range, the latest sample has 139!! Another indication of shifting further away from normal 🙁
Kegg Suggestions
Where there are so many items with issues, I usually do not bother looking at them individually. Instead, I look at what can be computed to address them. Because every item is low, we do not need to look at trying to reduce anything — just add,
KEGG Suggested Probiotics
This is done by seeking out probiotic bacteria producing enzymes etc that are not being produced enough by existing bacteria. These can be viewed as a biological supplement producing items not available as regular supplements. The retail probiotics Sun Wave Pharma/Bio Sun Instant and Prescription Assist appear to be good choices (if available).
These are the same ones as with the other Long COVID person. What surprised me was that the earlier sample had a higher value list than the latest sample. This implies that the new overgrowth are providing the material to stablize the microbiome (unfortunately, in the current state of dysfunction)
A common mistake is to slip into a homeopathic thinking, “oh, I am taking some — that is enough”. In general I recommend starting low and increasing to the maximum dosages used in clinical studies. See this page for amounts used and links to the study or clinical trial.
KEGG Suggested Supplements
I tossed in the prior review for reference, two supplements are in common with all three samples.
Earlier Sample
Latest Sample
Other Person
beta-alanine iron L-Cysteine L-glutamine L-Lysine L-Proline Molybdenum NADH Vitamin B-12
beta-alanine D-Ribose iron L-Histidine L-Lysine L-Phenylalanine L-Tryptophan magnesium
We similarly identify supplements that are available retail (defined as being available on Amazon.com)
Suggestions
Using the last Long COVID post as a model, I jump directly to suggestions using the latest results. EXCEPT – I selected everything — including antibiotics and antivirals. No antibiotic made it high on either list.
12%ile and COVID-19
Remember, we are restricting to only those reported for active COVID and with the same direction of shift
12%ile and Long COVID
We have a much longer list of bacteria selected — which likely reflect that it is long COVID.
Quick Kaltoft-Moldrup suggestions
A very short list – this happen because we do not have studies reporting what modifies many of these bacteria.
The earlier sample had just a half dozen bacteria picked. The latest had moreEarlier had only a few (not even 20 Add Suggectios)
Reminder – The WHY for suggestions
On the suggestion line, you may see a 📚. Clicking it will show the source of the recommendation and why. Remember the more positive impact (by number of studies reporting the same), the greater the confidence shown. It is the confidence that it will shift in the desired direction. It is not which works better.
Putting Suggestions Together
With much bigger lists of bacteria, we also run the risk of more complexity and contrary suggestions [for example, bifidobacterium longum bb536 (probiotics) was a take, but bifidobacterium longum (probiotics) was an avoid]. I find myself giving the 12%ile and Long COVID Suggestions the greatest credence. It has some interesting
What seems to be reoccurring – make sure you look up dosages where available. Start low and work up to the maximum dosages used in clinical trials (after consulting with your medical professional)
My read of the data is to avoid all Lactobacillus and Bifidobacterium probiotics. You have above the median amounts of both of them 85%ile and 66%ile respectively – you do not need more, in fact, they likely contribute to the dysfunction! Miyarisan, Prescript Assist (or Equilibrium), aor / probiotic-3 and Sun Wave Pharma/Bio Sun Instant appears to be the best retail candidates for probiotics.
This is a MODEL not a PROTOCOL
This is directed to people reading this post and saying “I will do what is described”. What is the difference? A Protocol comes from clinical experience and is a defined set of actions that are repeated for each patient. A model is a theoretical way to generate candidate actions that may help. This is not a model for Long COVID patients, it is a model for one person’s microbiome. Every Long COVID patient will have a different microbiome and thus different candidate actions. You can see this by looking at the next post on Long COVID microbiome.
An analogy, Long COVID can be compared to a headache. There are at least 17 types of headaches. You may need to see a dentist (tooth issues), or take a antihistamine (allergy) or take oxygen or …. Details drives the treatment.
To help illustrate this, I have put the bacteria targeted from each of them below. You will note a lot is in common.
Female Prior Long COVID
Male This Post
Logical Treatment Options based on test results
Above you read about this user’s frustrations with the medical professionals. The root problem is that profession runs on encyclopedic knowledge (often photographic memory) that looks for a match and retrieves it as treatment. I term this as cook-book medicine. If there are no matches, then we typically see “deer in the headlights“, a deer with a MD.
Microbiome Prescription builds predictive modelling with a wide variety of suggestion options. Most of the options do not require a prescription, the user is in primary control. There is a full chain-of-evidence to the basis of the suggestions for people to review (yes, some people may need to upgrade their reading skills). The core facts are your microbiome.
Improvements can be objectively measured (instead of a vague “do you feel better”). Feeling better is important, but it should not be the sole criteria.
Questions and Answers
For many of these questions I went to the “See Impact..” with the specific sample.
Q:I’m currently on bovine Colostrum, is it ok to keep taking it?
A: Bovine Colostrum is not the database, the closest match is whey. It has no known impact – so you can assume it is safe.
Q:I’m eating boiled and cooled down potato every day as source of resistant starch. Is it ok?
A: Yes, That is actually the product that was used in most of the studies cited.
Q: Which nuts is best for my case (pistachio, hazelnut, cashew, brazillian nut, etc.)? I’ve been eating walnuts and almonds for several months.
A: I checked the types that we have data for:
Peanuts – no known impact — so you can assume it is safe.
Walnuts – positive impact
Generic nuts – no known impact — so you can assume it is safe.
Q:My vitamin D turned out high-normal. My 25-hydroxy vitamin D reading is 29.1 ng/ml & reference range (20 – 40). The suggestions included Vitamin D.
A: Vitamin D supplement are estimated to be a net negative benefit (same numbers as above). I looked at the citations used to make that decision and see a mixed impact on different items according to different studies. The results illustrates why suggestions may change from month to month. If new studies are added (which happens monthly) then the impact estimates change. My goal is deliver the best estimate from current studies – a moving target,
Whatever happens, I just want you to know that you have helped me a lot even before getting Covid-19… One word, thank you Ken 💐
REMINDER: These are suggestions generated by an artificial intelligence program. Before implementing, they should be reviewed by your medical professional.
The Microbiome and COVID have strong relationships. The microbiome prior to COVID impacts the severity. The severity of the symptoms correlates with the microbiome changes. This leads naturally to Long COVID being a continuation of this theme.
One study suggests that a core microbiota could predict COVID-19 severity in healthy subjects.27 Another study shows that the composition of the intestinal microbiota in the Chinese cohort is different between COVID-19 infected and un-infected controls, with symptom severity correlating with specific bacterial taxa.2
A new study used fecal samples were collected at least 38 days following diagnosis. By common belief, the patients are fully recovered — except their microbiome are not! What is the difference? It depends on how COVID presented.
positive detection of SARS-COV-2 RNA from the respiratory tract, defined as respiratory positive (RP)
failure to detect in the respiratory tract, but had covid, is negative
They found changes in “13 phyla, 18 classes, 44 orders, 88 families, 234 genera, 1 phylum, 1 class, and 1 order were significant”. To put it simply, look at the changes below — they are NOT minor but major shifts!
MRI showed pericarditis.Tachycardia stopped once I resumed H1 blockers
I had stopped out of paranoia when acutely ill, and B started antacid prescribed by cardiologist.
Severe constipation started at around April 2020. So we’re talking about over a year ago.
I had a break from constipation issue for about 6 months – november 2020 to may 2021.
Other ongoing symptoms are pain on the left side under the ribcage and internal vibrations, numbing of sensation “down there” (don’t feel much the need to go to the toilet,
Sex life is hampered too, nerve damage very likely according to myself and also gynecologist who thinks it’s postviral).
The entire first half of 2021 i adopted a diet based on green smoothies.
Other than 80% veg based smoothies and flaxseed i ate some veg stir fries and fresh salmon and some crisps (in small quantities!!! but every day a little pack).
Before covid i ate only crap, all sort of crap, so that this diet was for me a huge sacrifice.
But since covid junk food made me feel bad anyway, so slowly i accepted to change my diet.
I’m also taking a very long list of supplements. I had high cholesterol before covid, had it at 18 already despite being slim, but after covid it remained high and my sugar level got very high (not yet in the red). [This may no longer be true — the measurements were from a year ago]
Pro Forma Analysis
First, we have two lists of bacteria available, the number of studies are few but slowly increasing.
I see 34 Outliers using the Kaltoft-Moldrup ranges (which are usually bigger ranges than most testing labs use). This person mentions 50+ out of range from their lab. Well, that huge number is precisely what the study above reported. This is not a typical microbiome disruption.
“About 30% of COVID-19 patients also presented with cardiomyopathy (Arentz et al., 2020). 1α,25(OH)2D3 plays a crucial role in the prevention of cholesterol build-up in the arteries by preventing the conversion of macrophages to foam cells (Oh et al., 2009) and enhancing the cholesterol efflux from blood vessels (Yin et al., 2015)”
She has cholesterol build up and a form of cardiomyopathy (See What About Tachycardia-induced Cardiomyopathy?) So low Vitamin D, the literature and her lab results are in agreement. This suggest serious Vitamin D3 supplementation (see Clinical Therapeutic Dosages here, I would suggest at least 10,000 IU/day — to be discussed with her physician)
KEGG Bacteria Products Out of Range
Every single one of a list of 47 was low. Not enough being produced
KEGG Modules Out of Range
Nothing reported
KEGG Enzymes Out of Range
As above, a list of 48 items with every item being low
Kegg Suggestions
Where there are so many items with issues, I usually do not bother looking at them individually. Instead, I look at what can be computed to address them. Because every item is low, we do not need to look at trying to reduce anything — just add,
KEGG Suggested Probiotics
This is done by seeking out probiotic bacteria producing enzymes etc that are not being produced enough by existing bacteria. These can be viewed as a biological supplement producing items not available as regular supplements. The retail probiotics Sun Wave Pharma/Bio Sun Instant and Prescript Assist appear to be good choices (if available). The fall back by species are:
A common mistake is to slip into a homeopathic thinking, “oh, I am taking some — that is enough”. In general I recommend starting low and increasing to the maximum dosages used in clinical studies.
KEGG Suggested Supplements
We similarly identify supplements that are available retail (defined as being available on Amazon.com)
beta-alanine
D-Ribose
iron
L-Histidine
L-Lysine
L-Phenylalanine
L-Tryptophan
magnesium
Suggestions
One unique feature of Microbiome Prescription is that it not only identifies candidate issue areas, it also makes suggestions based solely on studies from the US National Library of Medicine. These suggests factor in side-effects on other bacteria. Every other site, has a blinkered thinking with their suggestions and do not consider side effects. Of course, there is one layer of side effects that only your MD can help — medical conditions you have. A suggestion may suggest peanut butter and you have an allergy to peanuts!
Checking against COVID and LONG COVID Profiles
The studies report on the US National Library of Medicine and are coded for averages being statistically high higher or lower than controls. This does not mean that the values are extremes. Statistically, this presents some challenges. I decided to explore how many matches happened with different definitions (Kaltoft-Moldrup ranges, top/bottom 3,6,9,12,15 %ile) for COVID and LONG COVID
Process
For those who wish to do it themselves, go to advance suggestions and do settings like below.
We will be change Bacteria Slection and Explicit Bacteria
Then click the suggestions at the bottom. On the suggestion page, click Bacteria Details to see the bacteria that are picked
The results are below by bacteria. As we reduce how extreme values that are needed to be deemed “high” or “low”, we have more and more matches. C – active COVID; L – Long Haul COVID / Post COVID
C – active COVID, L – Long COVID (i.e. 30+days after infection)
Suggestions – 3 approaches
After viewing the table above, I decided to do 3 approaches:
12%ile and COVID-19
12%ile and Long COVID
Quick Kaltoft-Moldrup suggestions
I expect all to be similar but with some differences. I will cut off suggestions around .425 to prevent information overload (which happens easily with the microbiome)
12%ile and COVID-19
The lack of a fine graduation of Confidence implies that we do not have that many applicable studies for the bacteria identified as important. Also this is what they had, not currently have.
12%ile and Long COVID
This has the graduation of Confidence values that I like to see.
Quick Kaltoft-Moldrup suggestions
Reminder – The WHY for suggestions
On the suggestion line, you may see a 📚. Clicking it will show the source of the recommendation and why. Remember the more positive impact (by number of studies reporting the same), the greater the confidence shown. It is the confidence that it will shift in the desired direction. It is not which works better. Microbiome Prescription strives to be open on the basis of it’s logic and allow easy verification by people who are interested.
Putting Suggestions together
Remember that the purpose of the site is to create prescriptions — suggestions to correct microbiome shifts. The suggestions attempt to be adjusted for side-effects on other bacteria. Labs suggestions are based on blinkered analysis, “You are too high in X, Z reduces X so we recommend it” – which often ignores the fact that X also increases Y which is also too high.
Suggestions are computed in two different ways with no overlap of source data (KEGG based on genes, and studies where substances were tested). Items that are on both sets of recommendations are definitely things to consider. There are items that may be only on KEGG suggestions because no one has done studies on them.
Remember, you can get opinions on over 3000 items in our database by going to the bottom of this list:
Iron was suggested by KEGG. I wanted to check it’s impact using the data from studies and was pleased with the result.
Iron was suggested by KEGG and appears to have a beneficial impact using studies data
I also confirmed magnesium was also a positive (and magnesium deficient, a negative)
This is a MODEL not a PROTOCOL
This is directed to people reading this post and saying “I will do what is described”. What is the difference? A Protocol comes from clinical experience and is a defined set of actions that are repeated for each patient. A model is a theoretical way to generate candidate actions that may help. This is not a model for Long COVID patients, it is a model for one person’s microbiome. Every Long COVID patient will have a different microbiome and thus different candidate actions. You can see this by looking at the next post on Long COVID microbiome.
An analogy, Long COVID can be compared to a headache. There are at least 17 types of headaches. You may need to see a dentist (tooth issues), or take a antihistamine (allergy) or take oxygen or …. Details drives the treatment.
Another post COVID person just contacted me, with their samples, so a second COVID post is also available Both this person’s sample, and the recent study confirmed my suspicion that Long COVID is a Post-Infection Syndrome. Post-Infection Syndromes are, IMHO, infection altered microbiomes that failed to return to normal.
Dialog Notes with User
Q: “I’ve got a huge issue/reservation with a part of the concept: the norm in the distribution of the data base might be far from normal. And even further, what is normal might not be optimal at all. What is normal reflects an average diet, but maybe an optimal diet would lead to an outlier sample, how do you address that issue….”
A: I do not use a bell curve, See this post for where I have evolved to. It’s based on Percentile and shape of distributions
Q: As a laywoman looking at the data my immediate focus went to methane-sibo. This matches my current issues and I’m surprised you didn’t mention it.
REMINDER: These are suggestions generated by an artificial intelligence program. Before implementing, they should be reviewed by your medical professional.
A reader had initial success from modifying the microbiome but it did not persist.
The reason I ended up at your website doing research into the connection microbiome and ME/CFS was that firstly I tried Miyarisan and it turned out to be one of the best things I ever tried, MY headaches and brain fog were early completely gone and I had a lot more energy. Unfortunately this wonder only lasted about 6 weeks till I overdid it and crashed and with that crash Miyarisan lost it’s effect on me.
The other thing was Nystatin, which I was given for the candida found in my gut last year and right on from the first pills I took, it gave me more energy ( so I doubt it had anything to to with the candida, but rather must have changed something else in my gut for the better). This lasted about 10 weeks and then pooped out and was not reproducible.
But these two times that I felt I got energy because of some changes in my gut, were very rare in the way the they just generally provided a relief in all symptoms, as I was just overall feeling better and had more energy, but without crashing. Most of the times I have trouble, because I am easily overstimulated and most things that give me energy give me instant fatigue rebound, so Miyarisan and Nystatin really were different and made me try to work on my gut.
She attached her tests and summarized them as “As to my tests, I guess the most notable things are my low TH1(Interferon Gamma), my low glutathione, high TGF beta, my decreased SOD activity.”
Reminder that recovery is a journey
In an earlier youtube review of another ME/CFS patient, I used the graphic below
I used this model for my last flare and can be seen by the list of posts below on CFS Remission. Each report was associated with a new microbiome test and a change of supplements etc to address the changes that the prior changes caused.
At this point we get some very interesting results. First, the bacteria by themselves do not match any symptoms.
But when we go over to the KEGG components that the bacteria produces, we see the type of predictions that we would expect
Conclusion: She does not have the typical ME/CFS bacteria shifts but she has the typical jacked metabolites imbalance seen in people with ME/CFS. Same crime — different crime family!
Action Plan
At this point, we have identify major items of concern.
Hand Picked Suggestions
I am going to run it two ways — first with the extreme outliers shown above, then including Firmicutes (which I rarely do)
If your physician is willing to prescribe “off-label” also do alternating every two weeks between a PPI and atorvastatin (prescription). PPI is over the counter in some places and includes:
omeprazole (Prilosec, Prilosec OTC, Zegerid)
lansoprazole (Prevacid)
pantoprazole (Protonix)
rabeprazole (Aciphex)
esomeprazole (Nexium)
dexlansoprazole (Dexilant)
For items from the suggestions above, I would suggest going with handpicked suggestion list without firmicutes.
I would suggest an initial retest at 4 weeks or so, a full cycle of a PPI and atorvastatin, at the same time a cycle of alternating licorice and triphala. We want to see if this has caused a downward movement of the two species of concern.
I am a strong advocate on doing alternative pulses. It is what C. Jadin does for antibiotics (changing them every month) and I also have read several modelling studies that found rotation had better success than continuous. The english explanation is simple: for anything you may take — 90% of the bacteria may be killed and 10% survive (resistant). If you keep up with the same, then that 10% slowly regrows as resistant to whatever you are using. Changing between two things that are 90% effective (and different), then it becomes 99% killed and 1% survive.
As you have witnessed, 6 weeks with one item and then the resistors recovered your dysfunction, for another substance it lasted 10 weeks. We want to keep to 2 weeks on and then rotate.
I checked the parent taxa on these two, and I see Carthamus tinctorius L (Safflower) inhibits one of them – so using safflower oil may help. There is no simple parent for the other.
As always, consult with your medical professional before implementing.
The key for creating an upload is identifying the taxon and the percentage of bacteria for a taxon.
Example
A reader wanted to upload his results and the lab would not provide a suitable CSV file. What they had was a page like shown below
Example if a 3rd party report
The starting point is simple, hand copy the data to Excel or equivalent (in many cases you can just copy the page or report and paste into Excel
The next steps
Delete any lines that do not have a measurement
Copy the percentage (or compute it) into a new column.
For those familiar with excel I used these 3 formulas
C: =FIND(” “,A3)
D: =LEFT(A3,C3)
E: =SUBSTITUTE(MID(A3,C3,10),”%”,””) * 1
The result is partial success with a few errors like below
I forgot to delete the ND – none detectable
For those caused by compound names, I need to count the characters to the last space and update Column C (I cheated by counting from the end and using =LEN(A25)-6. We ended up with
Names and Numbers. Note we have a “o” which is not a ND, so we replace with 0.0001
Also “Unclassified” should be deleted.
The Long Lookup
The next stage is time consuming… looking up the taxon numbers for each bacteria. There are two sources:
Lookup on NCBI, i.e. https://www.ncbi.nlm.nih.gov/search/all/?term=lactobacillus
Alternatively use https://microbiomeprescription.com/Library/Lookup
Add a new column before the percentage and put the taxon numbers there.
Next copy rows E and F to a new worksheet (remember to paste as values) and save as CSV file
The file should look like below.
Now Insert your email address as the first line. resulting in:
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