Microbiomes and a glimpse to doctors becoming a small niche

Microbiomes, Gut and Spot the Salmonella

When I get up in the morning, I normally follow a path on my iPad through email, Facebook, LinkedIn, Twitter, Google+, Feedly (for my RSS feeds) and Downcast (to update my Podcasts for later listening). This morning, Kevin Kelly served up a comment on Google+ that piqued my interest, and that led to a long voyage of discovery. Much to my wifes disgust as I quoted gory details about digestive systems at the same time she was trying to eat her breakfast. He said:

There are 2 reasons this great Quantified Self experiment is so great. One, it shows how important your microbial ecosystem is. Two, it shows how significant DAILY genome sequencing will be.

He then gave a pointer to an article about Microbiomes here.

The Diet Journey

I’ve largely built models based on innocent attempts to lose weight, dating back to late 2000 when I tried the Atkins diet. That largely stalled after 3 weeks and one stone loss. Then fairly liberated in 2002 by a regime at my local gym, when I got introduced (as part of a six week program) to the website of Weight Loss Resources. This got me in the habit of recording my food intake and exercise very precisely, which translated branded foods and weights into daily intake of carbs, protein and fat. That gave me my calorie consumption and nutritional balance, and kept track alongside weekly weight readings. I’ve kept that data flowing now for over 12 years, which continues to this day.

Things i’ve learnt along the way are:

  • Weight loss is heavily dependent on me consuming less calories than my Basal Metabolic Rate (BMR), and at the same time keeping energy deduced from carbs, protein and fat at a specific balance (50% from Carbs, 20% Protein, 30% fat)
  • 1g of protein is circa 4.0 Kcals, 1g of carbs around 3.75 Kcals, and fat around 9.0 Kcals.
  • Muscle weighs 2x as much as fat
  • There is a current fixation at gyms with upping your muscle content at first, nominally to increase your energy burn rate (even at rest)
  • The digestive system is largely first in, first out; protein is largely processed in acidic conditions, and carbs later down the path in alkaline equivalents. Fat is used as part of both processes.
  • There are a wide variety of symbiotic (opposite of parasite!) organisms that assist the digestive process from beginning to end
  • Weight loss is both heat and exhaust. Probably other forms of radiation too, given we are all like a light bulb in the infrared spectrum (I always wonder how the SAS manage to deploy small teams in foreign territory and remain, for the most part, undetected)

I’ve always harboured a suspicion that taking antibiotics have an indiscriminate bombing effect on the population of microbiomes there to assist you. Likewise the effect of what used to be my habit of drinking (very acidic) Diet Coke. But never seen anyone classify the variety and numbers of Microbiomes, and to track this over time.

The two subjects had the laboratory resources to examine samples of their own saliva, and their own stool samples, and map things over time. Fascinating to see what happened when one of them suffered Salmonella (the green in the above picture), and the other got “Delhi Belly” during a trip abroad.

The links around the article led to other articles in National Geographic, including one where the author reported much wider analysis of the Microbiomes found in 60 different peoples belly buttons (here) – he had a zoo of 58 different ones in his own. And then to another article where the existence of certain microbiome mutations in the bloodstream were an excellent leading indicator of the presence of cancerous tumours in the individual (here).

Further dips into various Wikipedia articles cited examples of microbiome populations showing up in people suffering from various dilapidating illnesses such as ME, Fibromyalgia and Lyme disease, in some instances having a direct effect on driving imbalances to cause depression. Separately, that what you ate often had quite an effect in altering the relative sizes of parts of the Microbiome population in short order.

There was another article that suggested new research was going to study the Microbiome Zoo present in people’s armpits, but I thought that an appropriate time to do an exit stage left on my reading. Ugh.

Brain starts to wander again

Later on, I reflected for a while on how I could supply some skills i’ve got to build up data resources – at least should suitable sensors be able to measure, sample and sequence microbiomes systematically every day. I have the mobile phone programming, NoSQL database deployment and analytics skills. But what if we had sensors that everyone could have on them 24/7 that could track the microbiome zoo that is you (internally – and I guess externally too)? Load the data resources centrally, and I suspect the Wardley Map of what is currently the NHS would change fundamentally.

I also suspect that age-old Chinese Medicine will demonstrate it’s positive effects on further analysis. It was about the only thing that solved my wifes psoriasis on her hands and feet; she was told about the need to balance yin/yan and remove heat put things back to normal, which was achieved by consumption of various herbs and vegetation. It would have been fascinating to see how the profile of her microbiomes changed during that process.

Sensors

I guess the missing piece is the ability to have sensors that can help both identify and count types microbiomes on a continuous basis. It looks like a laboratory job at the moment. I wonder if there are other characteristics or conditions that could short cut the process. Health apps about to appear from Apple and Google initiatives tend to be effective at monitoring steps, heart rate. There looks to be provision for sensing blood glucose levels non-invasively by shining infrared light on certain parts of the skin (inner elbow is a favourite); meanwhile Google have patented contact lenses that can measure glucose levels in the blood vessels in the wearers eyes.

The local gym has a Boditrax machine that fires an electrical up one foot and senses the signal received back in the other, and can relate body water, muscle and fat content. Not yet small enough for a mobile phone. And Withings produce scales that can report back weight to the users handset over bluetooth (I sometimes wonder if the jarring of the body as you tread could let a handset sensors deduce approximate weight, but that’s for another day).

So, the mission is to see if anyone can produce sensors (or an edible, communicating pill) that can effectively work, in concert with someones phone and the interwebs, to reliably count and identify biome mixes and to store these for future analysis, research or notification purposes. Current research appears to be in monitoring biome populations in:

  1. Oral Cavity
  2. Nasal
  3. Gastrointestinal Organs
  4. Vaginal
  5. Skin

each with their own challenges for providing a representative sample surface sufficient to be able to provide regular, consistent and accurate readings. If indeed we can miniaturize or simplify the lab process reliably. The real progress will come when we can do this and large populations can be sampled – and cross referenced with any medical conditions that become apparent in the data provider(s). Skin and the large intestine appear to have the most interesting microbiome profiles to look at.

Long term future

The end result – if done thoroughly – is that the skills and error rates of GP provided treatment would become largely relegated, just as it was for farm workers in the 19th century (which went from 98% of the population working the land to less than 2% within 100 years).

With that, I think Kevin Kelly is 100% correct in his assessment – that the article shows how significant DAILY genome sequencing will be. So, what do we need to do to automate the process, and make the fruits of its discoveries available to everyone 24/7?

Footnote: there look to be many people attempting to automate subsets of the DNA/RNA identification process. One example highlighted by MIT Review today being this.

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