21  Appendix

This is a parking place for content that should be incorporated into other parts of the book

21.1 Skin Microbiome and Attractiveness to Mosquitoes

Skin microbiome alters attractiveness to Anopheles mosquitoes > Staphylococcus 2 ASVs are four times as abundant in the highly-attractive compared to poorly-attractive group.

via Axios

21.2 Ticks and Alpha-Gal

see Ticks, Alpha-Gal, Neu5gc and more

The CDC warns about

Alpha-gal syndrome (AGS) is a serious, potentially life-threatening allergic condition. AGS is also called alpha-gal allergy, red meat allergy, or tick bite meat allergy.

does it have an association with microbes?

Figure 2: IgM and IgG antibodies are generated by continuous stimulation by the intestinal microbiome and probably also by food

21.3 Gut-Brain

Science Magazine

a new study reveals the gut has a much more direct connection to the brain through a neural circuit that allows it to transmit signals in mere seconds.

21.4 Paleo Humans

Natural products from reconstructed bacterial genomes of the Middle and Upper Paleolithic from a German team that > Now, a new study from an interdisciplinary team has taken important steps to understanding stone age bacteria by sequencing genomes recovered from ancient dental calculus. The hardened tartar preserved bacterial fragments on the teeth of 12 Neanderthals and 34 humans that had lived anywhere from 102,000 to 150 years ago. Formed from plaque, this calculus fossilized during these humans’ lifetime, trapping genetic fragments inside.

Discover Magazine on Bacterial DNA from ancient humans

21.5 Microbiome uniqueness

See https://pubmed.ncbi.nlm.nih.gov/30150716/

A Chinese study that found microbiome patterns that predict health in one province don’t work in another.

He et al. (2018)

He Y, Wu W, Zheng HM, Li P, McDonald D, Sheng HF, Chen MX, Chen ZH, Ji GY, Zheng ZD, Mujagond P, Chen XJ, Rong ZH, Chen P, Lyu LY, Wang X, Wu CB, Yu N, Xu YJ, Yin J, Raes J, Knight R, Ma WJ, Zhou HW. Regional variation limits applications of healthy gut microbiome reference ranges and disease models. Nat Med. 2018 Oct;24(10):1532-1535. doi: 10.1038/s41591-018-0164-x. Epub 2018 Aug 27. Erratum in: Nat Med. 2018 Sep 24;: PMID: 30150716.


see evernote

Wilmanski et al. (2021)

21.6 Methods

Greengenes2 unifies microbial data in a single reference tree > Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. By inserting sequences into a whole-genome phylogeny, we show that 16S rRNA and shotgun metagenomic data generated from the same samples agree in principal coordinates space, taxonomy and phenotype effect size when analyzed with the same tree. >

21.7 Mapping the Capacity of a Single Subject’s Microbiome to Metabolize Hundreds of Drugs

57 drugs that are transformed by the microbiome, with lots of variance from person to person.


Javdan et al. (2020)