Another review from my lab out this week, on analyzing gut microbiome data from global populations -- tackling computational challenges and providing practical frameworks and resources for the field

With Sabrina Arif, @richabdill.com, @samanthagraham.bsky.social

www.cell.com/trends/micro...

Interested in microbiome GWAS and heritability studies? Check out our new Review in Nature Reviews Genetics! We explore key findings, challenges, and future directions of the field.
rdcu.be/epoRR

@blekhman.bsky.social @sambhawa.bsky.social and Dr. Kelsey Johnson.

We wrote up the process we've developed for processing microbiome data in bulk! Workflow management tools are miraculous for processing a project with lots of samples, but when you have lots of *projects* too, as we do when pulling data from NCBI databases, it gets hard to juggle. #microbiomesky

Last week @richabdill.com and @samanthagraham.bsky.social's paper was featured on the cover of Cell!

The cover, portraying microbes on shelves shaped like a world map, was possible thanks to the amazing team of illustrators at SciStories ✏️🦠

These are challenging times for science, but I'm happy to share a bright moment: our work is on the cover of Cell today.

We built a compendium of human gut microbiomes integrating 168K worldwide samples, revealing patterns of microbiome variation across the globe

www.cell.com/cell/current...

Use the Human Microbiome Compendium data!

We made the data and code available, & created a website and R package to navigate the compendium. Links:

- Website: microbiomap.org

- Data: zenodo.org/records/1373...

- R package: blekhmanlab.github.io/MicroBioMap/

- Code: github.com/blekhmanlab/...

Thank you! Yes, we're planning on continuing to process new data on SRA and update the resource

Thanks to our many collaborators who made this possible! This has been a huge effort from our lab and others, and we couldn’t have done it without all who helped.

We hope this is a useful resource for the microbiome community. Links below!
Paper: www.cell.com/cell/fulltex...
Dataset: doi.org/10.5281/zeno...
Website: microbiomap.org
Code: github.com/blekhmanlab/...

Altogether, this dataset shows us how microbiomes differ throughout the world, and emphasizes the importance of more even sampling moving forward. We’re excited to continue learning from the compendium, and we plan to continue to process more samples to keep it up to date with the available data.

The method of DNA extraction also has a strong effect on microbiome composition. But we found that a sample’s geographic location has a bigger effect on its alpha diversity than amplicon choice or the use of bead beating, a common technique in DNA extraction.

In addition to biological differences between samples, there are technical factors that can affect microbiome composition. Does the region of the 16S gene that was sequenced affect our observed results? Yes! We found genera that were differentially abundant between amplicons.

And because microbiomes from these regions are so different, we were able to train one-vs-all random forest classifiers to successfully predict where a microbiome sample came from.

And specifically, we wanted to know what microbes were driving these large differences between world regions. We found that dozens of genera differ in abundance! Taxa like Bacteroides and Prevotella differ the most, but we found that every genus tested differed between at least two regions.

With sampling so unbalanced, are we missing a lot of information? To answer this, we wanted to see how much microbiomes differ between world regions. This big PCoA plot showed us that microbiomes from around the world have pretty drastic differences in composition.

We previously found that microbiome sampling is unevenly distributed throughout the world (journals.plos.org/plosbiology/...), and we wanted to quantify just how uneven it is. Over half of our samples come from Europe/N. America, seen in this map that’s distorted to show sampling imbalance.

There’s tons of publicly available microbiome data, but this comes from 100s of studies that were processed separately, so we can’t directly compare results. We wanted to leverage this wealth of data, so we reprocessed raw data from 482 studies–that’s 5.7 terabases of data from all over the world!

We’re thrilled that our first paper on the Human Microbiome Compendium, an integrated dataset of over 168,000 uniformly processed human gut microbiome samples, is officially out today in Cell! @richabdill.com @blekhman.bsky.social www.cell.com/cell/fulltex...

attempting to start posting on here as I (hopefully) wrap up my PhD in the next several months, both about science and my one true passion--taking pictures of peanut butter sandwiches on hikes