Robin Herbert
PhD Candidate, UC Berkeley
ORCHID ID: 0000-0002-9174-1562

If you're looking for someone to use large-scale genetic data to understand how the ecology of the microbiome impacts it's function I would love to talk!

Publications include work in Microbial Cell Factories, Environmental Toxicology and Chemistry, Frontiers in Microbiology, Nature Reviews Microbiology, etc.

My long term goals are to use functional genomics, barcoding, and microbial ecology to learn how microorganisms cooperate, compete, and colonize their hosts!

In doing so I've developed skills in:
--High-throughput sequencing and analysis
--Strain engineering (RB-TnSeq, Cas9, VcDART)
--Plant-microbe / community interaction experiments
--Analysis of large datasets in R and Python

I've also genetically modified microorganisms for a variety of purposes, from the production of commodity chemicals to measuring the genes involved in colonization of the Sorghum rhizosphere using RB-TnSeq

Specifically, I developed BarTn7, a transposon-based DNA barcoding system which enables sub-species level tracking in model and non-model bacteria, which I used to draw some novel conclusions about Switchgrass root colonization (see thread below)

My work generally involves synthetic biology, microbial ecology, and plant-microbe interactions. I've worked with genetic and computational tools to track bacterial lineages and understand how bacteria adapt and interact during #microbiome assembly

And thank you to everyone in the Deutschbauer lab and Dr.s @tlowepower.bsky.social and Johan Leveau for the mentorship and advice! This was a great project to work on and I can’t wait to apply it to fun host-microbe interactions!

If you are interested in using BarTn7 for your own ecological or evolutionary work please feel free to reach out to [email protected]. We would love to collaborate!

Finally, we made “magic pools” of these BarTn7 vectors, which use a parts-based strategy to screen promoters and antibiotic markers in new species. These magic pools identified vector designs which enabled BarTn7 in bacteria which were recalcitrant to the original plasmids!

We then took steps to optimize the system by reversing cargo orientation to prevent host toxicity and combining transposon and transposase into one vector, improving conjugation efficiency by ~10X

BarTn7 was also more accurate than 16S sequencing at measuring community composition when different barcoded species were combined and outgrown in different media, and comparable to Illumina shotgun whole-genome sequencing (WGS) at a fraction of the cost

Next, we show that BarTn7 enables evolution experiments by identifying adaptive lineages (and the rise and fall of rare lineages). We detected selective sweeps linked to causal folA mutations in E. coli and Klebsiella treated with trimethoprim

Then we use BarTn7 to measure the colonization of Switchgrass roots by three plant-associated bacteria and find that lineage recruitment was species-specific: Pseudomonas (WCS417) often outcompeted lineages of the same species, while Paraburkholderia (Bfirm) colonized more evenly

First, we confirm that each lineage grows neutrally, showing population-level changes are due to drift or ecological dynamics rather than barcode bias

By chromosomally integrating DNA barcodes using the Tn7 transposon we created near-isogenic populations tagged with unique barcodes to we can track lineage behavior at the sub-species level

Populations of closely related bacteria interact in ways which change microbiome assembly, evolution, and host health/productivity, but can be hard to measure