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deeper genomic analysis revealed a complex symbiosis acquisition history in the beta-rhizobia that clearly separates the mimosoid and papilionoid nodulating groups

Recommended citation: De Meyer, S. E., Briscoe, L., Martinez-Hidalgo, P., Agapakis, C. M., de-los Santos, P. E., Seshadri, R., ... & Hirsch, A. M. (2016). Symbiotic Burkholderia species show diverse arrangements of nif/fix and nod genes and lack typical high-affinity cytochrome cbb3 oxidase genes. Molecular Plant-Microbe Interactions, 29(8), 609-619 https://doi.org/10.1094/MPMI-05-16-0091-R

SaVanT: a web-based tool for the sample-level visualization of molecular signatures in gene expression profiles

Published in BMC Genomics, 2017

Signature visualization of individual samples allows, for example, the identification of patient subcategories a priori on the basis of well-defined molecular signatures.

Recommended citation: Lopez, D., Montoya, D., Ambrose, M., Lam, L., Briscoe, L., Adams, C., ... & Pellegrini, M. (2017). SaVanT: a web-based tool for the sample-level visualization of molecular signatures in gene expression profiles. BMC genomics, 18(1), 824. https://doi.org/10.1186/s12864-017-4167-7

Whole genome analyses suggests that Burkholderia sensu lato contains two additional novel genera (Mycetohabitans gen. nov., and Trinickia gen. nov.): implications for the evolution of diazotrophy and nodulation in the Burkholderiaceae.

Published in Genes, 2018

The newly proposed combinations are Mycetohabitans endofungorum comb. nov., Mycetohabitansrhizoxinica comb. nov., Trinickia caryophylli comb. nov., Trinickiadabaoshanensis comb. nov., Trinickia soli comb. nov., and Trinickiasymbiotica comb. nov. Given that the division between the genera that comprise Burkholderia s.l. in terms of their lifestyles is often complex, differential characteristics of the genomes of these new combinations were investigated.

Recommended citation: Estrada-de los Santos, P., Palmer, M., Ch vez-Ramirez, B., Beukes, C., Steenkamp, E., Briscoe, L., ... & Arrabit, M. (2018). Whole genome analyses suggests that Burkholderia sensu lato contains two additional novel genera (Mycetohabitans gen. nov., and Trinickia gen. nov.): implications for the evolution of diazotrophy and nodulation in the Burkholderiaceae. Genes, 9(8), 389. https://doi.org/10.3390/genes9080389

FEAST: fast expectation-maximization for microbial source tracking

Published in Nature Methods, 2019

FEAST may provide insight into quantifying contamination, tracking the formation of developing microbial communities, as well as distinguishing and characterizing bacteria-related health conditions

Recommended citation: Shenhav, L., Thompson, M., Joseph, T. A., Briscoe, L., Furman, O., Bogumil, D., ... & Halperin, E. (2019). FEAST: fast expectation-maximization for microbial source tracking. Nature methods, 1. https://doi.org/10.1038/s41592-019-0431-x

Modeling the temporal dynamics of the gut microbial community in adults and infants

Published in PLoS Computational Biology, 2019

MTV-LMM can identify time-dependent microbes (i.e., microbes whose abundance can be predicted based on the previous microbial composition) in longitudinal studies, which can then be used to analyze the trajectory of the microbiome over time.

Recommended citation: Shenhav, L., Furman, O., Briscoe, L., Thompson, M., Silverman, J. D., Mizrahi, I., & Halperin, E. (2019). Modeling the temporal dynamics of the gut microbial community in adults and infants. PLOS Computational Biology, 15(6), e1006960. https://doi.org/10.1371/journal.pcbi.1006960

Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis

Published in Nature Communications, 2020

we provide a practical approach on selecting cost-effective designs for maximizing cell-type-specific eQTL power which is available in the form of a web tool.

Recommended citation: Mandric, I., Schwarz, T., Majumdar, A., Hou, K., Briscoe, L., Perez, R., ... & Halperin, E. (2020). Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis. Nature communications, 11(1), 1-9. https://doi.org/10.1038/s41467-020-19365-w

Correcting for Background Noise Improves Phenotype Prediction from Human Gut Microbiome Data

Published in Biorxiv, 2021

We show that application of the centered log-ratio transformation prior to correction with unsupervised approaches improves prediction accuracy for many phenotypes while simultaneously reducing variance due to unwanted sources of variation.

Recommended citation: Briscoe, L., Balliu, B., Sankararaman, S.,Halperin, E., & Garud, N. (2021). Correcting for Background Noise Improves Phenotype Prediction from Human Gut Microbiome Data. bioRxiv 2021.03.19.436199 (2021). doi:10.1101/2021.03.19.436199 https://doi.org/10.1101/2021.03.19.436199

The effect of gastric acid suppression on probiotic colonization in a double blinded randomized clinical trial

Published in Clinical Nutrition ESPEN, 2022

Probiotics contain living microorganisms consumed for their putative benefits on the intestinal microbiota and general health and a concept is emerging to use probiotic as a therapeutic intervention to reduce proton pump inhibitors (PPIs) negative effects, but data is lacking.

Recommended citation: Singh, G., Haileselassie, Y., Briscoe, L., Bai, L., Patel, A., Sanjines, E., ... Habtezion, A. (2022). The effect of gastric acid suppression on probiotic colonization in a double blinded randomized clinical trial.Clinical Nutrition ESPEN,47, 70-77. https://doi.org/10.1016/j.clnesp.2021.11.005

Evaluating supervised and unsupervised background noise correction in human gut microbiome data

Published in PLoS Computational Biology, 2022

The ability to predict human phenotypes and identify biomarkers of disease from metagenomic data is crucial for the development of therapeutics for microbiome-associated diseases. However, metagenomic data is commonly affected by technical variables unrelated to the phenotype of interest, such as sequencing protocol, which can make it difficult to predict phenotype and find biomarkers of disease. Supervised methods to correct for background noise, originally designed for gene expression and RNA-seq data, are commonly applied to microbiome data but may be limited because they cannot account for unmeasured sources of variation. Unsupervised approaches address this issue, but current methods are limited because they are ill-equipped to deal with the unique aspects of microbiome data, which is compositional, highly skewed, and sparse. We perform a comparative analysis of the ability of different denoising transformations in combination with supervised correction methods as well as an unsupervised principal component correction approach that is presently used in other domains but has not been applied to microbiome data to date. We find that the unsupervised principal component correction approach has comparable ability in reducing false discovery of biomarkers as the supervised approaches, with the added benefit of not needing to know the sources of variation apriori. However, in prediction tasks, it appears to only improve prediction when technical variables contribute to the majority of variance in the data. As new and larger metagenomic datasets become increasingly available, background noise correction will become essential for generating reproducible microbiome analyses.

Recommended citation: Briscoe, L., Balliu, B., Sankararaman, S., Halperin, E., & Garud, N. R. (2022). Evaluating supervised and unsupervised background noise correction in human gut microbiome data.PLoS computational biology,18(2), e1009838. https://doi.org/10.1371/journal.pcbi.1009838

SNV-FEAST: microbial source tracking with single nucleotide variants

Published in biorxiv, 2023

Elucidating the sources of a microbiome can provide insight into the ecological dynamics responsible for the formation of these communities. Source tracking approaches to date leverage species abundance information, however, single nucleotide variants (SNVs) may be more informative because of their high specificity to certain sources. To overcome the computational burden of utilizing all SNVs for a given sample, we introduce a novel method to identify signature SNVs for source tracking. We show that signature SNVs used as input into a previously designed source tracking algorithm, FEAST, can more accurately estimate contributions than species and provide novel insights, demonstrated in three case studies.

Recommended citation: Briscoe, L., Halperin, E., & Garud, N. R. (2023). Microbiome source tracking using single nucleotide variants.bioRxiv. https://doi.org/10.1101/2022.05.28.493810

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

Leah Briscoe

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Multilevel modeling and longitudinal data

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