The Callahan laboratory develops quantitative and computational methods that improve the precision, accuracy and reproducibility of marker-gene and metagenomics sequencing methods, and implements those methods in open-source and actively supported software. The Callahan laboratory collaborates with other research groups to investigate the role of host-associated microbial communities in various health problems, with a particular focus on the role of the vaginal microbiome preterm birth. Marker-gene and metagenomic sequencing methods have revolutionized the study of the human microbiome, but the relative abundances of microbial taxa measured by these technologies are systematically distorted (or ?biased?) from the true relative abundances by experiment- and taxa-specific factors we do not understand. Over the next five years we intend to solve the problem of bias in metagenomic sequencing via a multi-part program that includes developing and validating an explanatory mechanistic model of bias in metagenomics experiments, quantifying the sensitivity of downstream analysis methods to metagenomics bias and creating new analysis methods unaffected by bias, and developing open-source software that allows researchers to correct biased marker-gene and metagenomics measurements to their true values. Recently, marker-gene and metagenomic sequencing methods have revealed that the vaginal microbiome of pregnant women can predict risk of preterm birth. However, disagreements between studies on the specific microbial signatures of preterm risk currently limit translation of these results. We intend to develop dense longitudinal profiles with sub-species taxonomic resolution of the vaginal microbiota in hundreds of pregnancies. We will define precise biomarkers of preterm risk as early in possible in pregnancy, and identify candidate taxa that could be targeted as part of therapeutic interventions to reduce the rate of preterm birth. We will synthesize the larger evidence base on this topic while controlling for the different metagenomics biases in different studies in order to identify reproducible biomarkers of preterm birth risk. We will integrate the longitudinal profiles of the vaginal microbiota with other omics measurements of host response to build evidence for potential causative pathways between disturbances in the vaginal microbiota and preterm birth. By developing computational and statistical methods that correct measurements of the microbiome to their true values, the Callahan laboratory seeks to improve the precision and accuracy with which the wider research community can characterize the human microbiome, thereby accelerating our understanding of microbiome- related health conditions and the development of microbiome therapies that improve human health.
DNA sequencing of whole microbial communities has revolutionized how researchers investigate the human microbiome, but progress towards understanding and treating microbiome-related health conditions is being slowed by systematic distortions present in the pictures produced by these DNA sequencing methods. This research will develop new computational methods to correct those distortions, allowing researchers to accurately define healthy and unhealthy microbiomes. A better understanding of the human microbiome will allow new diagnostics and therapies to be developed for microbiome-related health conditions, and this research will also develop such a diagnostic based on the vaginal microbiome to predict the risk of preterm birth early in pregnancy.
