Biology subjects

Tripp, A. D.

Publications and source records attributed to Tripp, A. D..

9 recordsLinked to original sources

bioRxiv2026

Metagenome-scale Modeling to Assess Microbiome Metabolic Complementarity for Precision Microbiota Transplantation Therapies

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable, in part because existing computational models do not fully capture the metabolic compatibility between donor and recipient communities. Here, we present a metagenome-scale metabolic modeling framework that quantifies metabolic niche complementarity between donor and recipient microbiomes to predict transplantation outcomes. Using MICOM-derived community metabolic models, we show that donor taxa whose metabolic flux profiles are more dissimilar from the recipient community engraft at significantly higher rates in both murine and human FMT cohorts. In a human IBS trial, metabolic models accurately predicted post-FMT community composition via leave-one-out cross-validation and recapitulated disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to demonstrate a platform for personalized donor screening. This screen identified super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition, as quantified by a flux-derived ecological network balance index that strongly predicted engraftment potential. This framework provides a mechanistic, scalable tool for rational donor-recipient matching that could guide personalized microbiome-based therapies.

microbiology↗

bioRxiv2025

Phage-mediated lysis does not determine Cutibacterium acnes colonization on human skin

Despite Cutibacterium acnes being the most abundant and prevalent bacteria on human skin, only a single type of phage has been identified that infects this host. Here, we leverage this one-to-one system to systematically characterize how the phage-bacteria arms race shapes C. acnes evolution and community composition on individual people. Our analysis reveals a surprising lack of phage-mediated selection despite global prevalence of C. acnes phages. Analysis of anti-phage defense systems across 3,205 bacterial genomes revealed a limited, phylogenetically restricted defense repertoire under weak selective pressure to diversify or be maintained. Functional assays did not reveal alternative phage resistance mechanisms or fitness costs associated with defense gene carriage that could explain this limited immune arsenal. This lack of pressure to maintain phage resistance could not be explained by lack of phage colonization, as examination of 471 global human facial skin metagenomes demonstrated that even in samples with high virus-to-microbe ratio, phage-sensitive clades dominate on-person populations. Together, these findings indicate that phage pressure, while present, does not play a critical role in determining strain fitness and success within C. acnes populations on human skin. We propose that this observed weak phage-mediated selective pressure can be explained by the anatomy of skin: C. acnes growth is thought to occur at the bottom of pores, where exposure to phage may be limited by physical barriers. Together, this portrait of a static arms race provides a strong contrast with other microbial species in different ecosystems and expands understanding of phage-bacteria interactions in the human microbiome.

genomics↗

bioRxiv2025

Intraspecies associations from strain-rich metagenome samples

Genetically distinct strains of a species can vary widely in phenotype, reducing the utility of species-resolved microbiome measurements for detecting associations with health or disease. While metagenomics theoretically provides information on all strains in a sample, current strain-resolved analysis methods face a tradeoff: de novo genotyping approaches can detect novel strains but struggle when applied to strain-rich or low-coverage samples, while reference database methods work robustly across sample types but are insensitive to novel diversity. We present PHLAME, a method that bridges this divide by combining the advantages of reference-based approaches with novelty awareness. PHLAME explicitly defines clades at multiple phylogenetic levels and introduces a probabilistic, mutation-based, framework to accurately quantify novelty from the nearest reference. By applying PHLAME to publicly available human skin and vaginal metagenomes, we uncover previously undetected clade associations with coexisting species, geography, and host age. The ability to characterize intraspecies associations and dynamics in previously inaccessible environments will propel new mechanistic insights from accumulating metagenomic data.

microbiology↗

bioRxiv2024

Intraspecies warfare restricts strain coexistence in human skin microbiomes

Determining why only a fraction of encountered or applied strains engraft in a given persons microbiome is crucial for understanding and engineering these communities. Previous work has established that metabolic competition can restrict colonization success in vivo, but the relevance of bacterial warfare in preventing commensal engraftment has been less explored. Here, we demonstrate that intraspecies warfare presents a significant barrier to strain coexistence in the human skin microbiome by profiling 14,884 pairwise interactions between Staphylococcus epidermidis isolates cultured from eighteen people from six families. We find that intraspecies antagonisms are abundant, mechanistically diverse, independent of strain relatedness, and consistent with rapid evolution via horizontal gene transfer. Critically, these antagonisms are significantly depleted among strains residing on the same person relative to random assemblages, indicating a significant in vivo role. Together, our results emphasize that accounting for intraspecies warfare may be essential to the design of long-lasting probiotic therapeutics.

microbiology↗

bioRxiv2024

Highly-resolved within-species dynamics in the human facial skin microbiome

Adult human facial skin microbiomes are remarkably similar at the species-level, dominated by Cutibacterium acnes and Staphylococcus epidermidis, yet each person harbors a unique community of strains. Understanding how person-specific communities assemble is critical for designing microbiome-based therapies. Here, using 4,055 isolate genomes and 360 metagenomes, we reconstruct on-person evolutionary history to reveal on and between-person strain dynamics. We find that multiple cells are typically involved in transmission, indicating ample opportunity for migration. Despite this accessibility, family members share only some of their strains. S. epidermidis communities are dynamic, with each strain persisting for an average of only 2 years. C. acnes strains are more stable and have a higher colonization rate during the transition to an adult facial skin microbiome, suggesting this window could facilitate engraftment of therapeutic strains. These previously undetectable dynamics may influence the design of microbiome therapeutics and motivate the study of their effects on hosts.

microbiology↗

bioRxiv2021

Anatomy promotes neutral coexistence of strains in the human skin microbiome

What enables strains of the same species to coexist in a microbiome? Here, we investigate if host anatomy can explain strain co-residence of Cutibacterium acnes, the most abundant species on human skin. We reconstruct on-person evolution and migration using 947 C. acnes colony genomes acquired from 16 subjects, including from individual skin pores, and find that pores maintain diversity by limiting competition. Although strains with substantial fitness differences coexist within centimeter-scale regions, each pore is dominated by a single strain. Moreover, colonies from a pore typically have identical genomes. An absence of adaptive signatures suggests a genotype-independent source of low within-pore diversity. We therefore propose that pore anatomy imposes random single-cell bottlenecks during migration into pores and subsequently blocks new migrants; the resulting population fragmentation reduces competition and promotes coexistence. Our findings imply that therapeutic interventions involving pore-dwelling species should focus on removing resident populations over optimizing probiotic fitness.

microbiology↗

bioRxiv2020

The low complexity motif of cytoplasmic polyadenylation element binding protein 3 (CPEB3) is critical for the trafficking of its targets in neurons

Biomolecular condensates, membraneless organelles found throughout the cell, play critical roles in many aspects of cellular function. Ribonucleoprotein granules (RNPs), a type of biomolecular condensate found in neurons that are necessary for local protein synthesis and are involved in long-term potentiation (LTP). Several RNA-binding proteins present in RNPs are necessary for the synaptic plasticity involved in LTP and long-term memory. Most of these proteins possess low complexity motifs, allowing for increased promiscuity. We explore the role the low complexity motif plays for RNA binding protein cytoplasmic polyadenylation element binding protein 3 (CPEB3), a protein necessary for long-term memory persistence. We found that RNA binding and SUMOylation are necessary for CPEB3 localization to the P body, thereby having functional implications on translation. Here, we investigate the role of the low complexity motif of CPEB3 and find that it is necessary for P body localization and downstream targeting for local protein synthesis.

neuroscience↗

bioRxiv2020

Genome-wide Functional Characterization of Escherichia coli Promoters and Regulatory Elements Responsible for their Function.

Despite decades of intense genetic, biochemical, and evolutionary characterizations of bacterial promoters, we lack the ability to identify or predict transcriptional activities of promoters using primary sequence. Even in simple, well-characterized organisms such as E. coli there is little agreement on the number, location, and strength of promoters. We use a genomically-encoded massively parallel reporter assay to perform the first full characterization of autonomous promoter activity across the E. coli genome. We measure promoter activity of >300,000 sequences spanning the entire genome and map 2,228 promoters active in rich media. Surprisingly, 944 of these promoters were found within intragenic sequences and are associated with conciliatory sequence adaptations by both the protein-coding regions and overlapping RNAP binding sites. Furthermore, we perform a scanning mutagenesis of 2,057 promoters to uncover sequence elements regulating promoter activity, revealing 3,317 novel regulatory elements. Finally, we show that despite these large datasets and modern machine learning algorithms, predicting endogenous promoter activity from primary sequence is still challenging.

microbiology↗

bioRxiv2017

Systematic Dissection of Sequence Elements Controlling σ70 Promoters Using a Genomically-Encoded Multiplexed Reporter Assay in E. coli

Promoters are the key drivers of gene expression and are largely responsible for the regulation of cellular responses to time and environment. In E. coli, decades of studies have revealed most, if not all, of the sequence elements necessary to encode promoter function. Despite our knowledge of these motifs, it is still not possible to predict the strength and regulation of a promoter from primary sequence alone. Here we develop a novel multiplexed assay to study promoter function in E. coli by building a site-specific genomic recombination-mediated cassette exchange (RMCE) system that allows for the facile construction and testing of large libraries of genetic designs integrated into precise genomic locations. We build and test a library of 10,898 {sigma}70 promoter variants consisting of all combinations of a set of eight -35 elements, eight -10 elements, three UP elements, eight spacers, and eight backgrounds. We find that the -35 and -10 sequence elements can explain approximately 74% of the variance in promoter strength within our dataset using a simple log-linear statistical model. Simple neural network models explain greater than 95% of the variance in our dataset by capturing nonlinear interactions with the spacer, background, and UP elements.

molecular biology↗