Intraspecies warfare restricts strain coexistence in human skin microbiomes.

Determining why only a fraction of encountered or applied bacterial strains engraft in a given person's microbiome is crucial for understanding and engineering these communities1. Previous work has established that metabolism can determine colonization success in vivo2-4, but relevance of bacterial warfare in preventing engraftment has been less explored. Here, we demonstrate that intraspecies warfare presents a significant barrier to strain transmission in the skin microbiome by profiling 14,884 pairwise interactions between Staphylococcus epidermidis cultured from eighteen human subjects from six families. We find that intraspecies antagonisms are abundant; these interactions are mechanistically diverse, independent of the relatedness between strains, and consistent with rapid evolution via horizontal gene transfer. Ability to antagonize more strains is associated with reaching a higher fraction of the on-person S. epidermidis community. Moreover, antagonisms are significantly depleted among strains residing on the same person relative to random assemblages. Two notable exceptions, in which bacteria evolved to become sensitive to antimicrobials found on the same host, are explained by mutations that provide phage resistance, contextualizing the importance of warfare among other lethal selective pressures. Taken together, our results emphasize that accounting for intraspecies bacterial warfare is essential to the design of long-lasting probiotic therapeutics.

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

Human facial skin microbiomes (FSMs) on adults are dominated by just two bacterial species, Cutibacterium acnes and Staphylococcus epidermidis. Underlying this apparent simplicity, each FSM harbors multiple strains of both species whose assembly dynamics on individuals are unknown. Here, we use 4,055 isolate genomes and 360 metagenomes to trace the dynamics of strains on individuals and their transmission. Strains are shared amongst family members of all ages, but each individual harbors unique strain consortia. Strain stability changes upon formation of the adult-type FSM: S. epidermidis lineage turnover slows, and the rate of C. acnes colonization increases before stabilizing, suggesting this transitional window could facilitate engraftment of therapeutic strains. Our work reveals previously undetectable community dynamics and informs the design of therapeutic interventions.

Enhancing nutritional niche and host defenses by modifying the gut microbiome.

The gut microbiome is essential for processing complex food compounds and synthesizing nutrients that the host cannot digest or produce, respectively. New model systems are needed to study how the metabolic capacity provided by the gut microbiome impacts the nutritional status of the host, and to explore possibilities for altering host metabolic capacity via the microbiome. Here, we colonized the nematode Caenorhabditis elegans gut with cellulolytic bacteria that enabled C. elegans to utilize cellulose, an otherwise indigestible substrate, as a carbon source. Cellulolytic bacteria as a community component in the worm gut can also support additional bacterial species with specialized roles, which we demonstrate by using Lactobacillus plantarum to protect C. elegans against Salmonella enterica infection. This work shows that engineered microbiome communities can be used to endow host organisms with novel functions, such as the ability to utilize alternate nutrient sources or to better fight pathogenic bacteria.

Environmental fluctuations reshape an unexpected diversity-disturbance relationship in a microbial community.

Environmental disturbances have long been theorized to play a significant role in shaping the diversity and composition of ecosystems. However, an inability to specify the characteristics of a disturbance experimentally has produced an inconsistent picture of diversity-disturbance relationships (DDRs). Here, using a high-throughput programmable culture system, we subjected a soil-derived bacterial community to dilution disturbance profiles with different intensities (mean dilution rates), applied either constantly or with fluctuations of different frequencies. We observed an unexpected U-shaped relationship between community diversity and disturbance intensity in the absence of fluctuations. Adding fluctuations increased community diversity and erased the U-shape. All our results are well-captured by a Monod consumer resource model, which also explains how U-shaped DDRs emerge via a novel 'niche flip' mechanism. Broadly, our combined experimental and modeling framework demonstrates how distinct features of an environmental disturbance can interact in complex ways to govern ecosystem assembly and offers strategies for reshaping the composition of microbiomes.

A Semi-Quantitative Isothermal Diagnostic Assay Utilizing Competitive Amplification.

Quantitative diagnostics that are rapid, inexpensive, sensitive, robust, and field-deployable are needed to contain the spread of infectious diseases and inform treatment strategies. While current gold-standard techniques are highly sensitive and quantitative, they are slow and require expensive equipment. Conversely, current rapid field-deployable assays available provide essentially binary information about the presence of the target analyte, not a quantitative measure of concentration. Here, we report the development of a molecular diagnostic test [quantitative recombinase polymerase amplification (qRPA)] that utilizes competitive amplification during a recombinase polymerase amplification (RPA) assay to provide semi-quantitative information on a target nucleic acid. We demonstrate that qRPA can quantify DNA, RNA, and viral titers in HIV and COVID-19 patient samples and that it is more robust to environmental perturbations than traditional RPA. These features make qRPA potentially useful for at-home testing to monitor the progress of viral infections or other diseases.

Barcoded microbial system for high-resolution object provenance.

Determining where an object has been is a fundamental challenge for human health, commerce, and food safety. Location-specific microbes in principle offer a cheap and sensitive way to determine object provenance. We created a synthetic, scalable microbial spore system that identifies object provenance in under 1 hour at meter-scale resolution and near single-spore sensitivity and can be safely introduced into and recovered from the environment. This system solves the key challenges in object provenance: persistence in the environment, scalability, rapid and facile decoding, and biocontainment. Our system is compatible with SHERLOCK, a Cas13a RNA-guided nucleic acid detection assay, facilitating its implementation in a wide range of applications.

Sphingomonas solaris sp. nov., isolated from a solar panel in Boston, Massachusetts.

Solar panel surfaces, although subjected to a range of extreme environmental conditions, are inhabited by a diverse microbial community adapted to solar radiation, desiccation and temperature fluctuations. This is the first time a new bacterial species has been isolated from this environment. Strain R4DWNT belongs to the genus Sphingomonas and was isolated from a solar panel surface in Boston, MA, USA. Strain R4DWNT is a Gram-negative, non-motile and rod-shaped bacteria that tested positive for oxidase and catalase and forms round-shaped, shiny and orange-coloured colonies. It is mesophilic, neutrophilic and non-halophilic, and presents a more stenotrophic metabolism than its closest neighbours. The major fatty acids in this strain are C18:1ω7c/C18:1ω6c, C16:1ω7c/C16:1ω6c, C14:0 2OH and C16:0. Comparison of 16S rRNA gene sequences revealed that the closest type strains to R4DWNT are Sphingomonas fennica, Sphingomonas formosensis, Sphingomonas prati, Sphingomonas montana and Sphingomonas oleivorans with 96.3, 96.1, 96.0, 95.9 and 95.7 % pairwise similarity, respectively. The genomic G+C content of R4DWNT is 67.9 mol%. Based on these characteristics, strain R4DWNT represents a novel species of the genus Sphingomonas for which the name Sphingomonas solaris sp. nov. is proposed with the type strain R4DWNT (=CECT 9811T=LMG 31344T).

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER.

Continuous culture methods enable cells to be grown under quantitatively controlled environmental conditions, and are thus broadly useful for measuring fitness phenotypes and improving our understanding of how genotypes are shaped by selection. Extensive recent efforts to develop and apply niche continuous culture devices have revealed the benefits of conducting new forms of cell culture control. This includes defining custom selection pressures and increasing throughput for studies ranging from long-term experimental evolution to genome-wide library selections and synthetic gene circuit characterization. The eVOLVER platform was recently developed to meet this growing demand: a continuous culture platform with a high degree of scalability, flexibility, and automation. eVOLVER provides a single standardizing platform that can be (re)-configured and scaled with minimal effort to perform many different types of high-throughput or multi-dimensional growth selection experiments. Here, a protocol is presented to provide users of the eVOLVER framework a description for configuring the system to conduct a custom, large-scale continuous growth experiment. Specifically, the protocol guides users on how to program the system to multiplex two selection pressures - temperature and osmolarity - across many eVOLVER vials in order to quantify fitness landscapes of Saccharomyces cerevisiae mutants at fine resolution. We show how the device can be configured both programmatically, through its open-source web-based software, and physically, by arranging fluidic and hardware layouts. The process of physically setting up the device, programming the culture routine, monitoring and interacting with the experiment in real-time over the internet, sampling vials for subsequent offline analysis, and post experiment data analysis are detailed. This should serve as a starting point for researchers across diverse disciplines to apply eVOLVER in the design of their own complex and high-throughput cell growth experiments to study and manipulate biological systems.

Precise, automated control of conditions for high-throughput growth of yeast and bacteria with eVOLVER.

Precise control over microbial cell growth conditions could enable detection of minute phenotypic changes, which would improve our understanding of how genotypes are shaped by adaptive selection. Although automated cell-culture systems such as bioreactors offer strict control over liquid culture conditions, they often do not scale to high-throughput or require cumbersome redesign to alter growth conditions. We report the design and validation of eVOLVER, a scalable do-it-yourself (DIY) framework, which can be configured to carry out high-throughput growth experiments in molecular evolution, systems biology, and microbiology. High-throughput evolution of yeast populations grown at different densities reveals that eVOLVER can be applied to characterize adaptive niches. Growth selection on a genome-wide yeast knockout library, using temperatures varied over different timescales, finds strains sensitive to temperature changes or frequency of temperature change. Inspired by large-scale integration of electronics and microfluidics, we also demonstrate millifluidic multiplexing modules that enable multiplexed media routing, cleaning, vial-to-vial transfers and automated yeast mating.

A Genetic Tool to Track Protein Aggregates and Control Prion Inheritance.

Protein aggregation is a hallmark of many diseases but also underlies a wide range of positive cellular functions. This phenomenon has been difficult to study because of a lack of quantitative and high-throughput cellular tools. Here, we develop a synthetic genetic tool to sense and control protein aggregation. We apply the technology to yeast prions, developing sensors to track their aggregation states and employing prion fusions to encode synthetic memories in yeast cells. Utilizing high-throughput screens, we identify prion-curing mutants and engineer "anti-prion drives" that reverse the non-Mendelian inheritance pattern of prions and eliminate them from yeast populations. We extend our technology to yeast RNA-binding proteins (RBPs) by tracking their propensity to aggregate, searching for co-occurring aggregates, and uncovering a group of coalescing RBPs through screens enabled by our platform. Our work establishes a quantitative, high-throughput, and generalizable technology to study and control diverse protein aggregation processes in cells.

Coordinated regulation of acid resistance in Escherichia coli.

BACKGROUND: Enteric Escherichia coli survives the highly acidic environment of the stomach through multiple acid resistance (AR) mechanisms. The most effective system, AR2, decarboxylates externally-derived glutamate to remove cytoplasmic protons and excrete GABA. The first described system, AR1, does not require an external amino acid. Its mechanism has not been determined. The regulation of the multiple AR systems and their coordination with broader cellular metabolism has not been fully explored. RESULTS: We utilized a combination of ChIP-Seq and gene expression analysis to experimentally map the regulatory interactions of four TFs: nac, ntrC, ompR, and csiR. Our data identified all previously in vivo confirmed direct interactions and revealed several others previously inferred from gene expression data. Our data demonstrate that nac and csiR directly modulate AR, and leads to a regulatory network model in which all four TFs participate in coordinating acid resistance, glutamate metabolism, and nitrogen metabolism. This model predicts a novel mechanism for AR1 by which the decarboxylation enzymes of AR2 are used with internally derived glutamate. This hypothesis makes several testable predictions that we confirmed experimentally. CONCLUSIONS: Our data suggest that the regulatory network underlying AR is complex and deeply interconnected with the regulation of GABA and glutamate metabolism, nitrogen metabolism. These connections underlie and experimentally validated model of AR1 in which the decarboxylation enzymes of AR2 are used with internally derived glutamate.

Cellular Advantages to Signaling in a Digital World.

A newly revealed cellular strategy for modularizing function inspires engineers.