The metabolic responses of bacteria to dynamic extracellular conditions drives not only the behavior of single species, but also entire communities of microbes. Over the last decade, genome-scale metabolic network reconstructions have assisted in our appreciation of important metabolic determinants of bacterial physiology. These network models have been a powerful force in understanding the metabolic capacity that species may utilize in order to succeed in an environment. Increasingly, an understanding of context-specific metabolism is critical for elucidating metabolic drivers of larger phenotypes and disease. However, previous approaches to use network models in concert with omics data to better characterize experimental systems have met challenges due to assumptions necessary by the various integration platforms or due to large input data requirements. With these challenges in mind, we developed RIPTiDe (Reaction Inclusion by Parsimony and Transcript Distribution) which uses both transcriptomic abundances and parsimony of overall flux to identify the most costeffective usage of metabolism that also best reflects the cell's investments into transcription. Additionally, in biological samples where it is difficult to quantify specific growth conditions, it becomes critical to develop methods that require lower amounts of user intervention in order to generate accurate metabolic predictions. Utilizing a metabolic network reconstruction for the model organism Escherichia coli str. K-12 substr. MG1655 (iJO1366), we found that RIPTiDe correctly identifies context-specific metabolic pathway activity without supervision or knowledge of specific media conditions. We also assessed the application of RIPTiDe to in vivo metatranscriptomic data where E. coli was present at high abundances, and found that our approach also effectively predicts metabolic behaviors of host-associated bacteria. In the setting of human health, understanding metabolic changes within bacteria in environments where growth substrate availability is difficult to quantify can have large downstream impacts on our ability to elucidate molecular drivers of disease-associated dysbiosis across the microbiota. Our results indicate that RIPTiDe may have potential to provide understanding of context-specific metabolism of bacteria within complex communities.
The altered Schaedler flora (ASF) is a model microbial community with both in vivo and in vitro relevance. Here we provide the first characterization of the ASF community in vitro, independent of a murine host. We compared the functional genetic content of the ASF to wild murine metagenomes and found that the ASF functionally represents wild microbiomes better than random consortia of similar taxonomic composition. We developed a chemically defined medium that supported growth of seven of the eight ASF members. To elucidate the metabolic capabilities of these ASF species—including potential for interactions such as cross-feeding—we performed a spent media screen and analyzed the results through dynamic growth measurements and non-targeted metabolic profiling. We found that cross-feeding is relatively rare (32 of 3570 possible cases), but is enriched between Clostridium ASF356 and Parabacteroides ASF519. We identified many cases of emergent metabolism (856 of 3570 possible cases). These data will inform efforts to understand ASF dynamics and spatial distribution in vivo, to design pre- and probiotics that modulate relative abundances of ASF members, and will be essential for validating computational models of ASF metabolism. Well-characterized, experimentally tractable microbial communities enable research that can translate into more effective microbiome-targeted therapies to improve human health.
Although tissue engineered skin substitutes have demonstrated some clinical success for the treatment of chronic wounds such as diabetic and venous ulcers, persistent graft take and stability remain concerns. Current bilayered skin substitutes lack the characteristic microtopography of the dermal-epidermal junction that gives skin enhanced mechanical stability and creates cellular microniches that differentially promote keratinocyte function to form skin appendages and enhance wound healing. We developed a novel micropatterned dermal-epidermal regeneration matrix (μDERM) which incorporates this complex topography and substantially enhances epidermal morphology. Here, we describe the use of this 3D in vitro culture model to systematically evaluate different topographical geometries, to determine their relationship to keratinocyte function. We identified three distinct keratinocyte functional niches: the proliferative niche (narrow geometries), the basement membrane protein synthesis niche (wide geometries) and the putative keratinocyte stem cell niche (narrow geometries and corners). Specifically, epidermal thickness and keratinocyte proliferation is significantly (p<0.05) increased in 50 and 100 μm channels while laminin-332 deposition is significantly (p<0.05) increased in 400 μm channels compared to flat controls. Additionally, β1brip63+ keratinocytes, putative keratinocyte stem cells, preferentially cluster in channel geometries (similar to clustering observed in native skin) compared to a random distribution on flats. This study identifies specific target geometries to enhance skin regeneration and graft performance. Furthermore, these results suggest the importance of μDERM microtopography in designing next generation skin substitutes. Finally, we anticipate that 3D organotypic cultures on μDERMS will provide a novel tissue engineered skin substitute for in vitro investigations of skin morphogenesis, wound healing and pathology.
We present a miniaturized plate reader for measuring optical density in 96-well plates. Our standalone reader fits in most incubators, environmental chambers, or biological containment suites, allowing users to leverage their existing laboratory infrastructure. The device contains no moving parts, allowing an entire 96-well plate to be read several times per second. We demonstrate how the fast sampling rate allows our reader to detect small changes in optical density, even when the device is placed in a shaking incubator. A wireless communication module allows remote monitoring of multiple devices in real time. These features allow easy assembly of multiple readers to create a scalable, accurate solution for high-throughput phenotypic screening.
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