Environments that Induce Synthetic Microbial Ecosystems

Interactions between microbial species are sometimes mediated by the exchange of small molecules, secreted by one species and metabolized by another. Both one-way (commensal) and two-way (mutualistic) interactions may contribute to complex networks of interdependencies. Understanding these interactions constitutes an open challenge in microbial ecology, with applications ranging from the human microbiome to environmental sustainability. In parallel to natural communities, it is possible to explore interactions in artificial microbial ecosystems, e.g. pairs of genetically engineered mutualistic strains. Here we computationally generate artificial microbial ecosystems without re-engineering the microbes themselves, but rather by predicting their growth on appropriately designed media. We use genome-scale stoichiometric models of metabolism to identify media that can sustain growth for a pair of species, but fail to do so for one or both individual species, thereby inducing putative symbiotic interactions. We first tested our approach on two previously studied mutualistic pairs, and on a pair of highly curated model organisms, showing that our algorithms successfully recapitulate known interactions, robustly predict new ones, and provide novel insight on exchanged molecules. We then applied our method to all possible pairs of seven microbial species, and found that it is always possible to identify putative media that induce commensalism or mutualism. Our analysis also suggests that symbiotic interactions may arise more readily through environmental fluctuations than genetic modifications. We envision that our approach will help generate microbe-microbe interaction maps useful for understanding microbial consortia dynamics and evolution, and for exploring the full potential of natural metabolic pathways for metabolic engineering applications

Novel insights into RNAi off-target effects using C. elegans paralogs

<p>Abstract</p> <p>Background</p> <p>In the few years since its discovery, RNAi has turned into a very powerful tool for the study of gene function by allowing post-transcriptional gene silencing. The RNAi mechanism, which is based on the introduction of a double-stranded RNA (dsRNA) trigger whose sequence is similar to that of the targeted messenger RNA (mRNA), is subject to off-target cross-reaction.</p> <p>Results</p> <p>We use a novel strategy based on phenotypic analysis of paralogs and predict that, in <it>Caenorhabditis elegans</it>, off-target effects occur when an mRNA sequence shares more than 95% identity over 40 nucleotides with the dsRNA. Interestingly, our results suggest that the minimum length necessary of a high-similarity stretch between a dsRNA and its target in order to observe an efficient RNAi effect varies from 30 to 50 nucleotides rather than 22 nucleotides, which is the length of siRNAs in <it>C. elegans</it>.</p> <p>Conclusion</p> <p>Our predictive methods would improve the design of dsRNA and ultimately the use of RNAi as a therapeutic tool upon experimental verification.</p

Microbial diversity in individuals and their household contacts following typical antibiotic courses.

BackgroundAntibiotics are a mainstay of treatment for bacterial infections worldwide, yet the effects of typical antibiotic prescriptions on human indigenous microbiota have not been thoroughly evaluated. We examined the effects of the two most commonly prescribed antibiotics (amoxicillin and azithromycin) in the USA to discern whether short-term antibiotic courses may have prolonged effects on human microbiota.ResultsWe sampled the feces, saliva, and skin specimens from a cohort of unrelated, cohabitating individuals over 6 months. An individual in each household was given an antibiotic, and the other a placebo to discern antibiotic impacts on microbiota, as well as determine whether antibiotic use might reshape the microbiota of each household. We observed household-specific patterns of microbiota on each body surface, which persevered despite antibiotic perturbations. While the gut microbiota within an individual became more dissimilar over time, there was no evidence that the use of antibiotics accelerated this process when compared to household members. There was a significant change in microbiota diversity in the gut and mouth in response to antibiotics, but analogous patterns were not observed on the skin. Those who received 7 days of amoxicillin generally had greater reductions in diversity compared to those who received 3 days, in contrast to those who received azithromycin.ConclusionsAs few as 3 days of treatment with the most commonly prescribed antibiotics can result in sustained reductions in microbiota diversity, which could have implications for the maintenance of human health and resilience to disease

The Ability of Flux Balance Analysis to Predict Evolution of Central Metabolism Scales with the Initial Distance to the Optimum

The most powerful genome-scale framework to model metabolism, flux balance analysis (FBA), is an evolutionary optimality model. It hypothesizes selection upon a proposed optimality criterion in order to predict the set of internal fluxes that would maximize fitness. Here we present a direct test of the optimality assumption underlying FBA by comparing the central metabolic fluxes predicted by multiple criteria to changes measurable by a 13C-labeling method for experimentally-evolved strains. We considered datasets for three Escherichia coli evolution experiments that varied in their length, consistency of environment, and initial optimality. For ten populations that were evolved for 50,000 generations in glucose minimal medium, we observed modest changes in relative fluxes that led to small, but significant decreases in optimality and increased the distance to the predicted optimal flux distribution. In contrast, seven populations evolved on the poor substrate lactate for 900 generations collectively became more optimal and had flux distributions that moved toward predictions. For three pairs of central metabolic knockouts evolved on glucose for 600–800 generations, there was a balance between cases where optimality and flux patterns moved toward or away from FBA predictions. Despite this variation in predictability of changes in central metabolism, two generalities emerged. First, improved growth largely derived from evolved increases in the rate of substrate use. Second, FBA predictions bore out well for the two experiments initiated with ancestors with relatively sub-optimal yield, whereas those begun already quite optimal tended to move somewhat away from predictions. These findings suggest that the tradeoff between rate and yield is surprisingly modest. The observed positive correlation between rate and yield when adaptation initiated further from the optimum resulted in the ability of FBA to use stoichiometric constraints to predict the evolution of metabolism despite selection for rate

Geophysical evidence for the evolution of the California Inner Continental Borderland as a metamorphic core complex

Author Posting. © American Geophysical Union, 2000. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Solid Earth 105 (2000): 5835-5857, doi:10.1029/1999JB900318.We use new seismic and gravity data collected during the 1994 Los Angeles Region Seismic Experiment (LARSE) to discuss the origin of the California Inner Continental Borderland (ICB) as an extended terrain possibly in a metamorphic core complex mode. The data provide detailed crustal structure of the Borderland and its transition to mainland southern California. Using tomographic inversion as well as traditional forward ray tracing to model the wide-angle seismic data, we find little or no sediments, low (#6.6 km/s) P wave velocity extending down to the crust-mantle boundary, and a thin crust (19 to 23 km thick). Coincident multichannel seismic reflection data show a reflective lower crust under Catalina Ridge. Contrary to other parts of coastal California, we do not find evidence for an underplated fossil oceanic layer at the base of the crust. Coincident gravity data suggest an abrupt increase in crustal thickness under the shelf edge, which represents the transition to the western Transverse Ranges. On the shelf the Palos Verdes Fault merges downward into a landward dipping surface which separates “basement” from low-velocity sediments, but interpretation of this surface as a detachment fault is inconclusive. The seismic velocity structure is interpreted to represent Catalina Schist rocks extending from top to bottom of the crust. This interpretation is compatible with a model for the origin of the ICB as an autochthonous formerly hot highly extended region that was filled with the exhumed metamorphic rocks. The basin and ridge topography and the protracted volcanism probably represent continued extension as a wide rift until ;13 m.y. ago. Subduction of the young and hot Monterey and Arguello microplates under the Continental Borderland, followed by rotation and translation of the western Transverse Ranges, may have provided the necessary thermomechanical conditions for this extension and crustal inflow.The LARSE experiment was funded by NSF EAR-9416774, the U.S. Geological Survey’s Earthquake Hazards and Coastal and Marine Programs, and by the Southern California Earthquake Center (SCEC)

Paleogene geochronology: An integrated approach

Geochronology is the conceptual division of continuous time as measured (geochronometry) by the progression in an ordinal series of events. This is best achieved by an approach which integrates four independent data sets: magnetostratigraphy, seafloor spreading magnetic lineation patterns, biostratigraphy, and isotopic ages. This integrated approach results in an ordinal framework which can measure time with greater resolution, though perhaps less accuracy, than a radiometric approach alone. A comparative analysis of two recently proposed Paleogene geochronologic time scales is presented

Results of 1992 seismic reflection experiment in Lake Baikal

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95684/1/eost9857.pd

Intrinsic Disorder Is a Common Feature of Hub Proteins from Four Eukaryotic Interactomes

Recent proteome-wide screening approaches have provided a wealth of information about interacting proteins in various organisms. To test for a potential association between protein connectivity and the amount of predicted structural disorder, the disorder propensities of proteins with various numbers of interacting partners from four eukaryotic organisms (Caenorhabditis elegans, Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens) were investigated. The results of PONDR VL-XT disorder analysis show that for all four studied organisms, hub proteins, defined here as those that interact with ≥10 partners, are significantly more disordered than end proteins, defined here as those that interact with just one partner. The proportion of predicted disordered residues, the average disorder score, and the number of predicted disordered regions of various lengths were higher overall in hubs than in ends. A binary classification of hubs and ends into ordered and disordered subclasses using the consensus prediction method showed a significant enrichment of wholly disordered proteins and a significant depletion of wholly ordered proteins in hubs relative to ends in worm, fly, and human. The functional annotation of yeast hubs and ends using GO categories and the correlation of these annotations with disorder predictions demonstrate that proteins with regulation, transcription, and development annotations are enriched in disorder, whereas proteins with catalytic activity, transport, and membrane localization annotations are depleted in disorder. The results of this study demonstrate that intrinsic structural disorder is a distinctive and common characteristic of eukaryotic hub proteins, and that disorder may serve as a determinant of protein interactivity

Comment on "Tectonic Rotations in Extensional Regimes and Their Paleomagnetic Consequences for Ocean Basalts" by Kenneth L. Verosub and Eldridge M. Moores

One of the more intriguing results from palcomagnetic studies of Deep Sea Drilling Project (DSDP) basalts is that a surprisingly large number of samples have inclinations that deviate significantly from expected values. Vetosub and Moores [1981] sought to account for what appear to be systematic departures of mean inclination at several DSDP basement sites in terms of tectonic rotations along listtic normal faults. Such rotations, about horizontal axes perpendicular to the extension direction and typically amounting to 30ø-50 ø but as large as 70 ø to 90 ø, were suggested to be characteristic of an extensional tectonic regime such as near an ocean spreading ridge system. There is a clear implication that large tectonic rotations are a characteristic process associated with ocean crust formation