Biology subjects

Shou, W.

Publications and source records attributed to Shou, W..

26 records · Page 2Linked to original sources

bioRxiv2019

Disentangling strictly self-serving mutations from win-win mutations in a mutualistic microbial community

Mutualisms can be promoted by win-win mutations which directly benefit self (self-serving) and partner (partner-serving). Intuitively, partner-serving phenotype could be quantified as the benefit supply rate to partner by an individual. Here, we demonstrate the inadequacy of this thinking, and propose an alternative measure. Specifically, we evolved well-mixed mutualistic communities where two engineered yeast strains exchanged essential metabolites lysine and hypoxanthine. Among cells that consumed lysine and released hypoxanthine, a chromosome duplication mutation seemed win-win: it improved cells affinity for lysine, and increased hypoxanthine release rate per cell. However, increased release rate was due to increased cell size accompanied by increased lysine consumption per birth. Consequently this mutation is solely self-serving, since a fixed amount of intake lysine leads to an identical total hypoxanthine release rate - either by more numerous lower-releasing ancestors or fewer higher-releasing mutants. By extension, individuals with reduced benefit production rates may not be cheaters.

microbiology↗

bioRxiv2018

Rapid evolution of an overt metabolic defect restores balanced growth

In eukaryotes, conserved mechanisms ensure that cell growth is coordinated with nutrient availability. Overactive growth during nutrient limitation ("nutrient-growth dysregulation") can lead to rapid cell death. Here, we demonstrate that cells can adapt to nutrient-growth dysregulation by evolving major metabolic defects. Specifically, when yeast lysine auxotrophic mutant lys- encountered lysine limitation, an evolutionarily novel stress, cells suffered nutrient-growth dysregulation. A sub-population repeatedly evolved to lose the ability to synthesize organosulfurs (lys-orgS-). Organosulfurs, mainly glutathione and glutathione conjugates, were released by lys- cells during lysine limitation when growth was dysregulated, but not during glucose limitation when growth was regulated. Limiting organosulfurs conferred a frequency-dependent fitness advantage to lys-orgS- by eliciting a proper slow growth program including autophagy. Thus, nutrient-growth dysregulation is associated with rapid organosulfur release, which enables the selection of organosulfur auxotrophy to better tune cell growth to the metabolic environment. We speculate that evolutionarily novel stresses can trigger atypical release of certain metabolites, setting the stage for the evolution of new ecological interactions.

evolutionary biology↗

bioRxiv2018

Microbial coexistence through chemical-mediated interactions

Many microbial functions happen within communities of interacting species. Explaining how species with intrinsically disparate fitness can coexist is important for applications such as manipulating host-associated microbiota or engineering industrial communities. Previous coexistence studies have often neglected interaction mechanisms. Here, we formulate and experimentally constrain a model in which chemical mediators of microbial interactions (e.g. metabolites or waste-products) are explicitly incorporated. We construct many instances of coexistence by simulating community assembly through enrichment and ask how species interactions can explain coexistence. We show that growth-facilitating influences between members are favored in assembled communities. Among negative influences, self-restraint, such as production of self-inhibiting waste, contributes to coexistence, whereas inhibition of other species disrupts coexistence. Coexistence is also favored when interactions are mediated by depletable chemicals that get consumed or degraded, rather than by reusable chemicals that are unaffected by recipients. Our model creates null predictions for coexistence driven by chemical-mediated interactions.

ecology↗

bioRxiv2018

Resolving challenges in quantitative modeling of microbial community dynamics

Microbial communities can perform biochemical activities that monocultures cannot. Controlling communities requires an understanding of community dynamics. Here, we mathematically predict the growth rate of an engineered community consisting of two S. cerevisiae strains, each releasing a metabolite required and consumed by the partner. Initial model parameters were based on strain phenotypes measured in batch mono-cultures with zero or excess metabolite, and failed to quantitatively predict experimental results. To resolve model-experiment discrepancy, we chemically identified the correct exchanged metabolites, but this did not improve model performance. We then re-measured strain phenotypes in chemostats mimicking the metabolite-limited community environments, while mitigating or incorporating effects of rapid evolution. Almost all phenotypes we measured varied significantly with the metabolite environment. Once we used parameters measured in community-like chemostat environments, prediction agreed with experimental results. In summary, using a simplified community, we uncovered, and devised means to resolve, modeling challenges that are likely general.

microbiology↗

bioRxiv2018

Microscopy quantification of microbial birth and death dynamics

Microbes live in dynamic environments where nutrient concentrations fluctuate. Quantifying fitness (birth and death) in a wide range of environments is critical for understanding microbial evolution as well as ecological interactions where one species alters the fitness of another. Here, using high-throughput time-lapse microscopy, we have quantified how Saccharomyces cerevisiae mutants incapable of synthesizing an essential metabolite grow or die in various concentrations of the required metabolite. We establish that cells normally expressing fluorescent proteins lose fluorescence upon death and that the total fluorescence in an imaging frame is proportional to the number of live cells even when cells form multiple layers. We validate our microscopy approach of measuring birth and death rates using flow cytometry, cell counting, and chemostat culturing. For lysine-requiring cells, very low concentrations of lysine are not detectably consumed and do not support cell birth, but delay the onset of death phase and reduce the death rate. In contrast, in low hypoxanthine, hypoxanthine-requiring cells can produce new cells, yet also die faster than in the absence of hypoxanthine. For both strains, birth rates under various metabolite concentrations are better described by the sigmoidal-shaped Moser model than the well-known Monod model, while death rates depend on the metabolite concentration and can vary with time. Our work reveals how time-lapse microscopy can be used to discover non-intuitive microbial dynamics and to quantify growth rates in many environments.

microbiology↗

bioRxiv2018

Reducing compositional fluctuations facilitates artificial selection of microbial community function

Multi-species microbial communities often display functions - biochemical activities unattainable by member species alone, such as fighting pathogens. To improve community function, we can artificially select communities by growing \"Newborn\" communities over \"maturation time\" into \"Adult\" communities, and selecting highest-functioning Adults to \"reproduce\" by diluting each into multiple Newborns of the next cycle. Community selection has been attempted a few times on complex communities, often generating mixed results that are difficult to interpret. Here, we ask how costly community function may be improved via mutations and community selection. We simulate selection of two-species communities where Helpers digest Waste and generate Byproduct essential to Manufacturers; Manufacturers divert a fraction of their growth to make Product. Community function, the total Product in an \"Adult\", is sub-optimal even when both species have been pre-optimized as monocultures. If we dilute an Adult into Newborns by pipetting (a common experimental procedure), stochastic fluctuations in Newborn composition prevents community function from improving. Reducing fluctuations via cell sorting allows selection to work. Our conclusions hold regardless of whether H and M are commensal or mutualistic, or variations in model assumptions.

evolutionary biology↗

bioRxiv2018

Community function landscape and steady state species composition shape the eco-evolutionary dynamics of arti1cial community selection

Microbial communities often perform important functions that arise from interactions among member species. Community functions can be improved via artificial selection: Many communities are repeatedly grown, mutations arise, and communities with the highest desired function are chosen to reproduce where each is partitioned into multiple offspring communities for the next cycle. Since selection efficacy is often unimpressive in published experiments and since multiple experimental parameters need to be tuned, we sought to use computer simulations to learn how to design effective selection strategies. We simulated community selection to improve a community function that requires two species and imposes a fitness cost on one of the species. This simplified case allowed us to distill community function down to two fundamental and orthogonal components: a heritable determinant and a nonheritable determinant. We then visualize a "community function landscape" relating community function to these two determinants, and demonstrate that the evolutionary trajectory on the landscape is restricted along a path designated by ecological interactions. This path can prevent the attainment of maximal community function, and trap communities in landscape locations where community function has low heritability. Exploiting these observations, we devise a species spiking approach to shift the path to improve community function heritability and consequently selection efficacy. We show that our approach is applicable to communities with complex and unknown function landscapes.

evolutionary biology↗

bioRxiv2017

Developing a low-cost milliliter-scale chemostat array for precise control of cellular growth

Multiplexed milliliter-scale chemostats are useful for measuring cell physiology under various degrees of nutrient limitation and for experimental evolution. In each chemostat, fresh medium containing a growth rate-limiting metabolite is pumped into the culturing chamber at a constant rate, while culture effluent exits at an equal rate. Although such devices have been developed by various labs, key parameters - the accuracy and precision of flow rate and the operational range - are not explicitly characterized. Here we report the development of multiplexed milliliter-scale chemostats where flow rates for eight chambers can be independently controlled to vary within a wide range, corresponding to population doubling times of 3~ 13 hours. Importantly, flow rates are precise and accurate without the use of expensive feedback systems. Among the eight chambers, the maximal coefficient of variation in flow rate is less than 3%, and average flow rates are only slightly below targets, i.e., 3-6% for 13-hour and 0.6-1.0% for 3-hour doubling times. This deficit is largely due to evaporation and should be correctable. We experimentally demonstrate that our device allows accurate and precise quantification of population phenotypes.

microbiology↗