Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects: Distributions of fitness effects of spontaneous mutations.

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of two common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (~0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Direct visualization of emergent metastatic features within an ex vivo model of the tumor microenvironment.

Preventing tumor cells from acquiring metastatic properties would significantly reduce cancer mortality. However, due to the complex nature of this process, it remains one of the most poorly understood and untreatable aspects of cancer. Ischemia and hypoxia in solid tumors are requisite in metastasis formation -- conditions that arise far from functional blood vessels and deep within tumor tissues. These secluded locations impede the observation of pre-metastatic tumor cells and their interactions with stromal cells, which are also critical in the initiation of this process. Thus, the initiation of metastasis has been incredibly difficult to model in the lab and to observe in vivo. We present an ex vivo model of the tumor microenvironment, called 3MIC, which overcomes these experimental challenges and enables the observation of ischemic tumor cells in their native 3D context with high spatial and temporal resolutions. The 3MIC recreates ischemic conditions in the tumor microenvironment and facilitates the co-culture of different cell types. Using live microscopy, we showed that ischemia, but not hypoxia alone, increases the motility and invasive properties of cells derived from primary tumors. These changes are phenotypic and can occur without clonal selection. We directly observed how interactions with stromal cells such as macrophages increased tumor invasion in conjunction with the effects of an ischemic microenvironment. Finally, we tested the effects of chemotherapy drugs under different metabolic microenvironments and found that ischemic tumor cells are more resistant to paclitaxel, possibly due to a metabolic resistance mechanism. Overall, the 3MIC is a cost-effective system that allows for the dissection of the complexity of the tumor microenvironment and direct observation of the emergence of metastasis, as well as the testing of treatments that may halt this process.

The MEMIC is an ex vivo system to model the complexity of the tumor microenvironment.

There is an urgent need for accurate, scalable and cost-efficient models of the tumor microenvironment. Here, we detail how to fabricate and use the metabolic microenvironment chamber (MEMIC) - a 3D-printed ex vivo model of intratumoral heterogeneity. A major driver of the cellular and molecular diversity in tumors is accessibility to the blood stream. Whereas perivascular tumor cells have direct access to oxygen and nutrients, cells further from the vasculature must survive under progressively more ischemic environments. The MEMIC simulates this differential access to nutrients, allow co-culturing any number of cell types, and it is optimized for live imaging and other microscopy-based analyses. Owing to a modular design and full experimental control, the MEMIC provides insights into the tumor microenvironment that would be difficult to obtain via other methods. As proof of principle, we show that cells sense gradual changes in metabolite concentration leading to predictable molecular and cellular spatial patterns. We propose the MEMIC as a complement to standard in vitro and in vivo experiments, diversifying the tools available to accurately model, perturb and monitor the tumor microenvironment.