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Biology subjects

Doran, B. A.

Publications and source records attributed to Doran, B. A..

3 recordsLinked to original sources

Physiological architecture and evolutionary origins of cellular adaptability

The capacity to adapt to complex environments ( adaptability) is a defining property of cells. Yet, its relationship across single-cell physiology, population-level responses, and evolutionary timescales remains unclear. We performed single-cell transcriptional profiling of budding yeast across 20 complex environments before and after long-term selection for increased osmotolerance. In ancestral populations, transcriptional responses organized into a reproducible hierarchy where adaptation to certain cues took precedence over others. This hierarchy mechanistically originated within individual cells through contingent regulation of translation initiation. Evolution for >3,000 generations under osmotic stress increased osmotolerance while reordering this hierarchy, selectively deprioritizing osmotic stress as an organizing axis of adaptation. The derived strain exhibited impaired integration of stress responses, defective translational coordination, and reduced fitness outside the selected condition. Together, these findings illustrate that cellular adaptability is an evolved architecture whose form is set by the history of selection. One Sentence SummaryCells adapt to complex environments via a prioritization hierarchy; this hierarchy is shaped by the frequency and magnitude of environmental fluctuations in their evolutionary history.

cell biology↗

Conserved principles of spatial biology define tumor heterogeneity and response to immunotherapy

The complexity of tumor microenvironments (TMEs) poses a substantial challenge to understanding tumor heterogeneity and clinical outcomes. By studying an ensemble of 262 diverse solid tumors, we uncovered a conserved, hierarchical architecture of transcriptionally covarying regions we term Spatial Groups (SGs). SGs corresponded to discrete biological units as benchmarked against multiple spatial technologies, and their nested organization revealed context-dependent constraints within tumors. Using SGs for comparing tumors, we derived a pantumor classification where immune spatial heterogeneity was the dominant axis of variation. This classification stratified response to immune checkpoint blockade in an out-of-sample cohort of non-small cell lung cancer patients. Statistical approximation techniques defined a sparse set of protein markers capturing system-level properties of TME spatial biology, demonstrating a framework for distilling genome-wide information into clinically deployable diagnostics. Our findings position the architecture of SGs as a general model unifying TME structure with biological function and clinical translation.

cancer biology↗

An evolution-based framework for describing human gut bacteria

The human gut microbiome contains many bacterial strains of the same species ( strain-level variants). Describing strains in a biologically meaningful way rather than purely taxonomically is an important goal but challenging due to the genetic complexity of strain-level variation. Here, we measured patterns of co-evolution across >7,000 strains spanning the bacterial tree-of-life. Using these patterns as a prior for studying hundreds of gut commensal strains that we isolated, sequenced, and metabolically profiled revealed widespread structure beneath the phylogenetic level of species. Defining strains by their co-evolutionary signatures enabled predicting their metabolic phenotypes and engineering consortia from strain genome content alone. Our findings demonstrate a biologically relevant organization to strain-level variation and motivate a new schema for describing bacterial strains based on their evolutionary history. One Sentence SummaryDescribing bacterial strains in the human gut by a statistical model that captures their evolutionary history provides insight into their biology.

systems biology↗