Stacey, S. | Search bioRxiv

bioRxiv2025

Integration of Multiomic and Multi-phenotypic Data Identifies Biological Pathways Associated with Physical Fitness

Unraveling the complex associations between human phenotypes and molecular pathways can pave the way to improved health and performance, but faces a fundamental challenge: the measurable genes, proteins, and metabolites vastly outnumber the participants in even the largest studies, yielding spurious correlations. To address this imbalance, we have developed a bioinformatic framework and computational approach ("PhenoMol") to discover biological drivers of phenotypic characteristics that integrates all available phenotypic data predictive of outcomes and reduces multi-omic data dimensionality by generating "expression circuits" via graph theory constrained by prior biological knowledge of molecular interactions. We applied PhenoMol to analyze causal patterns and predict elite physical performance in a healthy cohort with deep physiological, physical, behavioral, cognitive, and molecular characterization. PhenoMol outperforms regression models based on equivalent analytic methodologies that do not employ network biology for dimensionality reduction. The PhenoMol software is provided for future studies.

bioinformatics↗

bioRxiv2024

Quantum Correlations in Engineered Magneto-Sensitive Fluorescent Proteins Enables Multi-Modal Sensing in Living Cells

Quantum mechanical phenomena have been identified as fundamentally significant to an increasing number of biological processes. Simultaneously, quantum sensing is emerging as a cutting-edge technology for diverse applications across materials and biological science. However, until recently, biological based candidates for quantum sensors have been limited to in vitro systems, were prone to light induced degradation, and the experimental setups involved are typically not amenable to high-throughput study as would enable further engineering e.g. via directed evolution. We recently created a new class of magneto-sensitive fluorescent proteins (MFPs), which we show overcome these challenges and represent a new form of engineered biological quantum sensors that function both at physiological conditions and in living cells. Through directed evolution, we demonstrate the possibility of engineering these proteins to alter properties of their response to magnetic fields and radio frequencies. These effects are explained in terms of the radical pair mechanism (RPM), involving the protein backbone and a bound flavin cofactor. Using this engineered system we demonstrate the first observation of a fluorescent protein exhibiting Optically Detected Magnetic Resonance (ODMR) in living bacterial cells at room temperature, at sufficiently high signal-to-noise to be detected in a single cell. These magnetic resonance and magnetic field effects measured via fluorescence enable novel technologies; examples we demonstrate include spatial localisation of fluorescence signals using gradient fields (i.e. Magnetic Resonance Imaging (MRI) using a genetically encoded probe), sensing of the molecular microenvironment, multiplexing of bio-imaging, and lock-in detection, overcoming typical fluorescence imaging challenges of light scattering and autofluorescence. Taken together, our results represent a new range of sensing modalities for engineered biological systems, based on and designed around understanding the quantum mechanical properties of MFPs.

bioengineering↗