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Biology subjects

Kelley, L.

Publications and source records attributed to Kelley, L..

4 recordsLinked to original sources

Reconstructing heterogeneous metabolic trajectories of E. coli diauxie via a dynamical Maximum Entropy Principle

The glucose-acetate diauxic shift in E. coli is classically described as an abrupt, population-wide switch from glucose to acetate consumption. Recent experiments challenge this view, revealing a robust intermediate regime of co-consumption whose single-cell basis remains unresolved: does it reflect coexisting specialized subpopulations, or genuine mixed metabolic states within individual cells? We first develop a two-state consumer-resource model in which cells optimally grow on either glucose or acetate, and show that observed co-consumption trajectories cannot be decomposed into convex combinations of the two subpopulations -- ruling out discrete metabolic states as a sufficient explanation. Physico-chemical constraints of the metabolic network instead enforce genuine single-cell co-consumption across a continuous spectrum of phenotypes. To resolve this, we apply a dynamical maximum entropy (maximum caliber) framework constrained by batch and chemostat experiments, inferring time-resolved distributions of metabolic fluxes that naturally predict a continuum of single-cell phenotypes spanning glucose overflow, mixed substrate utilization, and acetate consumption -- revealing co-consumption as a dominant, persistent feature of single-cell metabolism around the switch rather than an artifact of population averaging. Finally, we formulate a continuous consumer-resource model over metabolic state space, in which selection, phenotypic diffusion, and moving metabolic boundaries driven by environmental feedback reproduce single-cell co-consumption trajectories and complex dynamical trends inaccessible to discrete models. Together, our results recast diauxic adaptation as a continuous redistribution of single-cell metabolic states rather than a discrete switch.

systems biology↗

Weber's law of proportional processing influences coevolution of ornaments and preferences in models of sexual selection

Mate preferences are often influenced by the magnitude of sexual signals, which are presumed to indicate underlying aspects of signaller quality. Although the perception of these signals depends on sensory processes, the role of perceptual adaptations and constraints in mate assessment is frequently overlooked. Many sensory systems follow Webers law of proportional processing, where discrimination between signals is based upon their proportional, or relative, difference rather than their absolute difference. Because preference strength varies with relative trait magnitude, Webers law could strongly influence sexual selection, changing the coevolution of traits and preferences. Here, we explore the consequences of Webers law for sexual selection using individual-based models, applying Scalar Utility Theory to mate choice. We investigate the coevolution of male ornaments and female preferences under both Fisherian and good genes scenarios, as well as scrutinizing the sexual selection of multiple ornaments and preferences. Including Webers law in these models either reduced ornament exaggeration, or promoted exaggeration and diversification of ornaments and preferences, depending on the costs of choice and how rapidly female survival decreases when preferences evolve away from the naturally selected optimum. These results highlight the importance of perception and cognitive processing in shaping sexual selection and its evolutionary impacts.

evolutionary biology↗

Glutamine antagonism suppresses tumor growth in adrenocortical carcinoma through inhibition of de novo nucleotide biosynthesis

Dysregulation of cellular metabolism is a hallmark of cancer, which remains poorly understood in adrenocortical carcinoma (ACC). Here, we dissected ACC metabolism by integrating transcriptional profiling from human and mouse ACC, targeted tissue metabolomics from a mouse ACC model, and untargeted serum metabolomics from a large patient cohort, providing cross-species validation of metabolic rewiring in ACC. This study revealed global metabolic dysregulation, involving glutamine-dependent pathways such as non-essential amino-acid and hexosamine biosynthesis, nucleotide metabolism, and glutathione biosynthesis, suggesting glutamine catabolism is a critical metabolic vulnerability in ACC. Treatment with glutamine antagonists 6-Diazo-5-Oxo-L-Norleucine (DON) and JHU-083 elicited robust anti-tumor responses. Mechanistic studies revealed DONs anti-tumor effect was primarily driven by selective inhibition of glutamine-fueled de novo nucleotide biosynthesis. Additionally, DON led to DNA damage, which yielded potent synergism with inhibition of the DNA damage response pathway. Collectively, this work highlights glutamine metabolism as a central metabolic dependency and therapeutic target in ACC. HighlightsO_LIMouse and human ACC share conserved transcriptional-metabolic programs, revealing Gln metabolism as a central, targetable vulnerability. C_LIO_LITargeted tissue metabolomic analysis in a mouse model of ACC validates dysregulation in Gln-dependent metabolic pathways. C_LIO_LITargeting of Gln metabolism with JHU-083 (6-diazo-5-oxo-L-norleucine (DON) pro-drug) achieves marked inhibition of tumor growth in vivo. C_LIO_LIHigh expression of Gln-metabolizing genes mediating de novo nucleotide biosynthesis is associated with poor prognosis in ACC. C_LIO_LIDON drives nucleotide depletion and DNA damage, leading to potent synergy with inhibition of the DNA damage response. C_LIO_LIUntargeted serum metabolomic analysis in a large cohort of patients with adrenal tumors demonstrates dysregulation of Gln and nucleotide metabolism in ACC. C_LI

cancer biology↗

Low RT-based Genome Editing Fidelity in Mouse Hepatocytes: Challenges and Solutions

Abstract/SummaryIntegrase-mediated Programmable Genomic Integration (I-PGI) uses a Cas9 nickase (nCas9) with a reverse transcriptase (RT), to write a large serine integrase (LSI) target site (attB/P, here called "beacon") in a programmed location. Co-delivery of the LSI and a DNA template containing the cognate recognition site results in precise integration of the template in a specific genomic location. While we were able to achieve high-fidelity beacon placement in a range of primate cycling and non-dividing cells, when translating our technology into an in vivo rodent model (liver) we surprisingly observed very low beacon fidelity, with the vast majority of beacons being unsuitable for integration. This phenomenon was independent of mouse strain, but was specific to non-dividing cells, as a cycling mouse hepatocyte cell line (Hepa1-6) demonstrated very high levels of fidelity. To address this issue we utilized neonatal mice, which have a much higher proportion of proliferating hepatocytes than adult mice. This resulted in a significant increase in the placement of high-fidelity beacons, and achieved functional gene expression after I-PGI in a therapeutically relevant target site. In an alternate approach, we engineered transgenic mice with intact beacons placed in specific genomic locations, allowing us to optimize integrase and DNA template dosing and kinetics. In summary, we have identified a previously undescribed challenge when using RT-based editing to write long sequences (~40 bp) in non-dividing rodent hepatocytes. This phenomenon was specific to rodents and was not observed in primate dividing or non-dividing cells. This previously unidentified challenge using RTs will limit the use of I-PGI in mouse models, however here we describe two methods that address this issue.

bioengineering↗