Biology subjects

Rosales, A. M.

Publications and source records attributed to Rosales, A. M..

4 recordsLinked to original sources

bioRxiv2022

Fluorescent peptomer substrates for differential degradation by metalloproteases

Proteases, especially MMPs, are attractive biomarkers given their central role in both physiological and pathological processes. Distinguishing MMP activity with degradable substrates, however, is a difficult task due to overlapping substrate specificity profiles. Here, we developed a system of peptomers (peptide-peptoid hybrids) to probe the impact of non-natural residues on MMP specificity for a MMP peptide consensus sequence. Peptoids are non-natural, N-substituted glycines with a large side chain diversity. Given the presence of a hallmark proline residue in the P3 position of MMP consensus sequences, we hypothesized that peptoids may offer N-substituted alternatives to generate differential interactions with MMPs. To investigate this hypothesis, peptomer substrates were exposed to five different MMPs, as well as bacterial collagenase, and monitored by fluorescence resonance energy transfer and liquid chromatography-mass spectrometry to determine the rate of cleavage and the composition of degraded fragments, respectively. We found that peptoid residues are well-tolerated in the P3 and P3 substrate sites and that the identity of the peptoid in these sites displays moderate influence on the rate of cleavage. However, peptoid residues were even better tolerated in the P1 substrate site where activity was more strongly correlated with sidechain identity than sidechain position. All MMPs explored demonstrated similar trends in specificity for the peptomers but exhibited different degrees of variability in proteolytic rate. These kinetic profiles served as "fingerprints" for the proteases and yielded separation by multivariate data analysis. To further demonstrate practical application of this tunability in degradation kinetics, peptomer substrates were tethered into hydrogels and released over distinct timescales. Overall, this work represents a significant step toward the design of probes that maximize differential MMP behavior and presents design rules to tune degradation kinetics with peptoid substitutions, which has promising implications for diagnostic and prognostic applications using array-based sensors.

biochemistry↗

bioRxiv2022

A Strategy to Quantify Myofibroblast Activation on a Continuous Spectrum

Myofibroblasts are a highly secretory and contractile phenotype most commonly identified by the de novo expression and assembly of alpha-smooth muscle actin stress fibers. Traditionally, this activation process has been thought of as a binary process, with cells being labeled as "activated" or "quiescent (non-activated)". More recently, this view has been expanded to consider activation on a continuous spectrum. However, there is no established method to quantify a cells position on this spectrum, and as a result, the binary labeling system is still widely used. While transcriptomic analyses provide a continuous measure of myofibroblast markers, a faster and more facile screening method is needed. To this end, we utilized optical microscopy and machine learning methods to quantify myofibroblast activation on a spectrum. We first measured size and shape features of over 1,000 individual cardiac fibroblasts and found that these features provide enough information to predict activation state, on the binary scale, with 94% accuracy as compared to manual classification. We next performed dimensionality reduction techniques on these features to create a continuous scale of activation. Importantly, this new classification system captures a range of fibroblast activation states, but still possesses inherent bias due to choice of morphological features. Thus, we next used self-supervised machine learning to create a second continuous labeling system free from biases associated with the manually measured features. Lastly, we compared our findings for mechanically activated cardiac fibroblasts to a distribution of cell phenotypes generated from transcriptomic data using single-cell RNA sequencing. Altogether, these results demonstrate a continuous spectrum of activation from fibroblast to myofibroblast and provide a strategy to quantify a cells position on that spectrum.

bioengineering↗

bioRxiv2021

Transcriptional Regulation of Synthetic Polymer Networks

Individual cells direct non-equilibrium processes through coordinated signal transduction and gene expression, allowing for dynamic control over multicellular, system-wide behavior. This behavior extends to remodeling the extracellular polymer matrix that encases biofilms and tissues, where constituent cells dictate spatiotemporal network properties including stiffness, pattern formation, and transport properties. The majority of synthetic polymer networks cannot recreate these phenomena due to their lack of autonomous centralized actuators (i.e., cells). In addition, non-living polymer networks that perform computation are generally restricted to a few inputs (e.g., light, pH, enzymes), limiting the logical complexity available to a single network chemistry. Toward synergizing the advantages of living and synthetic systems, engineered living materials leverage genetic and metabolic programming to establish control over material-wide properties. Here we demonstrate that a bacterial metal respiration mechanism, extracellular electron transfer (EET), can control metal-catalyzed radical cross-linking of polymer networks. Linking metabolic electron flux to a synthetic redox catalyst allows dynamic, tunable, and predictable control over material formation and bulk polymer network mechanics using genetic circuits. By programming key EET genes with transcriptional Boolean logic, we rationally design computational networks that sense-and-respond to multiple inputs in biological contexts. Finally, we capitalize on the wide reactivity of EET and redox catalyses to predictably control another class of living synthetic materials using copper(I) alkyne-azide cycloaddition click chemistry. Our results demonstrate the utility of EET as a bridge for controlling abiotic materials and how the design rules of synthetic biology can be applied to emulate physiological behavior in polymer networks.

synthetic biology↗

bioRxiv2019

Genetic Control of Radical Crosslinking in a Semi-Synthetic Hydrogel

Enhancing materials with the qualities of living systems, including sensing, computation, and adaptation, is an important challenge in designing next-generation technologies. Living materials seek to address this challenge by incorporating live cells as actuating components that control material function. For abiotic materials, this requires new methods that couple genetic and metabolic processes to material properties. Toward this goal, we demonstrate that extracellular electron transfer (EET) from Shewanella oneidensis can be leveraged to control radical crosslinking of a methacrylate-functionalized hyaluronic acid hydrogel. Crosslinking rates and hydrogel mechanics, specifically storage modulus, were dependent on a variety of chemical and biological factors, including S. oneidensis genotype. Bacteria remained viable and metabolically active in the crosslinked network for a least one week, while cell tracking revealed that EET genes also encode control over hydrogel microstructure. Moreover, construction of an inducible gene circuit allowed transcriptional control of storage modulus and crosslinking rate via the tailored expression of a key electron transfer protein, MtrC. Finally, we quantitatively modeled dependence of hydrogel stiffness on steady-state gene expression, and generalized this result by demonstrating the strong relationship between relative gene expression and material properties. This general mechanism for radical crosslinking provides a foundation for programming the form and function of synthetic materials through genetic control over extracellular electron transfer.\n\nSignificance StatementNext-generation materials will require coupling the advantages of engineered and natural systems to solve complex challenges in energy, health, and the environment. Living cells, such as bacteria, naturally possess many of the qualities essential to addressing these challenges, including sensing, computation, and actuation, using their genetic and metabolic machinery. In addition, bacteria are attractive for incorporation into materials due to their durability, ease-of-use, and programmability. Here, we develop a platform for controlling hydrogel properties (e.g., stiffness, crosslinking rate) using extracellular electron transfer from the bacterium Shewanella oneidensis. In our system, metabolic electron flux from S. oneidensis to a metal catalyst generates radical species that crosslink an acrylate-based macromer to form the gel. This synthetic reaction is under direct control of bacterial genetics and metabolism, which we demonstrate through inducible circuits and quantitative modeling of gene expression and resultant hydrogel properties. Developing methods that capitalize on the programmability of biological systems to control synthetic material properties will enable hybrid material designs with unprecedented functions.

synthetic biology↗