Search

This paper presents an enzyme building block for the assembly of megamolecules. The system is based on the inhibition of the human‐derived cellular retinoic acid binding protein II (CRABP2) domain. We synthesized a synthetic retinoid bearing an arylfluorosulfate group, which uses sulfur fluoride exchange click chemistry to covalently inhibit CRABP2. We conjugated both the inhibitor and a fluorescein tag to an oligo(ethylene glycol) backbone and measured a second‐order rate constant for the protein inhibition reaction of approximately 3,600 M−1s−1. We used this new enzyme‐inhibitor pair to assemble multi‐protein structures in one‐pot reactions using three orthogonal assembly chemistries to demonstrate exact control over the placement of protein domains within a single, homogeneous molecule. This work enables a new dimension of control over specificity, orientation, and stoichiometry of protein domains within atomically precise nanostructures. [ABSTRACT FROM AUTHOR]

Phosphorylation controls important cellular signals and its dysregulation leads to disease. While most phospho-regulation studies are focused on kinases, phosphatases are comparatively overlooked. Combining peptide arrays with SAMDI mass spectrometry, we show that tyrosine phosphatase activity is restricted by basic amino acids adjacent to phosphotyrosines. We validate this model using two β-catenin mutants associated with cancer (T653R/K) and a mouse model for intellectual disability (T653K). These mutants introduce a basic residue next to Y654, an established phosphorylation site where modification shifts β-catenin from cell–cell adhesions and towards its essential nuclear role as Wnt-signaling effector. We show that T653-basic mutant β-catenins are less efficiently dephosphorylated by phosphatases, leading to sustained Y654 phosphorylation and elevated Wnt signals, similar to those observed for Y654E phospho-mimic mutant mice. This model rationalizes how basic mutations proximal to phosphotyrosines can restrict counter-regulation by phosphatases, providing new mechanismistic and treatment insights for 6000+ potentially relevant cancer mutations. [ABSTRACT FROM AUTHOR]

Accurate cancer detection and diagnosis is of utmost importance for reliable drug-response prediction. Successful cancer characterization relies on both genetic analysis and histological scans from tumor biopsies. It is known that the cytoskeleton is significantly altered in cancer, as cellular structure dynamically remodels to promote proliferation, migration, and metastasis. We exploited these structural differences with supervised feature extraction methods to introduce an algorithm that could distinguish cancer from non-cancer cells presented in high-resolution, single cell images. In this paper, we successfully identified the features with the most discriminatory power to successfully predict cell type with as few as 100 cells per cell line. This trait overcomes a key barrier of machine learning methodologies: insufficient data. Furthermore, normalizing cell shape via microcontact printing on self-assembled monolayers enabled better discrimination of cell lines with difficult-to-distinguish phenotypes. Classification accuracy remained robust as we tested dissimilar cell lines across various tissue origins, which supports the generalizability of our algorithm. [ABSTRACT FROM AUTHOR]

Raman spectroscopic-based biosensing strategies are often complicated by low signal and the presence of multiple chemical species. While surface-enhanced Raman spectroscopy (SERS) nanostructured platforms are able to deliver high quality signals by focusing the electromagnetic field into a tight plasmonic hot-spot, it is not a generally applicable strategy as it often depends on the specific adsorption of the analyte of interest onto the SERS platform. This paper describes a strategy to address this challenge by using surface potential as a physical binding agent in the context of microneedle sensors. We show that the potential-dependent adsorption of different chemical species allows scrutinization of the contributions of different chemical species to the final spectrum, and that the ability to cyclically adsorb and desorb molecules from the surface enables efficient application of multivariate analysis methods. We demonstrate how the strategy can be used to mitigate potentially confounding phenomena, such as surface reactions, competitive adsorption and the presence of molecules with similar structures. In addition, this decomposition helps evaluate criteria to maximize the signal of one molecule with respect to others, offering new opportunities to enhance the measurement of analytes in the presence of interferants. [ABSTRACT FROM AUTHOR]

This paper describes a method that combines a microfluidic device and self‐assembled monolayers for matrix‐assisted laser desorption/ionization mass spectrometry (SAMDI) mass spectrometry to calculate the cooperativity in binding of calcium ions to peptidylarginine deiminase type 2 (PAD2). This example uses only 120 μL of enzyme solution and three fluidic inputs. This microfluidic device incorporates a self‐assembled monolayer that is functionalized with a peptide substrate for PAD2. The enzyme and different concentrations of calcium ions are flowed through each of eight channels, where the position along the channel corresponds to reaction time and position across the channel corresponds to the concentration of Ca2+. Imaging SAMDI (iSAMDI) is then used to determine the yield for the enzyme reaction at each 200 μm pixel on the monolayer, providing a time course for the reactions. Analysis of the peptide conversion as a function of position and time gives the degree of cooperativity (n) and the concentration of ligand required for half maximal activity (K0.5) for the Ca2+ – dependent activation of PAD2. This work establishes a high‐throughput and label‐free method for studying enzyme‐ligand binding interactions and widens the applicability of microfluidics and matrix‐assisted laser desorption/ionization mass spectrometry (MALDI) imaging mass spectrometry. [ABSTRACT FROM AUTHOR]