Session Q03: Biological, Chemical, and Medical Physics

Transcription Regulation by Targeting G-quadruplex Forming Sequences with CRISPR/dCas9

Nuclease-dead Cas9 (dCas9) enables transient and sequence specific transcription regelation when putative quadruplex forming sequences (PQS) are targeted. We present functional in cellulo experiments where we monitored mRNA and protein expression levels and in vitro bulk and single molecule experiments where we investigated how RNA polymerase (RNAP) interacts with dCas9 and G-quadruplex (G4 or GQ) structures. We used the PQS within the human tyrosine hydroxylase (TH) and c-Myc promoters as model systems as they can form multiple G4 structures with different stabilities. In both systems, we demonstrate that transcription levels can be up or down regulated by targeting different parts of these G-rich sequences with dCas9. We demonstrate that dCas9 targeting, which is specific, transient and does not result in sequence modifications, yields similar levels of control to those attained with site directed mutagenesis and small molecule studies. To gain mechanistic understanding of these observations, we performed in vitro RNAP stop assay and single molecule FRET assays where the location and orientation of PQS was varied with respect to T7 RNAP promoter site and dCas9 target site. These studies shed light on the complex interactions between G4, CRISPR/dCas9, and RNAP and highlight the potent and versatile capabilities of dCas9 in gene expression regulation.   

Magnetic Particle Spectrometer for Characterization of Superparamagnetic Iron Oxide Nanoparticles

Magnetic Particle Imaging (MPI) is a relatively new tracer-based biomedical imaging technique that shows great promise for molecular imaging applications. Among these are malignant tumor detection, which can be used for diagnosis of diseases like breast cancer. In MPI the image quality, including resolution and SNR, is directly related to the properties of the tracer particle itself, known as superparamagnetic iron oxide nanoparticles (SPIONs). Magnetic Particle Spectrometry (MPS) is a necessary tool for the characterization of magnetization properties of these nanoparticles. This project aims to develop an MPS to study directly magnetization data on different types of SPIONs including their functionalization that will later be used in MPI. To create a low-cost MPS, our team employed techniques such as 3D printing, off-the-shelf components, and Arduino and DAQ communication. The device is controlled through a user-friendly interface on a dedicated application that was created in Python.   

Mapping Whole Exome Sequencing to In Vivo Imaging with Stereotactic Localization and Deep Learning

Objective: Intra-tumoral heterogeneity complicates the diagnosis and treatment of glioma. Multiparametric imaging enhances heterogeneity characterization, but limitations exist in assessing cellular and molecular properties across space due to a lack of easily accessible, co-located pathology and genomic data. This study presents a multi-faceted approach combining stereotactic biopsy with standard clinical open-craniotomy for sample collection, voxel-wise analysis of MR images, regression-based generalized additive model (GAM), and whole-exome sequencing. This work aims to demonstrate the potential of machine learning algorithms to predict variations in cellular and molecular tumor characteristics.  

Methods: This retrospective study enrolled ten treatment-naïve patients with radiologically confirmed glioma. Each underwent a multiparametric MR scan (T1_W, T1_W-CE, T2_W, T2_W-FLAIR, DWI) prior to surgery. During standard craniotomy, at least 1 stereotactic biopsy was collected from each patient, with screenshots of the sample locations saved for spatial registration to pre-surgical MR data. Whole-exome sequencing was performed on flash-frozen tumor samples, prioritizing the signatures of five glioma-related genes: IDH1, TP53, EGFR, PIK3CA, and NF1. Regression was implemented with a GAM using a univariate shape function for each predictor. Standard receiver operating characteristic analyses were used to evaluate detection, with AUC (area under curve) calculated for each gene target and MR contrast combination.  

Results: Mean AUC for five gene targets and 31 MR contrast combinations was 0.75±0.11; individual AUCs were as high as 0.96 for both IDH1 and TP53 with T2_W-FLAIR and ADC and 0.99 for EGFR with T2_W & ADC. An average AUC of 0.85 across the five mutations was achieved using T1_W, T2_W-FLAIR, and ADC combined.  

Conclusion: These results suggest the possibility of predicting exome-wide mutation events from non-invasive, in vivo imaging by combining stereotactic localization of glioma samples and a semi-parametric deep learning method. This approach holds potential for refining targeted therapy by better addressing the genomic heterogeneity of glioma tumors.    

Analyzing Perdew-Zunger self-interaction correction for reaction barrier heights beyond the LDSA: Unraveling the Evolution of Stretched Bond Errors

Incorporating self-interaction corrections (SIC) leads to significant improvements in the prediction of chemical reaction barrier heights using density functional theory methods. We present a thorough analysis of these corrections on an orbital-by-orbital basis for three semi-local density functional approximations positioned at the lowest rung of Jacob's Ladder of approximations. We conducted detailed Fermi-Löwdin Orbital SIC (FLOSIC) calculations at various steps along the reaction pathway, spanning from the reactants (R) to the transition state (TS) to the products (P), focusing on four representative reactions selected from the BH76 benchmark set. Across all three functionals, we observed that the primary contribution to SIC of the barrier heights originates from stretched bond orbitals that emerge near the TS configuration. We introduce the XC/H ratio, representing the ratio of the self-exchange-correlation energy to the self-Hartree energy, as an indicator of one-electron self-interaction error. A value of XC/H = 1.0 indicates that an orbital's self-exchange-correlation energy exactly cancels its self-Hartree energy, rendering the orbital neutral to the SIC in the FLOSIC scheme. Our analysis reveals that XC/H varies within a range of values for the practical DFAs studied here, with higher values typically associated with stretched or strongly lobed orbitals. We demonstrate that significant disparities in XC/H for corresponding orbitals across the R, TS, and P configurations can be leveraged to identify the principal contributors to the SIC of barrier heights and reaction energies. Based on these comparisons, we suggest that barrier height predictions achieved using the SCAN meta-generalized gradient approximation may have attained the best accuracy achievable for a semi-local functional employing the Perdew-Zunger SIC approach.   

Optimizing Binding among Bimolecular Tethered Complexes

Tethered motion is ubiquitous in nature, offering controlled movement and spatial constraints to otherwise chaotic systems. The enhanced functionality and practical utility of tethers has been exploited in biotechnology, catalyzing the design of novel biosensors and molecular assembly techniques. While notable technological advances incorporating tethered motifs have been made, a theoretical gap persists within the paradigm, hindering a comprehensive understanding of tethered-based technologies. In this work, we focus on the characterization of the binding kinetics of two tethered molecules functionalized to a hard surface. Using a mean-field approximation, the binding time of such bimolecular system is determined analytically. Furthermore, estimates of the grafting site separation and polymer lengths which expedite binding are provided. These estimates, along with the analytical theories and frameworks established here, have the potential to improve efficacy in self-assembly methods in DNA nanotechnology, and can be extended to more biologically-specific endeavors including drug-delivery and molecular sensing.