Impact of variability in cell cycle periodicity on cell population dynamics.

The cell cycle consists of a series of orchestrated events controlled by molecular sensing and feedback networks that ultimately drive the duplication of total DNA and the subsequent division of a single parent cell into two daughter cells. The ability to block the cell cycle and synchronize cells within the same phase has helped understand factors that control cell cycle progression and the properties of each individual phase. Intriguingly, when cells are released from a synchronized state, they do not maintain synchronized cell division and rapidly become asynchronous. The rate and factors that control cellular desynchronization remain largely unknown. In this study, using a combination of experiments and simulations, we investigate the desynchronization properties in cervical cancer cells (HeLa) starting from the G1/S boundary following double-thymidine block. Propidium iodide (PI) DNA staining was used to perform flow cytometry cell cycle analysis at regular 8 hour intervals, and a custom auto-similarity function to assess the desynchronization and quantify the convergence to an asynchronous state. In parallel, we developed a single-cell phenomenological model the returns the DNA amount across the cell cycle stages and fitted the parameters using experimental data. Simulations of population of cells reveal that the cell cycle desynchronization rate is primarily sensitive to the variability of cell cycle duration within a population. To validate the model prediction, we introduced lipopolysaccharide (LPS) to increase cell cycle noise. Indeed, we observed an increase in cell cycle variability under LPS stimulation in HeLa cells, accompanied with an enhanced rate of cell cycle desynchronization. Our results show that the desynchronization rate of artificially synchronized in-phase cell populations can be used a proxy of the degree of variance in cell cycle periodicity, an underexplored axis in cell cycle research.

Genetic physical unclonable functions in human cells.

A physical unclonable function (PUF) is a physical entity that provides a measurable output that can be used as a unique and irreproducible identifier for the artifact wherein it is embedded. Popularized by the electronics industry, silicon PUFs leverage the inherent physical variations of semiconductor manufacturing to establish intrinsic security primitives for attesting integrated circuits. Owing to the stochastic nature of these variations, photolithographically manufactured silicon PUFs are impossible to reproduce (thus unclonable). Inspired by the success of silicon PUFs, we sought to create the first generation of genetic PUFs in human cells. We demonstrate that these PUFs are robust (i.e., they repeatedly produce the same output), unique (i.e., they do not coincide with any other identically produced PUF), and unclonable (i.e., they are virtually impossible to replicate). Furthermore, we demonstrate that CRISPR-engineered PUFs (CRISPR-PUFs) can serve as a foundational principle for establishing provenance attestation protocols.

Cell morphology-based machine learning models for human cell state classification.

Herein, we implement and access machine learning architectures to ascertain models that differentiate healthy from apoptotic cells using exclusively forward (FSC) and side (SSC) scatter flow cytometry information. To generate training data, colorectal cancer HCT116 cells were subjected to miR-34a treatment and then classified using a conventional Annexin V/propidium iodide (PI)-staining assay. The apoptotic cells were defined as Annexin V-positive cells, which include early and late apoptotic cells, necrotic cells, as well as other dying or dead cells. In addition to fluorescent signal, we collected cell size and granularity information from the FSC and SSC parameters. Both parameters are subdivided into area, height, and width, thus providing a total of six numerical features that informed and trained our models. A collection of logistical regression, random forest, k-nearest neighbor, multilayer perceptron, and support vector machine was trained and tested for classification performance in predicting cell states using only the six aforementioned numerical features. Out of 1046 candidate models, a multilayer perceptron was chosen with 0.91 live precision, 0.93 live recall, 0.92 live f value and 0.97 live area under the ROC curve when applied on standardized data. We discuss and highlight differences in classifier performance and compare the results to the standard practice of forward and side scatter gating, typically performed to select cells based on size and/or complexity. We demonstrate that our model, a ready-to-use module for any flow cytometry-based analysis, can provide automated, reliable, and stain-free classification of healthy and apoptotic cells using exclusively size and granularity information.

Robust Filtering and Noise Suppression in Intragenic miRNA-Mediated Host Regulation.

MicroRNAs (miRNAs) are short non-coding RNA molecules that regulate gene expression post-transcriptionally by binding to target messenger RNAs (mRNAs). Many human miRNAs are intragenic, located within introns of protein-coding sequence (host). Intriguingly, a percentage of intragenic miRNAs downregulate the host transcript forming an incoherent feedforward motif topology. Here, we study intragenic miRNA-mediated host gene regulation using a synthetic gene circuit stably integrated within a safe-harbor locus of human cells. When the intragenic miRNA is directed to inhibit the host transcript, we observe a reduction in reporter expression accompanied by output filtering and noise reduction. Specifically, the system operates as a filter with respect to promoter strength, with the threshold being robust to promoter strength and measurement time. Additionally, the intragenic miRNA regulation reduces expression noise compared to splicing-alone architecture. Our results provide a new insight into miRNA-mediated gene expression, with direct implications to gene therapy and synthetic biology applications.

Regulating the Uptake of Viral Nanoparticles in Macrophage and Cancer Cells via a pH Switch.

Controlling the uptake of nanomaterials into phagocytes is a challenging problem. We describe an approach to inhibit the cellular uptake by macrophages and HeLa cells of nanoparticles derived from bacteriophage Qß by conjugating negatively charged terminal hexanoic acid moieties onto its surface. Additionally, we show hydrazone linkers can be installed between the surface of Qß and the terminal hexanoic acid moieties, resulting in a pH-responsive conjugate that, in acidic conditions, can release the terminal hexanoic acid moiety and allow for the uptake of the Qß nanoparticle. The installation of the "pH switch" did not change the structure-function properties of the hexanoic acid moiety and the uptake of the Qß conjugates by macrophages.

Nitroxyl Modified Tobacco Mosaic Virus as a Metal-Free High-Relaxivity MRI and EPR Active Superoxide Sensor.

Superoxide overproduction is known to occur in multiple disease states requiring critical care; yet, noninvasive detection of superoxide in deep tissue remains a challenge. Herein, we report a metal-free magnetic resonance imaging (MRI) and electron paramagnetic resonance (EPR) active contrast agent prepared by "click conjugating" paramagnetic organic radical contrast agents (ORCAs) to the surface of tobacco mosaic virus (TMV). While ORCAs are known to be reduced in vivo to an MRI/EPR silent state, their oxidation is facilitated specifically by reactive oxygen species-in particular, superoxide-and are largely unaffected by peroxides and molecular oxygen. Unfortunately, single molecule ORCAs typically offer weak MRI contrast. In contrast, our data confirm that the macromolecular ORCA-TMV conjugates show marked enhancement for T1 contrast at low field (<3.0 T) and T2 contrast at high field (9.4 T). Additionally, we demonstrated that the unique topology of TMV allows for a "quenchless fluorescent" bimodal probe for concurrent fluorescence and MRI/EPR imaging, which was made possible by exploiting the unique inner and outer surface of the TMV nanoparticle. Finally, we show TMV-ORCAs do not respond to normal cellular respiration, minimizing the likelihood for background, yet still respond to enzymatically produced superoxide in complicated biological fluids like serum.

CRISPR-Based Editing Reveals Edge-Specific Effects in Biological Networks.

Unraveling the properties of biological networks is central to understanding both normal and disease cellular phenotypes. Networks consist of functional elements (nodes) that form a variety of diverse connections (edges), with each node being a hub for multiple edges. Herein, in contrast to node-centric network perturbation and analysis approaches, we present a high-throughput CRISPR-based methodology for delineating the role of network edges. Ablation of network edges using a library targeting 93 miRNA target sites in 71 genes reveals numerous edges that control, with variable importance, cellular growth and survival under stress. To compare the impact of removing nodes versus edges in a biological network, we dissect a specific p53-microRNA pathway. We show that removal of the miR-34a target site from the anti-apoptotic gene BCL2 desensitizes the cell to ectopic delivery of miR-34a in a p53-dependent manner. In summary, we demonstrate that network edges are critical to the function and stability of biological networks. Our results introduce a novel genetic screening opportunity via edge ablation and highlight a new dimension in biological network analysis.

Guide RNA engineering for versatile Cas9 functionality.

The Clustered Regularly Interspaced Short Palindromic Repeats system allows a single guide RNA (sgRNA) to direct a protein with combined helicase and nuclease activity to the DNA. Streptococcus pyogenes Cas9 (SpCas9), a CRISPR-associated protein, has revolutionized our ability to probe and edit the human genome in vitro and in vivo Arguably, the true modularity of the Cas9 platform is conferred through the ease of sgRNA programmability as well as the degree of modifications the sgRNA can tolerate without compromising its association with SpCas9 and function. In this review, we focus on the properties and recent engineering advances of the sgRNA component in Cas9-mediated genome targeting.

Compromised RNA polymerase III complex assembly leads to local alterations of intergenic RNA polymerase II transcription in Saccharomyces cerevisiae.

BACKGROUND: Assembled RNA polymerase III (Pol III) complexes exert local effects on chromatin processes, including influencing transcription of neighboring RNA polymerase II (Pol II) transcribed genes. These properties have been designated as 'extra-transcriptional' effects of the Pol III complex. Previous coding sequence microarray studies using Pol III factor mutants to determine global effects of Pol III complex assembly on Pol II promoter activity revealed only modest effects that did not correlate with the proximity of Pol III complex binding sites. RESULTS: Given our recent results demonstrating that tDNAs block progression of intergenic Pol II transcription, we hypothesized that extra-transcriptional effects within intergenic regions were not identified in the microarray study. To reconsider global impacts of Pol III complex binding, we used RNA sequencing to compare transcriptomes of wild type versus Pol III transcription factor TFIIIC depleted mutants. The results reveal altered intergenic Pol II transcription near TFIIIC binding sites in the mutant strains, where we observe readthrough of upstream transcripts that normally terminate near these sites, 5'- and 3'-extended transcripts, and de-repression of adjacent genes and intergenic regions. CONCLUSIONS: The results suggest that effects of assembled Pol III complexes on transcription of neighboring Pol II promoters are of greater magnitude than previously appreciated, that such effects influence expression of adjacent genes at transcriptional start site and translational levels, and may explain a function of the conserved ETC sites in yeast. The results may also be relevant to synthetic biology efforts to design a minimal yeast genome.