Machine learning based DNA melt curve profiling enables automated novel genotype detection.

Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic screening for novel genotypes remains challenging in part due to technological limitations. Towards addressing this challenge, we present an advancement in universal microbial high resolution melting (HRM) analysis that is capable of accomplishing both known genotype identification and novel genotype detection. Specifically, this novel surveillance functionality is achieved through time-series modeling of sequence-defined HRM curves, which is uniquely enabled by the large-scale melt curve datasets generated using our high-throughput digital HRM platform. Taking the detection of bacterial genotypes as a model application, we demonstrate that our algorithms accomplish an overall classification accuracy over 99.7% and perform novelty detection with a sensitivity of 0.96, specificity of 0.96 and Youden index of 0.92. Since HRM-based DNA profiling is an inexpensive and rapid technique, our results add support for the feasibility of its use in surveillance applications.

Divergent iron-regulatory states contribute to heterogeneity in breast cancer aggressiveness.

Primary tumors with similar mutational profiles can progress to vastly different outcomes where transcriptional state, rather than mutational profile, predicts prognosis. A key challenge is to understand how distinct tumor cell states are induced and maintained. In triple negative breast cancer cells, invasive behaviors and aggressive transcriptional signatures linked to poor patient prognosis can emerge in response to contact with collagen type I. Herein, collagen-induced migration heterogeneity within a TNBC cell line was leveraged to identify transcriptional programs associated with invasive versus non-invasive phenotypes and implicate molecular switches. Phenotype-guided sequencing revealed that invasive cells upregulate iron uptake and utilization machinery, anapleurotic TCA cycle genes, actin polymerization promoters, and a distinct signature of Rho GTPase activity and contractility regulating genes. The non-invasive cell state is characterized by actin and iron sequestration modules along with glycolysis gene expression. These unique tumor cell states are evident in patient tumors and predict divergent outcomes for TNBC patients. Glucose tracing confirmed that non-invasive cells are more glycolytic than invasive cells, and functional studies in cell lines and PDO models demonstrated a causal relationship between phenotype and metabolic state. Mechanistically, the OXPHOS dependent invasive state resulted from transient HO-1 upregulation triggered by contact with dense collagen that reduced heme levels and mitochondrial chelatable iron levels. This induced expression of low cytoplasmic iron response genes regulated by ACO1/IRP1. Knockdown or inhibition of HO-1, ACO1/IRP1, MRCK, or OXPHOS abrogated invasion. These findings support an emerging theory that heme and iron flux serve as important regulators of TNBC aggressiveness.

Adhesion tunes speed and persistence by coordinating protrusions and extracellular matrix remodeling.

Cell migration through 3D environments is essential to development, disease, and regeneration processes. Conceptual models of migration have been developed primarily on the basis of 2D cell behaviors, but a general understanding of 3D cell migration is still lacking due to the added complexity of the extracellular matrix. Here, using a multiplexed biophysical imaging approach for single-cell analysis of human cell lines, we show how the subprocesses of adhesion, contractility, actin cytoskeletal dynamics, and matrix remodeling integrate to produce heterogeneous migration behaviors. This single-cell analysis identifies three modes of cell speed and persistence coupling, driven by distinct modes of coordination between matrix remodeling and protrusive activity. The framework that emerges establishes a predictive model linking cell trajectories to distinct subprocess coordination states.

Non-invasive sensing of transepithelial barrier function and tissue differentiation in organs-on-chips using impedance spectroscopy.

Here, we describe methods for combining impedance spectroscopy measurements with electrical simulation to reveal transepithelial barrier function and tissue structure of human intestinal epithelium cultured inside an organ-on-chip microfluidic culture device. When performing impedance spectroscopy measurements, electrical simulation enabled normalization of cell layer resistance of epithelium cultured statically in a gut-on-a-chip, which enabled determination of transepithelial electrical resistance (TEER) values that can be compared across device platforms. During culture under dynamic flow, the formation of intestinal villi was accompanied by characteristic changes in impedance spectra both measured experimentally and verified with simulation, and we demonstrate that changes in cell layer capacitance may serve as measures of villi differentiation. This method for combining impedance spectroscopy with simulation can be adapted to better monitor cell layer characteristics within any organ-on-chip in vitro and to enable direct quantitative TEER comparisons between organ-on-chip platforms which should help to advance research on organ function.

Organs-on-Chips with combined multi-electrode array and transepithelial electrical resistance measurement capabilities.

Here we demonstrate that microfluidic cell culture devices, known as Organs-on-a-Chips can be fabricated with multifunctional, real-time, sensing capabilities by integrating both multi-electrode arrays (MEAs) and electrodes for transepithelial electrical resistance (TEER) measurements into the chips during their fabrication. To prove proof-of-concept, simultaneous measurements of cellular electrical activity and tissue barrier function were carried out in a dual channel, endothelialized, heart-on-a-chip device containing human cardiomyocytes and a channel-separating porous membrane covered with a primary human endothelial cell monolayer. These studies confirmed that the TEER-MEA chip can be used to simultaneously detect dynamic alterations of vascular permeability and cardiac function in the same chip when challenged with the inflammatory stimulus tumor necrosis factor alpha (TNF-α) or the cardiac targeting drug isoproterenol. Thus, this Organ Chip with integrated sensing capability may prove useful for real-time assessment of biological functions, as well as response to therapeutics.

Organs-on-chips with integrated electrodes for trans-epithelial electrical resistance (TEER) measurements of human epithelial barrier function.

Trans-epithelial electrical resistance (TEER) is broadly used as an experimental readout and a quality control assay for measuring the integrity of epithelial monolayers cultured under static conditions in vitro, however, there is no standard methodology for its application to microfluidic organ-on-a-chip (organ chip) cultures. Here, we describe a new microfluidic organ chip design that contains embedded electrodes, and we demonstrate its utility for assessing formation and disruption of barrier function both within a human lung airway chip lined by a fully differentiated mucociliary human airway epithelium and in a human gut chip lined by intestinal epithelial cells. These chips with integrated electrodes enable real-time, non-invasive monitoring of TEER and can be applied to measure barrier function in virtually any type of cultured cell.