Validation of a non-invasive prenatal test for fetal RhD, C, c, E, K and Fya antigens.

We developed and validated a next generation sequencing-(NGS) based NIPT assay using quantitative counting template (QCT) technology to detect RhD, C, c, E, K (Kell), and Fya (Duffy) fetal antigen genotypes from maternal blood samples in the ethnically diverse U.S. population. Quantitative counting template (QCT) technology is utilized to enable quantification and detection of paternally derived fetal antigen alleles in cell-free DNA with high sensitivity and specificity. In an analytical validation, fetal antigen status was determined for 1061 preclinical samples with a sensitivity of 100% (95% CI 99-100%) and specificity of 100% (95% CI 99-100%). Independent analysis of two duplicate plasma samples was conducted for 1683 clinical samples, demonstrating precision of 99.9%. Importantly, in clinical practice the no-results rate was 0% for 711 RhD-negative non-alloimmunized pregnant people and 0.1% for 769 alloimmunized pregnancies. In a clinical validation, NIPT results were 100% concordant with corresponding neonatal antigen genotype/serology for 23 RhD-negative pregnant individuals and 93 antigen evaluations in 30 alloimmunized pregnancies. Overall, this NGS-based fetal antigen NIPT assay had high performance that was comparable to invasive diagnostic assays in a validation study of a diverse U.S. population as early as 10 weeks of gestation, without the need for a sample from the biological partner. These results suggest that NGS-based fetal antigen NIPT may identify more fetuses at risk for hemolytic disease than current clinical practice, which relies on paternal genotyping and invasive diagnostics and therefore is limited by adherence rates and incorrect results due to non-paternity. Clinical adoption of NIPT for the detection of fetal antigens for both alloimmunized and RhD-negative non-alloimmunized pregnant individuals may streamline care and reduce unnecessary treatment, monitoring, and patient anxiety.

A novel high-throughput molecular counting method with single base-pair resolution enables accurate single-gene NIPT.

Next-generation DNA sequencing is currently limited by an inability to accurately count the number of input DNA molecules. Molecular counting is particularly needed when accurate quantification is required for diagnostic purposes, such as in single gene non-invasive prenatal testing (sgNIPT) and liquid biopsy. We developed Quantitative Counting Template (QCT) molecular counting to reconstruct the number of input DNA molecules using sequencing data. We then used QCT molecular counting to develop sgNIPTs of sickle cell disease, cystic fibrosis, spinal muscular atrophy, alpha-thalassemia, and beta-thalassemia. The analytical sensitivity and specificity of sgNIPT was >98% and >99%, respectively. Validation of sgNIPTs was further performed with maternal blood samples collected during pregnancy, and sgNIPTs were 100% concordant with newborn follow-up.

Rewiring bacterial two-component systems by modular DNA-binding domain swapping.

Two-component systems (TCSs) are the largest family of multi-step signal transduction pathways and valuable sensors for synthetic biology. However, most TCSs remain uncharacterized or difficult to harness for applications. Major challenges are that many TCS output promoters are unknown, subject to cross-regulation, or silent in heterologous hosts. Here, we demonstrate that the two largest families of response regulator DNA-binding domains can be interchanged with remarkable flexibility, enabling the corresponding TCSs to be rewired to synthetic output promoters. We exploit this plasticity to eliminate cross-regulation, un-silence a gram-negative TCS in a gram-positive host, and engineer a system with over 1,300-fold activation. Finally, we apply DNA-binding domain swapping to screen uncharacterized Shewanella oneidensis TCSs in Escherichia coli, leading to the discovery of a previously uncharacterized pH sensor. This work should accelerate fundamental TCS studies and enable the engineering of a large family of genetically encoded sensors with diverse applications.

Phosphatase activity tunes two-component system sensor detection threshold.

Two-component systems (TCSs) are the largest family of multi-step signal transduction pathways in biology, and a major source of sensors for biotechnology. However, the input concentrations to which biosensors respond are often mismatched with application requirements. Here, we utilize a mathematical model to show that TCS detection thresholds increase with the phosphatase activity of the sensor histidine kinase. We experimentally validate this result in engineered Bacillus subtilis nitrate and E. coli aspartate TCS sensors by tuning their detection threshold up to two orders of magnitude. We go on to apply our TCS tuning method to recently described tetrathionate and thiosulfate sensors by mutating a widely conserved residue previously shown to impact phosphatase activity. Finally, we apply TCS tuning to engineer B. subtilis to sense and report a wide range of fertilizer concentrations in soil. This work will enable the engineering of tailor-made biosensors for diverse synthetic biology applications.

Engineering Diagnostic and Therapeutic Gut Bacteria.

Genetically engineered bacteria have the potential to diagnose and treat a wide range of diseases linked to the gastrointestinal tract, or gut. Such engineered microbes will be less expensive and invasive than current diagnostics and more effective and safe than current therapeutics. Recent advances in synthetic biology have dramatically improved the reliability with which bacteria can be engineered with the sensors, genetic circuits, and output (actuator) genes necessary for diagnostic and therapeutic functions. However, to deploy such bacteria in vivo, researchers must identify appropriate gut-adapted strains and consider performance metrics such as sensor detection thresholds, circuit computation speed, growth rate effects, and the evolutionary stability of engineered genetic systems. Other recent reviews have focused on engineering bacteria to target cancer or genetically modifying the endogenous gut microbiota in situ. Here, we develop a standard approach for engineering "smart probiotics," which both diagnose and treat disease, as well as "diagnostic gut bacteria" and "drug factory probiotics," which perform only the former and latter function, respectively. We focus on the use of cutting-edge synthetic biology tools, gut-specific design considerations, and current and future engineering challenges.

An open-hardware platform for optogenetics and photobiology.

In optogenetics, researchers use light and genetically encoded photoreceptors to control biological processes with unmatched precision. However, outside of neuroscience, the impact of optogenetics has been limited by a lack of user-friendly, flexible, accessible hardware. Here, we engineer the Light Plate Apparatus (LPA), a device that can deliver two independent 310 to 1550 nm light signals to each well of a 24-well plate with intensity control over three orders of magnitude and millisecond resolution. Signals are programmed using an intuitive web tool named Iris. All components can be purchased for under $400 and the device can be assembled and calibrated by a non-expert in one day. We use the LPA to precisely control gene expression from blue, green, and red light responsive optogenetic tools in bacteria, yeast, and mammalian cells and simplify the entrainment of cyanobacterial circadian rhythm. The LPA dramatically reduces the entry barrier to optogenetics and photobiology experiments.

FlowCal: A User-Friendly, Open Source Software Tool for Automatically Converting Flow Cytometry Data from Arbitrary to Calibrated Units.

Flow cytometry is widely used to measure gene expression and other molecular biological processes with single cell resolution via fluorescent probes. Flow cytometers output data in arbitrary units (a.u.) that vary with the probe, instrument, and settings. Arbitrary units can be converted to the calibrated unit molecules of equivalent fluorophore (MEF) using commercially available calibration particles. However, there is no convenient, nonproprietary tool available to perform this calibration. Consequently, most researchers report data in a.u., limiting interpretation. Here, we report a software tool named FlowCal to overcome current limitations. FlowCal can be run using an intuitive Microsoft Excel interface, or customizable Python scripts. The software accepts Flow Cytometry Standard (FCS) files as inputs and is compatible with different calibration particles, fluorescent probes, and cell types. Additionally, FlowCal automatically gates data, calculates common statistics, and produces publication quality plots. We validate FlowCal by calibrating a.u. measurements of E. coli expressing superfolder GFP (sfGFP) collected at 10 different detector sensitivity (gain) settings to a single MEF value. Additionally, we reduce day-to-day variability in replicate E. coli sfGFP expression measurements due to instrument drift by 33%, and calibrate S. cerevisiae Venus expression data to MEF units. Finally, we demonstrate a simple method for using FlowCal to calibrate fluorescence units across different cytometers. FlowCal should ease the quantitative analysis of flow cytometry data within and across laboratories and facilitate the adoption of standard fluorescence units in synthetic biology and beyond.

Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals.

Gene circuits are dynamical systems that regulate cellular behaviors, often using protein signals as inputs and outputs. Here we have developed an optogenetic 'function generator' method for programming tailor-made gene expression signals in live bacterial cells. We designed precomputed light sequences based on experimentally calibrated mathematical models of light-switchable two-component systems and used them to drive intracellular protein levels to match user-defined reference time courses. We used this approach to generate accelerated and linearized dynamics, sinusoidal oscillations with desired amplitudes and periods, and a complex waveform, all with unprecedented accuracy and precision. We also combined the function generator with a dual fluorescent protein reporter system, analogous to a dual-channel oscilloscope, to reveal that a synthetic repressible promoter linearly transforms repressor signals with an approximate 7-min delay. Our approach will enable a new generation of dynamical analyses of synthetic and natural gene circuits, providing an essential step toward the predictive design and rigorous understanding of biological systems.

Use of degradation tags to control protein levels in the Cyanobacterium Synechocystis sp. Strain PCC 6803.

We generated a collection of ssrA-based C-terminal protein degradation tags with different degradation strengths. The steady-state fluorescence levels of different enhanced yellow fluorescent protein (eYFP) tag variants in a Synechocystis sp. indicated a tunable range from 1% to 50% of untagged eYFP.