Next-generation molecular diagnostics: Leveraging digital technologies to enhance multiplexing in real-time PCR.

Real-time polymerase chain reaction (qPCR) enables accurate detection and quantification of nucleic acids and has become a fundamental tool in biological sciences, bioengineering and medicine. By combining multiple primer sets in one reaction, it is possible to detect several DNA or RNA targets simultaneously, a process called multiplex PCR (mPCR) which is key to attaining optimal throughput, cost-effectiveness and efficiency in molecular diagnostics, particularly in infectious diseases. Multiple solutions have been devised to increase multiplexing in qPCR, including single-well techniques, using target-specific fluorescent oligonucleotide probes, and spatial multiplexing, where segregation of the sample enables parallel amplification of multiple targets. However, these solutions are mostly limited to three or four targets, or highly sophisticated and expensive instrumentation. There is a need for innovations that will push forward the multiplexing field in qPCR, enabling for a next generation of diagnostic tools which could accommodate high throughput in an affordable manner. To this end, the use of machine learning (ML) algorithms (data-driven solutions) has recently emerged to leverage information contained in amplification and melting curves (AC and MC, respectively) - two of the most standard bio-signals emitted during qPCR - for accurate classification of multiple nucleic acid targets in a single reaction. Therefore, this review aims to demonstrate and illustrate that data-driven solutions can be successfully coupled with state-of-the-art and common qPCR platforms using a variety of amplification chemistries to enhance multiplexing in qPCR. Further, because both ACs and MCs can be predicted from sequence data using thermodynamic databases, it has also become possible to use computer simulation to rationalize and optimize the design of mPCR assays where target detection is supported by data-driven technologies. Thus, this review also discusses recent work converging towards the development of an end-to-end framework where knowledge-based and data-driven software solutions are integrated to streamline assay design, and increase the accuracy of target detection and quantification in the multiplex setting. We envision that concerted efforts by academic and industry scientists will help advance these technologies, to a point where they become mature and robust enough to bring about major improvements in the detection of nucleic acids across many fields.

Kinetics study on recombinant alkaline phosphatase and correlation with the generated fluorescent signal.

Alkaline phosphatase (AP) (EC 3.1.3.1) is one of the most commonly used enzymes in immunoassays. In VIDAS® assays (bioMérieux, Marcy l'Etoile, France), AP catalyzes the hydrolysis of 4-methylumbelliferyl phosphate (4-MUP) in 4-methylumbelliferone (4-MU) producing a fluorescent signal. This work introduces an original method of characterization of the kinetic parameters Km, Vmax, and Kcat of AP embedded in VIDAS® assays. Assessment of such constants allows us to predict the fluorescent signal generated for given amounts of enzyme and its associated substrate; in the particular case of VIDAS®, it has been estimated that 0.06 nmol/L of AP produces 3144 Relative Fluorescent Values (RFV). ABBREVIATIONS: 4-MUP, 4-Methylumbelliferyl phosphate; 4-MU, 4-Methylumbelliferone; RFV, Relative Fluorescent Values; RFU, Relative Fluorescent Units; QDs, Quantum Dots; LoD, Limit of Detection.

Low-to-moderate Reynolds number swirling flow in an annular channel with a rotating end wall.

This paper presents a new method for solving analytically the axisymmetric swirling flow generated in a finite annular channel from a rotating end wall, with no-slip boundary conditions along stationary side walls and a slip condition along the free surface opposite the rotating floor. In this case, the end-driven swirling flow can be described from the coupling between an azimuthal shear flow and a two-dimensional meridional flow driven by the centrifugal force along the rotating floor. A regular asymptotic expansion based on a small but finite Reynolds number is used to calculate centrifugation-induced first-order correction to the azimuthal Stokes flow obtained as the solution at leading order. For solving the first-order problem, the use of an integral boundary condition for the vorticity is found to be a convenient way to attribute boundary conditions in excess for the stream function to the vorticity. The annular geometry is characterized by both vertical and horizontal aspect ratios, whose respective influences on flow patterns are investigated. The vertical aspect ratio is found to involve nontrivial changes in flow patterns essentially due to the role of corner eddies located on the left and right sides of the rotating floor. The present analytical method can be ultimately extended to cylindrical geometries, irrespective of the surface opposite the rotating floor: a wall or a free surface. It can also serve as an analytical tool for monitoring confined rotating flows in applications related to surface viscosimetry or crystal growth from the melt.

Three-dimensional characterization of bacterial microcolonies on solid agar-based culture media.

For the last century, in vitro diagnostic process in microbiology has mainly relied on the growth of bacteria on the surface of a solid agar medium. Nevertheless, few studies focused in the past on the dynamics of microcolonies growth on agar surface before 8 to 10h of incubation. In this article, chromatic confocal microscopy has been applied to characterize the early development of a bacterial colony. This technology relies on a differential focusing depth of the white light. It allows one to fully measure the tridimensional shape of microcolonies more quickly than classical confocal microscopy but with the same spatial resolution. Placing the device in an incubator, the method was able to individually track colonies growing on an agar plate, and to follow the evolution of their surface or volume. Using an appropriate statistical modeling framework, for a given microorganism, the doubling time has been estimated for each individual colony, as well as its variability between colonies, both within and between agar plates. A proof of concept led on four bacterial strains of four distinct species demonstrated the feasibility and the interest of the approach. It showed in particular that doubling times derived from early tri-dimensional measurements on microcolonies differed from classical measurements in micro-dilutions based on optical diffusion. Such a precise characterization of the tri-dimensional shape of microcolonies in their late-lag to early-exponential phase could be beneficial in terms of in vitro diagnostics. Indeed, real-time monitoring of the biomass available in a colony could allow to run well established microbial identification workflows like, for instance, MALDI-TOF mass-spectrometry, as soon as a sufficient quantity of material is available, thereby reducing the time needed to provide a diagnostic. Moreover, as done for pre-identification of macro-colonies, morphological indicators such as three-dimensional growth profiles derived from microcolonies could be used to perform a first pre-identification step, but in a shorten time.