What is Phase in Cellular Clocks?

Four inter-related measures of phase are described to study the phase synchronization of cellular oscillators, and computation of these measures is described and illustrated on single cell fluorescence data from the model filamentous fungus, Neurospora crassa. One of these four measures is the phase shift ϕ in a sinusoid of the form x(t) = A(cos(ωt + ϕ), where t is time. The other measures arise by creating a replica of the periodic process x(t) called the Hilbert transform x̃(t), which is 90 degrees out of phase with the original process x(t). The second phase measure is the phase angle FH(t) between the replica x̃(t) and x(t), taking values between -π and π. At extreme values the Hilbert Phase is discontinuous, and a continuous form FC(t) of the Hilbert Phase is used, measuring time on the nonnegative real axis (t). The continuous Hilbert Phase FC(t) is used to define the phase MC(t1,t0) for an experiment beginning at time t0 and ending at time t1. In that phase differences at time t0 are often of ancillary interest, the Hilbert Phase FC(t0) is subtracted from FC(t1). This difference is divided by 2π to obtain the phase MC(t1,t0) in cycles. Both the Hilbert Phase FC(t) and the phase MC(t1,t0) are functions of time and useful in studying when oscillators phase-synchronize in time in signal processing and circadian rhythms in particular. The phase of cellular clocks is fundamentally different from circadian clocks at the macroscopic scale because there is an hourly cycle superimposed on the circadian cycle.

Selective Antagonism of Lactiplantibacillus plantarum and Pediococcus acidilactici against Vibrio and Aeromonas in the Bacterial Community of Artemia nauplii.

Empiric probiotics are commonly consumed by healthy individuals as a means of disease prevention, pathogen control, etc. However, controversy has existed for a long time regarding the safety and benefits of probiotics. Here, two candidate probiotics, Lactiplantibacillus plantarum and Pediococcus acidilactici, which are antagonistic to Vibrio and Aeromonas species in vitro, were tested on Artemia under in vivo conditions. In the bacterial community of Artemia nauplii, L. plantarum reduced the abundance of the genera Vibrio and Aeromonas and P. acidilactici significantly increased the abundance of Vibrio species in a positive dosage-dependent manner, while higher and lower dosages of P. acidilactici increased and decreased the abundance of the genus Aeromonas, respectively. Based on the liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) analyses of the metabolite of L. plantarum and P. acidilactici, pyruvic acid was used in an in vitro test to explain such selective antagonism; the results showed that pyruvic acid was conducive or suppressive to V. parahaemolyticus and beneficial to A. hydrophila. Collectively, the results of this study demonstrate the selective antagonism of probiotics on the bacterial community composition of aquatic organisms and the associated pathogens. IMPORTANCE Over the last decade, the common preventive method for controlling potential pathogens in aquaculture has been the use of probiotics. However, the mechanisms of probiotics are complicated and mostly undefined. At present, less attention has been paid to the potential risks of probiotic use in aquaculture. Here, we investigated the effects of two candidate probiotics, L. plantarum and P. acidilactici, on the bacterial community of Artemia nauplii and the in vitro interactions between these two candidate probiotics and two pathogens, Vibrio and Aeromonas species. The results demonstrated the selective antagonism of probiotics on the bacterial community composition of an aquatic organism and its associated pathogens. This research contributes to providing a basis and reference for the long-term rational use of probiotics and to reducing the inappropriate use of probiotics in aquaculture.

An open source 16-channel fluidics system for automating sequential fluorescent in situ hybridization (FISH)-based imaging.

Fluorescent in situ hybridization (FISH) can provide spatial information about DNA/RNA targets in fixed cells and tissues. However, the workflows of multiplexed FISH-based imaging that use sequential rounds of hybridization quickly become laborious as the number of rounds increases because of liquid handling demands. Here, we present an open-source and low-cost fluidics system that is purpose built for automating the workflows of sequential FISH-based imaging. Our system features a fluidics module with 16 addressable channels in which flow is positive pressure-driven and switched on/off by solenoid valves in order to transfer FISH reagents to the sample. Our system also includes a controller with a main printed circuit board that can control up to 120 solenoid valves and allows users to control the fluidics module via serial communication. We demonstrate the automatic and robust fluid exchange with this system by targeting the alpha satellite repeat in HeLa cell with 14 rounds of sequential hybridization and imaging. We anticipate that this simple and flexible system will be of utility to researchers performing multiplexed in situ assays in a range of experimental systems.

Synchronizing stochastic circadian oscillators in single cells of Neurospora crassa.

The synchronization of stochastic coupled oscillators is a central problem in physics and an emerging problem in biology, particularly in the context of circadian rhythms. Most measurements on the biological clock are made at the macroscopic level of millions of cells. Here measurements are made on the oscillators in single cells of the model fungal system, Neurospora crassa, with droplet microfluidics and the use of a fluorescent recorder hooked up to a promoter on a clock controlled gene-2 (ccg-2). The oscillators of individual cells are stochastic with a period near 21 hours (h), and using a stochastic clock network ensemble fitted by Markov Chain Monte Carlo implemented on general-purpose graphical processing units (or GPGPUs) we estimated that >94% of the variation in ccg-2 expression was stochastic (as opposed to experimental error). To overcome this stochasticity at the macroscopic level, cells must synchronize their oscillators. Using a classic measure of similarity in cell trajectories within droplets, the intraclass correlation (ICC), the synchronization surface ICC is measured on >25,000 cells as a function of the number of neighboring cells within a droplet and of time. The synchronization surface provides evidence that cells communicate, and synchronization varies with genotype.