Analysis of temporal gene regulation of Listeria monocytogenes revealed distinct regulatory response modes after exposure to high pressure processing

Constrained Fourier estimation of short-term time-series gene expression data reduces noise and improves clustering and gene regulatory network predictions

BACKGROUND

Biological data suffers from noise that is inherent in the measurements. This is particularly true for time-series gene expression measurements. Nevertheless, in order to to explore cellular dynamics, scientists employ such noisy measurements in predictive and clustering tools. However, noisy data can not only obscure the genes temporal patterns, but applying predictive and clustering tools on noisy data may yield inconsistent, and potentially incorrect, results.

RESULTS

To reduce the noise of short-term (< 48 h) time-series expression data, we relied on the three basic temporal patterns of gene expression: waves, impulses and sustained responses. We constrained the estimation of the true signals to these patterns by estimating the parameters of first and second-order Fourier functions and using the nonlinear least-squares trust-region optimization technique. Our approach lowered the noise in at least 85% of synthetic time-series expression data, significantly more than the spline method ([Formula: see text]). When the data contained a higher signal-to-noise ratio, our method allowed downstream network component analyses to calculate consistent and accurate predictions, particularly when the noise variance was high. Conversely, these tools led to erroneous results from untreated noisy data. Our results suggest that at least 5-7 time points are required to efficiently de-noise logarithmic scaled time-series expression data. Investing in sampling additional time points provides little benefit to clustering and prediction accuracy.

CONCLUSIONS

Our constrained Fourier de-noising method helps to cluster noisy gene expression and interpret dynamic gene networks more accurately. The benefit of noise reduction is large and can constitute the difference between a successful application and a failing one.

Landscape of Stress Response and Virulence Genes Among Listeria monocytogenes Strains

The pathogenic microorganism Listeria monocytogenes is ubiquitous and responsible for listeriosis, a disease with a high mortality rate in susceptible people. It can persist in different habitats, including the farm environment, the food production environments, and in foods. This pathogen can grow under challenging conditions, such as low pH, low temperatures, and high salt concentrations. However, L. monocytogenes has a high degree of strain divergence regarding virulence potential, environmental adaption, and stress response. This review seeks to provide the reader with an up-to-date overview of clonal and serotype-specific differences among L. monocytogenes strains. Emphasis on the genes and genomic islands responsible for virulence and resistance to environmental stresses is given to explain the complex adaptation among L. monocytogenes strains. Moreover, we highlight the use of advanced diagnostic technologies, such as whole-genome sequencing, to fine-tune quantitative microbiological risk assessment for better control of listeriosis.

A Diffusion Model to Quantify Membrane Repair Process in Listeria monocytogenes Exposed to High Pressure Processing Based on Fluorescence Microscopy Data

The effects of environmental stresses on microorganisms have been well-studied, and cellular responses to stresses such as heat, cold, acids, and salts have been extensively discussed. Although high pressure processing (HPP) is becoming more popular as a preservation method in the food industry, the characteristics of the cellular damage caused by high pressure are unclear, and the microbial response to this stress has not yet been well-explored. We exposed the pathogen Listeria monocytogenes to HPP (400 MPa, 8 min, 8°C) and found that the high pressure created plasma membrane pores. Using a common staining technique involving propidium iodide (PI) combined with high-frequency fluorescence microscopy, we monitored the rate of diffusion of PI molecules into hundreds of bacterial cells through these pores on days 0, 1, 2, 3, and 4 after pressurization. We also developed a mathematical dynamic model based on mass transfer and passive diffusion laws, calibrated using our microscopy experiments, to evaluate the response of bacteria to HPP. We found that the rate of diffusion of PI into the cells decreased over the 4 consecutive days after exposure to HPP, indicating repair of the pressure-created membrane pores. The model suggested a temporal change in the size of pores until closure. To the best of our knowledge, this is the first time that pressure-created membrane pores have been quantitatively described and shown to diminish with time. In addition, we found that the membrane repair rate in response to HPP was linear, and growth was temporarily arrested at the population level during the repair period. These results support the existence of a progressive repair process in some of the cells that take up PI, which can therefore be considered as being sub-lethally injured rather than dead. Hence, we showed that a subgroup of bacteria survived HPP and actively repaired their membrane pores.