Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes

Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations

Environmental perturbations are encountered by microorganisms regularly and will require metabolic adaptations to ensure an organism can survive in the newly presenting conditions. In order to study the mechanisms of metabolic adaptation in such conditions, various experimental and computational approaches have been used. Genome-scale metabolic models (GEMs) are one of the most powerful approaches to study metabolism, providing a platform to study the systems level adaptations of an organism to different environments which could otherwise be infeasible experimentally. In this review, we are describing the application of GEMs in understanding how microbes reprogram their metabolic system as a result of environmental variation. In particular, we provide the details of metabolic model reconstruction approaches, various algorithms and tools for model simulation, consequences of genetic perturbations, integration of '-omics' datasets for creating context-specific models and their application in studying metabolic adaptation due to the change in environmental conditions.

Integrating proteomic data with metabolic modeling provides insight into key pathways of Bordetella pertussis biofilms

Pertussis, commonly known as whooping cough is a severe respiratory disease caused by the bacterium, Bordetella pertussis. Despite widespread vaccination, pertussis resurgence has been observed globally. The development of the current acellular vaccine (ACV) has been based on planktonic studies. However, recent studies have shown that B. pertussis readily forms biofilms. A better understanding of B. pertussis biofilms is important for developing novel vaccines that can target all aspects of B. pertussis infection. This study compared the proteomic expression of biofilm and planktonic B. pertussis cells to identify key changes between the conditions. Major differences were identified in virulence factors including an upregulation of toxins (adenylate cyclase toxin and dermonecrotic toxin) and downregulation of pertactin and type III secretion system proteins in biofilm cells. To further dissect metabolic pathways that are altered during the biofilm lifestyle, the proteomic data was then incorporated into a genome scale metabolic model using the Integrative Metabolic Analysis Tool (iMAT). The generated models predicted that planktonic cells utilised the glyoxylate shunt while biofilm cells completed the full tricarboxylic acid cycle. Differences in processing aspartate, arginine and alanine were identified as well as unique export of valine out of biofilm cells which may have a role in inter-bacterial communication and regulation. Finally, increased polyhydroxybutyrate accumulation and superoxide dismutase activity in biofilm cells may contribute to increased persistence during infection. Taken together, this study modeled major proteomic and metabolic changes that occur in biofilm cells which helps lay the groundwork for further understanding B. pertussis pathogenesis.

TMT-Based Quantitative Proteomic Analysis of Intestinal Organoids Infected by Listeria monocytogenes Strains with Different Virulence

L. monocytogenes, consisting of 13 serotypes, is an opportunistic food-borne pathogen that causes different host reactions depending on its serotypes. In this study, highly toxic L. monocytogenes 10403s resulted in more severe infections and lower survival rates. Additionally, to investigate the remodeling of the host proteome by strains exhibiting differential toxicity, the cellular protein responses of intestinal organoids were analyzed using tandem mass tag (TMT) labeling and high-performance liquid chromatography−mass spectrometry. The virulent strain 10403s caused 102 up-regulated and 52 down-regulated proteins, while the low virulent strain M7 caused 188 up-regulated and 25 down-regulated proteins. Based on the analysis of gene ontology (GO) and KEGG databases, the expressions of differential proteins in organoids infected by L. monocytogenes 10403s (virulent strain) or M7 (low virulent strain) were involved in regulating essential processes such as the biological metabolism, the energy metabolism, and immune system processes. The results showed that the immune system process, as the primary host defense response to L. monocytogenes, comprised five pathways, including ECM−receptor interaction, the complement and coagulation cascades, HIF-1, ferroptosis, and NOD-like receptor signaling pathways. As for the L. monocytogenes 10403s vs. M7 group, the expression of differential proteins was involved in two pathways: systemic lupus erythematosus and transcriptional mis-regulation in cancer. All in all, these results revealed that L. monocytogenes strains with different toxicity induced similar biological functions and immune responses while having different regulations on differential proteins in the pathway.

Single and multiple detections of foodborne pathogens by gold nanoparticle assays

A late detection of pathogenic microorganisms in food and drinking water has a high potential to cause adverse health impacts in those who have ingested the pathogens. For this reason there is intense interest in developing precise, rapid and sensitive assays that can detect multiple foodborne pathogens. Such assays would be valuable components in the campaign to minimize foodborne illness. Here, we discuss the emerging types of assays based on gold nanoparticles (GNPs) for rapidly diagnosing single or multiple foodborne pathogen infections. Colorimetric and lateral flow assays based on GNPs may be read by the human eye. Refractometric sensors based on a shift in the position of a plasmon resonance absorption peak can be read by the new generation of inexpensive optical spectrometers. Surface-enhanced Raman spectroscopy and the quartz microbalance require slightly more sophisticated equipment but can be very sensitive. A wide range of electrochemical techniques are also under development. Given the range of options provided by GNPs, we confidently expect that some, or all, of these technologies will eventually enter routine use for detecting pathogens in food. This article is categorized under: Diagnostic Tools > Biosensing.

Establishment of Listeria monocytogenes in the Gastrointestinal Tract

Listeria monocytogenes is a Gram positive foodborne pathogen that can colonize the gastrointestinal tract of a number of hosts, including humans. These environments contain numerous stressors such as bile, low oxygen and acidic pH, which may impact the level of colonization and persistence of this organism within the GI tract. The ability of L. monocytogenes to establish infections and colonize the gastrointestinal tract is directly related to its ability to overcome these stressors, which is mediated by the efficient expression of several stress response mechanisms during its passage. This review will focus upon how and when this occurs and how this impacts the outcome of foodborne disease.