Comparing human-Salmonella with plant-Salmonella protein-protein interaction predictions

Isolation and Identification of Lactic Acid Bacteria Probiotic Culture Candidates for the Treatment of Salmonella enterica Serovar Enteritidis in Neonatal Turkey Poults

The effect of Lactobacillus spp.-based probiotic candidates on Salmonella enterica serovar Enteritidis (SE) colonization was evaluated in two separate experiments. In each experiment, sixty-one day-of-hatch female turkey poults were obtained from a local hatchery. In both experiments, poults were challenged via oral gavage with 10⁴ cfu/poult of SE and randomly allocated to one of two groups (n = 30 poults): (1) the positive control group and (2) the probiotic treated group. Heated brooder batteries were used for housing each group separately and poults were allowed ad libitum access to water and unmedicated turkey starter feed. 1 h following the SE challenge, poults were treated with 10⁶ cfu/poult of probiotic culture via oral gavage or phosphate-buffered saline （PBS）to control groups. A total of 24 h post-treatment, poults were euthanized and the ceca and cecal tonsils from twenty poults were collected aseptically for SE recovery. In both trials, a significant reduction in the incidence and log₁₀ cfu/g of SE were observed in poults treated with the probiotic when compared with control poults (p ≤ 0.05). The results of the present study suggest that the administration of this lactic acid-producing bacteria (LAB)-based probiotic 1 h after an SE challenge can be useful in reducing the cecal colonization of this pathogen in neonatal poults.

Controversy Surrounding the Function of SpiC Protein in Salmonella: An Overview

Salmonella is an important pathogenic microorganism that can infect humans and animals and has been studied globally as a model microorganism for its pathogenesis. The SpiC protein of T3SS2 is a significant factor that has been studied for almost 20 years, but to date, the function/effect of SpiC in the pathogenesis of Salmonella has not been completely understood. There is controversy over the functions of SpiC protein in the literature. Thus, an overview of the literature on SpiC protein is provided here which highlights expression features of SpiC protein and its various functions and effect.

Influence of prgH on the Persistence of Ingested Salmonella enterica in the Leafhopper Macrosteles quadrilineatus

Phytophagous insects can encounter Salmonella enterica on contaminated plant surfaces and transmit externally adhered and internalized bacteria on and among leaves. Excretion of ingested S. enterica by the leafhopper Macrosteles quadrilineatus has been previously reported; however, the sites of persistence of ingested bacteria remain undetermined. Fluorescence microscopy revealed the presence and persistence of S. enterica in various organs of M. quadrilineatus fed an inoculated diet for 12 h and then moved to two consecutive noninoculated diets for a total of 48 h. Ingested S. enterica was predominantly observed in the filter chamber, midgut, and Malpighian tubules of M. quadrilineatus dissected immediately after acquisition and at 24- and 48-h post-acquisition access periods (post-AAPs). Additionally, we examined the potential roles of the Salmonella pathogenicity island 1 (SPI-1) and SPI-2 type III secretion systems (T3SSs) in the persistence and excretion of ingested S. enterica. In competition assays, a prgH mutant lacking a functional SPI-1 T3SS was recovered at significantly lower levels than the WT in insect homogenates at 24 h post-AAP, and complementation with prgH restored S. enterica persistence in M. quadrilineatus. Moreover, expression of prgH inside M. quadrilineatus was observed up to 48 post-AAP. No differences were observed between the WT and an ssaK mutant lacking a functional SPI-2 T3SS in insect homogenates or between the WT and either mutant in insect excretions. This study provides novel insight into the presence and persistence of S. enterica inside M. quadrilineatus and demonstrates that the SPI-1 T3SS influences the persistence of the pathogen in the gut of a potential vector.

Computational approaches for prediction of pathogen-host protein-protein interactions

Infectious diseases are still among the major and prevalent health problems, mostly because of the drug resistance of novel variants of pathogens. Molecular interactions between pathogens and their hosts are the key parts of the infection mechanisms. Novel antimicrobial therapeutics to fight drug resistance is only possible in case of a thorough understanding of pathogen-host interaction (PHI) systems. Existing databases, which contain experimentally verified PHI data, suffer from scarcity of reported interactions due to the technically challenging and time consuming process of experiments. These have motivated many researchers to address the problem by proposing computational approaches for analysis and prediction of PHIs. The computational methods primarily utilize sequence information, protein structure and known interactions. Classic machine learning techniques are used when there are sufficient known interactions to be used as training data. On the opposite case, transfer and multitask learning methods are preferred. Here, we present an overview of these computational approaches for predicting PHI systems, discussing their weakness and abilities, with future directions.

Techniques for transferring host-pathogen protein interactions knowledge to new tasks

We consider the problem of building a model to predict protein-protein interactions (PPIs) between the bacterial species Salmonella Typhimurium and the plant host Arabidopsis thaliana which is a host-pathogen pair for which no known PPIs are available. To achieve this, we present approaches, which use homology and statistical learning methods called “transfer learning.” In the transfer learning setting, the task of predicting PPIs between Arabidopsis and its pathogen S. Typhimurium is called the “target task.” The presented approaches utilize labeled data i.e., known PPIs of other host-pathogen pairs (we call these PPIs the “source tasks”). The homology based approaches use heuristics based on biological intuition to predict PPIs. The transfer learning methods use the similarity of the PPIs from the source tasks to the target task to build a model. For a quantitative evaluation we consider Salmonella-mouse PPI prediction and some other host-pathogen tasks where known PPIs exist. We use metrics such as precision and recall and our results show that our methods perform well on the target task in various transfer settings. We present a brief qualitative analysis of the Arabidopsis-Salmonella predicted interactions. We filter the predictions from all approaches using Gene Ontology term enrichment and only those interactions involving Salmonella effectors. Thereby we observe that Arabidopsis proteins involved e.g., in transcriptional regulation, hormone mediated signaling and defense response may be affected by Salmonella.