Effects of different salinity on the transcriptome and antibiotic resistance of two Vibrio parahaemolyticus strains isolated from Penaeus vannamei cultured in seawater and freshwater ponds

High salt condition alters LPS synthesis and induces the emergence of drug resistance mutations in Helicobacter pylori

The burgeoning emergence of drug-resistant Helicobacter pylori strains poses a significant challenge to the clinical success of eradication therapies and is primarily attributed to mutations within drug-targeting genes that lead to antibiotic resistance. This study investigated the effect of high salt conditions on the occurrence of drug-resistance mutations in H. pylori. We found that high salt condition significantly amplifies the frequency of drug resistance mutations in H. pylori. This can be chiefly attributed to our discovery indicating that high salt concentration results in elevated reactive oxygen species (ROS) levels, initiating DNA damage within H. pylori. Mechanistically, high salt condition suppresses lipopolysaccharide (LPS) synthesis gene expression, inducing alterations in the LPS structure and escalating outer membrane permeability. This disruption of LPS synthesis attenuates the expression and activity of SodB, facilitates increased ROS levels, and consequently increases the drug resistance mutation frequency. Impairing LPS synthesis engenders a reduction in intracellular iron levels, leading to diminished holo-Fur activity and increased apo-Fur activity, which represses the expression of SodB directly. Our findings suggest a correlation between high salt intake and the emergence of drug resistance in the human pathogen H. pylori, implying that dietary choices affect the risk of emergence of antimicrobial resistance.IMPORTANCEDrug resistance mutations mainly contribute to the emergence of clinical antibiotic-resistant Helicobacter pylori, a bacterium linked to stomach ulcers and cancer. In this study, we explored how elevated salt conditions influence the emergence of drug resistance in H. pylori. We demonstrate that H. pylori exhibits an increased antibiotic resistance mutation frequency when exposed to a high salt environment. We observed an increase in reactive oxygen species (ROS) under high salt conditions, which can cause DNA damage and potentially lead to mutations. Moreover, our results showed that high salt condition alters the bacterium's lipopolysaccharide (LPS) synthesis, leading to a reduced expression of SodB in a Fur-dependent manner. This reduction, in turn, elevates ROS levels, culminating in a higher frequency of drug-resistance mutations. Our research underscores the critical need to consider environmental influences, such as diet and lifestyle, in managing bacterial infections and combating the growing challenge of antibiotic resistance.

Fitness and transcriptomic analysis of pathogenic Vibrio parahaemolyticus in seawater at different shellfish harvesting temperatures

IMPORTANCE

Given the involvement of Vibrio parahaemolyticus (Vp) in a wide range of seafood outbreaks, a systematical characterization of Vp fitness and transcriptomic changes at temperatures of critical importance for seafood production and storage is needed. In this study, one of each virulent Vp strain (tdh+ and trh+) was tested. While no difference in survival behavior of the two virulent strains was observed at 10°C, the tdh+ strain had a faster growth rate than the trh+ strain at 30°C. Transcriptomic analysis showed that a significantly higher number of genes were upregulated at 30°C than at 10°C. The majority of differentially expressed genes of Vp at 30°C were annotated to functional categories supporting cellular growth. At 10°C, the downregulation of the biofilm formation and histidine metabolism indicates that the current practice of storing seafood at low temperatures not only protects seafood quality but also ensures seafood safety.

Antibiotic resistance genes prevalence prediction and interpretation in beaches affected by urban wastewater discharge

Background

The annual death toll of over 1.2 million worldwide is attributed to infections caused by resistant bacteria, driven by the significant impact of antibiotic misuse and overuse in spreading these bacteria and their associated antibiotic resistance genes (ARGs). While limited data suggest the presence of ARGs in beach environments, efficient prediction tools are needed for monitoring and detecting ARGs to ensure public health safety. This study aims to develop interpretable machine learning methods for predicting ARGs in beach waters, addressing the challenge of black-box models and enhancing our understanding of their internal mechanisms.

Methods

In this study, we systematically collected beach water samples and subsequently isolated bacteria from these samples using various differential and selective media supplemented with different antibiotics. Resistance profiles of bacteria were determined by using Kirby-Bauer disk diffusion method. Further, ARGs were enumerated by using the quantitative polymerase chain reaction (qPCR) to detect and quantify ARGs. The obtained qPCR data and hydro-meteorological were used to create an ML model with high prediction performance and we further used two explainable artificial intelligence (xAI) model-agnostic interpretation methods to describe the internal behavior of ML model.

Results

Using qPCR, we detected blaCTX-M, blaNDM, blaCMY, blaOXA, blatetX, blasul1, and blaaac(6'-Ib-cr) in the beach waters. Further, we developed ML prediction models for blaaac(6'-Ib-cr), blasul1, and blatetX using the hydro-metrological and qPCR-derived data and the models demonstrated strong performance, with R2 values of 0.957, 0.997, and 0.976, respectively.

Conclusions

Our findings show that environmental factors, such as water temperature, precipitation, and tide, are among the important predictors of the abundance of resistance genes at beaches.

Prediction and interpretation of antibiotic-resistance genes occurrence at recreational beaches using machine learning models

Antibiotic-resistant bacteria and antibiotic resistance genes (ARGs) are pollutants of worldwide concern that seriously threaten public health and ecosystems. Machine learning (ML) prediction models have been applied to predict ARGs in beach waters. However, the existing studies were conducted at a single location and had low prediction performance. Moreover, ML models are "black boxes" that do not reveal their predictions' internal nuances and mechanisms. This lack of transparency and trust can result in serious consequences when using these models in high-stakes decisions. In this study, we developed a gradient boosted regression tree based (GBRT) ML model and then described its behavior using six explainable artificial intelligence (XAI) model-agnostic explanation methods. We used hydro-meteorological and qPCR data from the beaches in South Korea and Pakistan and developed ML prediction models for aac (6'-lb-cr), sul1, and tetX with 10-fold time-blocked cross-validation performances of 4.9, 2.06 and 4.4 root mean squared logarithmic error, respectively. We then analyzed the local and global behavior of the developed ML model using four interpretation methods. The developed ML models showed that water temperature, precipitation and tide are the most important predictors for prediction of ARGs at recreational beaches. We show that the model-agnostic interpretation methods not only explain the behavior of the ML model but also provide insights into the behavior of the ML model under new unseen conditions. Moreover, these post-processing techniques can be a debugging tool for ML-based modeling.

Pathogenicity and transcriptome analysis of a strain of Vibrio owensii in Fenneropenaeus merguiensis

Vibrio is an important conditional pathogen in shrimp aquaculture. This research reported a dominant bacteria strain E1 isolated from a shrimp tank with the method of biofloc culture, which was further identified as Vibrio owensii. To understand the interaction between V. owensii and the host shrimp, we studied the pathogenicity of the V. owensii and the molecular mechanisms of the Fenneropenaeus merguiensis immunity during the Vibrio invasion. Drug susceptibility tests showed that V. owensii was resistant to antibiotics streptomycin oxacillin, tetracycline, minocycline, and aztreonam, but highly sensitive to cefazolin, cefotaxime, and ciprofloxacin, and moderately sensitive to cefotaxime, ampicillin, and piperacillin. Lethal concentration 50 (LC₅₀) test was performed to evaluate the toxicity of V. owensii to F. merguiensis. The LC₅₀ of V. owensii infected F. merguiensis after 24, 48, 72, 96, 120, 144 and 168 h were 1.21 × 10⁷, 1.68 × 10⁶, 6.36 × 10⁵, 2.15 × 10⁵, 7.58 × 10⁴, 5.55 × 10⁴ and 4.33 × 10⁴ CFU/mL. In order to explore the molecular response mechanism of F. merguiensis infected with V. owensii, the hepatopancreas of F. merguiensis were sequenced at 24 hpi and 48 hpi, and a total 40,181 of unigenes were obtained. Through comparative transcriptomic analysis, 86 differentially expressed genes (DEGs) (including 38 up-regulated DEGs, and 48 down-regulated DEGs) and 305 DEGs (including 150 up-regulated DEGs, and 155 down-regulated DEGs) were identified at 24 hpi and 48 hpi, respectively. Annotation and classification analysis of these 391 DEGs showed that most of the DEGs were annotated to metableolic and immune pathways, which indicated that F. merguiensis responded to the invasion through the regulation of material metableolism and immune system genes during V. owensii infection. In the KEGG enrichment analysis, some pathways related to immune response were significantly influenced by V. owensii infection, including phagosome, MAPK signalling pathway and PI3K-Akt signalling pathway. In addition, some pathways related to the warburg effect were also significantly enriched after V. owensii infection, including pyruvate metableolism, glycolysis/gluconeogenesis, and citrate cycle (TAC cycle). Further analysis showed that C-type lectins and ficolin were also play important roles in the immune response of F. merguiensis against V. owensii infection. The current research preliminarily revealed the immune response of F. merguiensis to V. owensii infection at the molecular level, which provided valuable information to further understand the disease control and the interaction between shrimp and Vibrio.

Transcriptomic Analysis of Vibrio parahaemolyticus Underlying the Wrinkly and Smooth Phenotypes

Vibrio parahaemolyticus, a causative agent of seafood-associated gastroenteritis, undergoes opaque-translucent (OP-TR) colony switching associated with capsular polysaccharide (CPS) production. Here, we showed that V. parahaemolyticus was also able to naturally and reversibly switch between wrinkly and smooth phenotypes. More than 1,000 genes were significantly differentially expressed during colony morphology switching, including the major virulence gene loci and key biofilm-related genes. The genes responsible for type III secretion system 1 (T3SS1), type VI secretion systems (T6SS1 and T6SS2), and flagellar synthesis were downregulated in the wrinkly spreader phenotype, whereas genes located on the pathogenicity island Vp-PAI and those responsible for chitin-regulated pili (ChiRP) and Syp exopolysaccharide synthesis were upregulated. In addition, we showed that the wrinkly spreader grew faster, had greater motility and biofilm capacities, and produced more c-di-GMP than the smooth type. A dozen genes potentially associated with c-di-GMP metabolism were shown to be significantly differentially expressed, which may account for the differences in c-di-GMP levels between the two phenotypes. Most importantly, dozens of putative regulators were significantly differentially expressed, and hundreds of noncoding RNAs were detected during colony morphology switching, indicating that phenotype switching is strictly regulated by a complex molecular regulatory network in V. parahaemolyticus. Taken together, the presented work highlighted the gene expression profiles related to wrinkly-smooth switching, showing that the significantly differentially expressed genes were involved in various biological behaviors, including virulence factor production, biofilm formation, metabolism, adaptation, and colonization. IMPORTANCE We showed that Vibrio parahaemolyticus was able to naturally and reversibly switch between wrinkly and smooth phenotypes and disclosed the gene expression profiles related to wrinkly-smooth switching, showing that the significantly differentially expressed genes between the two colony morphology phenotypes were involved in various biological behaviors, including virulence factor production, biofilm formation, metabolism, adaptation, and colonization.

Transcriptome Analysis to Study the Molecular Response in the Gill and Hepatopancreas Tissues of Macrobrachium nipponense to Salinity Acclimation

Macrobrachium nipponense is an economically important prawn species and common in Chinese inland capture fisheries. During aquaculture, M. nipponense can survive under freshwater and low salinity conditions. The molecular mechanism underlying the response to salinity acclimation remains unclear in this species; thus, in this study, we used the Illumina RNA sequencing platform for transcriptome analyses of the gill and hepatopancreas tissues of M. nipponense exposed to salinity stress [0.4‰ (S0, control group), 6‰ (S6, low salinity group), and 12‰ (S12, high salinity group)]. Differentially expressed genes were identified, and several important salinity adaptation-related terms and signaling pathways were found to be enriched, such as "ion transport," "oxidative phosphorylation," and "glycometabolism." Quantitative real-time PCR demonstrated the participation of 12 key genes in osmotic pressure regulation in M. nipponense under acute salinity stress. Further, the role of carbonic anhydrase in response to salinity acclimation was investigated by subjecting the gill tissues of M. nipponense to in situ hybridization. Collectively, the results reported herein enhance our understanding of the mechanisms via which M. nipponense adapts to changes in salinity.