Genetic and Phenotypic Diversity of Morganella morganii Isolated From Cheese

Genomic Analysis of Two Histamine-Producing Strains Isolated from Yellowfin Tuna

Psychrotrophic Morganella spp. is a typical histamine producer commonly found in seafood, exhibiting a high histamine-producing capacity. In this study, two strains of Morganella (GWT 902 and GWT 904) isolated from yellowfin tuna were subjected to phenotypic and genotypic characterization. Phenotypic analysis reveals differences in growth temperature, NaCl tolerance, and D-galactose fermentation capacity between the two strains. Notably, the histamine production capacity of GWT 902 is significantly higher than that of GWT 904 at 4 °C. The complete genome sequences of strains GWT 902 and GWT 904 were sequenced, identifying GWT 902 as Morganella psychrotolerans and GWT 904 as Morganella morganii subsp. sibonii. Genomic analysis confirms the presence of histidine decarboxylase gene clusters (hdcT1, hdc, hdcT2, hisRS) in both strains, and sequence alignment shows that the amino acid sequence similarity of histidine decarboxylase encoded by the hdc gene was 95.24%. Gene function analysis further identified genes associated with putrescine biosynthesis, sulfur metabolism, lipase and protease secretion, and detected key genes in quorum sensing (QS), stress adaptation, and antibiotic resistance. This study provides valuable insights into the taxonomic analysis of psychrotrophic Morganella spp. and contributes to the development of efficient strategies for preventing histamine formation in seafood.

Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production

The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. These methods could be used to identify ingredients that deviate from their typical microbial composition, which could indicate food fraud or safety issues. The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive principal component analysis (PCA), cluster-based methods, and explainable artificial intelligence (AI) were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline (BL) samples collected under comparable circumstances. Traditional methods (alpha and beta diversity, clustering-based contrastive PCA, multidimensional scaling, and dendrograms) failed to differentiate anomalous sample classes; however, explainable AI was able to classify anomalous vs baseline samples and indicate microbial drivers in association with antibiotic use. We validated the potential for explainable AI to classify different milk sources using larger publicly available fluid milk 16S rDNA sequencing data sets and demonstrated that explainable AI is able to differentiate between milk storage methods, processing stages, and seasons. Our results indicate that the application of artificial intelligence continues to hold promise in the realm of microbiome data analysis and could present further opportunities for downstream analytic automation to aid in food safety and quality.

IMPORTANCE

We evaluated the feasibility of using untargeted metagenomic sequencing of raw milk for detecting anomalous food ingredient content with artificial intelligence methods in a study specifically designed to test this hypothesis. We also show through analysis of publicly available fluid milk microbial data that our artificial intelligence approach is able to successfully predict milk in different stages of processing. The approach could potentially be applied in the food industry for safety and quality control.

Tracing the possible evolutionary trends of Morganella morganii: insights from molecular epidemiology and phylogenetic analysis

Morganella morganii, encompassing two subspecies, subsp. morganii and subsp. sibonii, is a common opportunistic pathogen, notable for intrinsic resistance to multiple antimicrobial agents. Despite its clinical significance, research into the potential evolutionary dynamics of M. morganii remains limited. This study involved the analysis of genome sequences from 431 M. morganii isolates, comprising 206 isolates that cause host infections, obtained from this study and 225 from the NCBI genome data sets. A diverse array of antimicrobial resistance genes (ARGs) was identified in M. morganii isolates, including mcr-1, tet(X4), tmexCD-toprJ, and various carbapenemase genes. In addition, a novel blaKPC-2-bearing plasmid with demonstrated conjugative capability was discovered in M. morganii. The majority of virulence-related genes (VRGs), except for the hlyCABD gene cluster, were found in almost all M. morganii. Three novel genospecies of M. morganii were identified, designated as M. chanii, M. variant1, and M. variant2. Compared to M. sibonii, M. chanii genospecies possessed a greater number of flagellar-related genes, typically located within mobile genetic elements (MGEs), suggesting potential for better environmental adaptability. Phylogenetic analysis further disclosed that M. morganii was divided into 12 sequence clusters (SCs). Particularly, SC9 harbored an elevated abundance of ARGs and VRGs, mainly toxin-related genes, and was associated with a higher presence of MGEs compared to non-SC9 strains. The collective findings suggest that M. morganii undergoes evolution driven by the influence of MGEs, thereby significantly enhancing its adaptability to selective pressures of environmental changes and clinical antimicrobial agents.IMPORTANCEThe growing clinical significance of Morganella morganii arises from its abundant virulence factors and antimicrobial resistance genes, resulting in elevated infection rates and increased clinical scrutiny. However, research on the molecular epidemiology and evolutionary trends of M. morganii has been scarce. Our study established a list of virulence-related genes (VRGs) for M. morganii and conducted a large-scale epidemiological investigation into these VRGs. Based on genomic classification, three novel genotypes of M. morganii were identified, representing evolutionary adaptations and responses to environmental challenges. Furthermore, we discovered the emergence of a sequence cluster enriched with antimicrobial resistance genes, VRGs, and mobile genetic elements, attributed to the selective pressure of antimicrobial agents. In addition, we identified a novel conjugative plasmid harboring the blaKPC-2 gene. These findings hold significance in monitoring and comprehending the epidemiology of M. morganii.

New insights into the toxicological effects of dietary biogenic amines

Biogenic amines (BA) are molecules with biological functions, which can accumulate at toxic concentrations in foods. Several microorganisms have been identified as responsible for their accumulation at elevated concentrations. Histamine, tyramine and putrescine are the BA most commonly found at highest concentrations. The ingestion of food containing high BA concentrations leads to intoxication with symptoms depending on the BA and the amount consumed. Moreover, there is evidence of synergy between different BA, something of toxicological importance given that some foods accumulate different BA. This work reviews the BA toxic effects and examines recent discoveries regarding their synergy, cytotoxicity and genotoxicity. These advances in the toxicological consequences of ingesting BA contaminated foods support the need to regulate their presence in foods to preserve the consumer's health. However, more research efforts -focused on the establishment of risk assessments- are needed to reach a consensus in their limits in different food matrices.

The Microbial Diversity on the Surface of Smear-Ripened Cheeses and Its Impact on Cheese Quality and Safety

Smear-ripened cheeses are characterized by a viscous, red-orange surface smear on their rind. It is the complex surface microbiota on the cheese rind that is responsible for the characteristic appearance of this cheese type, but also for the wide range of flavors and textures of the many varieties of smear-ripened cheeses. The surface smear microbiota also represents an important line of defense against the colonization with undesirable microorganisms through various types of interaction, such as competitive exclusion or production of antimicrobial substances. Predominant members of the surface smear microbiota are salt-tolerant yeast and bacteria of the phyla Actinobacteria, Firmicutes, and Proteobacteria. In the past, classical culture-based approaches already shed light on the composition and succession of microorganisms and their individual contribution to the typicity of this cheese type. However, during the last decade, the introduction and application of novel molecular approaches with high-resolution power provided further in-depth analysis and, thus, a much more detailed view of the composition, structure, and diversity of the cheese smear microbiota. This led to abundant novel knowledge, such as the identification of so far unknown community members. Hence, this review is summarizing the current knowledge of the diversity of the surface smear microbiota and its contribution to the quality and safety of smear-ripened cheese. If the succession or composition of the surface-smear microbiota is disturbed, cheese smear defects might occur, which may promote food safety issues. Hence, the discussion of cheese smear defects in the context of an increased understanding of the intricate surface smear ecosystem in this review may not only help in troubleshooting and quality control but also paves the way for innovations that can lead to safer, more consistent, and higher-quality smear-ripened cheeses.

Sequencing and Characterization of M. morganii Strain UM869: A Comprehensive Comparative Genomic Analysis of Virulence, Antibiotic Resistance, and Functional Pathways

Morganella morganii is a Gram-negative opportunistic Enterobacteriaceae pathogen inherently resistant to colistin. This species causes various clinical and community-acquired infections. This study investigated the virulence factors, resistance mechanisms, functional pathways, and comparative genomic analysis of M. morganii strain UM869 with 79 publicly available genomes. The multidrug resistance strain UM869 harbored 65 genes associated with 30 virulence factors, including efflux pump, hemolysin, urease, adherence, toxin, and endotoxin. Additionally, this strain contained 11 genes related to target alteration, antibiotic inactivation, and efflux resistance mechanisms. Further, the comparative genomic study revealed a high genetic relatedness (98.37%) among the genomes, possibly due to the dissemination of genes between adjoining countries. The core proteome of 79 genomes contains the 2692 core, including 2447 single-copy orthologues. Among them, six were associated with resistance to major antibiotic classes manifested through antibiotic target alteration (PBP3, gyrB) and antibiotic efflux (kpnH, rsmA, qacG; rsmA; CRP). Similarly, 47 core orthologues were annotated to 27 virulence factors. Moreover, mostly core orthologues were mapped to transporters (n = 576), two-component systems (n = 148), transcription factors (n = 117), ribosomes (n = 114), and quorum sensing (n = 77). The presence of diversity in serotypes (type 2, 3, 6, 8, and 11) and variation in gene content adds to the pathogenicity, making them more difficult to treat. This study highlights the genetic similarity among the genomes of M. morganii and their restricted emergence, mostly in Asian countries, in addition to their growing pathogenicity and resistance. However, steps must be taken to undertake large-scale molecular surveillance and to direct suitable therapeutic interventions.

Antibiotic-Resistant Bacteria Dissemination in the Wildlife, Livestock, and Water of Maiella National Park, Italy

Antimicrobial resistance (AMR) is a global health concern that has been linked to humans, animals, and the environment. The One Health approach highlights the connection between humans, animals, and the environment and suggests that a multidisciplinary approached be used in studies investigating AMR. The present study was carried out to identify and characterize the antimicrobial resistance profiles of bacteria isolated from wildlife and livestock feces as well as from surface water samples in Maiella National Park, Italy. Ecological and georeferenced data were used to select two sampling locations, one where wildlife was caught within livestock grazing areas (sympatric group) and one where wildlife was caught outside of livestock grazing areas (non-sympatric group). Ninety-nine bacterial isolates from 132 feces samples and seven isolates from five water samples were collected between October and December 2019. The specimens were examined for species identification, antibiotic susceptibility and molecular detection of antibiotic resistance. Forty isolates were identified as Escherichia coli, forty-eight as Enterococcus spp., eight as Streptococcus spp. and ten as other gram-negative bacteria. Phenotypic antibiotic resistance to at least one antimicrobial agent, including some antibiotics that play a critical role in human medicine, was detected in 36/106 (33.9%, 95% CI: 25-43) isolates and multidrug resistance was detected in 9/106 isolates (8.49%, 95% CI: 3.9-15.5). In addition, genes associated with antibiotic resistance were identified in 61/106 (57.55%, 95% CI: 47.5-67) isolates. The samples from sympatric areas were 2.11 (95% CI: 1.2-3.5) times more likely to contain resistant bacterial isolates than the samples from non-sympatric areas. These data suggest that drug resistant bacteria may be transmitted in areas where wildlife and livestock cohabitate. This emphasizes the need for further investigations focusing on the interactions between humans, wildlife, and the environment, the results of which can aid in the early detection of emerging AMR profiles and possible transmission routes.