Large-Scale Field Trials of an Eimeria Vaccine Induce Positive Effects on the Production Index of Broilers.

Live coccidiosis vaccines have mainly been used to reduce Eimeria species infection, which is considered the most economically important disease in the poultry industry. Evaluation data on vaccine effectiveness through large-scale field experiments are lacking, especially in broilers. Thus, the effectiveness of a commercial coccidiosis vaccine was evaluated in approximately 900,000 chicks reared on three open-broiler farms where coccidiosis is prevalent. The vaccine's effectiveness after vaccination of 1-day-old chicks was monitored using three parameters (lesion score, fecal oocyst shedding, and production index, PI) in nine trials performed three times on each farm. Lesion scores were confirmed in three different areas of the intestine because the vaccine contained four Eimeria species. The average lesion scores were 0.36 to 0.64 in the duodenal region, 0.30 to 0.39 in the jejuno-ileal region, and 0.18 to 0.39 in the cecal region. The average fecal oocyst shedding rate ranged from 19,766 to 100,100 oocysts per gram, showing large variations depending on farms and buildings within the farm. Compared with the PI of the previous 9-10 trials on each farm, the PI increased by 2.45 to 23.55. Because of the potential for perturbation of the fecal microbiota by live coccidiosis vaccines, the fecal microbiota was investigated using 16S rRNA microbial profiling. Although the ß-diversity was significantly different in distribution and relative abundance among farms (PERMANOVA, pseudo-F = 4.863, p = 0.009), a Kyoto Encyclopedia of Genes and Genomes pathway analysis found no significant bacterial invasion of the epithelial cell pathway across farms. This large-scale field trial of a live Eimeria vaccine indicates that coccidiosis vaccines can have meaningful effects on the poultry industry and could be used as an alternative to the prophylactic use of anticoccidial drugs under field conditions.

Combining machine learning with high-content imaging to infer ciprofloxacin susceptibility in isolates of Salmonella Typhimurium.

Antimicrobial resistance (AMR) is a growing public health crisis that requires innovative solutions. Current susceptibility testing approaches limit our ability to rapidly distinguish between antimicrobial-susceptible and -resistant organisms. Salmonella Typhimurium (S. Typhimurium) is an enteric pathogen responsible for severe gastrointestinal illness and invasive disease. Despite widespread resistance, ciprofloxacin remains a common treatment for Salmonella infections, particularly in lower-resource settings, where the drug is given empirically. Here, we exploit high-content imaging to generate deep phenotyping of S. Typhimurium isolates longitudinally exposed to increasing concentrations of ciprofloxacin. We apply machine learning algorithms to the imaging data and demonstrate that individual isolates display distinct growth and morphological characteristics that cluster by time point and susceptibility to ciprofloxacin, which occur independently of ciprofloxacin exposure. Using a further set of S. Typhimurium clinical isolates, we find that machine learning classifiers can accurately predict ciprofloxacin susceptibility without exposure to it or any prior knowledge of resistance phenotype. These results demonstrate the principle of using high-content imaging with machine learning algorithms to predict drug susceptibility of clinical bacterial isolates. This technique may be an important tool in understanding the morphological impact of antimicrobials on the bacterial cell to identify drugs with new modes of action.

Identification of Critical Immune Regulators and Potential Interactions of IL-26 in Riemerella anatipestifer-Infected Ducks by Transcriptome Analysis and Profiling.

Riemerella anatipestifer (RA) is an economically important pathogen in the duck industry worldwide that causes high mortality and morbidity in infected birds. We previously found that upregulated IL-17A expression in ducks infected with RA participates in the pathogenesis of the disease, but this mechanism is not linked to IL-23, which primarily promotes Th17 cell differentiation and proliferation. RNA sequencing analysis was used in this study to investigate other mechanisms of IL-17A upregulation in RA infection. A possible interaction of IL-26 and IL-17 was discovered, highlighting the potential of IL-26 as a novel upstream cytokine that can regulate IL-17A during RA infection. Additionally, this process identified several important pathways and genes related to the complex networks and potential regulation of the host immune response in RA-infected ducks. Collectively, these findings not only serve as a roadmap for our understanding of RA infection and the development of new immunotherapeutic approaches for this disease, but they also provide an opportunity to understand the immune system of ducks.

Comparative Analysis of Antibiotic Resistance and Biofilm Characteristics of Two Major Enterococcus Species from Poultry Slaughterhouses in South Korea.

The spread of antibiotic-resistant Enterococcus in the poultry industry poses significant public health challenges due to multidrug resistance and biofilm formation. We investigated the antibiotic resistance profiles and biofilm characteristics of E. faecalis and E. faecium isolates from chicken meat in poultry slaughterhouses in South Korea. Ninety-six isolates (forty-eight each of E. faecalis and E. faecium) were collected between March and September 2022. Both species were analyzed using MALDI-TOF, PCR, antibiotic susceptibility testing, and biofilm assays. A high level of multidrug resistance was observed in E. faecalis (95.8%) and E. faecium (93.8%), with E. faecium exhibiting a broader range of resistance, particularly to linezolid (52.1%) and rifampicin (47.9%). All E. faecalis isolates formed biofilm in vitro, showing stronger biofilm formation than E. faecium with a significant difference (p < 0.001) in biofilm strength. Specific genes (cob, ccf, and sprE) were found to be correlated with biofilm strength. In E. faecium isolates, biofilm strength was correlated with resistance to linezolid and rifampicin, while a general correlation between antibiotic resistance and biofilm strength was not established. Through analysis, correlations were noted between antibiotics within the same class, while no general trends were evident in other analyzed factors. This study highlights the public health risks posed by multidrug-resistant enterococci collected from poultry slaughterhouses, emphasizing the complexity of the biofilm-resistance relationship and the need for enhanced control measures.

Enhanced photoreduction efficiency of Cr(VI) driven by visible light in a new Zr-based metal-organic framework modified by hydroxyl groups.

While metal-organic framework (MOF) photocatalysts have demonstrated a unique Cr(VI) photoreduction capability in recent decades, their performance is still insufficient for practical applications because of their low Cr(VI) uptake and poor visible light response. To cope with these drawbacks, a new OH-modified Zr-based MOF, termed HCMUE-1, was successfully prepared via a solvothermal method in this work. The complete characterization of HCMUE-1 was performed through various techniques, including powder X-ray diffraction (PXRD), Raman spectroscopy, Fourier transform infrared (FT-IR), thermogravimetric analysis and differential scanning calorimetry (TGA-DSC), scanning electron microscopy combined with energy-dispersive X-ray (SEM-EDX), and X-ray photoelectron spectroscopy (XPS). The obtained data exhibited the excellent Cr(VI) photoreduction efficiency of HCMUE-1, reaching up to 98% after 90 min and almost 100% after 120 min under visible light illumination in a low acidic medium. Noteworthily, HCMUE-1 retained the same Cr(VI) removal rate for at least seven cycles without considerable loss. Further experimental investigations demonstrated that the structural stability and surface morphology of HCMUE-1 were retained after photoreduction. Moreover, the photocatalytic reduction mechanism of Cr(VI) to Cr(III) was interpreted through a series of systematic experimental measurements. These results indicate that HCMUE-1 possesses potential as an efficient photocatalyst for reducing toxic Cr(VI) species from wastewater in real-life conditions.

Comparative Analysis of Hindgut Microbiota Variation in Protaetia brevitarsis Larvae across Diverse Farms.

Protaetia brevitarsis larvae are farm-raised for food, are used in traditional East Asian medicine, and convert organic waste into biofertilizers. Here, the comparative analysis of the gut microbiota of third-instar larvae obtained from five different farms was investigated using 16S rRNA microbial profiling. Species richness, evenness, and diversity results using α-diversity analysis (observed species, Chao1, Shannon, Simpson) were similar between farms, except for those between the TO and KO farms. ß-diversity was significantly different in distribution and relative abundance between farms (PERMANOVA, pseudo-F = 13.20, p = 0.001). At the phylum level, Bacillota, Bacteroidota, Actinomycetota, and Pseudomonadota were the most dominant, accounting for 73-88% of the hindgut microbial community. At the genus level, Tuberibacillus, Proteiniphilum, Desulfovibrio, Luoshenia, and Thermoactinomyces were the most abundant. Although oak sawdust was the main feed component, there were large variations in distribution and relative abundance across farms at the phylum and genus levels. Venn diagram and linear discriminant analysis effect size analyses revealed large variations in the hindgut microbial communities of P. brevitarsis larvae between farms. These results suggest environmental factors were more important than feed ingredients or genetic predisposition for the establishment of the intestinal microbiota of P. brevitarsis larvae. These findings serve as reference data to understand the intestinal microbiota of P. brevitarsis larvae.

Genetic Characterization and Phylogeographic Analysis of the First H13N6 Avian Influenza Virus Isolated from Vega Gull in South Korea.

Avian influenza virus (AIV) is a pathogen with zoonotic and pandemic potential. Migratory birds are natural reservoirs of all known subtypes of AIVs, except for H17N10 and H18N11, and they have been implicated in previous highly pathogenic avian influenza outbreaks worldwide. This study identified and characterized the first isolate of the H13N6 subtype from a Vega gull (Larus vegae mongolicus) in South Korea. The amino acid sequence of hemagglutinin gene showed a low pathogenic AIV subtype and various amino acid substitutions were found in the sequence compared to the reference sequence and known H13 isolates. High sequence homology with other H13N6 isolates was found in HA, NA, PB1, and PA genes, but not for PB2, NP, M, and NS genes. Interestingly, various point amino acid mutations were found on all gene segments, and some are linked to an increased binding to human-type receptors, resistance to antivirals, and virulence. Evolutionary and phylogenetic analyses showed that all gene segments are gull-adapted, with a phylogeographic origin of mostly Eurasian, except for PB2, PA, and M. Findings from this study support the evidence that reassortment of AIVs continuously occurs in nature, and migratory birds are vital in the intercontinental spread of avian influenza viruses.

Analyzing the correlation between protein expression and sequence-related features of mRNA and protein in Escherichia coli K-12 MG1655 model.

It was necessary to have a tool that could predict the amount of protein and optimize the gene sequences to produce recombinant proteins efficiently. The Transim model published by Tuller et al. in 2018 can calculate the translation rate in E. coli using features on the mRNA sequence, achieving a Spearman correlation with the amount of protein per mRNA of 0.36 when tested on the dataset of operons' first genes in E. coli K-12 MG1655 genome. However, this Spearman correlation was not high, and the model did not fully consider the features of mRNA and protein sequences. Therefore, to enhance the prediction capability, our study firstly tried expanding the testing dataset, adding genes inside the operon, and using the microarray of the mRNA expression data set, thereby helping to improve the correlation of translation rate with the amount of protein with more than 0.42. Next, the applicability of 6 traditional machine learning models to calculate a "new translation rate" was examined using initiation rate and elongation rate as inputs. The result showed that the SVR algorithm had the most correlated new translation rates, with Spearman correlation improving to R = 0.6699 with protein level output and to R = 0.6536 with protein level per mRNA. Finally, the study investigated the degree of improvement when combining more features with the new translation rates. The results showed that the model's predictive ability to produce a protein per mRNA reached R = 0.6660 when using six features, while the correlation of this model's final translation rate to protein level was up to R = 0.6729. This demonstrated the model's capability to predict protein expression of a gene, rather than being limited to predicting expression by an mRNA and showed the model's potential for development into gene expression predicting tools.