Time-restricted feeding mediated modulation of microbiota leads to changes in muscle physiology in Drosophila obesity models.

Recent research has highlighted the essential role of the microbiome in maintaining skeletal muscle physiology. The microbiota influences muscle health by regulating lipid metabolism, protein synthesis, and insulin sensitivity. However, metabolic disturbances such as obesity can lead to dysbiosis, impairing muscle function. Time-restricted feeding (TRF) has been shown to mitigate obesity-related muscle dysfunction, but its effects on restoring healthy microbiomes remain poorly understood. This study utilizes 16S microbiome analysis and bacterial supplementation to investigate the bacterial communities influenced by TRF that may benefit skeletal muscle physiology. In wild-type and obese Drosophila models (axenic models devoid of natural microbial communities), the absence of microbiota influence muscle performance and metabolism differently. Specifically, axenic wild-type Drosophila exhibited reduced muscle performance, higher glucose levels, insulin resistance, ectopic lipid accumulation, and decreased ATP levels. Interestingly, in obese Drosophila (induced by a high-fat diet or predisposed obesity mutant Sk2), the absence of microbiota improved muscle performance, lowered glucose levels, reduced insulin resistance, and increased ATP levels. TRF was found to modulate microbiota composition, notably increasing Acetobacter pasteurianus (AP) and decreasing Staphylococcus aureus (SA) in both obesity models. Supplementation with AP improved muscle performance and reduced glucose and insulin resistance, while SA supplementation had the opposite effect. This study provides novel insights into the complex interactions between TRF, microbiota, and skeletal muscle physiology in different Drosophila models.

Unfolding and de-confounding: biologically meaningful causal inference from longitudinal multi-omic networks using METALICA.

A key challenge in the analysis of microbiome data is the integration of multi-omic datasets and the discovery of interactions between microbial taxa, their expressed genes, and the metabolites they consume and/or produce. In an effort to improve the state of the art in inferring biologically meaningful multi-omic interactions, we sought to address some of the most fundamental issues in causal inference from longitudinal multi-omics microbiome data sets. We developed METALICA, a suite of tools and techniques that can infer interactions between microbiome entities. METALICA introduces novel unrolling and de-confounding techniques used to uncover multi-omic entities that are believed to act as confounders for some of the relationships that may be inferred using standard causal inferencing tools. The results lend support to predictions about biological models and processes by which microbial taxa interact with each other in a microbiome. The unrolling process helps identify putative intermediaries (genes and/or metabolites) to explain the interactions between microbes; the de-confounding process identifies putative common causes that may lead to spurious relationships to be inferred. METALICA was applied to the networks inferred by existing causal discovery, and network inference algorithms were applied to a multi-omics data set resulting from a longitudinal study of IBD microbiomes. The most significant unrollings and de-confoundings were manually validated using the existing literature and databases. IMPORTANCE: We have developed a suite of tools and techniques capable of inferring interactions between microbiome entities. METALICA introduces novel techniques called unrolling and de-confounding that are employed to uncover multi-omic entities considered to be confounders for some of the relationships that may be inferred using standard causal inferencing tools. To evaluate our method, we conducted tests on the inflammatory bowel disease (IBD) dataset from the iHMP longitudinal study, which we pre-processed in accordance with our previous work. From this dataset, we generated various subsets, encompassing different combinations of metagenomics, metabolomics, and metatranscriptomics datasets. Using these multi-omics datasets, we demonstrate how the unrolling process aids in the identification of putative intermediaries (genes and/or metabolites) to explain the interactions between microbes. Additionally, the de-confounding process identifies potential common causes that may give rise to spurious relationships to be inferred. The most significant unrollings and de-confoundings were manually validated using the existing literature and databases.

Bacterial Insights: Unraveling the Ocular Microbiome in Glaucoma Pathogenesis.

This review explores the connection between the ocular surface microbiome and glaucoma, highlighting its impact on disease progression. Beginning with an overview of global glaucoma significance, it emphasizes the importance of understanding the cellular characteristics and microbiology of the ocular microbiome. A search was conducted on the PubMed and Cochrane Library databases using the phrase "ocular microbiome glaucoma". 0 records were returned from the Cochrane Library while 21 were returned from PubMed. A total of 21 results were retrieved from 2017 to 2024. This comprised one opinion paper, four original research articles, and 16 reviews. This review covered the anatomy of the ocular surface, advanced analysis methods, and the ocular microbiome. It also delved into dysbiosis in glaucoma, addressing altered microbial communities and their potential role in disease progression. The intricate interplay between the ocular microbiome and the host's immune system is explored, emphasizing crosstalk and inflammatory responses. The review concludes by discussing therapeutic implications, including modulating ocular microbiota and potential future treatment strategies. Understanding the microbiome in healthy and glaucomatous eyes can help researchers and clinicians in innovative approaches to ocular health.

Unexplored microbial diversity from 2,500 food metagenomes and links with the human microbiome.

Complex microbiomes are part of the food we eat and influence our own microbiome, but their diversity remains largely unexplored. Here, we generated the open access curatedFoodMetagenomicData (cFMD) resource by integrating 1,950 newly sequenced and 583 public food metagenomes. We produced 10,899 metagenome-assembled genomes spanning 1,036 prokaryotic and 108 eukaryotic species-level genome bins (SGBs), including 320 previously undescribed taxa. Food SGBs displayed significant microbial diversity within and between food categories. Extension to >20,000 human metagenomes revealed that food SGBs accounted on average for 3% of the adult gut microbiome. Strain-level analysis highlighted potential instances of food-to-gut transmission and intestinal colonization (e.g., Lacticaseibacillus paracasei) as well as SGBs with divergent genomic structures in food and humans (e.g., Streptococcus gallolyticus and Limosilactobabillus mucosae). The cFMD expands our knowledge on food microbiomes, their role in shaping the human microbiome, and supports future uses of metagenomics for food quality, safety, and authentication.

Integrated In Vivo and In Vitro Evaluation of a Powder-to-Hydrogel, Film-Forming Polymer Complex Base with Tissue-Protective and Microbiome-Supportive Properties.

The study aimed to perform a comprehensive in vitro and in vivo evaluation of a newly developed, patent-pending, powder-to-hydrogel, film-forming polymer complex base, which possesses tissue-protective and microbiome-supportive properties, and to compare its characteristics with poloxamer 407. The study used a combination of in vitro assays, including tissue viability and cell migration, and in vivo wound healing evaluations in male diabetic mice. Microbiome dynamics at wound sites were also analyzed. The in vitro assays demonstrated that the polymer complex base was non-cytotoxic and that it enhanced cell migration over poloxamer 407. In vivo, the polymer complex base demonstrated superior wound healing capabilities, particularly in combination with misoprostol and phenytoin, as evidenced by the reduced wound area and inflammation scores. Microbiome analysis revealed favorable shifts in bacterial populations associated with the polymer complex base-treated wounds. The polymer complex base demonstrates clinical significance in wound care, potentially offering improved healing, safety and microbiome support. Its transformative properties and efficacy in drug delivery make it a promising candidate for advanced wound care applications, particularly in chronic wound management.

Intestinal Blastocystis is linked to healthier diets and more favorable cardiometabolic outcomes in 56,989 individuals from 32 countries.

Diet impacts human health, influencing body adiposity and the risk of developing cardiometabolic diseases. The gut microbiome is a key player in the diet-health axis, but while its bacterial fraction is widely studied, the role of micro-eukaryotes, including Blastocystis, is underexplored. We performed a global-scale analysis on 56,989 metagenomes and showed that human Blastocystis exhibits distinct prevalence patterns linked to geography, lifestyle, and dietary habits. Blastocystis presence defined a specific bacterial signature and was positively associated with more favorable cardiometabolic profiles and negatively with obesity (p < 1e-16) and disorders linked to altered gut ecology (p < 1e-8). In a diet intervention study involving 1,124 individuals, improvements in dietary quality were linked to weight loss and increases in Blastocystis prevalence (p = 0.003) and abundance (p < 1e-7). Our findings suggest a potentially beneficial role for Blastocystis, which may help explain personalized host responses to diet and downstream disease etiopathogenesis.

Environmentally relevant concentrations of naphthenic acids initiate intestinal injury and gut microbiota dysbiosis in marine medaka (Oryzias melastigma).

Naphthenic acids (NAs) are important pollutants in marine crude oils and have obvious toxic effects on marine organisms. However, the effects of NAs on the intestine are largely unknown. Thus, we evaluated the effects of NAs exposure in the intestines of marine medaka. Fish were experimentally exposed to NAs (0.5 mg/L, 5 mg/L, and 10 mg/L) for 96 h and monitored for changes in intestinal histology, markers of oxidative stress, and intestinal microbiome responses. Significant mucosal damage, inflammation, and oxidative stress were observed in the intestines of marine medaka after exposure to NAs. In addition, significant changes in the gut microbiota were observed. Specifically, the relative abundance of Proteobacteria decreased, while that of Verrucomicrobiota increased in the high-concentration exposure group. In addition, nutrient synthesis and metabolism in the gut were affected. The results of this study contribute to a better understanding of the ecological risk of different concentrations of NAs to marine organisms. CAPSULE ABSTRACT: Changes in the gut microbial community of marine medaka (Oryzias melastigma) caused by naphthenic acids in the marine environment were investigated through the assessment of gut inflammatory factors and comprehensive analysis using 16S rDNA high-throughput sequencing. The results indicated the induction of intestinal inflammation and changes in the structural composition of the intestinal flora.

Multi-class boosting for the analysis of multiple incomplete views on microbiome data.

BACKGROUND: Microbiome dysbiosis has recently been associated with different diseases and disorders. In this context, machine learning (ML) approaches can be useful either to identify new patterns or learn predictive models. However, data to be fed to ML methods can be subject to different sampling, sequencing and preprocessing techniques. Each different choice in the pipeline can lead to a different view (i.e., feature set) of the same individuals, that classical (single-view) ML approaches may fail to simultaneously consider. Moreover, some views may be incomplete, i.e., some individuals may be missing in some views, possibly due to the absence of some measurements or to the fact that some features are not available/applicable for all the individuals. Multi-view learning methods can represent a possible solution to consider multiple feature sets for the same individuals, but most existing multi-view learning methods are limited to binary classification tasks or cannot work with incomplete views. RESULTS: We propose irBoost.SH, an extension of the multi-view boosting algorithm rBoost.SH, based on multi-armed bandits. irBoost.SH solves multi-class classification tasks and can analyze incomplete views. At each iteration, it identifies one winning view using adversarial multi-armed bandits and uses its predictions to update a shared instance weight distribution in a learning process based on boosting. In our experiments, performed on 5 multi-view microbiome datasets, the model learned by irBoost.SH always outperforms the best model learned from a single view, its closest competitor rBoost.SH, and the model learned by a multi-view approach based on feature concatenation, reaching an improvement of 11.8% of the F1-score in the prediction of the Autism Spectrum disorder and of 114% in the prediction of the Colorectal Cancer disease. CONCLUSIONS: The proposed method irBoost.SH exhibited outstanding performances in our experiments, also compared to competitor approaches. The obtained results confirm that irBoost.SH can fruitfully be adopted for the analysis of microbiome data, due to its capability to simultaneously exploit multiple feature sets obtained through different sequencing and preprocessing pipelines.

Efficacy of Allogeneic and Xenogeneic Exosomes for the Treatment of Canine Atopic Dermatitis: A Pilot Study.

Canine atopic dermatitis (CAD) is a genetically predisposed inflammatory pruritic skin disease. The available treatments for CAD have several adverse effects and vary in efficacy, indicating the need for the development of improved treatments. In this study, we aimed to elucidate the therapeutic effects of allogeneic and xenogeneic exosomes on CAD. Six laboratory beagle dogs with CAD were randomly assigned to three treatment groups: control, canine exosome (cExos), or human exosome (hExos) groups. Dogs in the cExos and hExos groups were intravenously administered 1.5 mL of cExos (5 × 1010) and hExos (7.5 × 1011) solutions, respectively, while those in the control group were administered 1.5 mL of normal saline three times per week for 4 weeks. Skin lesion score and transepidermal water loss decreased in cExos and hExos groups compared with those in the control group. The exosome treatments decreased the serum levels of inflammatory cytokines (interferon-γ, interleukin-2, interleukin-4, interleukin-12, interleukin-13, and interleukin-31) but increased those of anti-inflammatory cytokines (interleukin-10 and transforming growth factor-ß), indicating the immunomodulatory effect of exosomes. Skin microbiome analysis revealed that the exosome treatments alleviated skin bacterial dysbiosis. These results suggest that allogeneic and xenogeneic exosome therapy may alleviate CAD in dogs.

Effects of Leishmania major infection on the gut microbiome of resistant and susceptible mice.

Cutaneous leishmaniasis, a parasitic disease caused by Leishmania major, is a widely frequent form in humans. To explore the importance of the host gut microbiota and to investigate its changes during L. major infection, two different groups of mouse models were assessed. The microbiome of two parts of the host gut-ileum and colon-from infected and non-infected mice were characterised by sequencing of 16S rDNA using an Ion Torrent PGM platform. Microbiome analysis was performed to reveal changes related to the susceptibility and the genetics of mice strains in two different gut compartments and to compare the results between infected and non-infected mice. The results showed that Leishmania infection affects mainly the ileum microbiota, whereas the colon bacterial community was more stable. Different biomarkers were determined in the gut microbiota of infected resistant mice and infected susceptible mice using LEfSe analysis. Lactobacillaceae was associated with resistance in the colon microbiota of all resistant mice strains infected with L. major. Genes related to xenobiotic biodegradation and metabolism and amino acid metabolism were primarily enriched in the small intestine microbiome of resistant strains, while genes associated with carbohydrate metabolism and glycan biosynthesis and metabolism were most abundant in the gut microbiome of the infected susceptible mice. These results should improve our understanding of host-parasite interaction and provide important insights into the effect of leishmaniasis on the gut microbiota. Also, this study highlights the role of host genetic variation in shaping the diversity and composition of the gut microbiome. KEY POINTS: • Leishmaniasis may affect mainly the ileum microbiota while colon microbiota was more stable. • Biomarkers related with resistance or susceptibility were determined in the gut microbiota of mice. • Several pathways were predicted to be upregulated in the gut microbiota of resistant or susceptible mice.

Effect of periodontitis induced by Fusobacterium nucleatum on the microbiota of the gut and surrounding organs.

Detection of the oral bacterium Fusobacterium nucleatum in colorectal cancer tissues suggests that periodontitis may alter gut microbiota. The purpose of this study was to analyze the influence and infection route of periodontal inflammation caused by F. nucleatum, and microbiota of the gut and surrounding organs (heart, liver, kidney). Wistar female rats were orally inoculated with F. nucleatum to establish an experimental periodontitis model that was confirmed by X-ray imaging and histopathological analysis. The mandibles, gut, liver, heart, and kidneys were collected from the experimental group at 2, 4, and 8 weeks, and from the uninfected control group at 0 weeks, for DNA extraction for PCR amplification and comprehensive microbiota analysis using the Illumina MiSeq platform. Imaging confirmed the onset of periodontitis at 2 weeks post-inoculation, and histopathology showed inflammatory cell infiltration from 2 to 8 weeks. PCR and comprehensive microbiota analysis showed the presence of F. nucleatum in the heart and liver at 2 weeks, and in the liver at 4 and 8 weeks. There were changes of microbiota of the gut, heart, liver, and kidneys at 4 weeks: namely, decreased Verrucomicrobia and Bacteroidetes, and increased Firmicutes. F. nucleatum induced the onset of periodontitis and infected the heart and liver in rats. As the periodontic lesion progressed, the microbiota of the gut, liver, heart, and kidneys were altered.

Single-cell phenotyping of bacteria combined with deep sequencing for improved contextualization of microbiome analyses.

Great effort was made to characterize the bacterial communities inhabiting the human body as a factor in disease, resulting in the realization that a wide spectrum of diseases is associated with an altered composition of the microbiome. However, the identification of disease-relevant bacteria has been hindered by the high cross-sectional diversity of individual microbiomes, and in most cases, it remains unclear whether the observed alterations are cause or consequence of disease. Hence, innovative analysis approaches are required that enable inquiries of the microbiome beyond mere taxonomic cataloging. This review highlights the utility of microbiota flow cytometry, a single-cell analysis platform to directly interrogate cellular interactions, cell conditions, and crosstalk with the host's immune system within the microbiome to take into consideration the role of microbes as critical interaction partners of the host and the spectrum of microbiome alterations, beyond compositional changes. In conjunction with advanced sequencing approaches it could reveal the genetic potential of target bacteria and advance our understanding of taxonomic diversity and gene usage in the context of the microenvironment. Single-cell bacterial phenotyping has the potential to change our perspective on the human microbiome and empower microbiome research for the development of microbiome-based therapy approaches and personalized medicine.

Quality and Microbiome Analysis of Pickled Swimming Crabs (Portunus trituberculatus) during Storage at Two Alternative Temperatures.

The storage quality and microbiome analysis of pickled swimming crabs (Portunus trituberculatus) stored at 20 and 4 °C were investigated. It showed that samples stored at 4 °C had a longer shelf life, lower total viable count (TVC), pH, and total volatile base nitrogen (TVB-N) contents than those stored at 20 °C. The biogenic amine (BA) results demonstrated that tyramine (tyr), putrescine (put), and cadaverine (cad) were the dominant amines in all samples, and samples stored at 4 °C had lower BA contents. A microbiome analysis indicated that a salt-alcohol water mixture significantly inhibited the growth of Tenericutes. Firmicutes, Proteobacteria, Bacteroidetes, Acidobacteria, Actinobacteria, and Cyanobacteria were the dominant bacteria of stored pickled crabs, and storage at 4 °C significantly inhibited the growth of dominant bacteria, more than that of 20 °C. In conclusion, 4 °C storage guaranteed the quality of samples by inhibiting changes in biochemical properties and the growth of dominant bacteria, thereby prolonging its shelf life.

Nanopore-Sequencing Metabarcoding for Identification of Phytopathogenic and Endophytic Fungi in Olive (Olea europaea) Twigs.

Metabarcoding approaches for the identification of plant disease pathogens and characterization of plant microbial populations constitute a rapidly evolving research field. Fungal plant diseases are of major phytopathological concern; thus, the development of metabarcoding approaches for the detection of phytopathogenic fungi is becoming increasingly imperative in the context of plant disease prognosis. We developed a multiplex metabarcoding method for the identification of fungal phytopathogens and endophytes in olive young shoots, using the MinION sequencing platform (Oxford Nanopore Technologies). Selected fungal-specific primers were used to amplify three different genomic DNA loci (ITS, beta-tubulin, and 28S LSU) originating from olive twigs. A multiplex metabarcoding approach was initially evaluated using healthy olive twigs, and further assessed with naturally infected olive twig samples. Bioinformatic analysis of basecalled reads was carried out using MinKNOW, BLAST+ and R programming, and results were also evaluated using the BugSeq cloud platform. Data analysis highlighted the approaches based on ITS and their combination with beta-tubulin as the most informative ones according to diversity estimations. Subsequent implementation of the method on symptomatic samples identified major olive pathogens and endophytes including genera such as Cladosporium, Didymosphaeria, Paraconiothyrium, Penicillium, Phoma, Verticillium, and others.

Washed microbiota transplantation improves renal function in patients with renal dysfunction: a retrospective cohort study.

BACKGROUND: Changes in the gut microbiota composition is a hallmark of chronic kidney disease (CKD), and interventions targeting the gut microbiota present a potent approach for CKD treatment. This study aimed to evaluate the efficacy and safety of washed microbiota transplantation (WMT), a modified faecal microbiota transplantation method, on the renal activity of patients with renal dysfunction. METHODS: A comparative analysis of gut microbiota profiles was conducted in patients with renal dysfunction and healthy controls. Furthermore, the efficacy of WMT on renal parameters in patients with renal dysfunction was evaluated, and the changes in gut microbiota and urinary metabolites after WMT treatment were analysed. RESULTS: Principal coordinate analysis revealed a significant difference in microbial community structure between patients with renal dysfunction and healthy controls (P = 0.01). Patients with renal dysfunction who underwent WMT exhibited significant improvement in serum creatinine, estimated glomerular filtration rate, and blood urea nitrogen (all P < 0.05) compared with those who did not undergo WMT. The incidence of adverse events associated with WMT treatment was low (2.91%). After WMT, the Shannon index of gut microbiota and the abundance of several probiotic bacteria significantly increased in patients with renal dysfunction, aligning their gut microbiome profiles more closely with those of healthy donors (all P < 0.05). Additionally, the urine of patients after WMT demonstrated relatively higher levels of three toxic metabolites, namely hippuric acid, cinnamoylglycine, and indole (all P < 0.05). CONCLUSIONS: WMT is a safe and effective method for improving renal function in patients with renal dysfunction by modulating the gut microbiota and promoting toxic metabolite excretion.

Microbiome analysis of maternal and neonatal microbial communities associated with the different delivery modes based on 16S rRNA gene amplicon sequencing.

OBJECTIVE: With the rising number of cases of non-vaginal delivery worldwide, scientists have been concerned about the influence of the different delivery modes on maternal and neonatal microbiomes. Although the birth rate trend is decreasing rapidly in Taiwan, more than 30 percent of newborns are delivered by caesarean section every year. However, it remains unclear whether the different delivery modes could have a certain impact on the postpartum maternal microbiome and whether it affects the mother-to-newborn vertical transmission of bacteria at birth. MATERIALS AND METHODS: To address this, we recruited 30 mother-newborn pairs to participate in this study, including 23 pairs of vaginal delivery (VD) and seven pairs of caesarean section (CS). We here investigate the development of the maternal prenatal and postnatal microbiomes across multiple body habitats. Moreover, we also explore the early acquisition of neonatal gut microbiome through a vertical multi-body site microbiome analysis. RESULTS AND CONCLUSION: The results indicate that no matter the delivery mode, it only slightly affects the maternal microbiome in multiple body habitats from pregnancy to postpartum. On the other hand, about 95% of species in the meconium microbiome were derived from one of the maternal body habitats; notably, the infants born by caesarean section acquire bacterial communities resembling their mother's oral microbiome. Consequently, the delivery modes play a crucial role in the initial colonization of the neonatal gut microbiome, potentially impacting children's health and development.

Meeting report of the sixth annual tri-service microbiome consortium symposium.

The Tri-Service Microbiome Consortium (TSMC) was founded to enhance collaboration, coordination, and communication of microbiome research among DoD organizations and to facilitate resource, material and information sharing amongst consortium members, which includes collaborators in academia and industry. The 6th Annual TSMC Symposium was a hybrid meeting held in Fairlee, Vermont on 27-28 September 2022 with presentations and discussions centered on microbiome-related topics within seven broad thematic areas: (1) Human Microbiomes: Stress Response; (2) Microbiome Analysis & Surveillance; (3) Human Microbiomes Enablers & Engineering; (4) Human Microbiomes: Countermeasures; (5) Human Microbiomes Discovery - Earth & Space; (6) Environmental Micro & Myco-biome; and (7) Environmental Microbiome Analysis & Engineering. Collectively, the symposium provided an update on the scope of current DoD microbiome research efforts, highlighted innovative research being done in academia and industry that can be leveraged by the DoD, and fostered collaborative opportunities. This report summarizes the activities and outcomes from the 6th annual TSMC symposium.

Comparing the transmission of carbapenemase-producing and extended-spectrum beta-lactamase-producing Escherichia coli between broiler chickens.

The emergence of carbapenemase-producing Enterobacteriaceae (CPE) is a threat to public health, because of their resistance to clinically important carbapenem antibiotics. The emergence of CPE in meat-producing animals is particularly worrying because consumption of meat contaminated with resistant bacteria comparable to CPE, such as extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae, contributed to colonization in humans worldwide. Currently, no data on the transmission of CPE in livestock is available. We performed a transmission experiment to quantify the transmission of CPE between broilers to fill this knowledge gap and to compare the transmission rates of CPE and other antibiotic-resistant E. coli. A total of 180 Ross 308 broiler chickens were distributed over 12 pens on the day of hatch (day 0). On day 5, half of the 10 remaining chickens in each pen were orally inoculated with 5·102 colony-forming units of CPE, ESBL, or chloramphenicol-resistant E. coli (catA1). To evaluate the effect of antibiotic treatment, amoxicillin was given twice daily in drinking water in 6 of the 12 pens from days 2-6. Cloacal swabs of all animals were taken to determine the number of infectious broilers. We used a Bayesian hierarchical model to quantify the transmission of the E. coli strains. E. coli can survive in the environment and serve as a reservoir. Therefore, the susceptible-infectious transmission model was adapted to account for the transmission of resistant bacteria from the environment. In addition, the caecal microbiome was analyzed on day 5 and at the end of the experiment on day 14 to assess the relationship between the caecal microbiome and the transmission rates. The transmission rates of CPE were 52 - 68 per cent lower compared to ESBL and catA1, but it is not clear if these differences were caused by differences between the resistance genes or by other differences between the E. coli strains. Differences between the groups in transmission rates and microbiome diversity did not correspond to each other, indicating that differences in transmission rates were probably not caused by major differences in the community structure in the caecal microbiome. Amoxicillin treatment from day 2-6 increased the transmission rate more than three-fold in all inoculums. It also increased alpha-diversity compared to untreated animals on day 5, but not on day 14, suggesting only a temporary effect. Future research could incorporate more complex transmission models with different species of resistant bacteria into the Bayesian hierarchical model.

Effect of surfactant on urease-producing flora from waste activated sludge using microbially induced calcite precipitation technology to suppress coal dust.

The wettability of microbially induced calcite precipitation (MICP) is a challenge in dust suppression. Herein, the tolerance of urease-producing flora to surfactants was investigated. The optimal tolerance concentrations of the urease-producing flora to sodium dodecylbenzene sulfonate (SDBS, anionic surfactant), alkyl polyglycoside (APG, non-ionic surfactant), and cocamidopropyl betaine (CAB, zwitterionic surfactant), and were 0.2%, 0.1%, and 0.05%. The cetyltrimethylammonium bromide (CTAB, cationic surfactant) inhibited urease production by urease-producing flora. The mineralization products of SDBS, APG, and CAB treatments were all transformed into calcite. The wind resistance test showed that the mass loss of all samples is less than 0.1%. The rain resistance and hardness tests showed that 0.2% SBDS had the best effect, followed by 0.1% APG and 0.05% CAB, and finally, No surfactants. Microbiome analysis showed that the abundance of Sporosarcina and Unclassified_bacillaceae reduced, and the intense competition between Paenalcaligenes and Sporosarcina are essential reasons for reducing urease activity. SDBS and APG could reduce the pathogenic risk of microbial dust suppressants. This study will facilitate the practical application of microbial dust suppressants.