Metagenomic Insights Into the Contribution of Phages to Antibiotic Resistance in Water Samples Related to Swine Feedlot Wastewater Treatment

In this study, we examined the types of antibiotic resistance genes (ARGs) possessed by bacteria and bacteriophages in swine feedlot wastewater before and after treatment using a metagenomics approach. We found that the relative abundance of ARGs in bacterial DNA in all water samples was significantly higher than that in phages DNA (>10.6-fold), and wastewater treatment did not significantly change the relative abundance of bacterial- or phage-associated ARGs. We further detected the distribution and diversity of the different types of ARGs according to the class of antibiotics to which they confer resistance, the tetracycline resistance genes were the most abundant resistance genes and phages were more likely to harbor ATP-binding cassette transporter family and ribosomal protection genes. Moreover, the colistin resistance gene mcr-1 was also detected in the phage population. When assessing the contribution of phages in spreading different groups of ARGs, β-lactamase resistance genes had a relatively high spreading ability even though the abundance was low. These findings possibly indicated that phages not only could serve as important reservoir of ARG but also carry particular ARGs in swine feedlot wastewater, and this phenomenon is independent of the environment

Analysis of genetic diversity in two different shell colors of the giant triton snail (Charonia tritonis) based on mitochondrial COI sequences

The giant triton snail (Charonia tritonis) is widely distributed in tropical coral reefs in the Indo-West Pacific. Its distribution areas in China include the Penghu Islands, Hengchun Peninsula, and Xisha Islands. In this study, we use Multivariate Analysis of Variance (MANOVA) to compare the live weight and shell length between different shell colors of C. tritonis. In addition, we conducted sequence analysis of the mitochondrial cytochrome oxidase (COI) gene to assess the affinity of C. tritonis with two different shell colors based on the sample we obtained. Then, we constructed phylogenetic trees using the maximum likelihood (ML) and Bayesian Inference methods, and constructed haplotype network diagrams. In addition, we performed Tajima’s D and Fu’s neutrality tests. The results show that The Partial mitochondrial COI sequences of 28 C. tritonis were all 603 base pairs in length, and seven haplotypes were detected from the samples, besides, the gene flow was calculated to be 11.78, the genetic differentiation coefficient was 0.02078. Our results indicated that the population size of C. tritonis remained relatively stable. Besides, the genetic and size differentiation between the two different shell colors was small, and individuals of C. tritonis with different shell colors belong to the same genetic clade. In fact, the two morphotypes could not be distinguished by both genetic and morphometric data. The mitochondrial COI gene fragments of the two different shell colors were sequenced and analyzed to accumulate information about the population genetics of C. tritonis and to provide a scientific basis for the conservation of its species resources.The giant triton snail (Charonia tritonis) is widely distributed in tropical coral reefs in the Indo-West Pacific. Its distribution areas in China include the Penghu Islands, Hengchun Peninsula, and Xisha Islands. In this study, we use Multivariate Analysis of Variance (MANOVA) to compare the live weight and shell length between different shell colors of C. tritonis. In addition, we conducted sequence analysis of the mitochondrial cytochrome oxidase (COI) gene to assess the affinity of C. tritonis with two different shell colors based on the sample we obtained. Then, we constructed phylogenetic trees using the maximum likelihood (ML) and Bayesian Inference methods, and constructed haplotype network diagrams. In addition, we performed Tajima’s D and Fu’s neutrality tests. The results show that The Partial mitochondrial COI sequences of 28 C. tritonis were all 603 base pairs in length, and seven haplotypes were detected from the samples, besides, the gene flow was calculated to be 11.78, the genetic differentiation coefficient was 0.02078. Our results indicated that the population size of C. tritonis remained relatively stable. Besides, the genetic and size differentiation between the two different shell colors was small, and individuals of C. tritonis with different shell colors belong to the same genetic clade. In fact, the two morphotypes could not be distinguished by both genetic and morphometric data. The mitochondrial COI gene fragments of the two different shell colors were sequenced and analyzed to accumulate information about the population genetics of C. tritonis and to provide a scientific basis for the conservation of its species resources

Analysis of Powder Rheometry of FT4: Effect of Air Flow

Understanding of particle flow behaviour as a function of strain rate is of great interest in many items of equipment of industrial processes, such as screw conveyors, impeller mixers, and feeders, etc. The traditional commercial instruments for bulk powder flow characterisation, such as shear cells, operate at low shear strain rates, and are not representative of unit operations under dynamic conditions. In recent years, the FT4 powder rheometer of Freeman Technology has emerged as a widely used technique for characterising particle flow under dynamic conditions of shear strain rate; yet little is known about its underlying powder mechanics. We analyse the effect of gas flow on the flow behaviour of cohesionless particles in FT4 both experimentally and by numerical simulations using the combined discrete element method (DEM) and computational fluid dynamics (CFD). The results show that the effect of gas flow on the flow energy could be described by the resultant fluid-induced drag on the particles above the blade position as the impeller penetrates the bed. The strain rate in front of the blade is mainly determined by the impeller tip speed, and is not sensitive to the gas flow and particle size. The flow energy correlates well with the shear stress in front of the blade. They both increase with the strain rate and are significantly reduced by the upward gas flow

Analysis of Powder Rheometry of FT4: Effect of Particle Shape

Particle shape has a strong influence on bulk powder flow and its associated rheology. It promotes mechanical arching and adversely affects fast feeding and dosing. We use the FT4 powder rheometer of Freeman Technology to experimentally characterise the particle flow as a function of the shear strain rate, and to predict its dynamics for rod-shape particles using the discrete element method. The results show a strong realignment of the orientation of particles in the horizontal plane as the bed is sheared by the blade motion. The flow energy required for agitating a bed of rodlike particles is much larger than that of spheres and it increases with the aspect ratio, due to a combined effect of the coordination number and excluded volume. The flowability of rodlike particles can be improved by the addition of spheres, and can be well predicted by the mathematical model developed in this work. The bulk friction coefficient of the binary mixture is a linear function of the volume fraction of its components. The flow energy correlates well with the shear stress arising in front of the blade, considering the effect of the bulk friction coefficient

Feature Selection and Transfer Learning for Alzheimer’s Disease Clinical Diagnosis

Background and Purpose: A majority studies on diagnosis of Alzheimer’s Disease (AD) are based on an assumption: the training and testing data are drawn from the same distribution. However, in the diagnosis of AD and mild cognitive impairment (MCI), this identical-distribution assumption may not hold. To solve this problem, we utilize the transfer learning method into the diagnosis of AD. Methods: The MR (Magnetic Resonance) images were segmented using spm-Dartel toolbox and registrated with Automatic Anatomical Labeling (AAL) atlas, then the gray matter (GM) tissue volume of the anatomical region were computed as characteristic parameter. The information gain was introduced for feature selection. The TrAdaboost algorithm was used to classify AD, MCI, and normal controls (NC) data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, meanwhile, the “knowledge” learned from ADNI was transferred to AD samples from local hospital. The classification accuracy, sensitivity and specificity were calculated and compared with four classical algorithms. Results: In the experiment of transfer task: AD to MCI, 177 AD and 40NC subjects were grouped as training data; 245 MCI and 45 remaining NC subjects were combined as testing data, the highest accuracy achieved 85.4%, higher than the other four classical algorithms. Meanwhile, feature selection that is based on information gain reduced the features from 90 to 7, controlled the redundancy efficiently. In the experiment of transfer task: ADNI to local hospital data, the highest accuracy achieved 93.7%, and the specificity achieved 100%. Conclusions: The experimental results showed that our algorithm has a clear advantage over classic classification methods with higher accuracy and less fluctuation

Antibiotic resistance genes occurrence and bacterial community composition in the Liuxi River

Antibiotic resistance genes (ARGs) in the environment have paid great concern due to their health risk. We investigated antibiotics concentrations (tetracyclines, sulfonamides and fluoroquinolones), ARGs abundances (tetracycline, sulfonamide and plasmid-mediated quinolone resistance (PMQR) genes), and bacterial community composition in sediment and water samples in the Liuxi River, China. Antibiotics concentrations were determined by ultra-performance liquid chromatography-electrospray tandem mass spectrometry. ARGs abundances were quantified by a culture-independent method. Bacterial community composition was analyzed by metagenomic approach based on Ion Torrent Personal Genome Machine platform. Antibiotics concentrations were at the levels of 1.19 to 622 ug kg-1 in sediment samples and below the limit of detection to 127 ng L-1 in water samples. Relative abundances (ARGs copies/16S rRNA gene copies) of detected ARGs were at the range of 10-5 to 10-2. The dominant phyla were Proteobacteria, Bacteroidetes and Verrucomicrobia in sediment samples, and were Proteobacteria, Actinobacteria and Bacteroidetes in water samples. The results indicated that the river environment was contaminated by antibiotics and may be as a reservoir of ARGs. This study provided quantitative data on antibiotics, ARGs and bacterial community composition in the Liuxi River, a geographical location different from the reported studies

Quantifying the Evolution of Giant Panda Habitats in Sichuan Province under Different Scenarios

The giant panda (Ailuropoda melanoleuca) is a relic species in China and a flagship species in the field of endangered wildlife conservation. The conservation of the giant panda’s habitat has gained widespread attention for this reason. Historically, Chinese Giant Panda Nature Reserves are surrounded by communities and the resource utilization behavior of households disturbs the giant panda habitat. Changes in these communities and in Giant Panda Nature Reserves began around 2010, with the feminization and aging of the farm labor force. These changes brought different resource utilization behaviors that led to different evolutionary tendencies in giant panda habitats. This research study assesses the impact of these tendencies based on data from the fourth survey of the giant panda in the Sichuan Province and from geographic information data. The paper aims to uncover the internal mechanisms of farmers’ resource utilization behavior in terms of the changes wrought to giant panda habitats. The paper simulates the future habitat of the giant panda based on the LUCC (land use/cover change) model to identify anticipated changes in future landscape patterns and the habitat quality of giant pandas under the current scenarios. The paper analyzes the spatial-temporal change of landscape patterns through the land use transfer matrix, based on the Markov model. The results of the scenario analyses illustrate the spatial and temporal difference in habitat quality. The driving mechanism for landscape pattern change is explored using the logistic regression model. The paper simulates the variation tendency of giant panda habitats under differential labor force structures and resource utilization behavior based on the CA (cellular automata) model, with the robustness of the results verified by participatory experiment. Through four scenarios of simulated farm labor force structure and resource utilization behavior, results suggest that the quality of giant panda habitats in the future will be relatively high when workforce feminization and aging is intense and resource utilization behavior is weakened. The simulated results confirm that the current agricultural labor force structure can reduce the intensity of resource utilization behavior. In this scenario, disturbance to giant panda habitats would decrease and their quality would improve

Shifts of Antibiotic Resistomes in Soil Following Amendments of Antibiotics-Contained Dairy Manure

Dairy manure is a nutrition source for cropland soils and also simultaneously serves as a contamination source of antibiotic resistance genes (ARGs). In this study, five classes of antibiotics including aminoglycosides, beta-lactams, macrolides, sulfonamides, and tetracyclines, were spiked in dairy manure and incubated with soil for 60 days. The high throughput qPCR and 16S rRNA amplicon sequencing were used to detect temporal shifts of the soil antibiotic resistomes and bacterial community. Results indicated dairy manure application increased the ARG abundance by 0.5–3.7 times and subtype numbers by 2.7–3.7 times and changed the microbial community structure in soils. These effects were limited to the early incubation stage. Selection pressure was observed after the addition of sulfonamides. Bacterial communities played an important role in the shifts of ARG profiles and accounted for 44.9% of the resistome variation. The incubation period, but not the different antibiotic treatments, has a strong impact on the bacteria community. Firmicutes and Bacteroidetes were the dominant bacterial hosts for individual ARGs. This study advanced our understanding of the effect of dairy manure and antibiotics on the antibiotic resistome in soils and provided a reference for controlling ARG dissemination from dairy farms to the environment

Evaluating the Antibacterial and Antivirulence Activities of Floxuridine against <i>Streptococcus suis</i>

Streptococcus suis is an emerging zoonotic pathogen that can cause fatal diseases such as meningitis and sepsis in pigs and human beings. The overuse of antibiotics is leading to an increased level of resistance in S. suis, and novel antimicrobial agents or anti-virulence agents for the treatment of infections caused by S. suis are urgently needed. In the present study, we investigated the antibacterial activity, mode of action and anti-virulence effects of floxuridine against S. suis. Floxuridine showed excessive antibacterial activity against S. suis both in vivo and in vitro; 4 × MIC of floxuridine could kill S. suis within 8 h in a time–kill assay. Meanwhile, floxuridine disrupted the membrane structure and permeability of the cytoplasmic membrane. Molecular docking revealed that floxuridine and SLY can be directly bind to each other. Moreover, floxuridine effectively inhibited the hemolytic capacity and expression levels of the virulence-related genes of S. suis. Collectively, these results indicate that the FDA-approved anticancer drug floxuridine is a promising agent and a potential virulence inhibitor against S. suis