Fecal source tracking by antibiotic resistance analysis on a watershed exhibiting low resistance

The ongoing development of microbial source tracking has made it possible to identify contamination sources with varying accuracy, depending on the method used. The purpose of this study was to test the efficiency of the antibiotic resistance analysis (ARA) method under low resistance by tracking the fecal sources at Turkey Creek, Oklahoma exhibiting this condition. The resistance patterns of 772 water-isolates, tested with nine antibiotics, were analyzed by discriminant analysis (DA) utilizing a five-source library containing 2250 isolates. The library passed various representativeness tests; however, two of the pulled-sample tests suggested insufficient sampling. The resubstitution test of the library individual sources showed significant isolate misclassification with an average rate of correct classification (ARCC) of 58%. These misclassifications were explained by low antibiotic resistance (Wilcoxon test P < 0.0001). Seasonal DA of stream E. coli isolates for the pooled sources human/livestock/deer indicated that in fall, the human source dominated (P < 0.0001) at a rate of 56%, and that human and livestock respective contributions in winter (35 and 39%), spring (43 and 40%), and summer (37 and 35%) were similar. Deer scored lower (17–28%) than human and livestock at every season. The DA was revised using results from a misclassification analysis to provide a perspective of the effect caused by low antibiotic resistance and a more realistic determination of the fecal source rates at Turkey Creek. The revision increased livestock rates by 13–14% (0.04 ≤ P ≤ 0.06), and decreased human and deer by 6–7%. Negative misclassification into livestock was significant (0.04 ≤ P ≤ 0.06). Low antibiotic resistance showed the greatest effect in this category.     

Enhanced metronidazole removal by binary-species photoelectrogenic biofilm of microaglae and anoxygenic phototrophic bacteria

High efficient removal of antibiotics during nutriments recovery for biomass production poses a major technical challenge for photosynthetic microbial biofilm-based wastewater treatment since antibiotics are always co-exist with nutriments in wastewater and resist biodegradation due to their strong biotoxicity and recalcitrance. In this study, we make a first attempt to enhance metronidazole (MNZ) removal from wastewater using electrochemistry-activated binary-species photosynthetic biofilm of Rhodopseudomonas Palustris (R. Palustris) and Chlorella vulgaris (C. vulgaris) by cultivating them under different applied potentials. The results showed that application of external potentials of -0.3, 0 and 0.2 V led to 11, 33 and 26-fold acceleration in MNZ removal, respectively, as compared to that of potential free. The extent of enhancement in MNZ removal was positively correlated to the intensities of photosynthetic current produced under different externally applied potentials. The binary-species photoelectrogenic biofilm exhibited 18 and 6-fold higher MNZ removal rate than that of single-species of C. vulgaris and R. Palustris, respectively, due to the enhanced metabolic interaction between them. Application of an external potential of 0V significantly promoted the accumulation of tryptophan and tyrosine-like compounds as well as humic acid in extracellular polymeric substance, whose concentrations were 7.4, 7.1 and 2.0-fold higher than those produced at potential free, contributing to accelerated adsorption and reductive and photosensitive degradation of MNZ.     

Short-term inhalation exposure evaluations of airborne antibiotic resistance genes in environments

Antibiotic resistance is a sword of Damocles that hangs over humans. In regards to airborne antibiotic resistance genes (AARGs), critical knowledge gaps still exist in the identification of hotspots and quantification of exposure levels in different environments. Here, we have studied the profiles of AARGs, mobile genetic elements (MGEs) and bacterial communities in various atmospheric environments by high throughput qPCR and 16S rRNA gene sequencing. We propose a new AARGs exposure dose calculation that uses short-term inhalation (STI). Swine farms and hospitals were high-risk areas where AARGs standardised abundance was more abundant than suburbs and urban areas. Additionally, resistance gene abundance in swine farm worker sputum was higher than that in healthy individuals in other environments. The correlation between AARGs with MGEs and bacteria was strong in suburbs but weak in livestock farms and hospitals. STI exposure analysis revealed that occupational intake of AARGs (via PM₁₀) in swine farms and hospitals were 110 and 29 times higher than in suburbs, were 1.5 × 10⁴, 5.6 × 10⁴ and 5.1 × 10² copies, i.e., 61.9%, 75.1% and 10.7% of the overall daily inhalation intake, respectively. Our study comprehensively compares environmental differences in AARGs to identify high-risk areas, and forwardly proposes the STI exposure dose of AARGs to guide risk assessment.     

Degradation of extracellular genomic,plasmid DNA and specific antibiotic resistance genes by chlorination

Extracellular DNA structure damaged by chlorination was characterized. Integrity of extracellular ARG genetic information after chlorination was determined. Typical chlorine doses will likely effectively diminish extracellular DNA and ARGs. Plasmid DNA/ARGs were less readily broken down than genomic DNA. The Bioanalyzer methodology effectively documented damage incurred to DNA. There is a need to improve understanding of the effect of chlorine disinfection on antibiotic resistance genes (ARGs) in order to advance relevant drinking water, wastewater, and reuse treatments. However, few studies have explicitly assessed the physical effects on the DNA. Here we examined the effects of free chlorine (1–20 mg Cl₂/L) on extracellular genomic, plasmid DNA and select ARGs. Chlorination was found to decrease the fluorometric signal of extracellular genomic and plasmid DNA (ranging from 0.005 to 0.05 mg/mL) by 70%, relative to a no-chlorine control. Resulting DNA was further subject to a fragment analysis using a Bioanalyzer, indicating that chlorination resulted in fragmentation. Moreover, chlorine also effectively deactivated both chromosomal- and plasmid-borne ARGs, mecA and tetA, respectively. For concentrations >2 mg Cl₂//L × 30 min, chlorine efficiently reduced the qPCR signal when the initial concentration of ARGs was 10⁵ copies/mL or less. Notably, genomic DNA and mecA gene signals were more readily reduced by chlorine than the plasmid-borne tetA gene (by ~2 fold). Based on the results of qPCR with short (~200 bps) and long amplicons (~1200 bps), chlorination could destroy the integrity of ARGs, which likely reduces the possibility of natural transformation. Overall, our findings strongly illustrate that chlorination could be an effective method for inactivating extracellular chromosomal- and plasmid-borne DNA and ARGs.     

Indigenous bacteria may interfere with the biocontrol of plant diseases

Prodigiosin is a reddish antibiotic pigment that plays an important role in the biocontrol of plant diseases by the bacterium Serratia marcescens. However, its activity is unstable under agricultural conditions; further, it can be degraded by various environmental factors. To examine the effect of epiphytic microbes on the stability of prodigiosin used for biological control processes, we collected a total of 1,280 bacterial isolates from the phylloplane of cyclamen and tomato plants. Approximately 72% of the bacterial strains isolated from the cyclamen plants and 66% of those isolated from the tomato plants grew on minimal agar medium containing 100 μg ml⁻¹ prodigiosin. Certain isolates obtained from both plant species exhibited prodigiosin-degrading activity. We compared the 16S rRNA gene sequences derived from the isolates with sequences in a database. The comparison revealed that the sequences determined for the prodigiosin-degrading isolates were homologous to those of the genera Pseudomonas, Caulobacter, Rhizobium, Sphingomonas, Janthinobacterium, Novosphingobium, and Rathayibacter. These results indicate that indigenous epiphytic microorganisms may interfere with the interaction between plant pathogens and biocontrol agents by degrading the antibiotics produced by the agents.     

Environmental effects and risk control of antibiotic resistance genes in the organic solid waste aerobic composting system: A review

• ARGs were detected in livestock manure, sludge, food waste and fermentation dregs. • The succession of microbial community is an important factor affecting ARGs. • Horizontal transfer mechanism of ARGs during composting should be further studied. Antibiotic resistance genes (ARGs) have been diffusely detected in several kinds of organic solid waste, such as livestock manure, sludge, antibiotic fermentation residues, and food waste, thus attracting great attention. Aerobic composting, which is an effective, harmless treatment method for organic solid waste to promote recycling, has been identified to also aid in ARG reduction. However, the effect of composting in removing ARGs from organic solid waste has recently become controversial. Thus, this article summarizes and reviews the research on ARGs in relation to composting in the past 5 years. ARGs in organic solid waste could spread in different environmental media, including soil and the atmosphere, which could widen environmental risks. However, the conventional composting technology had limited effect on ARGs removal from organic solid waste. Improved composting processes, such as hyperthermophilic temperature composting, could effectively remove ARGs, and the HGT of ARGs and the microbial communities are identified as vital influencing factors. Currently, during the composting process, ARGs were mainly affected by three response pathways, (I) “Microenvironment-ARGs”; (II) “Microenvironment-microorganisms-ARGs”; (III) “Microorganisms-horizontal gene transfer-ARGs”, respectively. Response pathway II had been studied the most which was believed that microbial community was an important factor affecting ARGs. In response pathway III, mainly believed that MGEs played an important role and paid less attention to eARGs. Further research on the role and impact of eARGs in ARGs may be considered in the future. It aims to provide support for further research on environmental risk control of ARGs in organic solid waste.     

Stenusine,an antimicrobial agent in the rove beetle genus <Emphasis Type="Italic">Stenus</Emphasis> (Coleoptera,Staphylinidae)

Stenusine is well known as the alkaloid, discharged by the rove beetle, genus Stenus Latreille (Coleoptera, Staphylinidae). The Stenus beetles employ the alkaloid as an escape mechanism when on water surfaces. In the case of danger, they lower their abdomen and emit stenusine from their pygidial glands. Stenusine shows a low surface tension and therefore a high spreading pressure; these properties propel the beetle quickly over the water. Many Steninae do not live in habitats with open waters, but in detritus, leaf litter, mosses, etc. This raises the possibility that stenusine might also have another function, e.g., as antibiotic or fungicide. Stenus beetles show an intense grooming behaviour. With gas chromatography-mass spectrometry analyses we could prove that they cover themselves with their secretion. To tests its antimicrobial properties we conducted agar diffusion tests with stenusine and norstenusine, another substance that is abundant in most Stenus species. Both compounds have an antimicrobial effect on entomopathogenic bacteria and fungi. Stenusine not only allows for an extraordinary method of locomotion on water surfaces, it also protects the Steninae from being infested with microorganisms.     

Removal of antibiotic-resistant genes during drinking water treatment: A review

Once contaminate the drinking water source, antibiotic resistance genes (ARGs) will propagate in drinking water systems and pose a serious risk to human health. Therefore, the drinking water treatment processes (DWTPs) are critical to manage the risks posed by ARGs. This study summarizes the prevalence of ARGs in raw water sources and treated drinking water worldwide. In addition, the removal efficiency of ARGs and related mechanisms by different DWTPs are reviewed. Abiotic and biotic factors that affect ARGs elimination are also discussed. The data on presence of ARGs in drinking water help come to the conclusion that ARGs pollution is prevalent and deserves a high priority. Generally, DWTPs indeed achieve ARGs removal, but some biological treatment processes such as biological activated carbon filtration may promote antibiotic resistance due to the enrichment of ARGs in the biofilm. The finding that disinfection and membrane filtration are superior to other DWTPs adds weight to the advice that DWTPs should adopt multiple disinfection barriers, as well as keep sufficient chlorine residuals to inhibit re-growth of ARGs during subsequent distribution. Mechanistically, DWTPs obtain direct and inderect ARGs reduction through DNA damage and interception of host bacterias of ARGs. Thus, escaping of intracellular ARGs to extracellular environment, induced by DWTPs, should be advoided. This review provides the theoretical support for developping efficient reduction technologies of ARGs. Future study should focus on ARGs controlling in terms of transmissibility or persistence through DWTPs due to their biological related nature and ubiquitous presence of biofilm in the treatment unit.     

Antibiotic resistance genes in manure-amended paddy soils across eastern China: Occurrence and influencing factors

• Manure fertilization resulted in antibiotic residues and increased metal contents. • The tet and sul genes were significantly enhanced with manure fertilization. • Soil physicochemical properties contributed to 12% of the variations in ARGs. • Soil metals and antibiotics co-select for ARGs. Pig manure, rich in antibiotics and metals, is widely applied in paddy fields as a soil conditioner, triggering the proliferation of antibiotic resistance genes (ARGs) in soil. However, comprehensive studies on the effects of manure fertilization on the abundance of ARGs and their influencing factors are still insufficient. Here, pig manure and manure-amended and inorganic-amended soils were collected from 11 rice-cropping regions in eastern China, and the accumulation of antibiotics, metals, and ARGs was assessed simultaneously. The results showed that manure fertilization led to antibiotic residues and increased the metal content (i.e., Zn, Cu, Ni, and Cr). Tetracycline and sulfonamide resistance genes (tetM, tetO, sul1, and sul2) were also significantly enhanced with manure fertilization. According to variance partitioning analysis, the most important factors that individually influenced ARGs were soil physicochemical properties, accounting for 12% of the variation. Significant correlations between soil nutrients and ARGs indicated that manure application enhanced the growth of resistant microorganisms by supplying more nutrients. Metals and antibiotics contributed 9% and 5% to the variations in ARGs, respectively. Their co-occurrence also increased the enrichment of ARGs, as their interactions accounted for 2% of the variation in ARGs. Interestingly, Cu was significantly related to most ARGs in the soil (r = 0.26–0.52, p<0.05). Sulfapyridine was significantly related to sul2, and tetracycline resistance genes were positively related to doxycycline. This study highlighted the risks of antibiotic and ARG accumulation with manure fertilization and shed light on the essential influencing factors of ARGs in paddy soils.     

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

• A spectral machine learning approach is proposed for predicting mixed antibiotic. • Pretreatment is far simpler than traditional detection methods. • Performance of the model is compared in different influencing factors. • Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.