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Vinasse fertirrigation alters soil resistome dynamics: an analysis based on metagenomic profiles
© The Author(s). 2017
- Received: 8 August 2016
- Accepted: 9 May 2017
- Published: 23 May 2017
Every year around 300 Gl of vinasse, a by-product of ethanol distillation in sugarcane mills, are flushed into more than 9 Mha of sugarcane cropland in Brazil. This practice links fermentation waste management to fertilization for plant biomass production, and it is known as fertirrigation. Here we evaluate public datasets of soil metagenomes mining for changes in antibiotic resistance genes (ARGs) of soils from sugarcane mesocosms repeatedly amended with vinasse. The metagenomes were annotated using the ResFam database. We found that the abundance of open read frames (ORFs) annotated as ARGs changed significantly across 43 different families (p-value < 0.05). Co-occurrence network analysis revealed distinct patterns of interactions among ARGs, suggesting that nutrient amendment to soil microbial communities can impact on the coevolutionary dynamics of indigenous ARGs within soil resistome.
- Resistance genes
- Metagenomic profiles
Vinasse is a by-product of the sugar-ethanol industry produced in large quantities , and it is chemically composed of water, organic matter, and mineral elements . It derives from the distillation process of the fermented broth, and it is obtained after the fermentation step in fuel ethanol production from sugarcane . Since the 1960’s, application of vinasse in natura has been used as fertilizer in the sugarcane fields of Brazil to resolve the ecological problem of its disposal within the environment, a process known as “fertirrigation” .
However, recent research has demonstrated that the utilization of organic compounds as fertilizers in agriculture soils can alter the selective pressure that drives antibiotic resistance genes (ARGs) on soil-borne microbial communities . Soil ecosystems are considered to harbor a remarkable diversity of ARGs . According to Wright et al. , the collection of all the ARGs and their precursors in both pathogenic and non-pathogenic bacteria can be defined by the term ‘resistome’. The number of studies reporting the dynamics of resistome in the environment is growing . To date, the impacting activities often reported are associated to manure fertilization and wastewater utilization in agricultural practices [6, 7]. The discovery of new sources of anthropogenic practices that may affect ARGs in the environment is a challenging and timely topic, since the mechanisms regulating the spread of resistance and evolution of pathogens in environmental resistome are widely unknown .
Next, in order to detect patterns of interaction among ARGs, we performed a network analysis. The models were built using the Co-occurrence Network inference tools (CoNet)  to detect strong and significant relationships among the different ARGs that were identified. Spearman (-0.8 > ρ > 0.8) and Pearson (-0.8 > r > 0.8) correlations with Steinhaus similarity index (>0.8) were the measures used to detect strong interactions. Relationships that were not detected by the three methods were not included in the network models. The p-values were computed by bootstrap (1000 interactions) based on a set of edge-specify score distribution , merged using the Brown method  and adjusted with the Benjamini-Hochberg procedure. Only relationships with p-values < 0.05 were kept in the models. The models were constructed separately for the compositions of ARGs found in V+ and V- across the three sampling points (7 dap, 157 dap and 217 dap), resulting in a total of 6 models. To evaluate the differences in the model structure we compared them by the change in the composition of nodes according to betweenness centrality (BC) (a parameter interpreted as the amount of influence that a node exert over the model ) and by the type of interactions whether negative or positive.
ARGs play important role in microbial ecology and evolution and are strongly associated with fitness, being responsible for detoxification by the exposure to antimicrobial compounds . The results presented here indicate that vinasse applications to the soil gradually changed mechanisms of resistance (Fig. 1). Although diverse antibiotic-specific resistance genes were changed by vinasse amendments, the enrichment of multidrug efflux systems of different types such as resistance nodulation-nodulation-division (RND), major facilitator superfamily (MFS), small multidrug resistance (SMR) superfamily and ATP-binding cassette (ABC) transporters, suggests a possible large-scale effect of detoxification.
Some antimicrobial compounds, such as sulfonamides, can act targeting the enzyme dihydropteroate synthase which is involved in the folate cycle, an important pathway in cell metabolism . Resistance mechanism against dihydropteroate synthase inhibitors (RF0165) was enriched in V+ (Fig. 1b). Likewise, dihydropteroate synthase, thymidilate synthase also participates on folate cycle and some drugs like 5-fluorouracil can target this enzyme. Mechanism of resistance against thymidylate synthase inhibitors (RF0146) was found to be enriched in V+ (Fig. 1c). The bicyclomycin resistance (RF0140), also enriched in V+ (Fig. 1b-c), is part of a family of multidrug antiporters, and was demonstrated to be involved in the protection of folate cycle . Folate synthesis is essential to most of microbial cells and the interference on this pathway can be harmful leading to the inability of DNA replication . Therefore, vinasse application to the soil might have disturbed the microbial capacity to synthetize essential metabolic compounds, and this would explain why mechanisms of protection to enzymes were found to be enriched in V+. This, together with the enrichment in several different types of multidrug efflux pumps, suggest a toxic effect of vinasse to soil microbes.
So far, the toxicity of vinasse to soil microbial community has not been evaluated. Vinasse applications follow agronomical recommendations taking into account plant nutritional requirements, soil characteristics and the mineral composition in vinasse. However, our results indicate that the effect of toxicity should be tested in further research. In addition, network analysis (Fig. 2; Additional file 7: Table S7) reveals that vinasse amendment can impact on ARGs coevolutionary processes , suggesting that vinasse amendment is capable to modify the selective pressure upon soil resistome. Nutrient amendment to soils favors copiotrophic microbes  and the use of antibiotics to antagonize the growth of competitors and to dominate niches may be employed as a strategy . Therefore, our dataset suggests that vinasse amendment to soils contributes to interference competition within soil microbial communities. Altogether, the results presented here indicate that the spread of resistance against antimicrobial compounds within soil microbial communities by vinasse amendment is a question of concern.
In order to prevent the negative impacts related to bacterial contamination, ethanol mills utilize different compounds with antimicrobial activity such as sulphuric acid, hop crops, chemical biocides and antibiotics . Therefore, it is important to determine if such compounds remain active in vinasse and do not influence resistance genes in soils. Nevertheless, determining antibiotic concentrations in soils can be difficult  especially considering the low concentrations used in the industry (in the ppm range). Brazil is one of the major fuel ethanol producers worldwide (more than 23 billions L.year-1), yielding 10 to 15 L of vinasse for each L of ethanol produced. This, in turn, results in more than 300 GL of vinasse being applied in 9.7 Mha [1, 2]. It is a considerable amount of vinasse potentially being flushed into soil microbiome in sugarcane croplands. Overall, with our results we were able to provide considerable information to support the hypothesis that vinasse fertirrigation can impact the soil resistome dynamics. We outline the need for experiments to evaluate the dimension of this impact concerning the emergence of resistance in the environment and its potential implications to human health.
LPPB was supported by a doctoral grant provided by the Sao Paulo Research Foundation (FAPESP) (FAPESP 13/22845-2). AAN was supported by FAPESP grant (FAPESP 12/13321-7).
Availability of data and materials
The datasets supporting the conclusions of this article are available in the MG-RAST server repository, in http://metagenomics.anl.gov/linkin.cgi?project=10854. Files V9T7, V10T7, V11T7, V9T157, V10T157, V11T157, V9T217, V10T157 and V11T217 were obtained from the pots without vinasse. Files V22T7, V23T7, V24T7, V22T157, V23T157, V24T157, V22T217, V23T217, V24T217 were obtained from the pots amended with vinasse.
LPPB, RFA and TOB conceived the idea of the manuscript. MTFD made contributions to the design of this study and discussions of the results. AAN and SMT designed the greenhouse experiment. AAN and LPPB performed the experiment. AAN obtained the soil metagenomes. LPPB analyzed the datasets and wrote the manuscript. TOB, RFA and AAN made contributions to manuscript writing. All co-authors critically revised the manuscript and approved the final version.
The authors declare that there are no competing interests.
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