Soil bacterial diversity correlates with precipitation and soil pH in long-term maize cropping systems

Revealing the hidden world of soil microbes: Metagenomic insights into plant, bacteria, and fungi interactions for sustainable agriculture and ecosystem restoration

The future of agriculture is questionable under the current climate change scenario. Climate change and climate-related calamities directly influence biotic and abiotic factors that control agroecosystems, endangering the safety of the world's food supply. The intricate interactions between soil microorganisms, including plants, bacteria, and fungi, play a pivotal role in promoting sustainable agriculture and ecosystem restoration. Soil microbes play a major part in nutrient cycling, including soil organic carbon (SOC), and play a pivotal function in the emission and depletion of greenhouse gases, including CH4, CO2, and N2O, which can impact the climate. At this juncture, developing a triumphant metagenomics approach has greatly increased our knowledge of the makeup, functionality, and dynamics of the soil microbiome. Currently, the involvement of plants in climate change indicates that they can interact with the microbial communities in their environment to relieve various stresses through the innate microbiome assortment of focused strains, a phenomenon dubbed "Cry for Help." The metagenomics method has lately appeared as a new platform to adjust and encourage beneficial communications between plants and microbes and improve plant fitness. The metagenomics of soil microbes can provide a powerful tool for designing and evaluating ecosystem restoration strategies that promote sustainable agriculture under a changing climate. By identifying the specific functions and activities of soil microbes, we can develop restoration programs that support these critical components of healthy ecosystems while providing economic benefits through ecosystem services. In the current review, we highlight the innate functions of microbiomes to maintain the sustainability of agriculture and ecosystem restoration. Through this insight study of soil microbe metagenomics, we pave the way for innovative strategies to address the pressing challenges of food security and environmental conservation. The present article elucidates the mechanisms through which plants and microbes communicate to enhance plant resilience and ecosystem restoration and to leverage metagenomics to identify and promote beneficial plant-microbe interactions. Key findings reveal that soil microbes are pivotal in nutrient cycling, greenhouse gas modulation, and overall ecosystem health, offering novel insights into designing ecosystem restoration strategies that bolster sustainable agriculture. As this is a topic many are grappling with, hope these musings will provide people alike with some food for thought.

Soil pH, developmental stages and geographical origin differently influence the root metabolomic diversity and root-related microbial diversity of Echium vulgare from native habitats

Improved understanding of the complex interaction between plant metabolism, environmental conditions and the plant-associated microbiome requires an interdisciplinary approach: Our hypothesis in our multiomics study posited that several environmental and biotic factors have modulating effects on the microbiome and metabolome of the roots of wild Echium vulgare plants. Furthermore, we postulated reciprocal interactions between the root metabolome and microbiome. We investigated the metabolic content, the genetic variability, and the prokaryotic microbiome in the root systems of wild E. vulgare plants at rosette and flowering stages across six distinct locations. We incorporated the assessment of soil microbiomes and the measurement of selected soil chemical composition factors. Two distinct genetic clusters were determined based on microsatellite analysis without a consistent alignment with the geographical proximity between the locations. The microbial diversity of both the roots of E. vulgare and the surrounding bulk soil exhibited significant divergence across locations, varying soil pH characteristics, and within the identified plant genetic clusters. Notably, acidophilic bacteria were characteristic inhabitants of both soil and roots under acidic soil conditions, emphasizing the close interconnectedness between these compartments. The metabolome of E. vulgare significantly differed between root samples from different developmental stages, geographical locations, and soil pH levels. The developmental stage was the dominant driver of metabolome changes, with significantly higher concentrations of sugars, pyrrolizidine alkaloids, and some of their precursors in rosette stage plant roots. Our study featured the complex dynamics between soil pH, plant development, geographical locations, plant genetics, plant metabolome and microbiome, shedding light on existing knowledge gaps.

Soil Layers Impact Lithocarpus Soil Microbial Composition in the Ailao Mountains Subtropical Forest, Yunnan, China

Plant litter decomposition is a complex, long-term process. The decomposition of litterfall is a major process influencing nutrient balance in forest soil. The soil microbiome is exceptionally diverse and is an essential regulator of litter decomposition. However, the microbiome composition and the interaction with litterfall and soil remain poorly understood. In this study, we examined the bacterial and fungal community composition of Lithocarpus across soil samples from different sampling seasons. Our results displayed that the microbiome assembly along the soil layer is influenced predominantly by the soil layer rather than by the sampling season. We identified that the soil layer strongly affected network complexity and that bacterial and fungal microbiomes displayed different patterns in different soil layers. Furthermore, source tracking and community composition analysis indicated that there are significantly different between soil and litter. Moreover, our results demonstrate that few dominant taxa (2% and 4% of bacterial and fungal phylotypes) dominated in the different soil layers. Hydnodontaceae was identified as the most important biomarker taxa for humic fragmented litter fungal microbiome and Nigrospora and Archaeorhizomycetaceae for organic soil and the organic mineral soil layer, and the phylum of Acidobacteria for the bacteria microbiome. Our work provides comprehensive evidence of significant microbiome differences between soil layers and has important implications for further studying soil microbiome ecosystem functions.

Solar park promoted microbial nitrogen and phosphorus cycle potentials but reduced soil prokaryotic diversity and network stability in alpine desert ecosystem

Solar park (SP) is rapidly growing throughout the planet due to the increasing demand for low-carbon energy, which represents a remarkable global land-use change with implications for the hosting ecosystems. Despite dozens of studies estimating the environmental impacts of SP based on local microclimate and vegetation, responses of soil microbial interactions and nutrient cycle potentials remain poorly understood. To bridge this gap, we investigated the diversity, community structure, complexity, and stability of co-occurrence network and soil enzyme activities of soil prokaryotes and fungi in habitats of ambient, the first, and sixth year since solar park establishment. Results revealed different response patterns of prokaryotes and fungi. SP led to significant differences in both prokaryotic and fungal community structures but only reduced prokaryotic alpha diversity significantly. Co-occurrence network analysis revealed a unimodal pattern of prokaryotic network features and more resistance of fungal networks to environmental variations. Microbial nitrogen and phosphorus cycle potentials were higher in SP and their variances were more explained by network features than by diversity and environmental characteristics. Our findings revealed for the first time the significant impacts of SP on soil prokaryotic and fungal stability and functional potentials, which provides a microbial insight for impact evaluation and evidence for the optimization of solar park management to maximize the delivery of ecosystem services from this growing land use.

Temperature mediated the balance between stochastic and deterministic processes and reoccurrence of microbial community during treating aniline wastewater

Seasonal temperature changes significantly affect microbial community diversity, composition, and performance in wastewater treatment plants. However, the community assembly mechanisms under seasonal temperature variations remain unclear. Here, we carried out temperature cycling experiments (30 °C, 35 °C, 37 °C, 40 °C, 42 °C, 45 °C, 40 °C, and 30 °C) to investigate how temperature impacts microbial performance and co-occurrence network and how assembly processes determine the structure and function of microbial communities during treating aniline wastewater. During the 195-day operation, the system achieved an efficient and stable aniline removal of 99%. Interestingly, α-diversity and network complexity were negatively correlated with temperature but could be recovered when the temperature was returned to 30 °C. The results showed that functional redundancy was probably responsible for the excellent microbial performance during the whole process. Null model analyses presented that deterministic process dominated the community when the temperature was 30 °C, and stochasticity dominated the assembly process when the temperature was over 30 °C. Overall, the balance between stochastic and deterministic processes in the treatment of aniline wastewater mediated the reoccurrence of microbial community and co-occurrence network at different temperatures. This study provides new insights into microbial community reoccurrence under seasonal temperature changes and a theoretical basis for regulating microbial communities in wastewater treatment plants.

Targeted metagenome sequencing reveals the abundance of Planctomycetes and Bacteroidetes in the rhizosphere of pomegranate

Agricultural productivity of pomegranate can be enhanced by identifying the crop-associated microbial diversity in the rhizosphere region with respect to plant growth promoters and other beneficial organisms. Traditional culture methods have limitations in microbial screening as only 1-2% of these organisms can be cultured. In the present study, 16S rRNA amplicon-based metagenomics approach using MinION Oxford Nanopore platform was employed to explore the microbial diversity in the rhizosphere of pomegranate Bhagwa variety, across variable soil depths from 0 to 5 cms (R2), 5-10 cms (R4) and 10-15 cms (R6), using bulk soil as the control. Across all the three layers, significant variations in pH, nitrogen content and total fungal count were observed. 16S rRNA analysis showed the abundance of planctomycetes, Pirellula staleyi, followed by bacteroidetes, Flavisolibacter LC59 and Niastella koreensis across the various soil depths in the rhizospheric soil samples. Pathway prediction analysis indicated arginine and proline metabolism (gamma-glutamyl putrescine oxidase) and hydrogen sulfide biosynthesis as the most abundant pathway hits. Comparative abundance analysis across layers showed the R6 layer with the maximum microbial diversity in terms of highest dimension of variation (79.2%) followed by R4 and R2 layers (p < 0.01). Our analysis shows the significant influence of root zone in shaping microbial diversity. This study has reported the presence of Planctomycetes, Pirellula staleyi for the first time in the pomegranate field.

Metagenomics: A Tool for Exploring Key Microbiome With the Potentials for Improving Sustainable Agriculture

Microorganisms are immense in nature and exist in every imaginable ecological niche, performing a wide range of metabolic processes. Unfortunately, using traditional microbiological methods, most microorganisms remain unculturable. The emergence of metagenomics has resolved the challenge of capturing the entire microbial community in an environmental sample by enabling the analysis of whole genomes without requiring culturing. Metagenomics as a non-culture approach encompasses a greater amount of genetic information than traditional approaches. The plant root-associated microbial community is essential for plant growth and development, hence the interactions between microorganisms, soil, and plants is essential to understand and improve crop yields in rural and urban agriculture. Although some of these microorganisms are currently unculturable in the laboratory, metagenomic techniques may nevertheless be used to identify the microorganisms and their functional traits. A detailed understanding of these organisms and their interactions should facilitate an improvement of plant growth and sustainable crop production in soil and soilless agriculture. Therefore, the objective of this review is to provide insights into metagenomic techniques to study plant root-associated microbiota and microbial ecology. In addition, the different DNA-based techniques and their role in elaborating plant microbiomes are discussed. As an understanding of these microorganisms and their biotechnological potentials are unlocked through metagenomics, they can be used to develop new, useful and unique bio-fertilizers and bio-pesticides that are not harmful to the environment.

The shifts in the structure of the prokaryotic community of mountain-grassland soil under the influence of artificial larch plantations

Creation of artificial forest plantations on a global scale is one of the ways to mitigate the negative effects of climate change on ecosystems, at the same time providing soil protection from erosion, regulation of the hydrological regime and carbon sequestration in soils of different natural and climatic zones. However, the change of the dominant plant community cause significant ecosystem changes, reflecting at the structure and functioning of the soil microbial complex as well. The shifts in prokaryotic community of the meadow soil resulting from the conversion of the native meadow (further grassland) phytocenosis to the artificial forest plantations was investigated with the use of NGS sequencing technology and metabarcoding approach–amplicon sequencing of V4 region of 16 S rRNA (performed on Illumina Miseq platform). The identified shifts in taxonomic structure and diversity may be the result of changes in the physic-chemical conditions of soils and, on the other hand, may serve as indicators of such changes. Cultivation of larch led to an increase in the diversity of the prokaryotic community and its stratification by depth. The acidifying effect of larch manifested itself in an increase in the proportion and diversity of acidobacteria, in the abundance of oligotrophic microorganisms of phyla Chloroflexi, Firmicutes, and a simultaneous comparative decrease in the bacteria of Verrucomicrobia phylum, alphaproteobacteria of or. Rhizobiales and Burkholderiales. The absence of clearly expressed dominants in the prokaryotic community, as well as a significant increase in alpha-diversity indices, compared with the control plot of native mountain-meadow soil under grassland vegetation, suggests a transitional nature of the soil ecosystem of artificial forest plantations.

The Fate of Foodborne Pathogens in Manure Treated Soil

The aim of this review was to provide an update on the complex relationship between manure application, altered pathogen levels and antibiotic resistance. This is necessary to protect health and improve the sustainability of this major farming practice in agricultural systems based on high levels of manure production. It is important to consider soil health in relation to environment and land management practices in the context of the soil microflora and the introduction of pathogens on the health of the soil microbiome. Viable pathogens in manure spread on agricultural land may be distributed by leaching, surface run-off, water source contamination and contaminated crop removal. Thus it is important to understand how multiple pathogens can persist in manures and on soil at farm-scale and how crops produced under these conditions could be a potential transfer route for zoonotic pathogens. The management of pathogen load within livestock manure is a potential mechanism for the reduction and prevention of outbreaks infection with Escherichia coli, Listeria Salmonella, and Campylobacter. The ability of Campylobacter, E. coli, Listeria and Salmonella to combat environmental stress coupled with their survival on food crops and vegetables post-harvest emphasizes the need for further study of these pathogens along with the emerging pathogen Providencia given its link to disease in the immunocompromised and its’ high levels of antibiotic resistance. The management of pathogen load within livestock manure has been widely recognized as a potential mechanism for the reduction and prevention of outbreaks infection but any studies undertaken should be considered as region specific due to the variable nature of the factors influencing pathogen content and survival in manures and soil. Mediocre soils that require nutrients could be one template for research on manure inputs and their influence on soil health and on pathogen survival on grassland and in food crops.

Ecological Insights Into Community Interactions, Assembly Processes and Function in the Denitrifying Phosphorus Removal Activated Sludge Driven by Phosphorus Sources

The microbial characteristics in the wastewater treatment plants (WWTPs) strongly affect their optimal performance and functional stability. However, a cognitive gap remains regarding the characteristics of the microbial community driven by phosphorus sources, especially co-occurrence patterns and community assembly based on phylogenetic group. In this study, 59 denitrifying phosphorus removal (DPR) activated sludge samples were cultivated with phosphorus sources. The results suggested that homogeneous selection accounted for the largest proportion that ranged from 35.82 to 64.48%. Deterministic processes dominated in 12 microbial groups (bins): Candidatus_Accumulibacter and Pseudomonas in these bins belonged to phosphate-accumulating organisms (PAOs). Network analysis revealed that species interactions were intensive in cyclic nucleoside phosphate-influenced microbiota. Function prediction indicated that cyclic nucleoside phosphates increased the activity of enzymes related to denitrification and phosphorus metabolism and increased the α-diversity of microorganism but decreased the diversity of metabolic function. Based on these results, it was assumed that cyclic nucleoside phosphates, rather than inorganic phosphates, are the most available phosphorus source for majority microorganisms in DPR activated sludge. The study revealed the important role of phosphorus source in the construction and assembly of microbial communities and provided new insights about pollutant removal from WWTPs.

Characterization of soils conducive and non-conducive to Prunus replant disease

Successive orchard plantings of almond and other Prunus species exhibit reduced growth and yield in many California soils. This phenomenon, known as Prunus replant disease (PRD), can be prevented by preplant soil fumigation or anaerobic soil disinfestation, but its etiology is poorly understood and its incidence and severity are hard to predict. We report here on relationships among physicochemical variables, microbial community structure, and PRD induction in 25 diverse replant soils from California. In a greenhouse bioassay, soil was considered to be "PRD-inducing" when growth of peach seedlings in it was significantly increased by preplant fumigation and pasteurization, compared to an untreated control. PRD was induced in 18 of the 25 soils, and PRD severity correlated positively with soil exchangeable-K, pH, %clay, total %N, and electrical conductivity. The structure of bacterial, fungal, and oomycete communities differed significantly between the PRD-inducing and non-inducing soils, based on PERMANOVA of Bray Curtis dissimilarities. Bacterial class MB-A2-108 of phylum Actinobacteria had high relative abundances among PRD-inducing soils, while Bacteroidia were relatively abundant among non-inducing soils. Among fungi, many ASVs classified only to kingdom level were relatively abundant among PRD-inducing soils whereas ASVs of Trichoderma were relatively abundant among non-inducing soils. Random forest classification effectively discriminated between PRD-inducing and non-inducing soils, revealing many bacterial ASVs with high explanatory values. Random forest regression effectively accounted for PRD severity, with soil exchangeable-K and pH having high predictive value. Our work revealed several biotic and abiotic variables worthy of further examination in PRD etiology.

Harnessing intercellular signals to engineer the soil microbiome

Covering: Focus on 2015 to 2020Plant and soil microbiomes consist of diverse communities of organisms from across kingdoms and can profoundly affect plant growth and health. Natural product-based intercellular signals govern important interactions between microbiome members that ultimately regulate their beneficial or harmful impacts on the plant. Exploiting these evolved signalling circuits to engineer microbiomes towards beneficial interactions with crops is an attractive goal. There are few reports thus far of engineering the intercellular signalling of microbiomes, but this article argues that it represents a tremendous opportunity for advancing the field of microbiome engineering. This could be achieved through the selection of synergistic consortia in combination with genetic engineering of signal pathways to realise an optimised microbiome.

Response of soil enzyme activity and bacterial community to copper hydroxide nanofertilizer and its ionic analogue under single versus repeated applications

Nanosized agrochemicals like nanofertilizers are being applied to soils. Adverse impacts of nanofertilizers on soil microflora were reported in past studies, but only considering a single application. Repeated applications are however more likely to occur in agriculture. We investigated effects of single versus repeated applications of a copper hydroxide nanofertilizer formulation (NFF) on soil enzyme activity and bacterial community. One or three applications were performed within 21 days to achieve same final level of Cu in soil (48 mg(Cu)/kg: the recommended dose of NFF). Besides, the active ingredient (i.e., copper hydroxide nanotubes (NT)) and dispersing agent (DA) of NFF, and an ionic fertilizer (i.e., CuSO₄) were examined. Fluorescein diacetate hydrolase (FDAse), N-acetylglucosaminidase (NAG), leucine aminopeptidase (LAP), and urease (URE) showed negligible changes in the activities between the control and DA treatment. Bacterial community abundance, composition and diversity exhibited similar phenomena. Exposures to copper hydroxide NFF and NT or CuSO₄ enhanced the activities of FDAse and NAG, weakened the activity of URE, and showed negligible changes in the LAP activity irrespective of single and repeated applications. Concentrations of NO₃^--N and NH₄⁺-N in soil were also affected by the application mode of NFF. More importantly, responses of soil bacterial community to copper hydroxide NFF were highly dependent on its application mode, whereas similar responses were observed in the CuSO₄ treatment regardless of single or repeated applications. This study provided new insights into environmental risk of copper hydroxide NFF that were ignored in previous studies using a single exposure.

Bacterial community changes and their responses to nitrogen addition among different alpine grassland types at the eastern edge of Qinghai-Tibetan Plateau

Soil microbes play a fundamental role in maintaining nutrient biogeochemical cycles. To understand the distribution of soil bacterial communities on grassland plateaus, high-throughput sequencing was used to compare bacterial communities in soils from swamp meadows (SM), alpine meadows (AM), alpine steppes (AS), and desert steppes (DS) at the eastern edge of the Qinghai-Tibetan Plateau (QTP) in China. We then compared response to nitrogen addition between SM and DS soils in microcosms. Bacterial α-diversity decreased from SM > AM > AS > DS. Variations in soil properties across grassland types was associated with different soil bacterial communities corresponding to bacterial species associated with nutrient cycles to those associated with degradation. Soil moisture, pH, and total phosphorus were the main drivers of these differences. Nitrogen addition decreased bacterial diversity but had inconsistent effects on soil bacterial communities in SM and DS, which may also indicate that different alpine grassland soil types have unique bacterial communities. Alpine grassland degradation significantly affects bacterial communities, and the response to nitrogen addition depends on the alpine grassland type. These results allow for better predictions of soil bacteria community-level responses to geochemical and environmental change in alpine areas.

Predicting microbiomes through a deep latent space

Motivation

Microbial communities influence their environment by modifying the availability of compounds, such as nutrients or chemical elicitors. Knowing the microbial composition of a site is therefore relevant to improve productivity or health. However, sequencing facilities are not always available, or may be prohibitively expensive in some cases. Thus, it would be desirable to computationally predict the microbial composition from more accessible, easily-measured features.

Results

Integrating deep learning techniques with microbiome data, we propose an artificial neural network architecture based on heterogeneous autoencoders to condense the long vector of microbial abundance values into a deep latent space representation. Then, we design a model to predict the deep latent space and, consequently, to predict the complete microbial composition using environmental features as input. The performance of our system is examined using the rhizosphere microbiome of Maize. We reconstruct the microbial composition (717 taxa) from the deep latent space (10 values) with high fidelity (>0.9 Pearson correlation). We then successfully predict microbial composition from environmental variables, such as plant age, temperature or precipitation (0.73 Pearson correlation, 0.42 Bray–Curtis). We extend this to predict microbiome composition under hypothetical scenarios, such as future climate change conditions. Finally, via transfer learning, we predict microbial composition in a distinct scenario with only 100 sequences, and distinct environmental features. We propose that our deep latent space may assist microbiome-engineering strategies when technical or financial resources are limited, through predicting current or future microbiome compositions.

Availability and implementation

Software, results and data are available at https://github.com/jorgemf/DeepLatentMicrobiome

Supplementary information

Supplementary data are available at Bioinformatics online.

Shift of Dominant Species in Plant Community and Soil Chemical Properties Shape Soil Bacterial Community Characteristics and Putative Functions: A Case Study on Topographic Variation in a Mountain Pasture

Reducing management intensity according to the topography of pastures can change the dominant plant species from sown forages to weeds. It is unclear how changes in species dominance in plant community drive spatial variation in soil bacterial community characteristics and functions in association with edaphic condition. Analysing separately the effects of both plant communities and soil chemical properties on bacterial community is crucial for understanding the biogeographic process at a small scale. In this paper, we investigated soil bacterial responses in five plant communities (two forage and three weed), where >65% of the coverage was by one or two species. The structure and composition of the bacterial communities in the different microbiome were analysed using sequencing and their characteristics were assessed using the Functional Annotation of Prokaryotic Taxa (FAPROTAX) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Firmicutes and Planctomycetes responded only to one specific plant community, and each plant community harboured unique operational taxonomic units (OTUs) at the species level. There were a large percentage of uniquely absent OTUs for specific plant communities, suggesting that a negative effect is critical in the relationship between plants and bacteria. Bacterial diversity indices were influenced more by soil chemical properties than by plant communities. Some putative functions related to C and N recycling including nitrogen fixation were correlated with pH, electrical conductivity (EC) and nutrient levels, and this also implied that some biological functions, such as ureolysis and carbon metabolism, may decline when fertilisation intensity is reduced. Taken together, these results suggest that a shift of dominant species in plant community exerts individual effects on the bacterial community composition, which is different from the effect of soil chemical properties.

Plant Microbiota Beyond Farming Practices: A Review

Plants have always grown and evolved surrounded by numerous microorganisms that inhabit their environment, later termed microbiota. To enhance food production, humankind has relied on various farming practices such as irrigation, tilling, fertilization, and pest and disease management. Over the past few years, studies have highlighted the impacts of such practices, not only in terms of plant health or yields but also on the microbial communities associated with plants, which have been investigated through microbiome studies. Because some microorganisms exert beneficial traits that improve plant growth and health, understanding how to modulate microbial communities will help in developing smart farming and favor plant growth-promoting (PGP) microorganisms. With tremendous cost cuts in NGS technologies, metagenomic approaches are now affordable and have been widely used to investigate crop-associated microbiomes. Being able to engineer microbial communities in ways that benefit crop health and growth will help decrease the number of chemical inputs required. Against this background, this review explores the impacts of agricultural practices on soil- and plant-associated microbiomes, focusing on plant growth-promoting microorganisms from a metagenomic perspective.

Simulated Winter Incubation of Soil With Swine Manure Differentially Affects Multiple Antimicrobial Resistance Elements

Gastrointestinal bacteria that harbor antibiotic resistance genes (ARG) become enriched with antibiotic use. Livestock manure application to cropland for soil fertility presents a concern that ARG and bacteria may proliferate and be transported in the environment. In the United States, manure applications typically occur during autumn with slow mineralization until spring planting season. A laboratory soil incubation study was conducted mimicking autumn swine manure application to soils with concentrations of selected ARG monitored during simulated 120-day winter incubation with multiple freeze-thaw events. Additionally, the effects of two soil moistures [10 and 30% water holding capacity (WHC)] and two manure treatments [raw versus hydrated lime alkaline stabilization (HLAS)] were assessed. Fourteen tetracycline resistance genes were evaluated; tet(D), tet(G), and tet(L) were detected in background soil while swine manure contained tet(A), tet(B), tet(C), tet(G), tet(M), tet(O), tet(Q), and tet(X). By day 120, the manure-borne tet(M) and tet(O) were still detected while tet(C), tet(D), tet(L), and tet(X) genes were detected less frequently. Other tet resistance genes were detected rarely, if at all. The sum of unique tet resistance genes among all treatments decreased during the incubation from an average of 8.9 to 3.8 unique tet resistance genes. Four resistance elements, intI1, bla_ctx–m–32, sul(I), erm(B), and 16s rRNA genes were measured using quantitative PCR. ARG abundances relative to 16S abundance were initially greater in the raw manure compared to background soil (−1.53 to −3.92 log abundance in manure; −4.02 to <−6.7 log abundance in soil). In the mixed manure/soil, relative abundance of the four resistance elements decreased (0.87 to 1.94 log abundance) during the incubation largely because 16S rRNA genes increased by 1.21 log abundance. Throughout the incubation, the abundance of intI1, bla_ctx–m–32, sul(I), and erm(B) per gram in soil amended with HLAS-treated manure was lower than in soil amended with raw manure. Under low initial soil moisture conditions, HLAS treatment reduced the abundance of intI1 and resulted in loss of bla_ctx–m–32, sul(I), and erm(B)] compared to other treatment-moisture combinations. Although one might expect antibiotic resistance to be relatively unchanged after simulated winter manure application to soil, a variety of changes in diversity and relative abundance can be expected.