OSTI.GOV Journal Article: Primer set 2.0 for highly parallel qPCR array targeting antibiotic resistance genes and mobile genetic elements
Title: Primer set 2.0 for highly parallel qPCR array targeting antibiotic resistance genes and mobile genetic elements
Stedtfeld, Robert D. [1]; Guo, Xueping [2]; Stedtfeld, Tiffany M. [1]; Sheng, Hongjie [3]; Williams, Maggie R. [1]; Hauschild, Kristin [4]; Gunturu, Santosh [4]; Tift, Leo [4]; Wang, Fang [3]; Howe, Adina [5]; Chai, Benli [4]; Yin, Daqiang [6]; Cole, James R. [7]; Tiedje, James M. [7]; Hashsham, Syed A. [8]
Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan 48824, USA
State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China; Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan 48824, USA; Center for Microbial Ecology, Michigan State University, East Lansing, Michigan 48824, USA
Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan 48824, USA; Center for Microbial Ecology, Michigan State University, East Lansing, Michigan 48824, USA; Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
Center for Microbial Ecology, Michigan State University, East Lansing, Michigan 48824, USA
Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, Iowa 50010, USA
State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan 48824, USA; Center for Microbial Ecology, Michigan State University, East Lansing, Michigan 48824, USA
Department of Civil and Environmental Engineering, Michigan State University, East Lansing, Michigan 48824, USA; Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan 48824, USA; Center for Microbial Ecology, Michigan State University, East Lansing, Michigan 48824, USA
Michigan State Univ., East Lansing, MI (United States)
USDOE Office of Science (SC)
FG02-99ER62848
FEMS Microbiology Ecology (Online)
Journal Volume: 94; Journal Issue: 9; Journal ID: ISSN 1574-6941
Federation of European Microbiological Societies
Stedtfeld, Robert D., Guo, Xueping, Stedtfeld, Tiffany M., Sheng, Hongjie, Williams, Maggie R., Hauschild, Kristin, Gunturu, Santosh, Tift, Leo, Wang, Fang, Howe, Adina, Chai, Benli, Yin, Daqiang, Cole, James R., Tiedje, James M., and Hashsham, Syed A. Primer set 2.0 for highly parallel qPCR array targeting antibiotic resistance genes and mobile genetic elements. United States: N. p., 2018. Web. doi:10.1093/femsec/fiy130.
Stedtfeld, Robert D., Guo, Xueping, Stedtfeld, Tiffany M., Sheng, Hongjie, Williams, Maggie R., Hauschild, Kristin, Gunturu, Santosh, Tift, Leo, Wang, Fang, Howe, Adina, Chai, Benli, Yin, Daqiang, Cole, James R., Tiedje, James M., & Hashsham, Syed A. Primer set 2.0 for highly parallel qPCR array targeting antibiotic resistance genes and mobile genetic elements. United States. doi:10.1093/femsec/fiy130.
Stedtfeld, Robert D., Guo, Xueping, Stedtfeld, Tiffany M., Sheng, Hongjie, Williams, Maggie R., Hauschild, Kristin, Gunturu, Santosh, Tift, Leo, Wang, Fang, Howe, Adina, Chai, Benli, Yin, Daqiang, Cole, James R., Tiedje, James M., and Hashsham, Syed A. Mon . "Primer set 2.0 for highly parallel qPCR array targeting antibiotic resistance genes and mobile genetic elements". United States. doi:10.1093/femsec/fiy130.
title = {Primer set 2.0 for highly parallel qPCR array targeting antibiotic resistance genes and mobile genetic elements},
author = {Stedtfeld, Robert D. and Guo, Xueping and Stedtfeld, Tiffany M. and Sheng, Hongjie and Williams, Maggie R. and Hauschild, Kristin and Gunturu, Santosh and Tift, Leo and Wang, Fang and Howe, Adina and Chai, Benli and Yin, Daqiang and Cole, James R. and Tiedje, James M. and Hashsham, Syed A.},
doi = {10.1093/femsec/fiy130},
journal = {FEMS Microbiology Ecology (Online)},
DOI: 10.1093/femsec/fiy130
Clusters of antibiotic resistance genes enriched together stay together in swine agriculture
Journal Article Johnson, Timothy A. ; Stedtfeld, Robert D. ; Wang, Qiong ; ... - mBio (Online)
Antibiotic resistance is a worldwide health risk, but the influence of animal agriculture on the genetic context and enrichment of individual antibiotic resistance alleles remains unclear. Using quantitative PCR followed by amplicon sequencing, we quantified and sequenced 44 genes related to antibiotic resistance, mobile genetic elements, and bacterial phylogeny in microbiomes from U.S. laboratory swine and from swine farms from three Chinese regions. We identified highly abundant resistance clusters: groups of resistance and mobile genetic element alleles that cooccur. For example, the abundance of genes conferring resistance to six classes of antibiotics together with class 1 integrase and the abundancemore » of IS6100-type transposons in three Chinese regions are directly correlated. These resistance cluster genes likely colocalize in microbial genomes in the farms. Resistance cluster alleles were dramatically enriched (up to 1 to 10% as abundant as 16S rRNA) and indicate that multidrug-resistant bacteria are likely the norm rather than an exception in these communities. This enrichment largely occurred independently of phylogenetic composition; thus, resistance clusters are likely present in many bacterial taxa. Furthermore, resistance clusters contain resistance genes that confer resistance to antibiotics independently of their particular use on the farms. Selection for these clusters is likely due to the use of only a subset of the broad range of chemicals to which the clusters confer resistance. The scale of animal agriculture and its wastes, the enrichment and horizontal gene transfer potential of the clusters, and the vicinity of large human populations suggest that managing this resistance reservoir is important for minimizing human risk.Agricultural antibiotic use results in clusters of cooccurring resistance genes that together confer resistance to multiple antibiotics. The use of a single antibiotic could select for an entire suite of resistance genes if they are genetically linked. No links to bacterial membership were observed for these clusters of resistance genes. These findings urge deeper understanding of colocalization of resistance genes and mobile genetic elements in resistance islands and their distribution throughout antibiotic-exposed microbiomes. In addition, as governments seek to combat the rise in antibiotic resistance, a balance is sought between ensuring proper animal health and welfare and preserving medically important antibiotics for therapeutic use. Metagenomic and genomic monitoring will be critical to determine if resistance genes can be reduced in animal microbiomes, or if these gene clusters will continue to be coselected by antibiotics not deemed medically important for human health but used for growth promotion or by medically important antibiotics used therapeutically.« less
DOI: 10.1128/mBio.02214-15
Xander: employing a novel method for efficient gene-targeted metagenomic assembly
Journal Article Wang, Qiong ; Fish, Jordan A. ; Gilman, Mariah ; ... - Microbiome
Here, metagenomics can provide important insight into microbial communities. However, assembling metagenomic datasets has proven to be computationally challenging. Current methods often assemble only fragmented partial genes. We present a novel method for targeting assembly of specific protein-coding genes. This method combines a de Bruijn graph, as used in standard assembly approaches, and a protein profile hidden Markov model (HMM) for the gene of interest, as used in standard annotation approaches. These are used to create a novel combined weighted assembly graph. Xander performs both assembly and annotation concomitantly using information incorporated in this graph. We demonstrate the utility ofmore » this approach by assembling contigs for one phylogenetic marker gene and for two functional marker genes, first on Human Microbiome Project (HMP)-defined community Illumina data and then on 21 rhizosphere soil metagenomic datasets from three different crops totaling over 800 Gbp of unassembled data. We compared our method to a recently published bulk metagenome assembly method and a recently published gene-targeted assembler and found our method produced more, longer, and higher quality gene sequences. In conclusion, xander combines gene assignment with the rapid assembly of full-length or near full-length functional genes from metagenomic data without requiring bulk assembly or post-processing to find genes of interest. HMMs used for assembly can be tailored to the targeted genes, allowing flexibility to improve annotation over generic annotation pipelines.« less
How Much Do rRNA Gene Surveys Underestimate Extant Bacterial Diversity?
Journal Article Rodriguez-R, Luis M. ; Castro, Juan C. ; Kyrpides, Nikos C. ; ... - Applied and Environmental Microbiology
The most common practice in studying and cataloguing prokaryotic diversity involves the grouping of sequences into operational taxonomic units (OTUs) at the 97% 16S rRNA gene sequence identity level, often using partial gene sequences, such as PCR-generated amplicons. Due to the high sequence conservation of rRNA genes, organisms belonging to closely related yet distinct species may be grouped under the same OTU. With this being said, it remains unclear how much diversity has been underestimated by this practice. To address this question, we compared the OTUs of genomes defined at the 97% or 98.5% 16S rRNA gene identity level againstmore » OTUs of the same genomes defined at the 95% whole-genome average nucleotide identity (ANI), which is a much more accurate proxy for species. Our results show that OTUs resulting from a 98.5% 16S rRNA gene identity cutoff are more accurate than 97% compared to 95% ANI (90.5% versus 89.9% accuracy) but indistinguishable from any other threshold in the 98.29 to 98.78% range. Even with the more stringent thresholds, the 16S rRNA gene-based approach commonly underestimates the number of OTUs by ~12%, on average, compared to the ANI-based approach (~14% underestimation when using the 97% identity threshold). Moreover, the degree of underestimation can become 50% or more for certain taxa, such as the genera Pseudomonas, Burkholderia, Escherichia, Campylobacter, and Citrobacter. These results provide a quantitative view of the degree of underestimation of extant prokaryotic diversity by 16S rRNA gene-defined OTUs and suggest that genomic resolution is often necessary. IMPORTANCE: Species diversity is one of the most fundamental pieces of information for community ecology and conservational biology. Thus, employing accurate proxies for what a species or the unit of diversity is are cornerstones for a large set of microbial ecology and diversity studies. The most common proxies currently used rely on the clustering of 16S rRNA gene sequences at some threshold of nucleotide identity, typically 97% or 98.5%. Here, we explore how well this strategy reflects the more accurate whole-genome-based proxies and determine the frequency with which the high conservation of 16S rRNA sequences masks substantial species-level diversity.« less
Land use intensification in the humid tropics increased both alpha and beta diversity of soil bacteria
Journal Article de Carvalho, Teotonio Soares ; Jesus, Ederson da Conceição ; Barlow, Jos ; ... - Ecology
DOI: 10.1002/ecy.1513