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Pubmed Article
Microbial community composition and diversity via 16S rRNA gene amplicons: evaluating the illumina platform.
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PLoS ONE
PUBLISHED: 02-04-2015
As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner - with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition.
Authors: Sylvie Sanschagrin, Etienne Yergeau.
Published: 08-29-2014
ABSTRACT
One of the major questions in microbial ecology is “who is there?” This question can be answered using various tools, but one of the long-lasting gold standards is to sequence 16S ribosomal RNA (rRNA) gene amplicons generated by domain-level PCR reactions amplifying from genomic DNA. Traditionally, this was performed by cloning and Sanger (capillary electrophoresis) sequencing of PCR amplicons. The advent of next-generation sequencing has tremendously simplified and increased the sequencing depth for 16S rRNA gene sequencing. The introduction of benchtop sequencers now allows small labs to perform their 16S rRNA sequencing in-house in a matter of days. Here, an approach for 16S rRNA gene amplicon sequencing using a benchtop next-generation sequencer is detailed. The environmental DNA is first amplified by PCR using primers that contain sequencing adapters and barcodes. They are then coupled to spherical particles via emulsion PCR. The particles are loaded on a disposable chip and the chip is inserted in the sequencing machine after which the sequencing is performed. The sequences are retrieved in fastq format, filtered and the barcodes are used to establish the sample membership of the reads. The filtered and binned reads are then further analyzed using publically available tools. An example analysis where the reads were classified with a taxonomy-finding algorithm within the software package Mothur is given. The method outlined here is simple, inexpensive and straightforward and should help smaller labs to take advantage from the ongoing genomic revolution.
19 Related JoVE Articles!
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A Hybrid DNA Extraction Method for the Qualitative and Quantitative Assessment of Bacterial Communities from Poultry Production Samples
Authors: Michael J. Rothrock Jr., Kelli L. Hiett, John Gamble, Andrew C. Caudill, Kellie M. Cicconi-Hogan, J. Gregory Caporaso.
Institutions: USDA-Agricultural Research Service, USDA-Agricultural Research Service, Oregon State University, University of Georgia, Northern Arizona University.
The efficacy of DNA extraction protocols can be highly dependent upon both the type of sample being investigated and the types of downstream analyses performed. Considering that the use of new bacterial community analysis techniques (e.g., microbiomics, metagenomics) is becoming more prevalent in the agricultural and environmental sciences and many environmental samples within these disciplines can be physiochemically and microbiologically unique (e.g., fecal and litter/bedding samples from the poultry production spectrum), appropriate and effective DNA extraction methods need to be carefully chosen. Therefore, a novel semi-automated hybrid DNA extraction method was developed specifically for use with environmental poultry production samples. This method is a combination of the two major types of DNA extraction: mechanical and enzymatic. A two-step intense mechanical homogenization step (using bead-beating specifically formulated for environmental samples) was added to the beginning of the “gold standard” enzymatic DNA extraction method for fecal samples to enhance the removal of bacteria and DNA from the sample matrix and improve the recovery of Gram-positive bacterial community members. Once the enzymatic extraction portion of the hybrid method was initiated, the remaining purification process was automated using a robotic workstation to increase sample throughput and decrease sample processing error. In comparison to the strict mechanical and enzymatic DNA extraction methods, this novel hybrid method provided the best overall combined performance when considering quantitative (using 16S rRNA qPCR) and qualitative (using microbiomics) estimates of the total bacterial communities when processing poultry feces and litter samples.
Molecular Biology, Issue 94, DNA extraction, poultry, environmental, feces, litter, semi-automated, microbiomics, qPCR
52161
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RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells
Authors: Dilyara Cheranova, Margaret Gibson, Suman Chaudhary, Li Qin Zhang, Daniel P. Heruth, Dmitry N. Grigoryev, Shui Qing Ye.
Institutions: Children's Mercy Hospital and Clinics, School of Medicine, University of Missouri-Kansas City.
The characterization of gene expression in cells via measurement of mRNA levels is a useful tool in determining how the transcriptional machinery of the cell is affected by external signals (e.g. drug treatment), or how cells differ between a healthy state and a diseased state. With the advent and continuous refinement of next-generation DNA sequencing technology, RNA-sequencing (RNA-seq) has become an increasingly popular method of transcriptome analysis to catalog all species of transcripts, to determine the transcriptional structure of all expressed genes and to quantify the changing expression levels of the total set of transcripts in a given cell, tissue or organism1,2 . RNA-seq is gradually replacing DNA microarrays as a preferred method for transcriptome analysis because it has the advantages of profiling a complete transcriptome, providing a digital type datum (copy number of any transcript) and not relying on any known genomic sequence3. Here, we present a complete and detailed protocol to apply RNA-seq to profile transcriptomes in human pulmonary microvascular endothelial cells with or without thrombin treatment. This protocol is based on our recent published study entitled "RNA-seq Reveals Novel Transcriptome of Genes and Their Isoforms in Human Pulmonary Microvascular Endothelial Cells Treated with Thrombin,"4 in which we successfully performed the first complete transcriptome analysis of human pulmonary microvascular endothelial cells treated with thrombin using RNA-seq. It yielded unprecedented resources for further experimentation to gain insights into molecular mechanisms underlying thrombin-mediated endothelial dysfunction in the pathogenesis of inflammatory conditions, cancer, diabetes, and coronary heart disease, and provides potential new leads for therapeutic targets to those diseases. The descriptive text of this protocol is divided into four parts. The first part describes the treatment of human pulmonary microvascular endothelial cells with thrombin and RNA isolation, quality analysis and quantification. The second part describes library construction and sequencing. The third part describes the data analysis. The fourth part describes an RT-PCR validation assay. Representative results of several key steps are displayed. Useful tips or precautions to boost success in key steps are provided in the Discussion section. Although this protocol uses human pulmonary microvascular endothelial cells treated with thrombin, it can be generalized to profile transcriptomes in both mammalian and non-mammalian cells and in tissues treated with different stimuli or inhibitors, or to compare transcriptomes in cells or tissues between a healthy state and a disease state.
Genetics, Issue 72, Molecular Biology, Immunology, Medicine, Genomics, Proteins, RNA-seq, Next Generation DNA Sequencing, Transcriptome, Transcription, Thrombin, Endothelial cells, high-throughput, DNA, genomic DNA, RT-PCR, PCR
4393
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Targeted DNA Methylation Analysis by Next-generation Sequencing
Authors: Dustin R. Masser, David R. Stanford, Willard M. Freeman.
Institutions: University of Oklahoma College of Medicine, University of Oklahoma College of Medicine.
The role of epigenetic processes in the control of gene expression has been known for a number of years. DNA methylation at cytosine residues is of particular interest for epigenetic studies as it has been demonstrated to be both a long lasting and a dynamic regulator of gene expression. Efforts to examine epigenetic changes in health and disease have been hindered by the lack of high-throughput, quantitatively accurate methods. With the advent and popularization of next-generation sequencing (NGS) technologies, these tools are now being applied to epigenomics in addition to existing genomic and transcriptomic methodologies. For epigenetic investigations of cytosine methylation where regions of interest, such as specific gene promoters or CpG islands, have been identified and there is a need to examine significant numbers of samples with high quantitative accuracy, we have developed a method called Bisulfite Amplicon Sequencing (BSAS). This method combines bisulfite conversion with targeted amplification of regions of interest, transposome-mediated library construction and benchtop NGS. BSAS offers a rapid and efficient method for analysis of up to 10 kb of targeted regions in up to 96 samples at a time that can be performed by most research groups with basic molecular biology skills. The results provide absolute quantitation of cytosine methylation with base specificity. BSAS can be applied to any genomic region from any DNA source. This method is useful for hypothesis testing studies of target regions of interest as well as confirmation of regions identified in genome-wide methylation analyses such as whole genome bisulfite sequencing, reduced representation bisulfite sequencing, and methylated DNA immunoprecipitation sequencing.
Molecular Biology, Issue 96, Epigenetics, DNA methylation, next-generation sequencing, bioinformatics, gene expression, cytosine, CpG, gene expression regulation
52488
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Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
Authors: Francine E. Garrett-Bakelman, Caroline K. Sheridan, Thadeous J. Kacmarczyk, Jennifer Ishii, Doron Betel, Alicia Alonso, Christopher E. Mason, Maria E. Figueroa, Ari M. Melnick.
Institutions: Weill Cornell Medical College, Weill Cornell Medical College, Weill Cornell Medical College, University of Michigan.
DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine methylation patterns in cells. Reduced representation of whole genome bisulfite sequencing was developed to detect quantitative base pair resolution cytosine methylation patterns at GC-rich genomic loci. This is accomplished by combining the use of a restriction enzyme followed by bisulfite conversion. Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) increases the biologically relevant genomic loci covered and has been used to profile cytosine methylation in DNA from human, mouse and other organisms. ERRBS initiates with restriction enzyme digestion of DNA to generate low molecular weight fragments for use in library preparation. These fragments are subjected to standard library construction for next generation sequencing. Bisulfite conversion of unmethylated cytosines prior to the final amplification step allows for quantitative base resolution of cytosine methylation levels in covered genomic loci. The protocol can be completed within four days. Despite low complexity in the first three bases sequenced, ERRBS libraries yield high quality data when using a designated sequencing control lane. Mapping and bioinformatics analysis is then performed and yields data that can be easily integrated with a variety of genome-wide platforms. ERRBS can utilize small input material quantities making it feasible to process human clinical samples and applicable in a range of research applications. The video produced demonstrates critical steps of the ERRBS protocol.
Genetics, Issue 96, Epigenetics, bisulfite sequencing, DNA methylation, genomic DNA, 5-methylcytosine, high-throughput
52246
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Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples
Authors: Miguel I. Uyaguari-Diaz, Jared R. Slobodan, Matthew J. Nesbitt, Matthew A. Croxen, Judith Isaac-Renton, Natalie A. Prystajecky, Patrick Tang.
Institutions: The University of British Columbia, Coastal Genomics, British Columbia Public Health Microbiology and Reference Laboratory.
Next-generation sequencing of environmental samples can be challenging because of the variable DNA quantity and quality in these samples. High quality DNA libraries are needed for optimal results from next-generation sequencing. Environmental samples such as water may have low quality and quantities of DNA as well as contaminants that co-precipitate with DNA. The mechanical and enzymatic processes involved in extraction and library preparation may further damage the DNA. Gel size selection enables purification and recovery of DNA fragments of a defined size for sequencing applications. Nevertheless, this task is one of the most time-consuming steps in the DNA library preparation workflow. The protocol described here enables complete automation of agarose gel loading, electrophoretic analysis, and recovery of targeted DNA fragments. In this study, we describe a high-throughput approach to prepare high quality DNA libraries from freshwater samples that can be applied also to other environmental samples. We used an indirect approach to concentrate bacterial cells from environmental freshwater samples; DNA was extracted using a commercially available DNA extraction kit, and DNA libraries were prepared using a commercial transposon-based protocol. DNA fragments of 500 to 800 bp were gel size selected using Ranger Technology, an automated electrophoresis workstation. Sequencing of the size-selected DNA libraries demonstrated significant improvements to read length and quality of the sequencing reads.
Environmental Sciences, Issue 98, environmental samples, next-generation sequencing, DNA libraries, Ranger Technology, gel size selection, metagenomics, water samples
52685
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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Authors: Savannah E. Sanchez, Daniel A. Cuevas, Jason E. Rostron, Tiffany Y. Liang, Cullen G. Pivaroff, Matthew R. Haynes, Jim Nulton, Ben Felts, Barbara A. Bailey, Peter Salamon, Robert A. Edwards, Alex B. Burgin, Anca M. Segall, Forest Rohwer.
Institutions: San Diego State University, San Diego State University, San Diego State University, San Diego State University, San Diego State University, Argonne National Laboratory, Broad Institute.
Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.
Immunology, Issue 100, phenomics, phage, viral metagenome, Multi-phenotype Assay Plates (MAPs), continuous culture, metabolomics
52854
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Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology
Authors: Andreas Florian Haas, Ben Knowles, Yan Wei Lim, Tracey McDole Somera, Linda Wegley Kelly, Mark Hatay, Forest Rohwer.
Institutions: San Diego State University, University of California San Diego.
Here we introduce a series of thoroughly tested and well standardized research protocols adapted for use in remote marine environments. The sampling protocols include the assessment of resources available to the microbial community (dissolved organic carbon, particulate organic matter, inorganic nutrients), and a comprehensive description of the viral and bacterial communities (via direct viral and microbial counts, enumeration of autofluorescent microbes, and construction of viral and microbial metagenomes). We use a combination of methods, which represent a dispersed field of scientific disciplines comprising already established protocols and some of the most recent techniques developed. Especially metagenomic sequencing techniques used for viral and bacterial community characterization, have been established only in recent years, and are thus still subjected to constant improvement. This has led to a variety of sampling and sample processing procedures currently in use. The set of methods presented here provides an up to date approach to collect and process environmental samples. Parameters addressed with these protocols yield the minimum on information essential to characterize and understand the underlying mechanisms of viral and microbial community dynamics. It gives easy to follow guidelines to conduct comprehensive surveys and discusses critical steps and potential caveats pertinent to each technique.
Environmental Sciences, Issue 93, dissolved organic carbon, particulate organic matter, nutrients, DAPI, SYBR, microbial metagenomics, viral metagenomics, marine environment
52131
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Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
Authors: Yan Wei Lim, Matthew Haynes, Mike Furlan, Charles E. Robertson, J. Kirk Harris, Forest Rohwer.
Institutions: San Diego State University, DOE Joint Genome Institute, University of Colorado, University of Colorado.
The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.
Molecular Biology, Issue 94, virome, microbiome, metagenomics, metatranscriptomics, cystic fibrosis, mucosal-surface
52117
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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
Authors: Shan Zong, Shuyun Deng, Kenian Chen, Jia Qian Wu.
Institutions: The University of Texas Graduate School of Biomedical Sciences at Houston.
Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study. RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment. In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo.
Genetics, Issue 93, EML Cells, Self-renewal, Differentiation, Hematopoietic precursor cell, RNA-Sequencing, Data analysis
52104
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Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources
Authors: Adrian W. Briggs, Jeffrey M. Good, Richard E. Green, Johannes Krause, Tomislav Maricic, Udo Stenzel, Svante Pääbo.
Institutions: Max-Planck Institute for Evolutionary Anthropology, Leipzig.
We present a method of targeted DNA sequence retrieval from DNA sources which are heavily degraded and contaminated with microbial DNA, as is typical of ancient bones. The method greatly reduces sample destruction and sequencing demands relative to direct PCR or shotgun sequencing approaches. We used this method to reconstruct the complete mitochondrial DNA (mtDNA) genomes of five Neandertals from across their geographic range. The mtDNA genetic diversity of the late Neandertals was approximately three times lower than that of contemporary modern humans. Together with analyses of mtDNA protein evolution, these data suggest that the long-term effective population size of Neandertals was smaller than that of modern humans and extant great apes.
Cellular Biology, Issue 31, Neandertal, anthropology, evolution, ancient DNA, DNA sequencing, targeted sequencing, capture
1573
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Scalable High Throughput Selection From Phage-displayed Synthetic Antibody Libraries
Authors: Shane Miersch, Zhijian Li, Rachel Hanna, Megan E. McLaughlin, Michael Hornsby, Tet Matsuguchi, Marcin Paduch, Annika Sääf, Jim Wells, Shohei Koide, Anthony Kossiakoff, Sachdev S. Sidhu.
Institutions: The Recombinant Antibody Network, University of Toronto, University of California, San Francisco at Mission Bay, The University of Chicago.
The demand for antibodies that fulfill the needs of both basic and clinical research applications is high and will dramatically increase in the future. However, it is apparent that traditional monoclonal technologies are not alone up to this task. This has led to the development of alternate methods to satisfy the demand for high quality and renewable affinity reagents to all accessible elements of the proteome. Toward this end, high throughput methods for conducting selections from phage-displayed synthetic antibody libraries have been devised for applications involving diverse antigens and optimized for rapid throughput and success. Herein, a protocol is described in detail that illustrates with video demonstration the parallel selection of Fab-phage clones from high diversity libraries against hundreds of targets using either a manual 96 channel liquid handler or automated robotics system. Using this protocol, a single user can generate hundreds of antigens, select antibodies to them in parallel and validate antibody binding within 6-8 weeks. Highlighted are: i) a viable antigen format, ii) pre-selection antigen characterization, iii) critical steps that influence the selection of specific and high affinity clones, and iv) ways of monitoring selection effectiveness and early stage antibody clone characterization. With this approach, we have obtained synthetic antibody fragments (Fabs) to many target classes including single-pass membrane receptors, secreted protein hormones, and multi-domain intracellular proteins. These fragments are readily converted to full-length antibodies and have been validated to exhibit high affinity and specificity. Further, they have been demonstrated to be functional in a variety of standard immunoassays including Western blotting, ELISA, cellular immunofluorescence, immunoprecipitation and related assays. This methodology will accelerate antibody discovery and ultimately bring us closer to realizing the goal of generating renewable, high quality antibodies to the proteome.
Immunology, Issue 95, Bacteria, Viruses, Amino Acids, Peptides, and Proteins, Nucleic Acids, Nucleotides, and Nucleosides, Life Sciences (General), phage display, synthetic antibodies, high throughput, antibody selection, scalable methodology
51492
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Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose
Authors: Yongqi Shao, Erika M Arias-Cordero, Wilhelm Boland.
Institutions: Max Planck Institute for Chemical Ecology.
Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to identify commensal or mutualistic bacteria species. The latter ones, have been observed to serve multiple functions to the insect, i.e. helping in insect reproduction1, boosting the immune response2, pheromone production3, as well as nutrition, including the synthesis of essential amino acids4, among others.     Due to the importance of these associations, many efforts have been made to characterize the communities down to the individual members. However, most of these efforts were either based on cultivation methods or relied on the generation of 16S rRNA gene fragments which were sequenced for final identification. Unfortunately, these approaches only identified the bacterial species present in the gut and provided no information on the metabolic activity of the microorganisms. To characterize the metabolically active bacterial species in the gut of an insect, we used stable isotope probing (SIP) in vivo employing 13C-glucose as a universal substrate. This is a promising culture-free technique that allows the linkage of microbial phylogenies to their particular metabolic activity. This is possible by tracking stable, isotope labeled atoms from substrates into microbial biomarkers, such as DNA and RNA5. The incorporation of 13C isotopes into DNA increases the density of the labeled DNA compared to the unlabeled (12C) one. In the end, the 13C-labeled DNA or RNA is separated by density-gradient ultracentrifugation from the 12C-unlabeled similar one6. Subsequent molecular analysis of the separated nucleic acid isotopomers provides the connection between metabolic activity and identity of the species. Here, we present the protocol used to characterize the metabolically active bacteria in the gut of a generalist insect (our model system), Spodoptera littoralis (Lepidoptera, Noctuidae). The phylogenetic analysis of the DNA was done using pyrosequencing, which allowed high resolution and precision in the identification of insect gut bacterial community. As main substrate, 13C-labeled glucose was used in the experiments. The substrate was fed to the insects using an artificial diet.
Microbiology, Issue 81, Insects, Sequence Analysis, Genetics, Microbial, Bacteria, Lepidoptera, Spodoptera littoralis, stable-isotope-probing (SIP), pyro-sequencing, 13C-glucose, gut, microbiota, bacteria
50734
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Pyrosequencing for Microbial Identification and Characterization
Authors: Patrick J. Cummings, Ray Ahmed, Jeffrey A. Durocher, Adam Jessen, Tamar Vardi, Kristina M. Obom.
Institutions: Johns Hopkins University, Qiagen Sciences, Inc..
Pyrosequencing is a versatile technique that facilitates microbial genome sequencing that can be used to identify bacterial species, discriminate bacterial strains and detect genetic mutations that confer resistance to anti-microbial agents. The advantages of pyrosequencing for microbiology applications include rapid and reliable high-throughput screening and accurate identification of microbes and microbial genome mutations. Pyrosequencing involves sequencing of DNA by synthesizing the complementary strand a single base at a time, while determining the specific nucleotide being incorporated during the synthesis reaction. The reaction occurs on immobilized single stranded template DNA where the four deoxyribonucleotides (dNTP) are added sequentially and the unincorporated dNTPs are enzymatically degraded before addition of the next dNTP to the synthesis reaction. Detection of the specific base incorporated into the template is monitored by generation of chemiluminescent signals. The order of dNTPs that produce the chemiluminescent signals determines the DNA sequence of the template. The real-time sequencing capability of pyrosequencing technology enables rapid microbial identification in a single assay. In addition, the pyrosequencing instrument, can analyze the full genetic diversity of anti-microbial drug resistance, including typing of SNPs, point mutations, insertions, and deletions, as well as quantification of multiple gene copies that may occur in some anti-microbial resistance patterns.
Microbiology, Issue 78, Genetics, Molecular Biology, Basic Protocols, Genomics, Eukaryota, Bacteria, Viruses, Bacterial Infections and Mycoses, Virus Diseases, Diagnosis, Therapeutics, Equipment and Supplies, Technology, Industry, and Agriculture, Life Sciences (General), Pyrosequencing, DNA, Microbe, PCR, primers, Next-Generation, high-throughput, sequencing
50405
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Depletion of Ribosomal RNA for Mosquito Gut Metagenomic RNA-seq
Authors: Phanidhar Kukutla, Matthew Steritz, Jiannong Xu.
Institutions: New Mexico State University.
The mosquito gut accommodates dynamic microbial communities across different stages of the insect's life cycle. Characterization of the genetic capacity and functionality of the gut community will provide insight into the effects of gut microbiota on mosquito life traits. Metagenomic RNA-Seq has become an important tool to analyze transcriptomes from various microbes present in a microbial community. Messenger RNA usually comprises only 1-3% of total RNA, while rRNA constitutes approximately 90%. It is challenging to enrich messenger RNA from a metagenomic microbial RNA sample because most prokaryotic mRNA species lack stable poly(A) tails. This prevents oligo d(T) mediated mRNA isolation. Here, we describe a protocol that employs sample derived rRNA capture probes to remove rRNA from a metagenomic total RNA sample. To begin, both mosquito and microbial small and large subunit rRNA fragments are amplified from a metagenomic community DNA sample. Then, the community specific biotinylated antisense ribosomal RNA probes are synthesized in vitro using T7 RNA polymerase. The biotinylated rRNA probes are hybridized to the total RNA. The hybrids are captured by streptavidin-coated beads and removed from the total RNA. This subtraction-based protocol efficiently removes both mosquito and microbial rRNA from the total RNA sample. The mRNA enriched sample is further processed for RNA amplification and RNA-Seq.
Genetics, Issue 74, Infection, Infectious Diseases, Molecular Biology, Cellular Biology, Microbiology, Genomics, biology (general), genetics (animal and plant), life sciences, Eukaryota, Bacteria, metagenomics, metatranscriptome, RNA-seq, rRNA depletion, mRNA enrichment, mosquito gut microbiome, RNA, DNA, sequencing
50093
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
4273
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Authors: Francesco Vallania, Enrique Ramos, Sharon Cresci, Robi D. Mitra, Todd E. Druley.
Institutions: Washington University School of Medicine, Washington University School of Medicine, Washington University School of Medicine.
As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought3. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease4,5. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants6-8. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators. To address this need, we have developed a pooled sequencing approach1,9 and a novel software package1 for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (http://www.ibridgenetwork.org/wustl/splinter). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.
Genetics, Issue 64, Genomics, Cancer Biology, Bioinformatics, Pooled DNA sequencing, SPLINTER, rare genetic variants, genetic screening, phenotype, high throughput, computational analysis, DNA, PCR, primers
3943
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Chromatin Interaction Analysis with Paired-End Tag Sequencing (ChIA-PET) for Mapping Chromatin Interactions and Understanding Transcription Regulation
Authors: Yufen Goh, Melissa J. Fullwood, Huay Mei Poh, Su Qin Peh, Chin Thing Ong, Jingyao Zhang, Xiaoan Ruan, Yijun Ruan.
Institutions: Agency for Science, Technology and Research, Singapore, A*STAR-Duke-NUS Neuroscience Research Partnership, Singapore, National University of Singapore, Singapore.
Genomes are organized into three-dimensional structures, adopting higher-order conformations inside the micron-sized nuclear spaces 7, 2, 12. Such architectures are not random and involve interactions between gene promoters and regulatory elements 13. The binding of transcription factors to specific regulatory sequences brings about a network of transcription regulation and coordination 1, 14. Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) was developed to identify these higher-order chromatin structures 5,6. Cells are fixed and interacting loci are captured by covalent DNA-protein cross-links. To minimize non-specific noise and reduce complexity, as well as to increase the specificity of the chromatin interaction analysis, chromatin immunoprecipitation (ChIP) is used against specific protein factors to enrich chromatin fragments of interest before proximity ligation. Ligation involving half-linkers subsequently forms covalent links between pairs of DNA fragments tethered together within individual chromatin complexes. The flanking MmeI restriction enzyme sites in the half-linkers allow extraction of paired end tag-linker-tag constructs (PETs) upon MmeI digestion. As the half-linkers are biotinylated, these PET constructs are purified using streptavidin-magnetic beads. The purified PETs are ligated with next-generation sequencing adaptors and a catalog of interacting fragments is generated via next-generation sequencers such as the Illumina Genome Analyzer. Mapping and bioinformatics analysis is then performed to identify ChIP-enriched binding sites and ChIP-enriched chromatin interactions 8. We have produced a video to demonstrate critical aspects of the ChIA-PET protocol, especially the preparation of ChIP as the quality of ChIP plays a major role in the outcome of a ChIA-PET library. As the protocols are very long, only the critical steps are shown in the video.
Genetics, Issue 62, ChIP, ChIA-PET, Chromatin Interactions, Genomics, Next-Generation Sequencing
3770
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Bromodeoxyuridine (BrdU) Labeling and Subsequent Fluorescence Activated Cell Sorting for Culture-independent Identification of Dissolved Organic Carbon-degrading Bacterioplankton
Authors: Steven Robbins, Jisha Jacob, Xinxin Lu, Mary Ann Moran, Xiaozhen Mou.
Institutions: Kent State University, University of Georgia (UGA).
Microbes are major agents mediating the degradation of numerous dissolved organic carbon (DOC) substrates in aquatic environments. However, identification of bacterial taxa that transform specific pools of DOC in nature poses a technical challenge. Here we describe an approach that couples bromodeoxyuridine (BrdU) incorporation, fluorescence activated cell sorting (FACS), and 16S rRNA gene-based molecular analysis that allows culture-independent identification of bacterioplankton capable of degrading a specific DOC compound in aquatic environments. Triplicate bacterioplankton microcosms are set up to receive both BrdU and a model DOC compound (DOC amendments), or only BrdU (no-addition control). BrdU substitutes the positions of thymidine in newly synthesized bacterial DNA and BrdU-labeled DNA can be readily immunodetected 1,2. Through a 24-hr incubation, bacterioplankton that are able to use the added DOC compound are expected to be selectively activated, and therefore have higher levels of BrdU incorporation (HI cells) than non-responsive cells in the DOC amendments and cells in no-addition controls (low BrdU incorporation cells, LI cells). After fluorescence immunodetection, HI cells are distinguished and physically separated from the LI cells by fluorescence activated cell sorting (FACS) 3. Sorted DOC-responsive cells (HI cells) are extracted for DNA and taxonomically identified through subsequent 16S rRNA gene-based analyses including PCR, clone library construction and sequencing.
Molecular Biology, Issue 55, BrdU incorporation, fluorescence-activated cell sorting, FACS, flow cytometry, microbial community, culture-independent, bacterioplankton
2855
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Screening Foodstuffs for Class 1 Integrons and Gene Cassettes
Authors: Liette S. Waldron, Michael R. Gillings.
Institutions: Macquarie University.
Antibiotic resistance is one of the greatest threats to health in the 21st century. Acquisition of resistance genes via lateral gene transfer is a major factor in the spread of diverse resistance mechanisms. Amongst the DNA elements facilitating lateral transfer, the class 1 integrons have largely been responsible for spreading antibiotic resistance determinants amongst Gram negative pathogens. In total, these integrons have acquired and disseminated over 130 different antibiotic resistance genes. With continued antibiotic use, class 1 integrons have become ubiquitous in commensals and pathogens of humans and their domesticated animals. As a consequence, they can now be found in all human waste streams, where they continue to acquire new genes, and have the potential to cycle back into humans via the food chain. This protocol details a streamlined approach for detecting class 1 integrons and their associated resistance gene cassettes in foodstuffs, using culturing and PCR. Using this protocol, researchers should be able to: collect and prepare samples to make enriched cultures and screen for class 1 integrons; isolate single bacterial colonies to identify integron-positive isolates; identify bacterial species that contain class 1 integrons; and characterize these integrons and their associated gene cassettes.
Environmental Sciences, Issue 100, integron, lateral gene transfer, epidemiology, resistome, antibiotic resistance, pollution, xenogenetic
52889
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