Samples were in all cases obtained from subjects under informed consent of parents and with IRB/Ethics Board approval. Each center was allowed to develop its own genotyping methods as long as a minimum accuracy of 98% was achieved. Five HLA screening laboratories were chosen for TEDDY screening and they employed four different genotyping strategies. Screening genotyping results were expected to be available by the time the infant was 2 months of age. Low-cost genotyping was achieved by adopting a two-stage screening strategy in four laboratories. In the first stage, approximately 90% of the ineligible subjects are excluded by the presence of specific alleles that can be detected inexpensively. In the second stage, detailed genotyping of DQB1 and DQA1 or DQB1 and DRB1 alleles are determined. For the general population, the DRB1*0403 allele is usually determined by a restriction digest of the exon 2 amplicon. The first-stage strategy used by the Finnish and Swedish screening laboratories was to exclude certain resistant alleles while requiring certain susceptible alleles, and was previously described [15 (link)]. The WAS laboratory used a first-stage strategy of exclusion of DQB1*05, DQB1*06, DQB1*0301 and DQA1*02 followed by direct exon 2 sequencing of specific DQB1 and DQA1 alleles in the second stage genotyping. The GEO screening laboratory excluded subjects with DQB1*05, DQB1*06 and DQB1*0301 using allele-specific amplifications in the first stage. The potentially eligible subjects were further genotyped for DQB1 by denaturing gradient gel electrophoresis using a previously published protocol [9 (link)] and DRB1 by Luminex beads. Samples from the COL center were genotyped in the laboratory of Dr. Erlich using a reverse line blot SSOP technique with a panel of immobilized probes for DRB1 and DQB1 alleles [11 (link)]. The same laboratory also served as the TEDDY HLA Reference Laboratory to carry out confirmatory tests of enrolled subjects from all six clinical centers using separate DRB1, DQA1 and DQB1 reverse line blots, each with a much higher resolution panel of immobilized probes [16 (link)].
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Denaturing Gradient Gel Electrophoresis
Denaturing Gradient Gel Electrophoresis
Denaturing Gradient Gel Electrophoresis (DGGE) is a powerful molecular biology technique used for the seperation and analysis of nucleic acid fragments.
It exploits the principle of differential denaturing properties of DNA sequences to achieve separation.
DGGE allows the identification of sequence variations within a conserved genetic region, making it a valuable tool for microbial community profiling, mutation detection, and genetic polymorphism studies.
PubCompare.ai's AI-driven platform can help researchers access the best DGGE protocols from literature, preprints, and patents, while using intelligent comparisons to optimize methods for reproducible and accurrate findings.
Discover the future of scientific discovery with PubCompare.ai today.
It exploits the principle of differential denaturing properties of DNA sequences to achieve separation.
DGGE allows the identification of sequence variations within a conserved genetic region, making it a valuable tool for microbial community profiling, mutation detection, and genetic polymorphism studies.
PubCompare.ai's AI-driven platform can help researchers access the best DGGE protocols from literature, preprints, and patents, while using intelligent comparisons to optimize methods for reproducible and accurrate findings.
Discover the future of scientific discovery with PubCompare.ai today.
Most cited protocols related to «Denaturing Gradient Gel Electrophoresis»
Alleles
Denaturing Gradient Gel Electrophoresis
Exons
Genotyping Techniques
Infant
DNA extractions from intestinal luminal contents were prepared as described previously [14 (link)]. In brief, DNA extracts and plasmids were quantified by using Quant-iT PicoGreen reagent (Invitrogen, UK) and all adjusted to 1 ng DNA/µl.
The abundance of specific intestinal bacterial groups was measured by qPCR with group-specific 16S rRNA gene primers (Tib MolBiol, Germany) as decribed previously [15 (link),16 (link)]. As reference for quantification standard curves with tenfold serial dilutions of plasmids (ranging from 2×108 to 2×102 copies) were generated for each run. The real-time PCR primers were first used to amplify cloned 16S rDNA of reference strains (seeTable 1 ). The number of 16S rRNA gene copies / ng DNA of each sample was determined. Frequencies of the given bacterial groups were calculated proportionally to the eubacterial (V3) amplicon.
Genetic fingerprints were generated by PCR-based denaturing gradient gel electrophoresis (PCR-DGGE) as described previously [14 (link)].
The abundance of specific intestinal bacterial groups was measured by qPCR with group-specific 16S rRNA gene primers (Tib MolBiol, Germany) as decribed previously [15 (link),16 (link)]. As reference for quantification standard curves with tenfold serial dilutions of plasmids (ranging from 2×108 to 2×102 copies) were generated for each run. The real-time PCR primers were first used to amplify cloned 16S rDNA of reference strains (see
Genetic fingerprints were generated by PCR-based denaturing gradient gel electrophoresis (PCR-DGGE) as described previously [14 (link)].
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Bacteria
Denaturing Gradient Gel Electrophoresis
DNA, Ribosomal
Genes
Intestinal Contents
Intestines
Oligonucleotide Primers
PicoGreen
Plasmids
Real-Time Polymerase Chain Reaction
Reproduction
Ribosomal RNA Genes
RNA, Ribosomal, 16S
Strains
Technique, Dilution
DGGE ITS2 diversity typing was performed following the protocol detailed in LaJeunesse (2002) . Briefly, the Symbiodinium ITS2 region was amplified with the primer pair ITSintfor2 and ITS2CLAMP using PCR conditions described in LaJeunesse et al. (2003) with the following modifications: the annealing temperature was maintained at 52 °C for 27 cycles after 20 cycles of touchdown amplification. PCR products were mixed with 10 μL Ficoll-based loading buffer and concentrated by a speed vacuum before loading on an 8% polyacrylamide gel using a Cipher DGGE kit (CBS Scientific Company, Del Mar, CA). Gels were run at 150 V for 15 h, stained for 30 min with 1× SYBR Green (Invitrogen, Carlsbad, CA) and visualized on a Dark Reader Transilluminator (Clare Chemical Research, Dolores, CO). Prominent band(s) were excised from the DGGE gel with a sterile scalpel. Each band was transferred into an Eppendorf tube that contained 500 μL DNase-free water and incubated at 4 °C for 24 h. Two microlitres of this were used for reamplification as described in LaJeunesse (2002) and purified with Illustra ExoStar (SelectScience, Bath, UK) enzyme mix following the manufacturer's instructions. Successful amplification was verified by running products on a 1% agarose gel stained with 1× SYBR Safe (Invitrogen). Samples were sent for bidirectional Sanger sequencing at the KAUST BioScience Core Laboratory (Thuwal, Saudi Arabia). Sequences were processed in CodonCode Aligner (CodonCode Corporation, Centerville, MA). After quality trimming, forward and reverse sequences were assembled into contigs. For phylogenetic assignment of ITS2 sequences, we built a custom BLAST database (File S1, Supporting information) of ITS2 types collected from 409 ITS2 sequences taken from GeoSymbio (Franklin et al. 2012 (link)) (denoted as GS), 7 ITS2 sequences from Scott Santos’ database (www.auburn.edu/∼santosr/sequencedatasets.htm ) (denoted as ST) and 17 DGGE ITS2 sequences from Todd LaJeunesse's SD2-GED database (https://131.204.120.103/srsantos/symbiodinium/sd2_ged/database/views.php ) denoted as LJ. ITS2 sequences were assigned to the ITS2 types that represented highest identity in the BLASTN hits.
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Bath
Buffers
Denaturing Gradient Gel Electrophoresis
Deoxyribonuclease I
Enzymes
Ficoll
Oligonucleotide Primers
polyacrylamide gels
Sepharose
Sterility, Reproductive
SYBR Green I
Vacuum
Molecular detection, biochemical identification, and cultural analyses of intestinal bacterial communities were performed as described [8] (link), [14] (link), [34] (link). Briefly, luminal feces samples were removed for molecular analyses from the distal colon, resuspended in PBS, and centrifuged (16,000×g/10 min/4°C). Total DNA, isolated by phenol extraction as described [8] (link), served as template for PCR amplification of bacterial 16S rRNA genes with consensus primers TPU1 (5′-AGAGTTTGATCMTGGC TCAG-3′, nt 8-27 in the E. coli 16S rRNA gene) / RTU8 (5′-AAGGAGGTGATCCANCCRCA-3′, nt 1541-1522 in the E. coli 16S rRNA gene). Gene libraries of the amplicons were constructed and analyzed as described [34] (link). For high-resolution DGGE, which yielded the highest numbers of individual bands from a given sample, the variable region V3 in bacterial 16S rRNA genes was amplified from total gut content DNA with GC clamp (underlined) primer HDA-1-GC (5′-GCCCGGGGCGCGCCCCGGGCGGGGCGGGGGC ACGGGGGGACTCCTACGGGAGGCAGCAGT-3′, nt 339-360 in the E. coli 16S rRNA gene) and primer HDA-2 (5′- GTATTACCGCGGCTGCTGGCAC-3′, nt 539-518 in the E. coli 16S rRNA gene).
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Bacteria
Colon
Denaturing Gradient Gel Electrophoresis
Escherichia coli
Feces
Gene Amplification
Gene Library
Genes
Genes, Bacterial
Oligonucleotide Primers
Phenobarbital
Phenols
RNA, Ribosomal, 16S
Bacteria
Biofilms
Denaturing Gradient Gel Electrophoresis
Drugs, Non-Prescription
Eukaryotic Cells
Food
Healthy Volunteers
Plankton
Saliva
Most recents protocols related to «Denaturing Gradient Gel Electrophoresis»
PCR-DGGE analyses were performed to investigate lactobacilli populations; for each sampling location, 17 (out of 20) DNA extracted from individual guts were processed. The PCR and subsequent denaturing gradient gel electrophoresis (DGGE) analysis, using the Dcode Universal Mutation Detection System (Bio-Rad Laboratories, Hercules, CA, USA), were performed as described by Alberoni et al. (2018) (link). Denaturing gradient was established at 35–65%. Fingerprinting analyses were carried out using the Bionumerics v 7.1 (Applied Maths, St. Martens-Latem, Belgium) and the UPGMA algorithm based on the Pearson correlation coefficient with an optimization of 1% was applied. Microbial diversity was analyzed with the following parameters: Shannon–Wiener index (H), Simpson index (S), and band evenness (EH), calculated according to Hill et al. (2003) (link). Moreover, principal components analysis (PCA) was carried out by using Bionumerics. Relevant bands were excised from the gels and processed to achieve purified amplicons to be sequenced (Gaggìa et al., 2015 ). Sequencing was carried out by Eurofins Genomics (Ebersberg, Germany) and obtained sequences were assigned to bacterial species using megablast algorithm.2
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Bacteria
Denaturing Gradient Gel Electrophoresis
Gels
Intestines
Lactobacillus
Martes
Mutation
Population Group
To compare the bacterial diversity among samples from different depth and different seasons, the PCR-amplified 16S rRNA genes of 189 water samples and 11 sediment samples were profiled by denaturing gradient gel electrophoresis (DGGE). Based on the DGGE results and physicochemical parameters of Lake Vechten, 51 samples from the water column and 4 samples from the sediment were selected for 16S rRNA gene amplicon sequencing (Table S3 ). Sequencing was performed on an Illumina MiSeq system by Research and Testing Laboratory (Lubbock, Texas, USA). The details of amplicon sequencing and operational taxonomic unit assignments were described in a previous study (Diao et al. 2017 (link)).
Bacteria
Denaturing Gradient Gel Electrophoresis
Genes
Ribosomal RNA Genes
RNA, Ribosomal, 16S
For community analysis (amplicon metabarcoding and Denaturing Gradient Gel Electrophoresis, DGGE), total DNA from both the original consortia and the consortia obtained after specific time points following serial transfers in N-FIX medium was analyzed using an FastDNA™ SPIN Kit for Soil (MP Biomedicals) per the standard protocol. For metagenomic analysis, a consortium sample obtained after 10 transfers via the N-FIX medium was used for DNA extraction. To improve cell recovery, 1 mL of 10% (volume/mass of approximately 0.03 M) sodium dodecyl sulfate solution was added to each flask containing culture medium, with a final concentration of approximately 0.25% (0.0008 M). The contents of three glass bottles (120 mL) containing the full-grown consortia were filtered through sterile 0.22-µm Millipore membranes; the membranes were then directly subjected to DNA extraction, and instead of the single lysis step in the FastPrep™ system (Bio 101, Inc., La Jolla, CA, USA), we performed the lysis step again. We used the FastPrep™ system at 6.0 rpm for 40 s. Nanodrop™ and Qubit™ (Thermo Fisher Scientific) were used to assess the quality (260/230 and 260/280 ratios) and amount of the extracted DNA, respectively. Electrophoresis was performed using 1.0% agarose gel for 40 min at 90 V, after which the gels were stained with SYBR™ Safe (Thermo Fisher Scientific) and observed under an ultraviolet (UV) transilluminator to assess DNA integrity.
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Cells
Culture Media
Denaturing Gradient Gel Electrophoresis
Electrophoresis
Gels
Metagenome
Sepharose
Sterility, Reproductive
Sulfate, Sodium Dodecyl
Tissue, Membrane
PCR amplification of the extracted DNA was performed using the primers U968-gc (5ʹ-CGCCCGGGGCGCGCCCCGGGCGGGGCGGGGGCACGGGGGAACGCGAAGAACCTTAC-3ʹ) and L1401 (5ʹ-CGGTGTGTACAAGGCCCGGGAACG −3ʹ). A hypervariable region of the gene rrs was amplified, and gene codification of the ribosomal RNA composing the small subunit of the bacterial ribosome (16 S) was performed52 (link). The amplification reaction was performed as described by Machado de Oliveira et al.53 (link). The results of the amplification reaction were determined via electrophoresis of samples on 1.5% agarose gel at 100 V for 40 min. The gel was stained with SYBR Safe and observed under a UV light transilluminator. DGGE was performed using the DCode™ System (Bio-Rad Laboratories, Inc., Hercules, CA, USA) at 70 V and 65 °C for 16 h. The denaturation gradient gel was prepared using a peristaltic pump and a gradient generator block. The gradient of the denaturing agents, urea and formamide, was in the range of 35–65%, and the gel contained 6% polyacrylamide. Gels were stained with SYBR Safe for 20 min and observed using a Storm® gel scanner (General Electric). Before the PCR products were applied to the DGGE gel, they were quantified and normalized to ensure that any changes in band intensities reflected the changes in their relative abundances.
The DNA obtained from the serial transfer in N-FIX was also used to amplify the hypervariable regions V5 and V6 of the bacterial 16 S rRNA gene (according to ref. 16 (link)), at the Argonne National Laboratory (http://ngs.igsb.anl.gov , Lemont, IL, USA) through the Next Generation Sequencing Core on an Illumina MiSeq System (Illumina, San Diego, CA, USA), following the manufacturer’s guidelines. The microbial data were also analyzed according to Santoro et al.16 (link). The data have been deposited with links to BioProject accession number PRJNA373874 in the DDBJ BioProject database: along with the accession numbers SAMN33200710, SAMN33200711, SAMN33200712, SAMN33200713, SAMN33200714; submission: SUB12816063.
The DNA obtained from the serial transfer in N-FIX was also used to amplify the hypervariable regions V5 and V6 of the bacterial 16 S rRNA gene (according to ref. 16 (link)), at the Argonne National Laboratory (
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Bacteria
Denaturing Gradient Gel Electrophoresis
Electricity
Electrophoresis
formamide
Genes, Bacterial
Genes, vif
Oligonucleotide Primers
Peristalsis
polyacrylamide
Ribosomal RNA
Ribosomal RNA Genes
Ribosome Subunits, Small
Sepharose
Ultraviolet Rays
Urea
One-way analysis of variance (ANOVA) followed by Fisher least-significant difference (LSD) were applied to analyze data obtained from the real-time PCR using Statistica 12.0 software (StatSoft, Palo Alto, CA, USA).
The Gel Compare II software v 4.6 (Applied Maths, Sint-Martens-Latem, Belgium) was used to analyze the foam DGGE and to convert it into a matching table based on the presence/absence and intensity of bands within each banding pattern, in order to be imported into the freely available PAST 4.03 software for subsequent multivariate statistical analysis [31 ]. Non-metric multidimensional scaling (nMDS) analysis and one-way analysis of similarity (ANOSIM) were performed using the Bray-Curtis distance measure and 9999 permutational tests, in order to visualize the similarity/dissimilarity of bacterial communities hosted in the collected foams in a two-dimensional space and to determine the extent of similarity/dissimilarity according to the different plant species, respectively. The accuracy of the nMDS plot was determined by calculating a 2D stress value. An ANOSIM R value of 1 indicates that the bacterial communities of foam collected from each plant species are more similar to each other than to any sample from another plant species, whereas an R value of 0 indicates that there is as much variation within a group as among the groups being compared. More specifically, 0.5 < R values < 0.75 were interpreted as separated but overlapping [32 (link)].
The Gel Compare II software v 4.6 (Applied Maths, Sint-Martens-Latem, Belgium) was used to analyze the foam DGGE and to convert it into a matching table based on the presence/absence and intensity of bands within each banding pattern, in order to be imported into the freely available PAST 4.03 software for subsequent multivariate statistical analysis [31 ]. Non-metric multidimensional scaling (nMDS) analysis and one-way analysis of similarity (ANOSIM) were performed using the Bray-Curtis distance measure and 9999 permutational tests, in order to visualize the similarity/dissimilarity of bacterial communities hosted in the collected foams in a two-dimensional space and to determine the extent of similarity/dissimilarity according to the different plant species, respectively. The accuracy of the nMDS plot was determined by calculating a 2D stress value. An ANOSIM R value of 1 indicates that the bacterial communities of foam collected from each plant species are more similar to each other than to any sample from another plant species, whereas an R value of 0 indicates that there is as much variation within a group as among the groups being compared. More specifically, 0.5 < R values < 0.75 were interpreted as separated but overlapping [32 (link)].
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Bacteria
Denaturing Gradient Gel Electrophoresis
Martes
Plants
Real-Time Polymerase Chain Reaction
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More about "Denaturing Gradient Gel Electrophoresis"
Denaturing Gradient Gel Electrophoresis (DGGE) is a powerful molecular biology technique used for the separation and analysis of nucleic acid fragments.
It exploits the principle of differential denaturing properties of DNA sequences to achieve separation.
DGGE allows the identification of sequence variations within a conserved genetic region, making it a valuable tool for microbial community profiling, mutation detection, and genetic polymorphism studies.
The DCode Universal Mutation Detection System and the DCode system are popular platforms for performing DGGE analysis.
These systems utilize a temperature- or chemical-based denaturing gradient to separate DNA fragments based on their sequence-specific melting behavior.
The Quantity One and Quantity One 4.6.2 software are commonly used for image analysis and processing of DGGE gels.
SYBR Gold is a sensitive fluorescent dye that can be used to visualize and quantify DNA fragments separated by DGGE.
The FastDNA SPIN Kit for Soil and the QIAamp DNA Stool Mini Kit are commonly used for efficient extraction and purification of nucleic acids from environmental samples prior to DGGE analysis.
PubCompare.ai's AI-driven platform can help researchers access the best DGGE protocols from literature, preprints, and patents, while using intelligent comparisons to optimize methods for reproducible and accuraate findings.
The GelCompar II software is also a useful tool for the analysis and comparison of DGGE profiles.
Discover the future of scientific discovery with PubCompare.ai today and explore the power of Denaturing Gradient Gel Electrophoresis in your research.
It exploits the principle of differential denaturing properties of DNA sequences to achieve separation.
DGGE allows the identification of sequence variations within a conserved genetic region, making it a valuable tool for microbial community profiling, mutation detection, and genetic polymorphism studies.
The DCode Universal Mutation Detection System and the DCode system are popular platforms for performing DGGE analysis.
These systems utilize a temperature- or chemical-based denaturing gradient to separate DNA fragments based on their sequence-specific melting behavior.
The Quantity One and Quantity One 4.6.2 software are commonly used for image analysis and processing of DGGE gels.
SYBR Gold is a sensitive fluorescent dye that can be used to visualize and quantify DNA fragments separated by DGGE.
The FastDNA SPIN Kit for Soil and the QIAamp DNA Stool Mini Kit are commonly used for efficient extraction and purification of nucleic acids from environmental samples prior to DGGE analysis.
PubCompare.ai's AI-driven platform can help researchers access the best DGGE protocols from literature, preprints, and patents, while using intelligent comparisons to optimize methods for reproducible and accuraate findings.
The GelCompar II software is also a useful tool for the analysis and comparison of DGGE profiles.
Discover the future of scientific discovery with PubCompare.ai today and explore the power of Denaturing Gradient Gel Electrophoresis in your research.