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Hybridization capture: Array-capture vs. in solution

Hybridization capture: Array-capture vs. in solution


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If I wanted to utilize hybridization capture for capturing certain genomic regions, I could do it by utilizing complementary probes immobilized on an array or to use the probes in solution and then capture probes using biotin-streptavidin binding.

How do the two compare? Does in solution hybridization e.g. require more probes? What would I need to think about when making my choice?


Frontiers in Microbiology

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Abstract

The design and interpretation of surface hybridization assays is complicated by poorly understood aspects of the interfacial environment that cause both kinetic and thermodynamic behaviors to deviate from those in solution. The origins of these differences lie in the additional interactions experienced by hybridizing strands at the surface. In this report, an analysis of surface hybridization equilibria is provided for end-tethered, single-stranded oligonucleotide “probes” hybridizing with similarly sized, single-stranded solution “target” molecules. Theoretical models by Vainrub and Pettitt (Phys. Rev. E2002, 66, 041905) and by Halperin, Buhot, and Zhulina (Biophys. J.2004, 86, 718), and an “extended” model that in addition includes a solution-like salt dependence of probe-target dimerization, are compared to experiments as a function of salt concentration and probe coverage. Good agreement with experiment is observed when the DNA volume fraction at the surface remains below ∼0.25. None of the models, however, can account for strong suppression of hybridization when the volume fraction of DNA approaches 0.3, realizable in the limit of high buffer strength and densely tethered films. Under these conditions, hybridization yields become insensitive to increases in analyte concentration even though many probes remain available to bind targets. These observations are attributed to the onset of packing constraints which, interestingly, become limiting significantly below maximum DNA coverages estimated from ideally efficient hexagonal packing. By delineating conditions under which specific hybridization behaviors are observed, the results advance fundamental knowledge in support of DNA microarray and biosensor applications.


Abstract

Current microarray assay technology predominately uses fluorescence as a detectable signal end point. This study assessed real-time in situ surface hybridization capture kinetics for single printed DNA microspots on solid array surfaces using fluorescence. The influence of the DNA target and probe cyanine dye position on oligo-DNA duplex formation behavior was compared in solution versus surface-hybridized single DNA printed spots using fluorescence resonance energy transfer (FRET) analysis. Fluorophore Cy3/Cy5 fluorescence intensities were analyzed both through the printed hybridized DNA spot thickness and radially across single-spot surfaces. Confocal single-spot imaging shows that real-time in situ hybridization kinetics with constant target concentrations changes as a function of the printed probe density. Target-specific imaging in single spots exhibits a heterogeneous printed probe radial density that influences hybridization spatially and temporally via radial hemispherical diffusion of dye-labeled target from the outside edge of the spot to the interior. FRET of the surface-captured target occurs irrespective of the probe/target fluorophore position, resulting from excess printed probe density and spot thickness. Both heterogeneous probe density distributions in printed spots and the fluorophore position on short DNA oligomers influence duplex formation kinetics, hybridization efficiencies, and overall fluorescence intensity end points in surface-capture formats. This analysis is important to understanding, controlling, and quantifying the array assay signal essential to reliable application of the surface-capture format.


Contents

Historically, microscopy was the primary method of investigating nuclear organization, [6] which can be dated back to 1590. [7]

  • In 1879, Walther Flemming coined the term chromatin. [8]
  • In 1883, August Weismann connected chromatin with heredity.
  • In 1884, Albrecht Kossel discovered histones.
  • In 1888, Sutton and Boveri proposed the theory of continuity of chromatin during the cell cycle [9]
  • In 1889, Wilhelm von Waldemeyer created the term "chromosome". [10]
  • In 1928, Emil Heitz coined the term Heterochromatin and Euchromatin. [11]
  • In 1942, Conrad Waddington postulated the epigenetic landscapes. [12]
  • In 1948, Rollin Hotchkiss discovered DNA methylation. [13]
  • In 1953, Watson and Crick discovered the double helix structure of DNA. [14]
  • In 1961, Mary Lyon postulated the principle of X-inactivation.
  • In 1973/1974, chromatin fiber was discovered. [12]
  • In 1975, Pierre Chambon coined the term nucleosomes. [12]
  • In 1982, Chromosome territories were discovered. [15]
  • In 1984, John T. Lis innovated the Chromatin immunoprecipitation technique.
  • In 1993, the Nuclear Ligation Assay was published, a method that could determine circularization frequencies of DNA in solution. This assay was used to show that estrogen induces an interaction between the prolactin gene promoter and a nearby enhancer. [16]
  • In 2002, Job Dekker introduced the new idea that dense matrices of interaction frequencies between loci could be used to infer the spatial organization of genomes. This idea was the basis for his development of the chromosome conformation capture (3C) assay, published in 2002 by Job Dekker and colleagues in the Kleckner lab at Harvard University. [17][18]
  • In 2003, the Human Genome Project was finished.
  • In 2006, Marieke Simonis invented 4C, [19] Dostie, in the Dekker lab, invented 5C. [20]
  • In 2007, B. Franklin Pugh innovated ChIP-seq technique. [21]
  • In 2009, Lieberman-Aiden and Job Dekker invented Hi-C, [22] Melissa J. Fullwood and Yijun Ruan invented ChIA-PET. [23]
  • In 2012, The Ren group, and the groups led by Edith Heard and Job Dekker discovered Topologically Associating Domains (TADs) in mammals. [24][25]
  • In 2013, Takashi Nagano and Peter Fraser introduced in-nuclei ligation for Hi-C and single-cell Hi-C. [26]

All 3C methods start with a similar set of steps, performed on a sample of cells.

First, the cell genomes are cross-linked with formaldehyde, [27] which introduces bonds that "freeze" interactions between genomic loci. Treatment of cells with 1-3% formaldehyde, for 10-30min at room temperature is most common, however, standardization for preventing high protein-DNA cross linking is necessary, as this may negatively affect the efficiency of restriction digestion in the subsequent step. [28] The genome is then cut into fragments with a restriction endonuclease. The size of restriction fragments determines the resolution of interaction mapping. Restriction enzymes (REs) that make cuts on 6bp recognition sequences, such as EcoR1 or HindIII, are used for this purpose, as they cut the genome once every 4000bp, giving

1 million fragments in the human genome. [28] [29] For more precise interaction mapping, a 4bp recognizing RE may also be used. The next step is, proximity based ligation. This takes place at low DNA concentrations or within intact, permeabilized nuclei [26] in the presence of T4 DNA ligase, [30] such that ligation between cross-linked interacting fragments is favored over ligation between fragments that are not cross-linked. Subsequently, interacting loci are quantified by amplifying ligated junctions by PCR methods. [28] [30]

Original methods Edit

3C (one-vs-one) Edit

The chromosome conformation capture (3C) experiment quantifies interactions between a single pair of genomic loci. For example, 3C can be used to test a candidate promoter-enhancer interaction. Ligated fragments are detected using PCR with known primers. [2] [17] That is why this technique requires the prior knowledge of the interacting regions.

4C (one-vs-all) Edit

Chromosome conformation capture-on-chip (4C) captures interactions between one locus and all other genomic loci. It involves a second ligation step, to create self-circularized DNA fragments, which are used to perform inverse PCR. Inverse PCR allows the known sequence to be used to amplify the unknown sequence ligated to it. [31] [2] [19] In contrast to 3C and 5C, the 4C technique does not require the prior knowledge of both interacting chromosomal regions. Results obtained using 4C are highly reproducible with most of the interactions that are detected between regions proximal to one another. On a single microarray, approximately a million interactions can be analyzed. [ citation needed ]

5C (many-vs-many) Edit

Chromosome conformation capture carbon copy (5C) detects interactions between all restriction fragments within a given region, with this region's size typically no greater than a megabase. [2] [20] This is done by ligating universal primers to all fragments. However, 5C has relatively low coverage. The 5C technique overcomes the junctional problems at the intramolecular ligation step and is useful for constructing complex interactions of specific loci of interest. This approach is unsuitable for conducting genome-wide complex interactions since that will require millions of 5C primers to be used. [ citation needed ]

Hi-C (all-vs-all) Edit

Hi-C uses high-throughput sequencing to find the nucleotide sequence of fragments [2] [22] and uses paired end sequencing, which retrieves a short sequence from each end of each ligated fragment. As such, for a given ligated fragment, the two sequences obtained should represent two different restriction fragments that were ligated together in the proximity based ligation step. The pair of sequences are individually aligned to the genome, thus determining the fragments involved in that ligation event. Hence, all possible pairwise interactions between fragments are tested.

Sequence capture-based methods Edit

A number of methods use oligonucleotide capture to enrich 3C and Hi-C libraries for specific loci of interest. [32] [33] These methods include Capture-C, [34] NG Capture-C, [35] Capture-3C, [34] HiCap, [32] [36] Capture Hi-C. [37] and Micro Capture-C. [38] These methods are able to produce higher resolution and sensitivity than 4C based methods, [39] Micro Capture-C provides the highest resolution of the available 3C techniques and it is possible to generate base pair resolution data. [38]

Single-cell methods Edit

Single-cell adaptations of these methods, such as ChIP-seq and Hi-C can be used to investigate the interactions occurring in individual cells. [40] [41]

Immunoprecipitation-based methods Edit

ChIP-loop Edit

ChIP-loop combines 3C with ChIP-seq to detect interactions between two loci of interest mediated by a protein of interest. [2] [42] The ChIP-loop may be useful in identifying long-range cis-interactions and trans interaction mediated through proteins since frequent DNA collisions will not occur. [ citation needed ]

Genome wide methods Edit

ChIA-PET combines Hi-C with ChIP-seq to detect all interactions mediated by a protein of interest. [2] [23] HiChIP was designed to allow similar analysis as ChIA-PET with less input material. [43]

3C methods have led to a number of biological insights, including the discovery of new structural features of chromosomes, the cataloguing of chromatin loops, and increased understanding of transcriptional regulation mechanisms (the disruption of which can lead to disease). [6]

3C methods have demonstrated the importance of spatial proximity of regulatory elements to the genes that they regulate. For example, in tissues that express globin genes, the β-globin locus control region forms a loop with these genes. This loop is not found in tissues where the gene is not expressed. [44] This technology has further aided the genetic and epigenetic study of chromosomes both in model organisms and in humans. [ not verified in body ]

These methods have revealed large-scale organization of the genome into topologically associating domains (TADs), which correlate with epigenetic markers. Some TADs are transcriptionally active, while others are repressed. [45] Many TADs have been found in D. melanogaster, mouse and human. [46] Moreover, CTCF and cohesin play important roles in determining TADs and enhancer-promoter interactions. The result shows that the orientation of CTCF binding motifs in an enhancer-promoter loop should be facing to each other in order for the enhancer to find its correct target. [47]

Human disease Edit

There are several diseases caused by defects in promoter-enhancer interactions, which are reviewed in this paper. [48]

Beta thalassemia is a certain type of blood disorders caused by a deletion of LCR enhancer element. [49] [50]

Holoprosencephaly is cephalic disorder caused by a mutation in the SBE2 enhancer element, which in turn weakened the production of SHH gene. [51]

PPD2 (polydactyly of a triphalangeal thumb) is caused by a mutation of ZRS enhancer, which in turn strengthened the production of SHH gene. [52] [53]

Adenocarcinoma of the lung can be caused by a duplication of enhancer element for MYC gene. [54]

T-cell acute lymphoblastic leukemia is caused by an introduction of a new enhancer. [55]

The different 3C-style experiments produce data with very different structures and statistical properties. As such, specific analysis packages exist for each experiment type. [33]

Hi-C data is often used to analyze genome-wide chromatin organization, such as topologically associating domains (TADs), linearly contiguous regions of the genome that are associated in 3-D space. [45] Several algorithms have been developed to identify TADs from Hi-C data. [4] [60]

Hi-C and its subsequent analyses are evolving. Fit-Hi-C [3] is a method based on a discrete binning approach with modifications of adding distance of interaction (initial spline fitting, aka spline-1) and refining the null model (spline-2). The result of Fit-Hi-C is a list of pairwise intra-chromosomal interactions with their p-values and q-values. [59]

The 3-D organization of the genome can also be analyzed via eigendecomposition of the contact matrix. Each eigenvector corresponds to a set of loci, which are not necessarily linearly contiguous, that share structural features. [61]

A significant confounding factor in 3C technologies is the frequent non-specific interactions between genomic loci that occur due to random polymer behavior. An interaction between two loci must be confirmed as specific through statistical significance testing. [3]

Normalization of Hi-C contact map Edit

There are two major ways of normalizing raw Hi-C contact heat maps. The first way is to assume equal visibility, meaning there is an equal chance for each chromosomal position to have an interaction. Therefore, the true signal of a Hi-C contact map should be a balanced matrix (Balanced matrix has constant row sums and column sums). An example of algorithms that assumes equal visibility is Sinkhorn-Knopp algorithm, which scales the raw Hi-C contact map into a balanced matrix.

The other way is to assume there is a bias associated with each chromosomal position. The contact map value at each coordinate will be the true signal at that position times bias associated with the two contact positions. An example of algorithms that aim to solve this model of bias is iterative correction, which iteratively regressed out row and column bias from the raw Hi-C contact map. There are a number of software tools available for analysis of Hi-C data. [62]

DNA motif analysis Edit

DNA motifs are specific short DNA sequences, often 8-20 nucleotides in length [63] which are statistically overrepresented in a set of sequences with a common biological function. Currently, regulatory motifs on the long-range chromatin interactions have not been studied extensively. Several studies have focused on elucidating the impact of DNA motifs in promoter-enhancer interactions.

Bailey et al. has identified that ZNF143 motif in the promoter regions provides sequence specificity for promoter-enhancer interactions. [64] Mutation of ZNF143 motif decreased the frequency of promoter-enhancer interactions suggesting that ZNF143 is a novel chromatin-looping factor.

For genome-scale motif analysis, in 2016, Wong et al. reported a list of 19,491 DNA motif pairs for K562 cell line on the promoter-enhancer interactions. [65] As a result, they proposed that motif pairing multiplicity (number of motifs that are paired with a given motif) is linked to interaction distance and regulatory region type. In the next year, Wong published another article reporting 18,879 motif pairs in 6 human cell lines. [66] A novel contribution of this work is MotifHyades, a motif discovery tool that can be directly applied to paired sequences.

Cancer genome analysis Edit

The 3C-based techniques can provide insights into the chromosomal rearrangements in the cancer genomes. [67] Moreover, they can show changes of spatial proximity for regulatory elements and their target genes, which bring deeper understanding of the structural and functional basis of the genome. [68]


Hybridization Conditions and Melting Temperature

Stringency is a term that many molecular technologists are all very familiar with. It is a term that describes the combination of conditions under which a target is exposed to the probe. Typically, conditions that exhibit high stringency are more demanding of probe to target complementarity and length. Low stringency conditions are much more forgiving.

  • If conditions of stringency are too HIGH → Probe doesn’t bind to the target
  • If conditions of stringency are too LOW → Probe binds to unrelated targets

Important Factors That Affect Stringency and Hybridization

  • Temperature of hybridization and salt concentration
    • Increasing the hybridization temperature or decreasing the amount of salt in the buffer increases probe specificity and decreases hybridization of the probe to sequences that are not 100% the same.
    • For example: Deionized Formamide and SDS can be used to reduce non-specific binding of the probe

    – Probe has increased number of G and C bases

    – Probe has increased number of A and T bases

    Melting Temperature (Tm) Long Probes

    • The ideal hybridization conditions are estimated from the calculation of the Tm.
    • The Tm of the probe sequence is a way to express the amount of energy required to separate the hybridized strands of a given sequence.
    • At the Tm: Half of the sequence is double stranded and half of the sequence is single stranded.
    • Tm = 81.5°C + 16.6logM + 0.41(%G+C) – 0.61(%formamide) – (600/n)

    Where M = Sodium concentration in mol/L

    n = number of base pairs in smallest duplex

    • If we keep in mind that RNA is single stranded (ss) and DNA is double stranded (ds), then the following must be true:

    RNA : DNA Hybrids More stable

    DNA : DNA Hybrids Less stable

    Calculating the Tm for Short Probes (14 – 20 base pairs)

    • Tm = 4°C x number of G/C pairs + 2°C x number of A/T pairs
    • The hybridization temperature (annealing temp) of oligonucleotide probes is approximately 5°C below the melting temperature.

    Sequence Complexity (Cot)

    • Sequence complexity refers to the length of unique, non-repetitive nucleotide sequences.
    • Cot = Initial DNA Concentration (Co) x time required to reanneal it (t)
    • Cot1/2 = Time required for half of the double-stranded sequence to anneal under a given set of conditions.
    • Short probes can hybridize in 1 – 2 hours, where long probes require more time.

    Test Your Knowledge

    Answer
    If the number of G/C pairs = 11, and the number of A/T pairs = 9. The calculation is as follows:
    4(11) + 2(9) = X
    X = 62°C

    -LeAnne Noll, BS, MB(ASCP) CM is a molecular technologist in Wisconsin and was recognized as one of ASCP’s Top Five from the 40 Under Forty Program in 2015.

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    Related


    Contaminant sensors: nanosensors, an efficient alarm for food pathogen detection

    Cheunjit Prakitchaiwattana , Rachatida Det-udom , in Nanobiosensors , 2017

    3.2.2 Nanotechnology and Nanomaterials-Based Polymerase Chain Reaction (PCR) Assay

    Nucleic acid probe hybridization assay is not the only nucleic acid–based method which is used in the detection and identification of foodborne pathogens, but polymerase chain reaction (PCR) is also extensively employed. The PCR assays are able to amplify single DNA target and multiple targets (multiplex PCR) for specific detection of pathogens. For detection of viable cells, reverse transcriptase PCR was further developed to detect mRNA transcripts from the specific genes of target bacteria ( Klein and Juneja, 1997 Hill et al., 1998 ). Both conventional and real-time PCR can be applied to detect and identify bacterial pathogens. Furthermore, the variation in genomic targets that can be selected for use is highlighted by several key references as summarized in Byrne et al. (2015) . The key advantage of PCR-based assays is the ability to simultaneously detect multiple pathogens in a single sample using multiplex PCR. Additionally, PCR assays can be constructed to differentiate between viable and nonviable cells by nanotechnology modification.

    Nanomagnetic beads as magnetic primers have been used in new strategies for DNA electrochemical sensor to improve sensitivity and selectivity. For example, Lermo et al. (2007) used magnetic primers for in situ amplification of Salmonella genome on magnetic beads and further separated the amplified product with magneto electrodes based on graphite–epoxy composite. The PCR assay was done by immobilization of the biotinylated capture probe on the modified magnetic bead, together with hybridization of IS200 sequence specific for Salmonella and the digoxigenin probe. Enzymatic labeling was subsequently performed using the anti-digoxigenin horseradish peroxidase antibody. After in situ amplification of the DNA template on magnetic beads, the doubly labeled PCR product was thus rapidly detected by the electrochemical magneto biosensing strategy. The amperometric change due to the doubly labeled duplex was then evaluated. The results showed the direct DNA amplification successfully performed on magnetic beads by using the magnetic primer. In addition, the magneto electrode was able to detect changes at single nucleotide polymorphism, when stringent hybridization conditions were used. In conclusion, this strategy could be used for the rapid and sensitive detection of PCR amplified samples.

    The nanomagnetic beads based separation combined with multiplex PCR assay was also demonstrated by Yang et al. (2013) . The technique was proposed for simultaneous detection of Salmonella Typhimurium, E. coli O157:H7, and Listeria monocytogenes, and also tested in food products. Magnetic nanobeads based immunomagnetic separation was used to separate the target bacterial cells while multiplex PCR was used to amplify the target genes. Initially, the target bacteria were also treated with propidium monoazide prior to DNA extraction to eliminate the interference from nonviable cells. The result showed the detection limit of the assay was about 100 cfu/mL for all three bacterial strains in pure culture and around 1,000 cfu/g for all strains spiked in food samples of lettuce, tomato, and ground beef. Although this assay is highly innovative compared to the other nucleic acid–based methods, it requires bacterial isolation, lysis, and/or isolation of bacterial DNA which limits the application in actual circumstances during field work.


    Discussion

    We present what to our knowledge is the first attempt to capture ancient DNA with two independent in-solution capture methods. Although based on a limited dataset, we believe that the data presented contains useful information to help guide future studies. Our data suggests that several of the variables tested appear to be of limited importance. For example, in general we did not observe any overwhelming advantage of one kit over the other. Although the SureSelect experiments contained higher proportions of on-target sequences, they also contained higher levels of clonal data, thus reducing the overall levels of useful sequence post filtering. Furthermore, while the use of different tiling designs in the MySelect experiments allowed a direct estimation of the advantage of using tighter designs (higher tiling density) at the expense of less target sequence, we observed the use of tighter designs was not consistently translated into better enrichment values.

    In contrast, we believe that there are two major observations that will be important for future aDNA target-sequencing studies to consider. Firstly, a large proportion of the sequences derived from clonal amplification and thus would be of limited use in down-stream analyses. Because ancient DNA capture-enrichment experiments are still in its earliest stage, we found difficult to compare our observations to the other few reports on the subject since no standardisation has been made to report enrichment rates and it was not clear at first sight if these included clonality or not in their estimations. We therefore believe clonality should be unambiguously discussed in relevant publications and such data should be excluded from enrichment calculations at the very least we feel that our discipline should engage in a salient discussion on the matter to ultimately reach a standardized convention of enrichment rates.

    Secondly, the inclusion of targets present at different levels in the genome in the same capture array appears to have a negative effect on the results. Specifically we speculate that repeat regions are preferentially captured and amplified. This highlights the relevance of designing probes to exclusively target single-copy loci as well as keeping the number of cycles to a minimum, which would also have a positive effect on the results by reducing the number of clones.

    Although we demonstrate the plausibility of capturing aDNA from maize kernels, the efficiency in other ancient tissues remains to be explored. Even though the only additional report on nuclear aDNA capture-enrichment is limited to Neandertal bone, the future looks quite promising for aDNA investigation with targeted sequencing becoming more accessible and newer sequencing platforms entering the market.


    Nucleic Acid Capture Assays

    Streptavidin-coupled Dynabeads are ideal for capture of low abundance DNA/RNA sequences from clinical samples (blood, stool, cerebrospinal fluid etc.). The method offers several advantages, including the removal of extraneous DNA/RNA and inhibitory substances as well as concentration of your diluted and precious target into a small volume for further analysis. Depending on the probe, target and specific application, the capture approach can be either direct or indirect.

    Viral RNA, DNA from fastidious bacteria, mutated sequences and microsatellites and many other specific targets are captured from complex samples using streptavidin-coupled Dynabeads and a biotinylated probe.

    Dynabeads show excellent reaction kinetics comparable to liquid-phase kinetics, and are particularly well suited for automated sample preparation and handling. Their high magnetic mobility and low sedimentation rate make them ideal for robotic handling.

    Direct or indirect nucleic acid capture?

    Depending on your target molecule and the specific application, the direct or indirect capture method can be applied.

    For some applications, using a pre-coupled ligand for direct capture allows you to reuse the Dynabeads and thus further reduce sample preparation costs.

    An indirect approach can be of benefit when the concentration of your target is low, the specific affinity is weak or the binding kinetics is slow. In the indirect approach, the probe/ligand is allowed to bind to the target in suspension prior to addition of the beads.

    A monolayer of streptavidin is covalently coupled to the Dynabeads, ensuring negligible leakage that could otherwise disturb your assay.


    Watch the video: SureSelect: Post Hybridization Capture (May 2022).