Name: interactome-seq: a protocol for domainome library construction, validation and selection by phage display and next generation sequencing
Uploaded: 2018-10-03T13:00:00
Description: Watch this Scientific Journal Video about Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing at JoVE.com

This work was supported by a grant from the Italian Ministry of Education and University (2010P3S8BR_002 to CP).

1. Construction of the ORF Library (Figure 1)
<ol>
	<li>Preparation of insert DNA
	<ol>
		<li>Fragments preparation from synthetic or genomic DNA
		<ol>
			<li>Extract/purify DNA using standard methods26.</li>
			<li>Fragment DNA by sonication. If using a standard sonicator, as a general suggestion start with 30 s pulses at 100% power output. 
			NOTE: Pilot experiments should be done with different power and sonication times t...

<ol>
	<li>Loman, N. J., Pallen, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Twenty+years+of+bacterial+genome+sequencing.">Twenty years of bacterial genome sequencing.</a> Nat Rev Microbiol. 13 (12), 787-794 (2015).</li><li>Jones, C. E., Brown, A. L., Baumann, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimating+the+annotation+error+rate+of+curated+GO+database+sequence+annotations.">Estimating the annotation error rate of curated GO database sequence annotations.</a> BMC Bioinformatics. 8 (1), 170 (2007).</li><li>Andorf, C., Dobbs, D., Honavar, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exploring+inconsistencies+in+genome-wide+protein+function+annotations:+a+machine+learning+approach.">Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach.</a> BMC Bioinformatics. 8 (1), 284 (2007).</li><li>Wong, W. -. C., Maurer-Stroh, S., Eisenhaber, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=More+Than+1,001+Problems+with+Protein+Domain+Databases:+Transmembrane+Regions,+Signal+Peptides+and+the+Issue+of+Sequence+Homology.">More Than 1,001 Problems with Protein Domain Databases: Transmembrane Regions, Signal Peptides and the Issue of Sequence Homology.</a> PLoS Comput Biol. 6 (7), e1000867 (2010).</li><li>Bioinformatics, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+and+correction+of+abnormal,+incomplete+and+mispredicted+proteins+in+public+databases.">Identification and correction of abnormal, incomplete and mispredicted proteins in public databases.</a> BMC Bioinformatics. 9 (9), (2008).</li><li>Phizicky, E., Bastiaens, P. I. H., Zhu, H., Snyder, M., Fields, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+analysis+on+a+proteomic+scale.">Protein analysis on a proteomic scale.</a> Nature. 422 (6928), 208-215 (2003).</li><li>DiDonato, M., Deacon, A. M., Klock, H. E., McMullan, D., Lesley, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+scaleable+and+integrated+crystallization+pipeline+applied+to+mining+the+Thermotoga+maritima+proteome.">A scaleable and integrated crystallization pipeline applied to mining the Thermotoga maritima proteome.</a> J Struct Funct Genomics. 5 (1-2), 133-146 (2004).</li><li>Nordlund, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+production+and+purification.">Protein production and purification.</a> Nat Methods. 5 (2), 135-146 (2008).</li><li>Zacchi, P., Sblattero, D., Florian, F., Marzari, R., Bradbury, A. R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selecting+open+reading+frames+from+DNA.">Selecting open reading frames from DNA.</a> Genome Res. 13 (5), 980-990 (2003).</li><li>Di Niro, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+interactome+profiling+by+massive+sequencing.">Rapid interactome profiling by massive sequencing.</a> Nucleic Acids Res. 38 (9), e110 (2010).</li><li>Gourlay, L. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selecting+soluble/foldable+protein+domains+through+single-gene+or+genomic+ORF+filtering:+Structure+of+the+head+domain+of+Burkholderia+pseudomallei+antigen+BPSL2063.">Selecting soluble/foldable protein domains through single-gene or genomic ORF filtering: Structure of the head domain of Burkholderia pseudomallei antigen BPSL2063.</a> Acta Crystallogr Sect D Biol Crystallogr. 71 (Pt 11), 2227-2235 (2015).</li><li>D'Angelo, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Filtering+&amp;#34;genic&amp;#34;+open+reading+frames+from+genomic+DNA+samples+for+advanced+annotation.">Filtering &amp;#34;genic&amp;#34; open reading frames from genomic DNA samples for advanced annotation.</a> BMC Genomics. 12 (Suppl 1), S5 (2011).</li><li>D'Angelo, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Profiling+celiac+disease+antibody+repertoire.">Profiling celiac disease antibody repertoire.</a> Clin Immunol. 148 (1), 99-109 (2013).</li><li>Robinson, M. D., McCarthy, D. J., Smyth, G. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=edgeR:+A+Bioconductor+package+for+differential+expression+analysis+of+digital+gene+expression+data.">edgeR: A Bioconductor package for differential expression analysis of digital gene expression data.</a> Bioinformatics. 26 (1), 139-140 (2009).</li><li>Heger, A., Holm, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exhaustive+enumeration+of+protein+domain+families.">Exhaustive enumeration of protein domain families.</a> J Mol Biol. 328 (3), 749-767 (2003).</li><li>Zacchi, P., Sblattero, D., Florian, F., Marzari, R., Bradbury, A. R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selecting+open+reading+frames+from+DNA.">Selecting open reading frames from DNA.</a> Genome Res. 13 (5), 980-990 (2003).</li><li>Faix, P. H., Burg, M. A., Gonzales, M., Ravey, E. P., Baird, A., Larocca, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phage+display+of+cDNA+libraries:+Enrichment+of+cDNA+expression+using+open+reading+frame+selection.">Phage display of cDNA libraries: Enrichment of cDNA expression using open reading frame selection.</a> Biotechniques. 36 (6), 1018-1029 (2004).</li><li>Patrucco, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+novel+proteins+binding+the+AU-rich+element+of+&#945;-prothymosin+mRNA+through+the+selection+of+open+reading+frames+(RIDome).">Identification of novel proteins binding the AU-rich element of &#945;-prothymosin mRNA through the selection of open reading frames (RIDome).</a> RNA Biol. 12 (12), 1289-1300 (2015).</li><li>Collins, M. O., Choudhary, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mapping+multiprotein+complexes+by+affinity+purification+and+mass+spectrometry.">Mapping multiprotein complexes by affinity purification and mass spectrometry.</a> Curr Opin Biotechnol. 19 (4), 324-330 (2008).</li><li>Suter, B., Kittanakom, S., Stagljar, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Two-hybrid+technologies+in+proteomics+research.">Two-hybrid technologies in proteomics research.</a> Curr Opin Biotechnol. 19 (4), 316-323 (2008).</li><li>Nakai, Y., Nomura, Y., Sato, T., Shiratsuchi, A., Nakanishi, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolation+of+a+Drosophila+gene+coding+for+a+protein+containing+a+novel+phosphatidylserine-binding+motif.">Isolation of a Drosophila gene coding for a protein containing a novel phosphatidylserine-binding motif.</a> J Biochem. 137 (5), 593-599 (2005).</li><li>Deng, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selection+of+antibody+single-chain+variable+fragments+with+improved+carbohydrate+binding+by+phage+display.">Selection of antibody single-chain variable fragments with improved carbohydrate binding by phage display.</a> J Biol Chem. 269 (13), 9533-9538 (1994).</li><li>Danner, S., Belasco, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=T7+phage+display:+A+novel+genetic+selection+system+for+cloning+RNA-binding+proteins+from+cDNA+libraries.">T7 phage display: A novel genetic selection system for cloning RNA-binding proteins from cDNA libraries.</a> Proc Natl Acad Sci. 98 (23), 12954-12959 (2001).</li><li>Gargir, A., Ofek, I., Meron-Sudai, S., Tanamy, M. G., Kabouridis, P. S., Nissim, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single+chain+antibodies+specific+for+fatty+acids+derived+from+a+semi-synthetic+phage+display+library.">Single chain antibodies specific for fatty acids derived from a semi-synthetic phage display library.</a> Biochim Biophys Acta - Gen Subj. 1569 (1-3), 167-173 (2002).</li><li>Patrucco, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+novel+proteins+binding+the+AU-rich+element+of+&#945;-prothymosin+mRNA+through+the+selection+of+open+reading+frames+(RIDome).">Identification of novel proteins binding the AU-rich element of &#945;-prothymosin mRNA through the selection of open reading frames (RIDome).</a> RNA Biol. 12 (12), 1289-1300 (2015).</li><li>Ausubel, F. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Current+Protocols+in+Molecular+Biology.">Current Protocols in Molecular Biology.</a> Mol Biol. 1 (2), 146 (2003).</li><li>Sblattero, D., Bradbury, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exploiting+recombination+in+single+bacteria+to+make+large+phage+antibody+libraries.">Exploiting recombination in single bacteria to make large phage antibody libraries.</a> Nat Biotechnol. 18, 75-80 (2000).</li><li>Martin, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cutadapt+removes+adapter+sequences+from+high-throughput+sequencing+reads.">Cutadapt removes adapter sequences from high-throughput sequencing reads.</a> EMBnet.journal. 17 (1), 10 (2011).</li><li>Camacho, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BLAST+:+architecture+and+applications.">BLAST+: architecture and applications.</a> BMC Bioinformatics. 10 (1), 421 (2009).</li><li>Li, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Sequence+Alignment/Map+format+and+SAMtools.">The Sequence Alignment/Map format and SAMtools.</a> Bioinformatics. 25 (16), 2078-2079 (2009).</li><li>Quinlan, A. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BEDTools:+The+Swiss-Army+tool+for+genome+feature+analysis.">BEDTools: The Swiss-Army tool for genome feature analysis.</a> Curr Protoc Bioinforma. , (2014).</li><li>Skinner, M. E., Uzilov, A. V., Stein, L. D., Mungall, C. J., Holmes, I. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=JBrowse:+A+next-generation+genome+browser.">JBrowse: A next-generation genome browser.</a> Genome Res. 19 (9), 1630-1638 (2009).</li><li>Gourlay, L. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selecting+soluble/foldable+protein+domains+through+single-gene+or+genomic+ORF+filtering:+Structure+of+the+head+domain+of+Burkholderia+pseudomallei+antigen+BPSL2063.">Selecting soluble/foldable protein domains through single-gene or genomic ORF filtering: Structure of the head domain of Burkholderia pseudomallei antigen BPSL2063.</a> Acta Crystallogr Sect D Biol Crystallogr. 71, 2227-2235 (2015).</li><li>D'Angelo, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Filtering+&amp;#34;genic&amp;#34;+open+reading+frames+from+genomic+DNA+samples+for+advanced+annotation.">Filtering &amp;#34;genic&amp;#34; open reading frames from genomic DNA samples for advanced annotation.</a> BMC Genomics. 12 (Suppl 1), S5 (2011).</li><li>Di Niro, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterizing+monoclonal+antibody+epitopes+by+filtered+gene+fragment+phage+display.">Characterizing monoclonal antibody epitopes by filtered gene fragment phage display.</a> Biochem J. 388 (Pt 3), 889-894 (2005).</li><li>D'Angelo, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Profiling+celiac+disease+antibody+repertoire.">Profiling celiac disease antibody repertoire.</a> Clin Immunol. 148 (1), 99-109 (2013).</li></ol>

The creation of a high quality highly diverse ORFs filtered library is the first critical step in the whole procedure since it will affect all the subsequent steps of the pipeline.
An important advantageous feature of our method is that any source of (intronless) DNA (cDNA, genomic DNA, PCR derived or synthetic DNA) is suitable for library construction. The first parameter that should be taken into account is that the length of the DNA fragments cloned into the pFILTER vector should provide a ...

Here, we describe a high-throughput method for the construction and selection of libraries of folded and soluble protein domains from any genic/genomic starting source. The approach combines three different technologies: phage display, the use of a folding reporter and next generation sequencing (NGS) with a specific web tool for data analysis. The methods can be used in many different contexts of protein-based research, for identification and annotation of new proteins/protein domains, characterization of structural and functional properties of known proteins as well as definition of protein-interaction network.
Many open questions are still present in protein-based research and the development of methods for optimal protein production is an important need for several fields of investigation. For example, despite the availability of thousands of prokaryotic and eukaryotic genomes1, a corresponding map of the relative proteomes with a direct annotation of the coded proteins and peptides is still missing for the great majority of organisms. The catalogue of complete proteomes is emerging as a challenging goal requiring a huge effort in terms of time and resources. The gold standard for experimental annotation remains the cloning of all the Open Reading Frames (ORFs) of a genome, building the so called &#34;ORFeome&#34;. Usually gene function is assigned based on homology to related genes of known activity but this approach is poorly accurate due to the presence of many incorrect annotations in the reference databases2,3,4,5. Moreover, even for proteins that have been identified and annotated, additional studies are required to achieve characterization in terms of abundance, expression patterns in different contexts, including structural and functional properties as well as interaction networks.
Furthermore, since proteins are composed of different domains, each of them showing specific features and differently contributing to protein functions, the study and the exact definition of these domains can allow a more comprehensive picture, both at the single gene and at the full genome level. All this necessary information makes protein-based research a wide and challenging field.
In this perspective, an important contribution could be given by unbiased and high-throughput methods for protein production. However, the success of such approaches, beside the considerable investment required, relies on the ability to produce soluble/stable protein constructs. This is a major limiting factor since it has been estimated that only about 30% of proteins can be successfully expressed and produced at sufficient levels to be experimentally useful6,7,8. An approach to overcome this limitation is based on the use of randomly fragmented DNA to produce different polypeptides, which together provide overlapping fragment representation of individual genes. Only a small percentage of the randomly generated DNA fragments are functional ORFs whilst the great majority of them are non-functional (due to the presence of stop codons inside their sequences) or encode for un-natural (ORF in a frame other than the original) polypeptides with no biological meaning.
To address all these issues, our group has developed an high-throughput protein expression and interaction analysis platform that can be used on a genomic scale9,10,11,12. This platform integrates the following techniques: 1) a method to select collections of correctly folded protein domains from the coding portion of DNA from any organism; 2) the phage display technology for selecting partners of interactions; 3) the NGS to completely characterize the whole interactome under study and identify the clones of interest; and 4) a web tool for data analysis for users without any bioinformatics or programming skills to perform Interactome-Seq analysis in an easy and user-friendly way.
The use of this platform offers important advantages over alternative strategies of investigation; above all the method is completely unbiased, high-throughput, and modular for study ranging from a single gene up to a whole genome. The first step of the pipeline is the creation of a library from randomly fragmented DNA under study, which is then deeply characterized by NGS. This library is generated using an engineered vector where genes/fragments of interest are cloned between a signal sequence for protein secretion into the periplasmic space (i.e., a Sec leader) and the TEM1 &#946;-lactamase gene. The fusion protein will confer ampicillin resistance and the ability to survive under ampicillin pressure only if cloned fragments are in-frame with both these elements and the resulting fusion protein is correctly folded10,13,14. All clones rescued after antibiotic selection, the so called &#34;filtered clones&#34;, are ORFs and, a great majority of them (more than 80%), are derived from real genes9. Moreover, the power of this strategy lies in the findings that all ORF filtered clones are encoding for correctly folded/soluble proteins/domains15. As many clones, present in the library and mapping in the same region/domain, have different starting and ending points, this allows unbiased, single-step&#160;identification of the minimum fragments that are likely to result in soluble products.
A further improvement in the technology is given by the use of NGS to characterize the library. The combination of this platform and of a specific web tool for data analysis gives important unbiased information on the exact nucleotide sequences and on the location of selected ORFs on the reference DNA under study without the need of further extensive analyses or experimental effort.
Domainome libraries can be transferred into a selection context and used as a universal instrument to perform functional studies. The high-throughput protein expression and interaction analysis platform that we integrated and that we called Interactome-Seq takes advantage of the phage display technology by transferring the filtered ORF into a phagemid vector and creating a phage-ORF library. Once re-cloned into a phage display context, protein domains are displayed on the surface of M13 particles; in this way domainome libraries can be directly selected for gene fragments encoding domains with specific enzymatic activities or binding properties, allowing interactome networks profiling. This approach was initially described by Zacchi et al.16 and later used in several other context13,17,18.
Compared to other technologies used to study protein-protein interaction (including yeast two hybrid system and mass spectrometry19,20), one major advantage is the amplification of the binding partner that occurs during phage display multiple rounds of selection. This increases the selection sensitivity thus allowing the identification of low abundant binding proteins&#39; domains present in the library. The efficiency of the selection performed with ORF-filtered library is further increased due to the absence of non-functional clones. Finally, the technology allows the selection to be performed against both protein and non-protein baits21,22,23,24,25.
Phage selections using the domainome-phage library can be performed using antibodies coming from sera of patients with different pathological conditions, e.g. autoimmune diseases13, cancer or infection diseases as bait. This approach is used to obtain the so called &#34;antibody signature&#34; of the disease under study allowing to massively identify and characterize the antigens/epitopes specifically recognized by the patients&#39; antibodies at the same time. Compared to other methods the use of phage display allows the identification of both linear and conformational antigenic epitopes. The identification of a specific signature could potentially have an important impact for understanding pathogenesis, new vaccine design, identification of new therapeutic targets and development of new and specific diagnostic and prognostic tools. Moreover, when the study is focused on infectious diseases, a major advantage is that the discovery of immunogenic proteins is independent from pathogen cultivation.
Our approach confirms that the folding reporters can be used on a genomic scale to select the &#34;domainome&#34;: a collection of correctly folded, well expressed, soluble protein domains from the coding portion of the DNA and/or cDNA from any organism. Once isolated the protein fragments are useful for many purposes, providing essential experimental information for gene annotation as well as for structural studies, antibody epitope mapping, antigen identification, etc. The completeness of high-throughput data provided by NGS enables the analysis of highly complex samples, such as phage display libraries, and holds the potential to circumvent the traditional laborious picking and testing of individual phage rescued clones.
At the same time thanks to the features of the filtered library and to the extreme sensitivity and power of the NGS analysis, it is possible to identify the protein domain responsible of each interaction directly in an initial screen, without the need to create additional libraries for each bound protein. NGS allows to obtain a comprehensive definition of the whole domainome of any genic/genomic starting source and the data analysis web tool enables the obtainment of a highly specific characterization both from a qualitative and quantitative point of view of the interactome proteins&#39; domains.

<table border="0" cellpadding="0" cellspacing="0" style="width:1817px;" width="1817">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Sonopuls&#160; ultrasonic homogenizer</td>
			<td style="width:444px;">Bandelin</td>
			<td style="width:423px;">HD2070</td>
			<td style="width:557px;">or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">GeneRuler 100 bp Plus DNA Ladder</td>
			<td style="width:444px;">Thermo Scientific</td>
			<td style="width:423px;">SM0321</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">GeneRuler 1 kb DNA Ladder</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td style="width:423px;">SM0311</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Molecular Biology Agarose</td>
			<td style="width:444px;">BioRad</td>
			<td style="width:423px;">161-3102</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Green Gel Plus</td>
			<td style="width:444px;">Fisher Molecular Biology</td>
			<td style="width:423px;">FS-GEL01</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">6x DNA Loading Dye</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td style="width:423px;">R0611</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">QIAquick Gel Extraction Kit</td>
			<td style="width:444px;">Qiagen</td>
			<td style="width:423px;">28704</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Quick Blunting Kit</td>
			<td style="width:444px;">New England Biolabs</td>
			<td style="width:423px;">E1201S</td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:393px;">NanoDrop 2000 UV-Vis Spectrophotometer</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td style="width:423px;">ND-2000</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">High-Capacity cDNA Reverse Transcription Kit</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td style="width:423px;">4368813</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Streptavidin Magnetic Beads</td>
			<td style="width:444px;">New England Biolabs</td>
			<td style="width:423px;">S1420S</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">QIAquick PCR purification Kit</td>
			<td style="width:444px;">Qiagen</td>
			<td style="width:423px;">28104</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">EcoRV</td>
			<td style="width:444px;">New England Biolabs</td>
			<td>R0195L</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Antarctic Phosphatase</td>
			<td style="width:444px;">New England Biolabs</td>
			<td>M0289S</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">T4 DNA Ligase</td>
			<td style="width:444px;">New England Biolabs</td>
			<td>M0202T</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Sodium Acetate 3M pH5.2</td>
			<td style="width:444px;">general lab supplier</td>
			<td style="width:423px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Ethanol for molecular biology</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td style="width:423px;">E7023</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">DH5aF&#39; bacteria cells</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td style="width:423px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">0,2 ml tubes</td>
			<td style="width:444px;">general lab supplier</td>
			<td style="width:423px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">1,5 ml tubes</td>
			<td style="width:444px;">general lab supplier</td>
			<td style="width:423px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">0,1 cm electroporation cuvettes</td>
			<td style="width:444px;">Biosigma</td>
			<td style="width:423px;">4905020</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Electroporator 2510</td>
			<td style="width:444px;">Eppendorf</td>
			<td style="width:423px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">2x YT medium</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>Y1003</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Ampicillin sodium salt</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>A9518</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">Chloramphenicol</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>C0378</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">DreamTaq DNA Polymerase</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td>EP0702</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Deoxynucleotide (dNTP) Solution Mix</td>
			<td style="width:444px;">New England Biolabs</td>
			<td>N0447S</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">96-well thermal cycler (with heated lid)</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">150 mm plates</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:393px;">100 mm plates</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Glycerol</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>G5516</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BssHII</td>
			<td style="width:444px;">New England Biolabs</td>
			<td>R0199L</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">NheI</td>
			<td style="width:444px;">New England Biolabs</td>
			<td>R0131L</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">QIAprep Spin Miniprep Kit</td>
			<td style="width:444px;">Qiagen</td>
			<td>27104</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">M13KO7 Helper Phage</td>
			<td style="width:444px;">GE Healthcare Life Sciences</td>
			<td>27-1524-01&#160;</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Kanamycin sulfate from Streptomyces kanamyceticus</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>K1377</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Polyethylene glycol (PEG)</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>P5413</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Sodium Cloride (NaCl)</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>S3014</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PBS</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Dynabeads Protein G for Immunoprecipitation</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td>10003D</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MagnaRack Magnetic Separation Rack</td>
			<td style="width:444px;">Thermo Fisher Scientific</td>
			<td>CS15000</td>
			<td>or equivalent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Tween 20</td>
			<td style="width:444px;">Sigma-Aldrich</td>
			<td>P1379</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Nonfat dried milk powder</td>
			<td style="width:444px;">EuroClone</td>
			<td>EMR180500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">KAPA HiFi HotStart ReadyMix&#160;</td>
			<td style="width:444px;">Kapa Biosystems, Fisher Scientific</td>
			<td>7958935001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">AMPure XP beads&#160;</td>
			<td>Agencourt, Beckman Coulter</td>
			<td>A63881</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Nextera XT dual Index&#160; Primers&#160;</td>
			<td style="width:444px;">Illumina</td>
			<td>FC-131-2001 or FC-131-2002 or FC-131-2003 or FC-131-2004</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MiSeq or Hiseq2500&#160;</td>
			<td>Illumina</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Spectrophotomer</td>
			<td>Nanodrop</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Agilent Bioanalyzer or TapeStation</td>
			<td>Agilent</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Forward PCR primer</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td>5&#8217; TACCTATTGCCTACGGCAGCCGCTGGATTGTTATTACTC 3&#8217;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Reverse PCR primer</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td>5&#8217; TGGTGATGGTGAGTACTATCCAGGCCCAGCAGTGGGTTTG 3&#8217;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Forward primer for NGS</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td>&#160;5&#8217; TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGCAGCAAGCGGCGCGCATGC 3&#8217;;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Reverse primer for NGS</td>
			<td style="width:444px;">general lab supplier</td>
			<td></td>
			<td>5&#8217; GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGGGATTGGTTTGCCGCTAGC 3&#8217;;</td>
		</tr>
	</tbody>
</table>

interactome-seq: a protocol for domainome library construction, validation and selection by phage display and next generation sequencing

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to poorly folding proteins or random open reading frames. We have developed a strategy where, by using TEM-1 &#946;-lactamase (the enzyme conferring ampicillin resistance) on a genomic scale, we can select collections of correctly folded protein domains from the coding portion of the DNA of any intronless genome. The protein fragments obtained by this approach, the so called &#34;domainome&#34;, will be well expressed and soluble, making them suitable for structural/functional studies.
By cloning and displaying the &#34;domainome&#34; directly in a phage display system, we have showed that it is possible to select specific protein domains with the desired binding properties (e.g., to other proteins or to antibodies), thus providing essential experimental information for gene annotation or antigen identification.
The identification of the most enriched clones in a selected polyclonal population can be achieved by using novel next-generation sequencing technologies (NGS). For these reasons, we introduce deep sequencing analysis of the library itself and the selection outputs to provide complete information on diversity, abundance and precise mapping of each of the selected fragment. The protocols presented here show the key steps for library construction, characterization, and validation.

The filtering approach is schematized in Figure 1. Each kind of intronless DNA can be used. In Figure 1A the first part of the filtering approach is represented: after loading on an agarose gel or a bioanalyzer, a good fragmentation of the DNA of interest appears as a smear of fragments with a length distribution in the desired size of 150-750 bp. A representative virtual gel image of the fragmented DNA obtained is given. Fragmen...

Watch this Scientific Journal Video about Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing at JoVE.com

Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing

The protocols described allow the construction, characterization and selection (against the target of choice) of a &#34;domainome&#34; library made from any DNA source. This is achieved by a research pipeline that combines different technologies: phage display, a folding reporter and next generation sequencing with a web tool for data analysis.

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to ...

This method can help answer key questions in the protein based research such as annotation of new proteins or protein domains, characterization of structural and functional properties of known proteins, definition of protein interaction networks or antigen antibody signatures in different conditions. The main advantage of this technique is that it is completely unbiased, high throughput and modular for any kind of study ranging from a single gene up to a whole genome. The construction of a domainone library is very useful for functional studies.It can be transferred to a phage display context and used for the selection against different targets such as binding proteins or purified antibodies. The coupling with NGS enables an extremely sensitive and powerful analysis. At the same time, the web tools specifically developed gives a precise characterization of the whole domainome and interactome.To construct the ORF library first, sonicate the DNA with 30 second pulses at 100%output. After sonication, load the ladder and the sonicated DNA on a 1.5%agarose gel. Then start the electrophoresis unit at five volts per centimeter for 15 minutes.The agarose gel electrophoresis shows the presence of DNA smear confirming sonication. This is in comparison to the solid band obtained from a DNA not subjected to sonication. Then cut the gel portion with the fragmented DNA smear and purify using column based gel extraction kit.Measure the concentration of the purified DNA in the UV spectrophotometer. Then follow the manufacturer's instructions and treat five micrograms of the insert with one microliter of quick blunting enzyme mix. Then inactivate the enzyme mix at 70 degrees Celsius for 10 minutes.To prepare the filtering vector, first digest five micrograms of the purified cloning vector with EcoRV restriction enzyme. Then load the digested and undigested vectors and the molecular marker on a 1%agarose gel. Then heat inactivate the restriction enzyme at 80 degrees Celsius for 20 minutes.Next, phosphorylate the digested vector with five units of phosphatase enzyme and 1/10 volume of the 10X phosphatase buffer. Then incubate the mixture at 37 degrees Celsius for 15 minutes. Then inactivate the phosphatase enzyme at 65 degrees Celsius for five minutes.Next, extract the plasmid from the gel and purify the DNA. Then measure the concentration of the DNA in the UV spectrophotometer. To perform the ligation reaction, add 400 nanograms of the phosphorylated inserts to one microgram of digested vector, 10X T4 DNA ligase buffer and T4 DNA ligase to a final volume of 100 microliters.Then incubate the ligation reaction at 16 degrees Celsius for overnight. The next day, heat inactivate the ligase at 65 degrees Celsius for 10 minutes. Next, add 1/10 volume of three molar sodium acetate at pH 5.2 and 2.5 volumes of 100%ethanol to precipitate the ligation product.To precipitate DNA, mix the reagents and freeze at minus 80 degrees Celsius for 20 minutes. After 20 minutes, centrifuge at the highest speed for 20 minutes at four degrees Celsius. After centrifugation, expel the supernatant.To the pellet, add 500 microliters of cold 70%ethanol and again centrifuge. Discard the supernatant at the end of the centrifugation. Once the pellet is air dried, dissolve the precipitated DNA in 10 microliters of water.Before performing electroporation, arrange for the appropriate number of microcentrifuge tubes and 0.1 centimeter electroporation cuvettes on ice. Then add one microliter of the purified ligation product to 25 microliters of the cells. Then pipette the DNA, cell mixture to the cold electroporation cuvette and flick the tube.Then wipe the water from the exterior of the cuvette and place in the electroporation unit and hit pulse. After the electroporation is over, quickly add one milliliter of liquid 2X YT medium without any antibiotic to the cells in the cuvette. Then transfer the cellular mixture to a 10 milliliter tube.Leave the tube on a shaker at 220 revolutions per minute at 37 degrees Celsius for an hour. Plate the dilutions of the library on 10 centimeter 2X YT agar plates supplemented with chloramphenicol, ampicillin and only chloramphenicol. This is to obtain single colonies to be tested by PCR and to perform titration.Next, plate the transformed competent cells on 15 centimeter 2X YT agar plates supplemented with chloramphenicol and ampicillin. Then incubate the plates at 30 degrees Celsius for overnight. The next day, count the colonies choosing the dilution where they are countable.Then calculate the library size. Library size is calculated as follows, mean colony number times dilution factor times total library volume. Library size should be in the order of 10 to the power of six clones.If ampicillin concentration is optimal to perform more filtering, the clone number reduces to one to 20 of that obtained in the absence of this antibiotic. To test for the positive colonies, use a tip to pick up around 15 to 20 single colonies. Then dilute the colonies with 100 microliters of 2X YT medium without antibiotics.Next, PCR amplify 0.5 microliter of the culture as DNA template with Taq DNA polymerase. During the PCR, run 25 cycles of amplifications using annealing temperature of 55 degrees Celsius and an extension time of 40 seconds at 72 degrees Celsius. Check that the length of the insert is in the expected range of 150 to 750 base pair.And that different colonies present different inserts with different size. This indicate a good library preparation in terms of variability. Next, add three milliliters of fresh 2X YT medium to the 150 millimeter plates to collect the bacteria.Then harvest the bacteria using a sterile scraper. After mixing thoroughly, add 20%glycerol and leave in minus 80 degrees Celsius in aliquots for future use. For immediate use, perform column based plasmid extraction kit to purify the plasmid DNA from one of the aliquots of the library before adding glycerol.Measure the concentration of the DNA in the UV spectrophotometer and then store the samples at minus 20 degrees Celsius until use. Use 2.5 microliters of the library as DNA template for PCR amplification. Set the thermocycler conditions and start the run.Next, use an index PCR kit to perform index PCR. This will sequence the double indexed libraries within multiplexed Illumina runs. Then set the thermocycler conditions and start the run.After purification with AMPure XP beads, to verify the size, run one microliter of the one to 10 dilution of the final library on the bioanalyzer. Then quantify by selecting the region of the final library trace. These schematic representations demonstate that after cloning into P filter vector, only colonies corresponding to ORFs produce functional beta-lactamase in the presence of antibiotics.After filtering a decrease in the clone number of 20-fold is expected. With good-folder ORFs growing at higher antibiotic concentrations. Moreover, the ORF fragments can be easily recovered from the filtered library.A phagemid ORF library is constructed to perform phage display selection against target proteins or antibodies. All the libraries and the outputs obtained are then deeply analyzed by the NGS. The NGS provides a complete information on library diversity, abundance and precise mapping of each of the selected fragments.Finally the interactome seek webtool developed generates raw sequencing reads ranging to the list of putative domains with genomic annotations. After watching this video, you should have a good understanding of how to construct and validate a domainome library from a desired DNA source. And to perform a high throughput screening of the library by next generation sequencing.We have optimized the sequencing of the ORF filtering libraries with the Illumina platforms and developed a webtool which make possible the analysis of this kind of data without any need of programming skills.

interactome-seq-protocol-for-domainome-library-construction

Research

JoVE Journal

Biology

Primer-Free Aptamer Selection Using A Random DNA Library

Aptamers are highly structured oligonucleotides (DNA or RNA) that can bind to targets with affinities comparable to antibodies 1. They are identified through an in vitro selection process called Systematic Evolution of Ligands by EXponential enrichment (SELEX) to recognize a wide variety of targets, from small molecules to proteins and other macromolecules 2-4. Aptamers have properties that are well suited for in vivo diagnostic and/or therapeutic applications: Besides good specificity and affinity, they are easily synthesized, survive more rigorous processing conditions, they are poorly immunogenic, and their relatively small size can result in facile penetration of tissues.
Aptamers that are identified through the standard SELEX process usually comprise ~80 nucleotides (nt), since they are typically selected from nucleic acid libraries with ~40 nt long randomized regions plus fixed primer sites of ~20 nt on each side. The fixed primer sequences thus can comprise nearly ~50% of the library sequences, and therefore may positively or negatively compromise identification of aptamers in the selection process 3, although bioinformatics approaches suggest that the fixed sequences do not contribute significantly to aptamer structure after selection 5. To address these potential problems, primer sequences have been blocked by complementary oligonucleotides or switched to different sequences midway during the rounds of SELEX 6, or they have been trimmed to 6-9 nt 7, 8. Wen and Gray 9 designed a primer-free genomic SELEX method, in which the primer sequences were completely removed from the library before selection and were then regenerated to allow amplification of the selected genomic fragments. However, to employ the technique, a unique genomic library has to be constructed, which possesses limited diversity, and regeneration after rounds of selection relies on a linear reamplification step. Alternatively, efforts to circumvent problems caused by fixed primer sequences using high efficiency partitioning are met with problems regarding PCR amplification 10.
We have developed a primer-free (PF) selection method that significantly simplifies SELEX procedures and effectively eliminates primer-interference problems 11, 12. The protocols work in a straightforward manner. The central random region of the library is purified without extraneous flanking sequences and is bound to a suitable target (for example to a purified protein or complex mixtures such as cell lines). Then the bound sequences are obtained, reunited with flanking sequences, and re-amplified to generate selected sub-libraries. As an example, here we selected aptamers to S100B, a protein marker for melanoma. Binding assays showed Kd s in the 10-7 - 10-8 M range after a few rounds of selection, and we demonstrate that the aptamers function effectively in a sandwich binding format.

SELEX protocols comprise multiple rounds of selection, each of which require regeneration of bound ligands, which in turn require fixed primer sequences flanking the random library regions. These fixed primer sequences can interfere with the selection process (false positives and negatives). Here we present a primer-free protocol.

Aptamers are highly structured oligonucleotides (DNA or RNA) that can bind to targets with affinities comparable to antibodies 1. They are identified ...

Peptides from Phage Display Library Modulate Gene Expression in Mesenchymal Cells and Potentiate Osteogenesis in Unicortical Bone Defects

Two novel synthetic peptides accelerate bone formation and can be delivered using a collagen matrix. The aim of this study was to investigate the effects on bone repair in a unicortical defect model. Treatment of mesenchymal cells produced an increase in alkaline phosphatase activity, showed nodule formation by the cells, and increased the expression of genes for runx2, osterix, bone sialoprotein, and osteocalcin. A collagen sponge soaked with peptide promoted repair of bone defects, whereas the control was less effective. The results from this study demonstrated that mesenchymal cells treated with peptide in vitro differentiate towards osteogenesis, and, that peptides delivered in vivo using a collagen sponge promote the repair of unicortical defects.

A phage display library was used to identify peptide sequences that target bone. The objective was to investigate the effect of these peptides on mesenchymal cell differentiation and to determine their effect on bone regeneration.

Two novel synthetic peptides accelerate bone formation and can be delivered using a collagen matrix. The aim of this study was to investigate the effects ...

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the subcellular distribution of a specific tagged fluorescent marker in the secretory pathway. Arabidopsis is a powerful biological model for genetic studies because of its genome size, generation time, and conservation of molecular mechanisms among kingdoms. The array genotyping as an approach to map the mutation in alternative to the traditional method based on molecular markers is advantageous because it is relatively faster and may allow the mapping of several mutants in a really short time frame. This method allows the identification of proteins that can influence the integrity of any organelle in plants. Here, as an example, we propose a screen to map genes important for the integrity of the endoplasmic reticulum (ER). Our approach, however, can be easily extended to other plant cell organelles (for example see1,2), and thus represents an important step toward understanding the molecular basis governing other subcellular structures.

A fundamental quest in cell biology is to define the mechanisms that underlie the identity of the organelles that make eukaryotic cells. Here we propose a method to identify the genes responsible for the morphological and functional integrity of plant organelles using fluorescence microscopy and next-generation sequencing tools.

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the ...

A Protocol for Phage Display and Affinity Selection Using Recombinant Protein Baits

Using recombinant phage as a scaffold to present various protein portions encoded by a directionally cloned cDNA library to immobilized bait molecules is an efficient means to discover interactions. The technique has largely been used to discover protein-protein interactions but the bait molecule to be challenged need not be restricted to proteins. The protocol presented here has been optimized to allow a modest number of baits to be screened in replicates to maximize the identification of independent clones presenting the same protein. This permits greater confidence that interacting proteins identified are legitimate interactors of the bait molecule. Monitoring the phage titer after each affinity selection round provides information on how the affinity selection is progressing as well as on the efficacy of negative controls. One means of titering the phage, and how and what to prepare in advance to allow this process to progress as efficiently as possible, is presented. Attributes of amplicons retrieved following isolation of independent plaque are highlighted that can be used to ascertain how well the affinity selection has progressed. Trouble shooting techniques to minimize false positives or to bypass persistently recovered phage are explained. Means of reducing viral contamination flare up are discussed.

Phage display is a powerful technique to capture proteins or protein moieties that interact with an immobilized molecule of interest. Once a decision of the type of phage cDNA library to create and screen has been made, the protocol described here permits efficient affinity selection leading to identification of interactors.

Using  recombinant phage as a scaffold to present various protein portions encoded by  a directionally cloned cDNA library to immobilized bait molecules ...

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

One of the major questions in microbial ecology is &#8220;who is there?&#8221; 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.

Characterizing microbial community has been a longstanding goal in environmental microbiology. Next-generation sequencing methods now allow for the characterization of microbial communities at an unprecedented depth with minimal cost and labor. We detail here our approach to sequence bacterial 16S ribosomal RNA genes using a benchtop sequencer.

One of the major questions in microbial ecology is &#8220;who is there?&#8221; This question can be answered using various tools, but one of the ...

Targeted DNA Methylation Analysis by Next-generation Sequencing

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.

Bisulfite amplicon sequencing (BSAS) is a method for quantifying cytosine methylation in targeted genomic regions of interest. This method uses bisulfite conversion paired with PCR amplification of target regions prior to next-generation sequencing to produce absolute quantitation of DNA methylation at a base-specific level.

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 ...

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of diverse libraries of retroviral integration sites using ligation-mediated PCR (LM-PCR) amplification and next-generation sequencing (NGS), (2) mapping the genomic location of each virus-host junction using BEDTools, and (3) analyzing the data for statistical relevance. Genomic DNA extracted from infected cells is fragmented by digestion with restriction enzymes or by sonication. After suitable DNA end-repair, double-stranded linkers are ligated onto the DNA ends, and semi-nested PCR is conducted using primers complementary to both the long terminal repeat (LTR) end of the virus and the ligated linker DNA. The PCR primers carry sequences required for DNA clustering during NGS, negating the requirement for separate adapter ligation. Quality control (QC) is conducted to assess DNA fragment size distribution and adapter DNA incorporation prior to NGS. Sequence output files are filtered for LTR-containing reads, and the sequences defining the LTR and the linker are cropped away. Trimmed host cell sequences are mapped to a reference genome using BLAT and are filtered for minimally 97% identity to a unique point in the reference genome. Unique integration sites are scrutinized for adjacent nucleotide (nt) sequence and distribution relative to various genomic features. Using this protocol, integration site libraries of high complexity can be constructed from genomic DNA in three days. The entire protocol that encompasses exogenous viral infection of susceptible tissue culture cells to integration site analysis can therefore be conducted in approximately one to two weeks. Recent applications of this technology pertain to longitudinal analysis of integration sites from HIV-infected patients.

We describe a protocol for amplifying retroviral integration sites from the genomic DNA of infected cells, sequencing the amplified virus-host junctions, and then mapping these sequences to a reference genome. We also describe techniques to quantify the distribution of integration sites relative to various genomic annotations using BEDTools.

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of ...

3' End Sequencing Library Preparation with A-seq2

Studies in the last decade have revealed a complex and dynamic variety of pre-mRNA cleavage and polyadenylation reactions. mRNAs with long 3&#39; untranslated regions (UTRs) are generated in differentiated cells whereas proliferating cells preferentially express transcripts with short 3&#39;UTRs. We describe the A-seq protocol, now at its second version, which was developed to map polyadenylation sites genome-wide and study the regulation of pre-mRNA 3&#39; end processing. Also this current protocol takes advantage of the polyadenylate (poly(A)) tails that are added during the biogenesis of most mammalian mRNAs to enrich for fully processed mRNAs. A DNA adaptor with deoxyuracil at its fourth position allows the precise processing of mRNA 3&#39; end fragments for sequencing. Not including the cell culture and the overnight ligations, the protocol requires about 8 h hands-on time. Along with it, an easy-to-use software package for the analysis of the derived sequencing data is provided. A-seq2 and the associated analysis software provide an efficient and reliable solution to the mapping of pre-mRNA 3&#39; ends in a wide range of conditions, from 106 or fewer cells.

3&#039; End Sequencing Library Preparation with A-seq2

This protocol describes a method for mapping pre-mRNA 3&#39; end processing sites.

Studies in the last decade have revealed a complex and dynamic variety of pre-mRNA cleavage and polyadenylation reactions. mRNAs with long 3&#39; ...

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

In recent decades, vector-borne diseases have re-emerged and expanded at alarming rates, causing considerable morbidity and mortality worldwide. Effective and widely available vaccines are lacking for a majority of these diseases, necessitating the development of novel disease mitigation strategies. To this end, a promising avenue of disease control involves targeting the vector microbiome, the community of microbes inhabiting the vector. The vector microbiome plays a pivotal role in pathogen dynamics, and manipulations of the microbiome have led to reduced vector abundance or pathogen transmission for a handful of vector-borne diseases. However, translating these findings into disease control applications requires a thorough understanding of vector microbial ecology, historically limited by insufficient technology in this field. The advent of next-generation sequencing approaches has enabled rapid, highly parallel sequencing of diverse microbial communities. Targeting the highly-conserved 16S rRNA gene has facilitated characterizations of microbes present within vectors under varying ecological and experimental conditions. This technique involves amplification of the 16S rRNA gene, sample barcoding via PCR, loading samples onto a flow cell for sequencing, and bioinformatics approaches to match sequence data with phylogenetic information. Species or genus-level identification for a high number of replicates can typically be achieved through this approach, thus circumventing challenges of low detection, resolution, and output from traditional culturing, microscopy, or histological staining techniques. Therefore, this method is well-suited for characterizing vector microbes under diverse conditions but cannot currently provide information on microbial function, location within the vector, or response to antibiotic treatment. Overall, 16S next-generation sequencing is a powerful technique for better understanding the identity and role of vector microbes in disease dynamics.

Here we present a next-generation sequencing protocol for 16S rRNA sequencing which enables identification and characterization of microbial communities within vectors. This method involves DNA extraction, amplification and barcoding of samples through PCR, sequencing on a flow-cell, and bioinformatics to match sequence data to phylogenetic information.

In recent decades, vector-borne diseases have re-emerged and expanded at alarming rates, causing considerable morbidity and mortality worldwide. Effective ...

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has become the first step towards defining the microbiome&#8217;s role in health and disease. Use of 16S rRNA metagenomic sequencing for profiling bacterial community has helped in advancing microbiome research. Despite its wide use, there is no uniform protocol for 16S rRNA-based taxonomic profiling analysis. Another limitation is the low resolution of taxonomic assignment due to technical difficulties such as smaller sequencing reads, as well as use of only forward (R1) reads in the final analysis due to low quality of reverse (R2) reads. There is need for a simplified method with high resolution to characterize bacterial diversity in a given biospecimen. Advancements in sequencing technology with the ability to sequence longer reads at high resolution have helped to overcome some of these challenges. Present sequencing technology combined with a publicly available metagenomic analysis pipeline such as R-based Divisive Amplicon Denoising Algorithm-2 (DADA2) has helped advance microbial profiling at high resolution, as DADA2 can assign sequence at the genus and species levels. Described here is a guide for performing bacterial profiling using two-step amplification of the V3-V4 region of the 16S rRNA gene, followed by analysis using freely available analysis tools (i.e., DADA2, Phyloseq, and METAGENassist). It is believed that this simple and complete workflow will serve as an excellent tool for researchers interested in performing microbiome profiling studies.

Described here is a simplified standard operating procedure for microbiome profiling using 16S rRNA metagenomic sequencing and analysis using freely available tools. This protocol will help researchers who are new to the microbiome field as well as those requiring updates on methods to achieve bacterial profiling at a higher resolution.

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the ...