Profiles Research Networking Software – An Open Source Project

Introduction: Profiles Research Networking Software (RNS) is a free semantic web application which uses the VIVO ontology to generate searchable online profiles of an organization’s investigators (http://profiles.catalyst.harvard.edu). As an open source product, Profiles RNS benefits from a community of developers who contribute code to the software, customize the website in unique ways for their institutions, and provide helpful suggestions for future functionality. This poster describes how the Profiles RNS open source code is managed and how we have built a community around it. <br><br>Developers: Profiles RNS has a core development team at Harvard Medical School and also receives community submissions, with significant parts of the code base written and updated by University of California San Francisco (UCSF) and Boston University (BU). Additional institutions have contributed modular “gadgets” they built for Profiles RNS; and, some sites hired commercial vendors (e.g., Recombinant Data Corp) to build custom features for Profiles RNS, which they ultimately made available to others for free. <br><br>Release Process: Updates to the Profiles RNS open source code occur about 2-3 times per year. We use GitHub for source control. The distributed nature of Git is ideal for collaborative open source project. A continuous build system hooks into GitHub and deploys Profiles RNS to multiple environments each time code is contributed. We perform three types of automated testing: (1) Link Checking: This spiders a site looking for broken links and identifying 404 and 500 errors. This is easy to configure and provides broad coverage of the pages in a Profiles RNS installation. (2) API tests: These are custom tests that query the Profiles API and compare the results with the test data, covering database install scripts and the APIs. (3) Selenium UI testing: Selenium allows automated interaction with a site, allowing for testing of search and edit functionality. Selenium requires significant development effort but has deep coverage. <br><br>Community: We use several approaches to building a Profiles RNS open source community and engaging sites that use the software: (1) a restricted mailing list for official Profiles RNS announcements; (2) an open Google group allowing discussion of Profiles RNS; (3) a monthly Developers webinar to discuss technical topics; (4) a monthly Users Group webinar to discuss long-term plans and for guest presentations; and (5) a partnership with Symplectic, which provides commercial support to institutions using Profiles RNS. <br><br>Future Plans: In the future we would like to use issue tracking software to link every source code commit to a bug or enhancement. This would increase accessibility to the code base and help provide a bridge between users and developers. Additionally, we would like to create a community Wiki, which would provide easier management of the software documentation and enable other sites to contribute to it. <br><br>This project was funded by NIH grants 8UL1TR000170 and 1UL1TR001102, and Harvard University and its affiliated academic health centers

Specific conservation values for the yeast SH3 domain family.

<p>A. Alignment of the core 60 positions colored by ortholog SC values as a heat map (red high and yellow low SC values, with domains sorted alphabetically). The average SC value across the family is indicated for each position at the bottom of the table, along with the paralog positional entropy, surface labels and secondary structure. Dark Boxes indicate the 2 principal loop regions where high SC values are found. B. Specific conservation across the domain. The line is set at an SC value of 1.7, which is considered a potential threshold for significant specific conservation (where ortholog conservation is almost twice that of paralog conservation).</p

SI and SII family dendograms.

<p>Clustering was based on SI (left) and SII (right) PSSMs. For SI dendogram, there is more significant clustering, which appears to concentrate domains that bind class I peptides into the red group and domains that bind class II peptides into the magenta group.</p

General mechanisms to obtain binding specificity in domain families.

<p>A. Domains may use the interaction with an extended region that goes beyond the canonical binding site to obtain intrinsic specificity (1). For example, the Abp1p SH3 domain binds extended target peptides (17 residues) and was shown to possess high intrinsic binding specificity [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref009" target="_blank">9</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref010" target="_blank">10</a>]. Domains may also achieve intrinsic specificity through non-canonical recognition via an alternative binding surface far from the canonical one. For example, Pex13 is a peroxisomal membrane protein that contains an SH3 domain that binds Pex14p via the canonical binding surface, however, it also binds Pex5p through an alternative non-canonical surface [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref011" target="_blank">11</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref012" target="_blank">12</a>]. Furthermore, intrinsic specificity may be achieved through replacing the canonical binding site with a non-canonical one (2) that would lead to negative selection (3) with respect to proline-rich peptides that bind SH3 domains. For example, Fus1 peptide targets do not contain a canonical PxxP motif thus minimizing cross reactivity to proline containing peptides [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref013" target="_blank">13</a>]. Some domains may have potential for contextual specificity using adjacent domains (4). For example, at least 2 of the 3 adjacent SH3 domains of Nck are required to bind their targets [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref014" target="_blank">14</a>]. Spatial and temporal separation mechanisms may be another contextual specificity mechanism (6). For example, <i>in vitro</i>, Fyn SH3 domain and CD2BP2 both bind and compete with each other for the proline region in the target protein CD2. However CD2BP2 localizes to the cytosolic compartment where it interacts with CD2 in T-cells, while Fyn is present permanently in the lipid raft fraction unable to compete [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref015" target="_blank">15</a>]. In some cases, both intrinsic and contextual specificity mechanisms may be used by a domain, such as the Pex13p example above (5). We note here that contextual specificity has been used elsewhere to mean the extended regions of SH3 domain binding peptides, outside their core binding motif [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref016" target="_blank">16</a>]. This definition does not pertain to contextual specificity as discussed within this study. Figure adapted from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref017" target="_blank">17</a>] and [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref007" target="_blank">7</a>]. B. An example of an extended peptide-domain interaction. The Ark1 peptide is represented in stick and the SH3 domain from Abp1 uses space-filling. The red region is surface I and the blue region is surface II. W36 is represented as green and is on the boundary of the two surfaces. Adapted from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref018" target="_blank">18</a>] (pdb code 2rpn).</p

Example sequence conservation analysis for orthologs of Abp1 SH3 domain.

<p>The residues are colored according to the residue equivalence groups defined for entropy and PSSM calculations. The species names end with a number that refers to their taxonomic group (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.s003" target="_blank">S1 Fig</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.s001" target="_blank">S1 Table</a>). The SC value is calculated as (paralog entropy)/(ortholog entropy). A standard numbering system [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.ref046" target="_blank">46</a>] for the core 60 SH3 domain residues is indicated on the top row as well as the residue number in the full length <i>S.cerevisiae</i> protein (fifth row). The paralog entropy is calculated from an alignment of the 28 SH3 domains in <i>S.cerevisiae</i>.</p

SI and SII PSSM for yeast paralog alignment (28 domains) and example ortholog alignments for Fus1 (16 species) and Bud14 (29 species).

<p>Total occurrence for each amino acid group for each position is indicated and colored as yellow (low) to red (high). Residues are grouped into SI (left) and SII (right). Dark outlined regions indicate most common preference for the family (≥ 20 occurrences). Overall, for SI there is a family preference for aromatic residues except the less conserved positions 9, 52 and 53. Notable exceptions include Fus1 that has cysteines at positions 37 and 54 (which are usually in the FWYH group). For SII, there is a loose family preference for polar/acidic residues except at position 49 where hydrophobic residues are found. The extent of conservation in the orthlog alignments in SI and SII vary, with a much greater variation seen in SII PSSMs. PSSMs for all domains (showing both complete domain sequence and only surface I/II) can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193128#pone.0193128.s008" target="_blank">S4 File</a>.</p

The influence of intersecting complexities on sanitation solutions in challenging contexts

This record includes an extended abstract and MP4 presentation. Presented at the 42nd WEDC International Conference

Rapid reconstitution of ubiquitinated nucleosome using a non-denatured histone octamer ubiquitylation approach.

BACKGROUND: Histone ubiquitination modification is emerging as a critical epigenetic mechanism involved in a range of biological processes. In vitro reconstitution of ubiquitinated nucleosomes is pivotal for elucidating the influence of histone ubiquitination on chromatin dynamics. RESULTS: In this study, we introduce a Non-Denatured Histone Octamer Ubiquitylation (NDHOU) approach for generating ubiquitin or ubiquitin-like modified histone octamers. The method entails the co-expression and purification of histone octamers, followed by their chemical cross-linking to ubiquitin using 1,3-dibromoacetone. We demonstrate that nucleosomes reconstituted with these octamers display a high degree of homogeneity, rendering them highly compatible with in vitro biochemical assays. These ubiquitinated nucleosomes mimic physiological substrates in function and structure. Additionally, we have extended this method to cross-linking various histone octamers and three types of ubiquitin-like proteins. CONCLUSIONS: Overall, our findings offer an efficient strategy for producing ubiquitinated nucleosomes, advancing biochemical and biophysical studies in the field of chromatin biology