Wide dynamic range magnetic field cycler: Harnessing quantum control at low and high fields

We describe the construction of a fast field cycling device capable of sweeping a 4-order-of-magnitude range of magnetic fields, from ~1mT to 7T, in under 700ms. Central to this system is a high-speed sample shuttling mechanism between a superconducting magnet and a magnetic shield, with the capability to access arbitrary fields in between with high resolution. Our instrument serves as a versatile platform to harness the inherent dichotomy of spin dynamics on offer at low and high fields - in particular, the low anisotropy, fast spin manipulation, and rapid entanglement growth at low field as well as the long spin lifetimes, spin specific control, and efficient inductive measurement possible at high fields. Exploiting these complementary capabilities in a single device open up applications in a host of problems in quantum control, sensing, and information storage, besides in nuclear hypepolarization, relaxometry and imaging. In particular, in this paper, we focus on the ability of the device to enable low-field hyperpolarization of 13C nuclei in diamond via optically pumped electronic spins associated with Nitrogen Vacancy (NV) defect centers

ModBase, a database of annotated comparative protein structure models, and associated resources

ModBase (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by ModPipe, an automated modeling pipeline that relies primarily on Modeller for fold assignment, sequence–structure alignment, model building and model assessment (http://salilab.org/modeller/). ModBase currently contains 10 355 444 reliable models for domains in 2 421 920 unique protein sequences. ModBase allows users to update comparative models on demand, and request modeling of additional sequences through an interface to the ModWeb modeling server (http://salilab.org/modweb). ModBase models are available through the ModBase interface as well as the Protein Model Portal (http://www.proteinmodelportal.org/). Recently developed associated resources include the SALIGN server for multiple sequence and structure alignment (http://salilab.org/salign), the ModEval server for predicting the accuracy of protein structure models (http://salilab.org/modeval), the PCSS server for predicting which peptides bind to a given protein (http://salilab.org/pcss) and the FoXS server for calculating and fitting Small Angle X-ray Scattering profiles (http://salilab.org/foxs)

Collaborative annotation of genes and proteins between UniProtKB/Swiss-Prot and dictyBase

UniProtKB/Swiss-Prot, a curated protein database, and dictyBase, the Model Organism Database for Dictyostelium discoideum, have established a collaboration to improve data sharing. One of the major steps in this effort was the ‘Dicty annotation marathon’, a week-long exercise with 30 annotators aimed at achieving a major increase in the number of D. discoideum proteins represented in UniProtKB/Swiss-Prot. The marathon led to the annotation of over 1000 D. discoideum proteins in UniProtKB/Swiss-Prot. Concomitantly, there were a large number of updates in dictyBase concerning gene symbols, protein names and gene models. This exercise demonstrates how UniProtKB/Swiss-Prot can work in very close cooperation with model organism databases and how the annotation of proteins can be accelerated through those collaborations

Improving model construction of profile HMMs for remote homology detection through structural alignment

<p>Abstract</p> <p>Background</p> <p>Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addressing this important problem. pHMM packages present a relatively small computational cost, and perform particularly well at recognizing remote homologies. This raises the question of whether structural alignments could impact the performance of pHMMs trained from proteins in the <it>Twilight Zone</it>, as structural alignments are often more accurate than sequence alignments at identifying motifs and functional residues. Next, we assess the impact of using structural alignments in pHMM performance.</p> <p>Results</p> <p>We used the SCOP database to perform our experiments. Structural alignments were obtained using the 3DCOFFEE and MAMMOTH-mult tools; sequence alignments were obtained using CLUSTALW, TCOFFEE, MAFFT and PROBCONS. We performed leave-one-family-out cross-validation over super-families. Performance was evaluated through ROC curves and paired two tailed t-test.</p> <p>Conclusion</p> <p>We observed that pHMMs derived from structural alignments performed significantly better than pHMMs derived from sequence alignment in low-identity regions, mainly below 20%. We believe this is because structural alignment tools are better at focusing on the important patterns that are more often conserved through evolution, resulting in higher quality pHMMs. On the other hand, sensitivity of these tools is still quite low for these low-identity regions. Our results suggest a number of possible directions for improvements in this area.</p

Evaluation of the Sublingual Route for Administration of Influenza H5N1 Virosomes in Combination with the Bacterial Second Messenger c-di-GMP

Avian influenza A H5N1 is a virus with pandemic potential. Mucosal vaccines are attractive as they have the potential to block viruses at the site of entry, thereby preventing both disease and further transmission. The intranasal route is safe for the administration of seasonal live-attenuated influenza vaccines, but may be less suitable for administration of pandemic vaccines. Research into novel mucosal routes is therefore needed. In this study, a murine model was used to compare sublingual administration with intranasal and intramuscular administration of influenza H5N1 virosomes (2 µg haemagglutinin; HA) in combination with the mucosal adjuvant (3′,5′)-cyclic dimeric guanylic acid (c-di-GMP). We found that sublingual immunisation effectively induced local and systemic H5N1-specific humoral and cellular immune responses but that the magnitude of response was lower than after intranasal administration. However, both the mucosal routes were superior to intramuscular immunisation for induction of local humoral and systemic cellular immune responses including high frequencies of splenic H5N1-specific multifunctional (IL-2+TNF-α+) CD4+ T cells. The c-di-GMP adjuvanted vaccine elicited systemic haemagglutination inhibition (HI) antibody responses (geometric mean titres ≥40) both when administered sublingually, intranasally and inramuscularly. In addition, salivary HI antibodies were elicited by mucosal, but not intramuscular vaccination. We conclude that the sublingual route is an attractive alternative for administration of pandemic influenza vaccines

Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families

VLPs and particle strategies for cancer vaccines

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