We investigate the pressure-induced structural changes in the mature human immunodeficiency virus type 1 protease dimer, using residual dipolar coupling (RDC) measurements in a weakly oriented solution. 1DNH RDCs were measured under high-pressure conditions for an inhibitor-free PR and an inhibitor-bound complex, as well as for an inhibitor-free multidrug resistant protease bearing 20 mutations (PR20). While PR20 and the inhibitor-bound PR were little affected by pressure, inhibitor-free PR showed significant differences in the RDCs measured at 600 bar compared with 1 bar. The structural basis of such changes was investigated by MD simulations using the experimental RDC restraints, revealing substantial conformational perturbations, specifically a partial opening of the flaps and the penetration of water molecules into the hydrophobic core of the subunits at high pressure. This study highlights the exquisite sensitivity of RDCs to pressure-induced conformational changes and illustrates how RDCs combined with MD simulations can be used to determine the structural properties of metastable intermediate states on the folding energy landscape. Proteins 2015; 83:2117–2123. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a “top-down” temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche− rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model.

Preprints called on to support controversial talks

Nature 526, 7574 (2015). doi:10.1038/526479f

Author: Rachel Becker

Scientists on social media grapple with the idea of posting preprints of provocative research presented at meetings.

Drawing a random variate from a given binomial distribution B(n, p) is an important subroutine in many large-scale simulations. The naive algorithm takes \(\mathcal {O}(n)\) time w.h.p. in the WordRAM model, which is too slow in many settings, though to its credit, it does not suffer from precision loss. The problem of sampling from a binomial distribution in sublinear time has been extensively studied and implemented in such packages as R [22] and the GNU Scientific Library  [11], however, all previous sublinear-time algorithms involve precision loss, which introduces artifacts such as discontinuities into the sampling. In this paper, we present the first algorithm, to the best of our knowledge, that samples binomial distributions in sublinear time with no precision loss. We assume that each bit of p can be obtained in \(\mathcal {O}(1)\) time.

We present a liquid chromatography–mass spectrometry (LC-MS)-based method for comprehensive quantitative identification of post-transcriptional modifications (PTMs) of RNA. We incorporated an in vitro-transcribed, heavy isotope-labeled reference RNA into a sample RNA solution, digested the mixture with a number of RNases and detected the post-transcriptionally modified oligonucleotides quantitatively based on shifts in retention time and the MS signal in subsequent LC-MS. This allowed the determination and quantitation of all PTMs in Schizosaccharomyces pombe ribosomal (r)RNAs and generated the first complete PTM maps of eukaryotic rRNAs at single-nucleotide resolution. There were 122 modified sites, most of which appear to locate at the interface of ribosomal subunits where translation takes place. We also identified PTMs at specific locations in rRNAs that were altered in response to growth conditions of yeast cells, suggesting that the cells coordinately regulate the modification levels of RNA.

We developed an innovative hybrid sequencing approach, IDP-fusion, to detect fusion genes, determine fusion sites and identify and quantify fusion isoforms. IDP-fusion is the first method to study gene fusion events by integrating Third Generation Sequencing long reads and Second Generation Sequencing short reads. We applied IDP-fusion to PacBio data and Illumina data from the MCF-7 breast cancer cells. Compared with the existing tools, IDP-fusion detects fusion genes at higher precision and a very low false positive rate. The results show that IDP-fusion will be useful for unraveling the complexity of multiple fusion splices and fusion isoforms within tumorigenesis-relevant fusion genes.

Rapid characterization of unknown biological samples is under the focus of many current studies. Here we report a method for screening of biological samples by optical mapping of their DNA. We use a novel, one-step chemo-enzymatic reaction to covalently bind fluorophores to DNA at the four-base recognition sites of a DNA methyltransferase. Due to the diffraction limit of light, the dense distribution of labels results in a continuous fluorescent signal along the DNA. The amplitude modulations (AM) of the fluorescence intensity along the stretched DNA molecules exhibit a unique molecular fingerprint that can be used for identification. We show that this labelling scheme is highly informative, allowing accurate genotyping. We demonstrate the method by labelling the genomes of and T7 bacteriophages, resulting in a consistent, unique AM profile for each genome. These profiles are also successfully used for identification of the phages from a background phage library. Our method may provide a facile route for screening and typing of various organisms and has potential applications in metagenomics studies of various ecosystems.

The CRISPR system has become a powerful biological tool with a wide range of applications. However, improving targeting specificity and accurately predicting potential off-targets remains a significant goal. Here, we introduce a web-based CRISPR/Cas9 Off-target Prediction and Identification Tool (CROP-IT) that performs improved off-target binding and cleavage site predictions. Unlike existing prediction programs that solely use DNA sequence information; CROP-IT integrates whole genome level biological information from existing Cas9 binding and cleavage data sets. Utilizing whole-genome chromatin state information from 125 human cell types further enhances its computational prediction power. Comparative analyses on experimentally validated datasets show that CROP-IT outperforms existing computational algorithms in predicting both Cas9 binding as well as cleavage sites. With a user-friendly web-interface, CROP-IT outputs scored and ranked list of potential off-targets that enables improved guide RNA design and more accurate prediction of Cas9 binding or cleavage sites.

Binding of transcription factors to DNA is one of the keystones of gene regulation. The existence of statistical dependencies between binding site positions is widely accepted, while their relevance for computational predictions has been debated. Building probabilistic models of binding sites that may capture dependencies is still challenging, since the most successful motif discovery approaches require numerical optimization techniques, which are not suited for selecting dependency structures. To overcome this issue, we propose sparse local inhomogeneous mixture (Slim) models that combine putative dependency structures in a weighted manner allowing for numerical optimization of dependency structure and model parameters simultaneously. We find that Slim models yield a substantially better prediction performance than previous models on genomic context protein binding microarray data sets and on ChIP-seq data sets. To elucidate the reasons for the improved performance, we develop dependency logos, which allow for visual inspection of dependency structures within binding sites. We find that the dependency structures discovered by Slim models are highly diverse and highly transcription factor-specific, which emphasizes the need for flexible dependency models. The observed dependency structures range from broad heterogeneities to sparse dependencies between neighboring and non-neighboring binding site positions.

Genetic therapy holds great promise for the treatment of inherited or acquired genetic diseases; however, its breakthrough is hampered by the lack of suitable gene delivery systems. Dumbbell-shaped DNA minimal vectors represent an attractive, safe alternative to the commonly used viral vectors which are fraught with risk, but dumbbell generation appears to be costly and time-consuming. We developed a new PCR-based method for dumbbell production which comprises only two steps. First, PCR amplification of the therapeutic expression cassette using chemically modified primers to form a ready-to-ligate DNA structure; and second, a highly efficient intramolecular ligation reaction. Compared with conventional strategies, the new method produces dumbbell vectors more rapidly, with higher yields and purity, and at lower costs. In addition, such produced small hairpin RNA expressing dumbbells triggered superior target gene knockdown compared with conventionally produced dumbbells or plasmids. Our novel method is suitable for large-scale dumbbell production and can facilitate clinical applications of this vector system.

Intrinsically disordered proteins and regions (IDPs and IDRs) lack stable 3D structure under physiological conditions in-vitro, are common in eukaryotes, and facilitate interactions with RNA, DNA and proteins. Current methods for prediction of IDPs and IDRs do not provide insights into their functions, except for a handful of methods that address predictions of protein-binding regions. We report first-of-its-kind computational method DisoRDPbind for high-throughput prediction of RNA, DNA and protein binding residues located in IDRs from protein sequences. DisoRDPbind is implemented using a runtime-efficient multi-layered design that utilizes information extracted from physiochemical properties of amino acids, sequence complexity, putative secondary structure and disorder and sequence alignment. Empirical tests demonstrate that it provides accurate predictions that are competitive with other predictors of disorder-mediated protein binding regions and complementary to the methods that predict RNA- and DNA-binding residues annotated based on crystal structures. Application in Homo sapiens, Mus musculus, Caenorhabditis elegans and Drosophila melanogaster proteomes reveals that RNA- and DNA-binding proteins predicted by DisoRDPbind complement and overlap with the corresponding known binding proteins collected from several sources. Also, the number of the putative protein-binding regions predicted with DisoRDPbind correlates with the promiscuity of proteins in the corresponding protein–protein interaction networks. Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/

RNA-seq is a key technology for understanding the biology of the cell because of its ability to profile transcriptional and post-transcriptional regulation at single nucleotide resolutions. Compared to DNA sequencing alignment algorithms, RNA-seq alignment algorithms have a diminished ability to accurately detect and map base pair substitutions, gaps, discordant pairs and repetitive regions. These shortcomings adversely affect experiments that require a high degree of accuracy, notably the ability to detect RNA editing. We have developed RNASequel, a software package that runs as a post-processing step in conjunction with an RNA-seq aligner and systematically corrects common alignment artifacts. Its key innovations are a two-pass splice junction alignment system that includes de novo splice junctions and the use of an empirically determined estimate of the fragment size distribution when resolving read pairs. We demonstrate that RNASequel produces improved alignments when used in conjunction with STAR or Tophat2 using two simulated datasets. We then show that RNASequel improves the identification of adenosine to inosine RNA editing sites on biological datasets. This software will be useful in applications requiring the accurate identification of variants in RNA sequencing data, the discovery of RNA editing sites and the analysis of alternative splicing.

Adenine at position 752 in a loop of helix 35 from positions 745 to 752 in domain II of 23S rRNA is involved in binding to the ribosome of telithromycin (TEL), a member of ketolides. Methylation of guanine at position 748 by the intrinsic methyltransferase RlmAII enhances binding of telithromycin (TEL) to A752 in Streptococcus pneumoniae. We have found that another intrinsic methylation of the adjacent uridine at position 747 enhances G748 methylation by RlmAII, rendering TEL susceptibility. U747 and another nucleotide, U1939, were methylated by the dual-specific methyltransferase RlmCD encoded by SP_1029 in S. pneumoniae. Inactivation of RlmCD reduced N1-methylated level of G748 by RlmAII in vivo, leading to TEL resistance when the nucleotide A2058, located in domain V of 23S rRNA, was dimethylated by the dimethyltransferase Erm(B). In vitro methylation of rRNA showed that RlmAII activity was significantly enhanced by RlmCD-mediated pre-methylation of 23S rRNA. These results suggest that RlmCD-mediated U747 methylation promotes efficient G748 methylation by RlmAII, thereby facilitating TEL binding to the ribosome.

The Sm proteins are loaded on snRNAs by the SMN complex, but how snRNP-specific proteins are assembled remains poorly characterized. U4 snRNP and box C/D snoRNPs have structural similarities. They both contain the 15.5K and proteins with NOP domains (PRP31 for U4, NOP56/58 for snoRNPs). Biogenesis of box C/D snoRNPs involves NUFIP and the HSP90/R2TP chaperone system and here, we explore the function of this machinery in U4 RNP assembly. We show that yeast Prp31 interacts with several components of the NUFIP/R2TP machinery, and that these interactions are separable from each other. In human cells, PRP31 mutants that fail to stably associate with U4 snRNA still interact with components of the NUFIP/R2TP system, indicating that these interactions precede binding of PRP31 to U4 snRNA. Knock-down of NUFIP leads to mislocalization of PRP31 and decreased association with U4. Moreover, NUFIP is associated with the SMN complex through direct interactions with Gemin3 and Gemin6. Altogether, our data suggest a model in which the NUFIP/R2TP system is connected with the SMN complex and facilitates assembly of U4 snRNP-specific proteins.

In recent times, high-throughput screening analyses have broadly defined the RNA cellular targets of TDP-43, a nuclear factor involved in neurodegeneration. A common outcome of all these studies is that changing the expression levels of this protein can alter the expression of several hundred RNAs within cells. What still remains to be clarified is which changes represent direct cellular targets of TDP-43 or just secondary variations due to the general role played by this protein in RNA metabolism. Using an HTS-based splicing junction analysis we identified at least six bona fide splicing events that are consistent with being controlled by TDP-43. Validation of the data, both in neuronal and non-neuronal cell lines demonstrated that TDP-43 substantially alters the levels of isoform expression in four genes potentially important for neuropathology: MADD/IG20, STAG2, FNIP1 and BRD8. For MADD/IG20 and STAG2, these changes could also be confirmed at the protein level. These alterations were also observed in a cellular model that successfully mimics TDP-43 loss of function effects following its aggregation. Most importantly, our study demonstrates that cell cycle alterations induced by TDP-43 knockdown can be recovered by restoring the STAG2, an important component of the cohesin complex, normal splicing profile.

PSF (a.k.a. SFPQ) is a ubiquitously expressed, essential nuclear protein with important roles in DNA damage repair and RNA biogenesis. In stimulated T cells, PSF binds to and suppresses the inclusion of CD45 exon 4 in the final mRNA; however, in resting cells, TRAP150 binds PSF and prevents access to the CD45 RNA, though the mechanism for this inhibition has remained unclear. Here, we show that TRAP150 binds a region encompassing the RNA recognition motifs (RRMs) of PSF using a previously uncharacterized, 70 residue region we have termed the PSF-interacting domain (PID). TRAP150's PID directly inhibits the interaction of PSF RRMs with RNA, which is mediated through RRM2. However, interaction of PSF with TRAP150 does not appear to inhibit the dimerization of PSF with other Drosophila Behavior, Human Splicing (DBHS) proteins, which is also dependent on RRM2. Finally, we use RASL-Seq to identify ~40 T cell splicing events sensitive to PSF knockdown, and show that for the majority of these, PSF's effect is antagonized by TRAP150. Together these data suggest a model in which TRAP150 interacts with dimeric PSF to block access of RNA to RRM2, thereby regulating the activity of PSF toward a broad set of splicing events in T cells.

Despite conservation of the signal recognition particle (SRP) from bacteria to man, computational approaches have failed to identify SRP components from genomes of many lower eukaryotes, raising the possibility that they have been lost or altered in those lineages. We report purification and analysis of SRP in the human pathogen Cryptococcus neoformans, providing the first description of SRP in basidiomycetous yeast. The C. neoformans SRP RNA displays a predicted structure in which the universally conserved helix 8 contains an unprecedented stem-loop insertion. Guided by this sequence, we computationally identified 152 SRP RNAs throughout the phylum Basidiomycota. This analysis revealed additional helix 8 alterations including single and double stem-loop insertions as well as loop diminutions affecting RNA structural elements that are otherwise conserved from bacteria to man. Strikingly, these SRP RNA features in Basidiomycota are accompanied by phylum-specific alterations in the RNA-binding domain of Srp54, the SRP protein subunit that directly interacts with helix 8. Our findings reveal unexpected fungal SRP diversity and suggest coevolution of the two most conserved SRP features—SRP RNA helix 8 and Srp54—in basidiomycetes. Because members of this phylum include important human and plant pathogens, these noncanonical features provide new targets for antifungal compound development.

Selenocysteine (Sec), the 21st amino acid in translation, uses its specific tRNA (tRNASec) to recognize the UGA codon. The Sec-specific elongation factor SelB brings the selenocysteinyl-tRNASec (Sec-tRNASec) to the ribosome, dependent on both an in-frame UGA and a Sec-insertion sequence (SECIS) in the mRNA. The bacterial SelB binds mRNA through its C-terminal region, for which crystal structures have been reported. In this study, we determined the crystal structure of the full-length SelB from the bacterium Aquifex aeolicus, in complex with a GTP analog, at 3.2-Å resolution. SelB consists of three EF-Tu-like domains (D1–3), followed by four winged-helix domains (WHD1–4). The spacer region, connecting the N- and C-terminal halves, fixes the position of WHD1 relative to D3. The binding site for the Sec moiety of Sec-tRNASec is located on the interface between D1 and D2, where a cysteine molecule from the crystallization solution is coordinated by Arg residues, which may mimic Sec binding. The Sec-binding site is smaller and more exposed than the corresponding site of EF-Tu. Complex models of Sec-tRNASec, SECIS RNA, and the 70S ribosome suggest that the unique secondary structure of tRNASec allows SelB to specifically recognize tRNASec and characteristically place it at the ribosomal A-site.

Rad6 is a yeast E2 ubiquitin conjugating enzyme that monoubiquitinates histone H2B in conjunction with the E3, Bre1, but can non-specifically modify histones on its own. We determined the crystal structure of a Rad6~Ub thioester mimic, which revealed a network of interactions in the crystal in which the ubiquitin in one conjugate contacts Rad6 in another. The region of Rad6 contacted is located on the distal face of Rad6 opposite the active site, but differs from the canonical E2 backside that mediates free ubiquitin binding and polyubiquitination activity in other E2 enzymes. We find that free ubiquitin interacts weakly with both non-canonical and canonical backside residues of Rad6 and that mutations of non-canonical residues have deleterious effects on Rad6 activity comparable to those observed to mutations in the canonical E2 backside. The effect of non-canonical backside mutations is similar in the presence and absence of Bre1, indicating that contacts with non-canonical backside residues govern the intrinsic activity of Rad6. Our findings shed light on the determinants of intrinsic Rad6 activity and reveal new ways in which contacts with an E2 backside can regulate ubiquitin conjugating activity.