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High purity and ultrafine DAAF (u-DAAF) is an emerging insensitive charge in initiators. Although there are many ways to obtain u-DAAF, developing a preparation method with stable operation, accurate control, good quality consistency, equipment miniaturization, and minimum manpower is an inevitable requirement to adapt to the current social technology development trend. Here reported is the microfluidic preparation of u-DAAF with tunable particle size by a passive swirling microreactor. Under the guidance of recrystallization growth kinetics and mixing behavior of fluids in the swirling microreactor, the key parameters (liquid flow rate, explosive concentration and crystallization temperature) were screened and optimized through screening experiments. Under the condition that no surfactant is added and only experimental parameters are controlled, the particle size of recrystallized DAAF can be adjusted from 98 nm to 785 nm, and the corresponding specific surface area is 8.45 m2·g−1 to 1.33 m2·g−1. In addition, the preparation method has good batch stability, high yield (90.8%–92.6%) and high purity (99.0%–99.4%), indicating a high practical application potential. Electric explosion derived flyer initiation tests demonstrate that the u-DAAF shows an initiation sensitivity much lower than that of the raw DAAF, and comparable to that of the refined DAAF by conventional spraying crystallization method. This study provides an efficient method to fabricate u-DAAF with narrow particle size distribution and high reproducibility as well as a theoretical reference for fabrication of other ultrafine explosives.

ABSTRACT Kaposi’s sarcoma-associated herpesvirus (KSHV) encodes six highly conserved core replication proteins essential for the viral lytic DNA synthesis, including ORF6 (single-stranded DNA-binding protein), ORF9 (DNA polymerase), ORF40/41 (primase-associated factor), ORF44 (helicase), ORF56 (primase), and ORF59 (polymerase processivity factor). Since the protein-protein interactions among KSHV core replication proteins are largely unknown, this study aimed to decipher their interrelationships. Herein, we propose a protein-protein interaction network of these six core replication proteins according to the results obtained from confocal fluorescence microscopy, coimmunoprecipitation, and mammalian two-hybrid (GAL4/VP16) reporter assays. In this interaction network, ORF40/41 plays a central role in the connection of different replication subcomplexes. In addition to the well-conserved helicase-primase subcomplex (consisting of ORF44, ORF56, and ORF40/41) and the replisome subcomplex (consisting of ORF9 and ORF59), our data also suggest that several discrete, stable subcomplexes exist in the cell nucleus. Among these replication subcomplexes in the nucleus, the tetrameric subcomplex composed of ORF44, ORF56, ORF40/41, and ORF6 exhibited the ability to trigger a DNA damage response. By using an established GAL4/VP16-based reporter system and confocal fluorescence microscopy, we additionally found that the heat shock protein 90 (Hsp90) inhibitor, radicicol, significantly inhibited the formation of both the helicase-primase subcomplex and the replisome subcomplex in a dose-dependent manner. Collectively, these data not only provide further insights into the interaction and assembly of KSHV-encoded core replication proteins but also suggest a critical role of Hsp90 in assisting the construction of the viral core replication machinery. IMPORTANCE Eukaryotic DNA replication is a highly regulated process that requires multiple replication enzymes assembled onto DNA replication origins. Due to the complexity of the cell’s DNA replication machinery, most of what we know about cellular DNA replication has come from the study of viral systems. Herein, we focus our study on the assembly of the Kaposi’s sarcoma-associated herpesvirus core replication complex and propose a pairwise protein-protein interaction network of six highly conserved viral core replication proteins. A detailed understanding of the interaction and assembly of the viral core replication proteins may provide opportunities to develop new strategies against viral propagation.

Cross-linking mass spectrometry can provide insights into protein structures and interactions but its scope depends on the reactivity of the cross-linker. Here, the authors develop Arg-Arg and Lys-Arg cross-linkers, which provide structural information elusive to the widely used Lys-Lys cross-linkers.

The identification of cross-linked peptides at a proteome scale for interactome analyses represents a complex challenge. Here the authors report an efficient and reliable search engine pLink 2 for proteome-scale cross-linking mass spectrometry analyses, and demonstrate how to systematically evaluate the credibility of search engines.

Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

To improve chemical cross-linking of proteins coupled with mass spectrometry (CXMS), we developed a lysine-targeted enrichable cross-linker containing a biotin tag for affinity purification, a chemical cleavage site to separate cross-linked peptides away from biotin after enrichment, and a spacer arm that can be labeled with stable isotopes for quantitation. By locating the flexible proteins on the surface of 70S ribosome, we show that this trifunctional cross-linker is effective at attaining structural information not easily attainable by crystallography and electron microscopy. From a crude Rrp46 immunoprecipitate, it helped identify two direct binding partners of Rrp46 and 15 protein-protein interactions (PPIs) among the co-immunoprecipitated exosome subunits. Applying it to E. coli and C. elegans lysates, we identified 3130 and 893 inter-linked lysine pairs, representing 677 and 121 PPIs. Using a quantitative CXMS workflow we demonstrate that it can reveal changes in the reactivity of lysine residues due to protein-nucleic acid interaction.

Motivation: Proteogenomics has been well accepted as a tool to discover novel genes. In most conventional proteogenomic studies, a global false discovery rate is used to filter out false positives for identifying credible novel peptides. However, it has been found that the actual level of false positives in novel peptides is often out of control and behaves differently for different genomes. Results: To quantitatively model this problem, we theoretically analyze the subgroup false discovery rates of annotated and novel peptides. Our analysis shows that the annotation completeness ratio of a genome is the dominant factor influencing the subgroup FDR of novel peptides. Experimental results on two real datasets of Escherichia coli and Mycobacterium tuberculosis support our conjecture. [ABSTRACT FROM AUTHOR]

Background: Tandem mass spectrometry-based database searching has become an important technology for peptide and protein identification. One of the key challenges in database searching is the remarkable increase in computational demand, brought about by the expansion of protein databases, semi- or non-specific enzymatic digestion, post-translational modifications and other factors. Some software tools choose peptide indexing to accelerate processing. However, peptide indexing requires a large amount of time and space for construction, especially for the non-specific digestion. Additionally, it is not flexible to use. Results: We developed an algorithm based on the longest common prefix (ABLCP) to efficiently organize a protein sequence database. The longest common prefix is a data structure that is always coupled to the suffix array. It eliminates redundant candidate peptides in databases and reduces the corresponding peptide-spectrum matching times, thereby decreasing the identification time. This algorithm is based on the property of the longest common prefix. Even enzymatic digestion poses a challenge to this property, but some adjustments can be made to this algorithm to ensure that no candidate peptides are omitted. Compared with peptide indexing, ABLCP requires much less time and space for construction and is subject to fewer restrictions. Conclusions: The ABLCP algorithm can help to improve data analysis efficiency. A software tool implementing this algorithm is available at http://pfind.ict.ac.cn/pfind2dot5/index.htm. [ABSTRACT FROM AUTHOR]

Background: Peptide identification via tandem mass spectrometry is the basic task of current proteomics research. Due to the complexity of mass spectra, the majority of mass spectra cannot be interpreted at present. The existence of unexpected or unknown protein post-translational modifications is a major reason. Results: This paper describes an efficient and sequence database-independent approach to detecting abundant post-translational modifications in high-accuracy peptide mass spectra. The approach is based on the observation that the spectra of a modified peptide and its unmodified counterpart are correlated with each other in their peptide masses and retention time. Frequently occurring peptide mass differences in a data set imply possible modifications, while small and consistent retention time differences provide orthogonal supporting evidence. We propose to use a bivariate Gaussian mixture model to discriminate modification-related spectral pairs from random ones. Due to the use of two-dimensional information, accurate modification masses and confident spectral pairs can be determined as well as the quantitative influences of modifications on peptide retention time. Conclusion: Experiments on two glycoprotein data sets demonstrate that our method can effectively detect abundant modifications and spectral pairs. By including the discovered modifications into database search or by propagating peptide assignments between paired spectra, an average of 10% more spectra are interpreted. [ABSTRACT FROM AUTHOR]

Scalability considerations drive the evolution of switch design from output queueing to input queueing and further to combined input and crosspoint queueing (CICQ). However, CICQ switches with credit-based flow control face new challenges of scalability and predictability. In this paper, we propose a novel approach of rate-based smoothed switching, and design a CICQ switch called the smoothed buffered crossbar or sBUX. First, the concept of smoothness is developed from two complementary perspectives of covering and spacing, which, commonly known as fairness and jitter, are unified in the same model. Second, a smoothed multiplexer sMUX is designed that allocates bandwidth among competing flows sharing a link and guarantees almost ideal smoothness for each flow. Third, the buffered crossbar sBUX is designed that uses the scheduler sMUX at each input and output, and a two-cell buffer at each crosspoint. It is proved that sBUX guarantees 100% throughput for real-time services and almost ideal smoothness for each flow. Fourth, an on-line bandwidth regulator is designed that periodically estimates bandwidth demand and generates admissible allocations, which enables sBUX to support best-effort services. Simulation shows almost 100% throughput and multi-microsecond average delay. In particular, neither credit-based flow control nor speedup is used, and arbitrary fabric-internal latency is allowed between line cards and the switch core, simplifying the switch implementation. [ABSTRACT FROM AUTHOR]

Motivation: Identification of post-translationally modified proteins has become one of the central issues of current proteomics. Spectral library search is a new and promising computational approach to mass spectrometry-based protein identification. However, its potential in identification of unanticipated post-translational modifications has rarely been explored. The existing spectral library search tools are designed to match the query spectrum to the reference library spectra with the same peptide mass. Thus, spectra of peptides with unanticipated modifications cannot be identified. [ABSTRACT FROM PUBLISHER]

Motivation: RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is proved to be NP-hard. Due to kinetic reasons the real RNA secondary structure often has local instead of global minimum free energy. This implies that we may improve the performance of RNA secondary structure prediction by taking kinetics into account and minimize free energy in a local area. Result: we propose a novel algorithm named FlexStem to predict RNA secondary structures with pseudoknots. Still based on MFE criterion, FlexStem adopts comprehensive energy models that allow complex pseudoknots. Unlike classical thermodynamic methods, our approach aims to simulate the RNA folding process by successive addition of maximal stems, reducing the search space while maintaining or even improving the prediction accuracy. This reduced space is constructed by our maximal stem strategy and stem-adding rule induced from elaborate statistical experiments on real RNA secondary structures. The strategy and the rule also reflect the folding characteristic of RNA from a new angle and help compensate for the deficiency of merely relying on MFE in RNA structure prediction. We validate FlexStem by applying it to tRNAs, 5SrRNAs and a large number of pseudoknotted structures and compare it with the well-known algorithms such as RNAfold, PKNOTS, PknotsRG, HotKnots and ILM according to their overall sensitivities and specificities, as well as positive and negative controls on pseudoknots. The results show that FlexStem significantly increases the prediction accuracy through its local search strategy. Availability: Software is available at http://pfind.ict.ac.cn/FlexStem/ Contact: xchen@jdl.ac.cn; wgao@pku.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Chemical cross-linking coupled with mass spectroscopy (CXMS) provides proximity information for the cross-linked residues and is used increasingly for modeling protein structures. However, experimentally identified cross-links are sometimes incompatible with the known structure of a protein, as the distance calculated between the cross-linked residues far exceeds the maximum length of the cross-linker. The discrepancies may persist even after eliminating potentially false cross-links and excluding intermolecular ones. Thus the "overlength" cross-links may arise from alternative excited-state conformation of the protein. Here we present a method and associated software DynaXL for visualizing the ensemble structures of multidomain proteins based on intramolecular cross-links identified by mass spectrometry with high confidence. Representing the cross-linkers and cross-linking reactions explicitly, we show that the protein excited-state structure can be modeled with as few as two over-length cross-links. We demonstrate the generality of our method with three systems: calmodulin, enzyme I, and glutamine-binding protein, and we show that these proteins alternate between different conformations for interacting with other proteins and ligands. Taken together, the over-length chemical cross-links contain valuable information about protein dynamics, and our findings here illustrate the relationship between dynamic domain movement and protein function. [ABSTRACT FROM AUTHOR]