Lixin Zhang

Bio: Lixin Zhang is an academic researcher from East China University of Science and Technology. The author has contributed to research in topics: Cache & Thylakoid. The author has an hindex of 78, co-authored 659 publications receiving 23737 citations. Previous affiliations of Lixin Zhang include Chinese Academy of Sciences & University of Science and Technology of China.

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

Abstract: The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Chemical mapping of a single molecule by plasmon-enhanced Raman scattering

Abstract: Chemical mapping of a single molecule by optical means down to subnanometre resolution is achieved by spectrally matching the resonance of a nanocavity plasmon to the vibronic transitions of the molecules being studied, using tip-enhanced Raman scattering. Raman spectroscopy is widely used to identify molecules by detecting their signature molecular vibrations. The technology has been refined to be effective at the single-molecule level by making use of strong localized plasmonic fields that can enhance spectral signals. This study goes further, with the demonstration of a technique related to 'tip-enhanced Raman scattering' (TERS) that allows precise tuning of the plasmon resonance and Raman spectral imaging with a spatial resolution below 1 nm, resolving even the inner structure of a single molecule and its configuration on the surface. The technique opens a new path to photochemistry at the single-molecule level, offering the potential to design, control and engineer the functionality of molecules on demand. Visualizing individual molecules with chemical recognition is a longstanding target in catalysis, molecular nanotechnology and biotechnology. Molecular vibrations provide a valuable ‘fingerprint’ for such identification. Vibrational spectroscopy based on tip-enhanced Raman scattering allows us to access the spectral signals of molecular species very efficiently via the strong localized plasmonic fields produced at the tip apex1,2,3,4,5,6,7,8,9,10,11. However, the best spatial resolution of the tip-enhanced Raman scattering imaging is still limited to 3−15 nanometres5,12,13,14,15,16, which is not adequate for resolving a single molecule chemically. Here we demonstrate Raman spectral imaging with spatial resolution below one nanometre, resolving the inner structure and surface configuration of a single molecule. This is achieved by spectrally matching the resonance of the nanocavity plasmon to the molecular vibronic transitions, particularly the downward transition responsible for the emission of Raman photons. This matching is made possible by the extremely precise tuning capability provided by scanning tunnelling microscopy. Experimental evidence suggests that the highly confined and broadband nature of the nanocavity plasmon field in the tunnelling gap is essential for ultrahigh-resolution imaging through the generation of an efficient double-resonance enhancement for both Raman excitation and Raman emission. Our technique not only allows for chemical imaging at the single-molecule level, but also offers a new way to study the optical processes and photochemistry of a single molecule.

Mechanisms of antibiotic resistance

Abstract: Antibiotics represent one of the most successful forms of therapy in medicine. But the efficiency of antibiotics is compromised by a growing number of antibiotic-resistant pathogens. Antibiotic resistance, which is implicated in elevated morbidity and mortality rates as well as in the increased treatment costs, is considered to be one of the major global public health threats (www.who.int/drugresistance/en/) and the magnitude of the problem recently prompted a number of international and national bodies to take actions to protect the public (http://

Superconductivity Modulated by Quantum Size Effects

Abstract: We have fabricated ultrathin lead films on silicon substrates with atomic-scale control of the thickness over a macroscopic area. We observed oscillatory behavior of the superconducting transition temperature when the film thickness was increased by one atomic layer at a time. This oscillating behavior was shown to be a manifestation of the Fabry-Perot interference modes of electron de Broglie waves (quantum well states) in the films, which modulate the electron density of states near the Fermi level and the electron-phonon coupling, which are the two factors that control superconductivity transitions. This result suggests the possibility of modifying superconductivity and other physical properties of a thin film by exploiting well-controlled and thickness-dependent quantum size effects.

Molecular Networking as a Dereplication Strategy

Abstract: A major goal in natural product discovery programs is to rapidly dereplicate known entities from complex biological extracts We demonstrate here that molecular networking, an approach that organizes MS/MS data based on chemical similarity, is a powerful complement to traditional dereplication strategies Successful dereplication with molecular networks requires MS/MS spectra of the natural product mixture along with MS/MS spectra of known standards, synthetic compounds, or well-characterized organisms, preferably organized into robust databases This approach can accommodate different ionization platforms, enabling cross correlations of MS/MS data from ambient ionization, direct infusion, and LC-based methods Molecular networking not only dereplicates known molecules from complex mixtures, it also captures related analogues, a challenge for many other dereplication strategies To illustrate its utility as a dereplication tool, we apply mass spectrometry-based molecular networking to a diverse array of m

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

Abstract: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.

Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies.

Abstract: The recent advent of DNA sequencing technologies facilitates the use of genome sequencing data that provide means for more informative and precise classification and identification of members of the Bacteria and Archaea. Because the current species definition is based on the comparison of genome sequences between type and other strains in a given species, building a genome database with correct taxonomic information is of paramount need to enhance our efforts in exploring prokaryotic diversity and discovering novel species as well as for routine identifications. Here we introduce an integrated database, called EzBioCloud, that holds the taxonomic hierarchy of the Bacteria and Archaea, which is represented by quality-controlled 16S rRNA gene and genome sequences. Whole-genome assemblies in the NCBI Assembly Database were screened for low quality and subjected to a composite identification bioinformatics pipeline that employs gene-based searches followed by the calculation of average nucleotide identity. As a result, the database is made of 61 700 species/phylotypes, including 13 132 with validly published names, and 62 362 whole-genome assemblies that were identified taxonomically at the genus, species and subspecies levels. Genomic properties, such as genome size and DNA G+C content, and the occurrence in human microbiome data were calculated for each genus or higher taxa. This united database of taxonomy, 16S rRNA gene and genome sequences, with accompanying bioinformatics tools, should accelerate genome-based classification and identification of members of the Bacteria and Archaea. The database and related search tools are available at www.ezbiocloud.net/.