Biomedical subjects

Chongle Pan

Publications and source records attributed to Chongle Pan.

10 recordsLinked to original sources

PubMed2024

Ammonia-oxidizing bacteria and archaea exhibit differential nitrogen source preferences.

Ammonia-oxidizing microorganisms (AOM) contribute to one of the largest nitrogen fluxes in the global nitrogen budget. Four distinct lineages of AOM: ammonia-oxidizing archaea (AOA), beta- and gamma-proteobacterial ammonia-oxidizing bacteria (β-AOB and γ-AOB) and complete ammonia oxidizers (comammox), are thought to compete for ammonia as their primary nitrogen substrate. In addition, many AOM species can utilize urea as an alternative energy and nitrogen source through hydrolysis to ammonia. How the coordination of ammonia and urea metabolism in AOM influences their ecology remains poorly understood. Here we use stable isotope tracing, kinetics and transcriptomics experiments to show that representatives of the AOM lineages employ distinct regulatory strategies for ammonia or urea utilization, thereby minimizing direct substrate competition. The tested AOA and comammox species preferentially used ammonia over urea, while β-AOB favoured urea utilization, repressed ammonia transport in the presence of urea and showed higher affinity for urea than for ammonia. Characterized γ-AOB co-utilized both substrates. These results reveal contrasting niche adaptation and coexistence patterns among the major AOM lineages.

Archaea↗

PubMed2006

ProRata: A quantitative proteomics program for accurate protein abundance ratio estimation with confidence interval evaluation.

A profile likelihood algorithm is proposed for quantitative shotgun proteomics to infer the abundance ratios of proteins from the abundance ratios of isotopically labeled peptides derived from proteolysis. Previously, we have shown that the estimation variability and bias of peptide abundance ratios can be predicted from their profile signal-to-noise ratios. Given multiple quantified peptides for a protein, the profile likelihood algorithm probabilistically weighs the peptide abundance ratios by their inferred estimation variability, accounts for their expected estimation bias, and suppresses contribution from outliers. This algorithm yields maximum likelihood point estimation and profile likelihood confidence interval estimation of protein abundance ratios. This point estimator is more accurate than an estimator based on the average of peptide abundance ratios. The confidence interval estimation provides an "error bar" for each protein abundance ratio that reflects its estimation precision and statistical uncertainty. The accuracy of the point estimation and the precision and confidence level of the interval estimation were benchmarked with standard mixtures of isotopically labeled proteomes. The profile likelihood algorithm was integrated into a quantitative proteomics program, called ProRata, freely available at www.MSProRata.org.

Algorithms↗

PubMed2006

Robust estimation of peptide abundance ratios and rigorous scoring of their variability and bias in quantitative shotgun proteomics.

The abundance ratio between the light and heavy isotopologues of an isotopically labeled peptide can be estimated from their selected ion chromatograms. However, quantitative shotgun proteomics measurements yield selected ion chromatograms at highly variable signal-to-noise ratios for tens of thousands of peptides. This challenge calls for algorithms that not only robustly estimate the abundance ratios of different peptides but also rigorously score each abundance ratio for the expected estimation bias and variability. Scoring of the abundance ratios, much like scoring of sequence assignment for tandem mass spectra by peptide identification algorithms, enables filtering of unreliable peptide quantification and use of formal statistical inference in the subsequent protein abundance ratio estimation. In this study, a parallel paired covariance algorithm is used for robust peak detection in selected ion chromatograms. A peak profile is generated for each peptide, which is a scatterplot of ion intensities measured for the two isotopologues within their chromatographic peaks. Principal component analysis of the peak profile is proposed to estimate the peptide abundance ratio and to score the estimation with the signal-to-noise ratio of the peak profile (profile signal-to-noise ratio). We demonstrate that the profile signal-to-noise ratio is inversely correlated with the variability and bias of peptide abundance ratio estimation.

Algorithms↗

PubMed2006

Efficient and specific trypsin digestion of microgram to nanogram quantities of proteins in organic-aqueous solvent systems.

Mass spectrometry-based identification of the components of multiprotein complexes often involves solution-phase proteolytic digestion of the complex. The affinity purification of individual protein complexes often yields nanogram to low-microgram amounts of protein, which poses several challenges for enzymatic digestion and protein identification. We tested different solvent systems to optimize trypsin digestions of samples containing limited amounts of protein for subsequent analysis by LC-MS-MS. Data collected from digestion of 10-, 2-, 1-, and 0.2-microg portions of a protein standard mixture indicated that an organic-aqueous solvent system containing 80% acetonitrile consistently provided the most complete digestion, producing more peptide identifications than the other solvent systems tested. For example, a 1-h digestion in 80% acetonitrile yielded over 52% more peptides than the overnight digestion of 1 microg of a protein mixture in purely aqueous buffer. This trend was also observed for peptides from digested ribosomal proteins isolated from Rhodopseudomonas palustris. In addition to improved digestion efficiency, the shorter digestion times possible with the organic solvent also improved trypsin specificity, resulting in smaller numbers of semitryptic peptides than an overnight digestion protocol using an aqueous solvent. The technique was also demonstrated for an affinity-isolated protein complex, GroEL. To our knowledge, this report is the first using mass spectrometry data to show a linkage between digestion solvent and trypsin specificity.

Acetonitriles↗

PubMed2005

Multipole-storage-assisted dissociation for the characterization of large proteins and simple protein mixtures by ESI-FTICR-MS.

In Fourier transform ion cyclotron resonance mass spectrometry, collisionally activated dissociation (CAD) typically is accomplished within the analyzer ion cell. An alternative approach of multipole-storage-assisted dissociation (MSAD) has previously been demonstrated by inducing collisional fragmentation in the external multipole that is usually employed for ion accumulation. To explore the utility of MSAD for interrogating intact proteins and simple protein mixtures in a multiplexed manner, we have investigated the means of controlling the collisional energy and the fragmentation pattern for this experimental approach. With protein samples in the low micromolar concentration range, the two major experimental parameters affecting MSAD in the hexapole region were found to be the dc offset voltage and accumulation time. While low-energy MSAD of intact proteins yields fragment ions similar to sustained off resonance irradiation collision-activated dissociation (SORI-CAD), high-energy MSAD induces sequential fragmentation for intact proteins to yield a rich variety of singly charged ions in the m/z 600-1200 Da region. Each of the seven proteins (Mr range of 8.5-116 kDa) examined in this study exhibited their own characteristic MSAD fragmentation pattern, which could be used as a signature of the presence of a given protein, even in a mixture. In addition, any MSAD fragment can be isolated and dissociated further by SORI-CAD in an MS3-type experiment inside the FTICR analyzer cell. This presents a novel way to interrogate the identities of these fragment ions as well as obtain amino acid sequence tag information that can be used to identify proteins from mixtures.

Amino Acid Sequence↗

PubMed2004

Structural rationalization of a large difference in RNA affinity despite a small difference in chemistry between two 2'-O-modified nucleic acid analogues.

Chemical modification of nucleic acids at the 2'-position of ribose has generated antisense oligonucleotides (AONs) with a range of desirable properties. Electron-withdrawing substituents such as 2'-O-[2-(methoxy)ethyl] (MOE) confer enhanced RNA affinity relative to that of DNA by conformationally preorganizing an AON for pairing with the RNA target and by improving backbone hydration. 2'-Substitution of the ribose has also been shown to increase nuclease resistance and cellular uptake via changes in lipophilicity. Interestingly, incorporation of either 2'-O-[2-(methylamino)-2-oxoethyl]- (NMA) or 2'-O-(N-methylcarbamate)-modified (NMC) residues into AONs has divergent effects on RNA affinity. Incorporation of 2'-O-NMA-T considerably improves RNA affinity while incorporation of 2'-O-NMC-T drastically reduces RNA affinity. Crystal structures at high resolution of A-form DNA duplexes containing either 2'-O-NMA-T or 2'-O-NMC-T shed light on the structural origins of the surprisingly large difference in stability given the relatively minor difference in chemistry between NMA and NMC. NMA substituents adopt an extended conformation and use either their carbonyl oxygen or amino nitrogen to trap water molecules between phosphate group and sugar. The conformational properties of NMA and the observed hydration patterns are reminiscent of those found in the structures of 2'-O-MOE-modified RNA. Conversely, the carbonyl oxygen of NMC and O2 of T are in close contact, providing evidence that an unfavorable electrostatic interaction and the absence of a stable water structure are the main reasons for the loss in thermodynamic stability as a result of incorporation of 2'-O-NMC-modified residues.

Biomimetic Materials↗

PubMed2004

A graph-theoretic approach for the separation of b and y ions in tandem mass spectra.

MOTIVATION: Ion-type identification is a fundamental problem in computational proteomics. Methods for accurate identification of ion types provide the basis for many mass spectrometry data interpretation problems, including (a) de novo sequencing, (b) identification of post-translational modifications and mutations and (c) validation of database search results. RESULTS: Here, we present a novel graph-theoretic approach for solving the problem of separating b ions from y ions in a set of tandem mass spectra. We represent each spectral peak as a node and consider two types of edges: type-1 edge connecting two peaks probably of the same ion types and type-2 edge connecting two peaks probably of different ion types. The problem of ion-separation is formulated and solved as a graph partition problem, which is to partition the graph into three subgraphs, representing b, y and others ions, respectively, through maximizing the total weight of type-1 edges while minimizing the total weight of type-2 edges within each partitioned subgraph. We have developed a dynamic programming algorithm for rigorously solving this graph partition problem and implemented it as a computer program PRIME (PaRtition of Ion types in tandem Mass spEctra). The tests on a large amount of simulated mass spectra and 19 sets of high-quality experimental Fourier transform ion cyclotron resonance tandem mass spectra indicate that an accuracy level of approximately 90% for the separation of b and y ions was achieved. AVAILABILITY: The executable code of PRIME is available upon request. CONTACT: xyn@bmb.uga.edu.

Algorithms↗

PubMed2004

Separation of ion types in tandem mass spectrometry data interpretation -- a graph-theoretic approach.

Mass spectrometry is one of the most popular analytical techniques for identification of individual proteins in a protein mixture, one of the basic problems in proteomics. It identifies a protein through identifying its unique mass spectral pattern. While the problem is theoretically solvable, it remains a challenging problem computationally. One of the key challenges comes from the difficulty in distinguishing the N- and C-terminus ions, mostly b- and y-ions respectively. In this paper, we present a graph algorithm for solving the problem of separating bfrom y-ions in a set of mass spectra. We represent each spectral peak as a node and consider two types of edges: a type-1 edge connects two peaks possibly of the same ion types and a type-2 edge connects two peaks possibly of different ion types, predicted based on local information. The ion-separation problem is then formulated and solved as a graph partition problem, which is to partition the graph into three subgraphs, namely b-, y-ions and others respectively, so to maximize the total weight of type-1 edges while minimizing the total weight of type-2 edges within each subgraph. We have developed a dynamic programming algorithm for rigorously solving this graph partition problem and implemented it as a computer program PRIME. We have tested PRIME on 18 data sets of high accurate FT-ICR tandem mass spectra and found that it achieved ~90% accuracy for separation of b- and y- ions.

Algorithms↗

PubMed2004

Mass spectrometric approaches for characterizing bacterial proteomes.

The emergence of advanced liquid chromatography mass spectrometry technologies for characterizing very complex mixtures of proteins has greatly propelled the field of proteomics, the goal of which is the simultaneous examination of all the proteins expressed by an organism. This research area represents a paradigm shift in molecular biology by attempting to provide a top-down qualitative and quantitative view of all the proteins (including their modifications and interactions) that are essential for an organism's life cycle, rather than targeting a particular protein family. This level of global protein information about an organism such as a bacterium can be combined with genomic and metabolomic data to enable a systems biology approach for understanding how these organisms live and function.

Bacterial Proteins↗

PubMed2002

Selenium-assisted nucleic acid crystallography: use of phosphoroselenoates for MAD phasing of a DNA structure.

The combination of synchrotron radiation and a variety of atoms or ions (either covalently attached to the biomolecule prior to crystallization or soaked into crystals) that serve as anomalous scatterers constitutes a powerful tool in the X-ray crystallographer's repertoire of structure determination techniques. Phosphoroselenoates in which one of the nonbridging phosphate oxygens in the backbone is replaced by selenium offer a simplified means for introducing an anomalous scatterer into oligonucleotides by conventional solid-phase synthesis. Unlike other methods that are used to derivatize DNA or RNA by covalent attachment of a heavy atom (i.e., bromine at the C5 position of pyrimidines), tedious synthesis of specialized nucleosides is not required. Introduction of selenium is readily accomplished in solid-phase oligonucleotide synthesis by replacing the standard oxidation agent with a solution of potassium selenocyanide. This results in a diastereomeric mixture of phosphoroselenoates that can be separated by strong anion-exchange HPLC. As a test case, all 10 DNA hexamers of the sequence CGCGCG containing a single phosphoroselenoate linkage (PSe) were prepared. Crystals were grown for a subset of them, and the structure of [d(C(PSe)GCGCG)](2) was determined by the multiwavelength anomalous dispersion technique and refined to 1.1 A resolution.

Crystallization↗