Proteomic Interrogation of Human Chromatin

Chromatin proteins provide a scaffold for DNA packaging and a basis for epigenetic regulation and genomic maintenance. Despite understanding its functional roles, mapping the chromatin proteome (i.e. the “Chromatome”) is still a continuing process. Here, we assess the biological specificity and proteomic extent of three distinct chromatin preparations by identifying proteins in selected chromatin-enriched fractions using mass spectrometry-based proteomics. These experiments allowed us to produce a chromatin catalog, including several proteins ranging from highly abundant histone proteins to less abundant members of different chromatin machinery complexes. Using a Normalized Spectral Abundance Factor approach, we quantified relative abundances of the proteins across the chromatin enriched fractions giving a glimpse into their chromosomal abundance. The large-scale data sets also allowed for the discovery of a variety of novel post-translational modifications on the identified chromatin proteins. With these comparisons, we find one of the probed methods to be qualitatively superior in specificity for chromatin proteins, but inferior in proteomic extent, evidencing a compromise that must be made between biological specificity and broadness of characterization. Additionally, we attempt to identify proteins in eu- and heterochromatin, verifying the enrichments by characterizing the post-translational modifications detected on histone proteins from these chromatin regions. In summary, our results provide insights into the value of different methods to extract chromatin-associated proteins and provide starting points to study the factors that may be involved in directing gene expression and other chromatin-related processes

Biomass and Natural Gas to Liquid Transportation Fuels: Process Synthesis, Global Optimization, and Topology Analysis

An optimization-based process synthesis framework is proposed for the thermochemical conversion of biomass and natural gas to liquid fuels (BGTL). Hydrocarbons are produced from synthesis gas either directly via Fischer–Tropsch synthesis or indirectly via catalytic conversion of methanol over ZSM-5. Different conversion technologies are investigated to examine their economic effects on BGTL refineries that produce gasoline, diesel, and kerosene. The process synthesis framework includes simultaneous heat, power, and water integration and utilizes a rigorous deterministic global optimization strategy to mathematically guarantee the minimal cost of the BGTL refineries. The refineries have at least 50% less life-cycle CO₂ emissions than a standard petroleum-based refinery. Forty-eight case studies are presented to determine the effect of refinery capacity, liquid fuel composition, and biomass feedstock on the overall cost, topological design, material/energy balances, and life-cycle greenhouse gas emissions. Results suggest that these systems can be economically competitive with petroleum-based processes while achieving the 50% emissions reduction

Optimal energy supply network determination and life cycle analysis for hybrid coal, biomass, and natural gas to liquid (CBGTL) plants using carbon-based hydrogen production

A mixed-integer linear optimization formulation is developed to analyze the United States energy supply chain network for the hybrid coal, biomass, and natural gas to liquids (CBGTL) facilities. Each state is discretized into octants and each octant centroid serves as a potential location of one facility. The model selects the optimal locations of CBGTL facilities, the feedstock combination, and size of each facility that gives the minimum overall production cost. Two case studies are presented to investigate the effects of various technologies and hydrogen prices. The CBGTL network is capable to supply transportation fuel demands for the country at a cost between $15.68 and$22.06/GJ LHV ($76.55-$112.91/bbl crude oil) of produced liquid fuels for both case studies. Life cycle analysis on each facility in the supply chain network shows that the United States fuel demands can be fulfilled with an excess of 50% emissions reduction compared to petroleum based processes. (C) 2011 Elsevier Ltd. All rights reserved

Ind. Eng. Chem. Res.

The thermochemical conversion of coal and biomass to liquid transportation fuels from a synthesis gas intermediate is investigated using an optimization-based process synthesis framework. Two distinct types of coal (LV bituminous and coal commonly found in the province of Anhui, China) and two types of biomass (hardwood and duckweed) are considered as feedstocks. The superstructure incorporates alternative conversion pathways of synthesis gas which include methanol formation and conversion into FischerTropsch hydrocarbons. Methanol may be converted to gasoline or olefins, and the olefins may be subsequently converted to gasoline and distillate. A rigorous deterministic global optimization branch-and-bound framework is utilized to determine the optimal process topology that produces liquid fuels at the lowest possible cost. Economies of scale are evident as the refinery capacity increases and it is observed that the fuel ratios of the final liquid products have a significant impact on the optimal topology of the plant. The results suggest that liquid fuels production from coal and biomass can be competitive with petroleum-based processes.The thermochemical conversion of coal and biomass to liquid transportation fuels from a synthesis gas intermediate is investigated using an optimization-based process synthesis framework. Two distinct types of coal (LV bituminous and coal commonly found in the province of Anhui, China) and two types of biomass (hardwood and duckweed) are considered as feedstocks. The superstructure incorporates alternative conversion pathways of synthesis gas which include methanol formation and conversion into FischerTropsch hydrocarbons. Methanol may be converted to gasoline or olefins, and the olefins may be subsequently converted to gasoline and distillate. A rigorous deterministic global optimization branch-and-bound framework is utilized to determine the optimal process topology that produces liquid fuels at the lowest possible cost. Economies of scale are evident as the refinery capacity increases and it is observed that the fuel ratios of the final liquid products have a significant impact on the optimal topology of the plant. The results suggest that liquid fuels production from coal and biomass can be competitive with petroleum-based processes

Discovery of biomarker combinations that predict periodontal health or disease with high accuracy from GCF samples based on high‐throughput proteomic analysis and mixed‐integer linear optimization

Aim To identify optimal combination(s) of proteomic based biomarkers in gingival crevicular fluid (GCF ) samples from chronic periodontitis (CP ) and periodontally healthy individuals and validate the predictions through known and blind test sets. Materials and Methods GCF samples were collected from 96 CP and periodontally healthy subjects and analysed using high‐performance liquid chromatography, tandem mass spectrometry and the PILOT _PROTEIN algorithm. A mixed‐integer linear optimization (MILP ) model was then developed to identify the optimal combination of biomarkers which could clearly distinguish a blind subject sample as healthy or diseased. Results A thorough cross‐validation of the MILP model capability was performed on a training set of 55 samples and greater than 99% accuracy was consistently achieved when annotating the testing set samples as healthy or diseased. The model was then trained on all 55 samples and tested on two different blind test sets, and using an optimal combination of 7 human proteins and 3 bacterial proteins, the model was able to correctly predict 40 out of 41 healthy and diseased samples. Conclusions The proposed large‐scale proteomic analysis and MILP model led to the identification of novel combinations of biomarkers for consistent diagnosis of periodontal status with greater than 95% predictive accuracy

PILOT_PROTEIN: Identification of Unmodified and Modified Proteins via High-Resolution Mass Spectrometry and Mixed-Integer Linear Optimization

A novel protein identification framework, PILOT_PROTEIN, has been developed to construct a comprehensive list of all unmodified proteins that are present in a living sample. It uses the peptide identification results from the PILOT_SEQUEL algorithm to initially determine all unmodified proteins within the sample. Using a rigorous biclustering approach that groups incorrect peptide sequences with other homologous sequences, the number of false positives reported is minimized. A sequence tag procedure is then incorporated along with the untargeted PTM identification algorithm, PILOT_PTM, to determine a list of all modification types and sites for each protein. The unmodified protein identification algorithm, PILOT_PROTEIN, is compared to the methods SEQUEST, InsPecT, X!Tandem, VEMS, and ProteinProspector using both prepared protein samples and a more complex chromatin digest. The algorithm demonstrates superior protein identification accuracy with a lower false positive rate. All materials are freely available to the scientific community at http://pumpd.princeton.edu

Novel protein identification methods for biomarker discovery via a proteomic analysis of periodontally healthy and diseased gingival crevicular fluid samples

Aim To identify possible novel biomarkers in gingival crevicular fluid (GCF ) samples from chronic periodontitis (CP ) and periodontally healthy individuals using high‐throughput proteomic analysis. Materials and Methods Gingival crevicular fluid samples were collected from 12 CP and 12 periodontally healthy subjects. Samples were trypically digested with trypsin, eluted using high‐performance liquid chromatography, and fragmented using tandem mass spectrometry (MS /MS ). MS /MS spectra were analysed using PILOT _PROTEIN to identify all unmodified proteins within the samples. Results Using the database derived from Homo sapiens taxonomy and all bacterial taxonomies, 432 human (120 new) and 30 bacterial proteins were identified. The human proteins, angiotensinogen, clusterin and thymidine phosphorylase were identified as biomarker candidates based on their high‐scoring only in samples from periodontal health. Similarly, neutrophil defensin‐1, carbonic anhydrase‐1 and elongation factor‐1 gamma were associated with CP . Candidate bacterial biomarkers include 33 kD a chaperonin, iron uptake protein A2 and phosphoenolpyruvate carboxylase (health‐associated) and ribulose biphosphate carboxylase, a probable succinyl‐CoA :3‐ketoacid‐coenzyme A transferase, or DNA ‐directed RNA polymerase subunit beta (CP ‐associated). Most of these human and bacterial proteins have not been previously evaluated as biomarkers of periodontal conditions and require further investigation. Conclusions The proposed methods for large‐scale comprehensive proteomic analysis may lead to the identification of novel biomarkers of periodontal health or disease

Biomass and Natural Gas to Liquid Transportation Fuels and Olefins (BGTL+C2_C4): Process Synthesis and Global Optimization

This paper introduces a process synthesis and a global optimization framework toward the coproduction of liquid fuels and olefins from biomass and natural gas. A superstructure of alternatives is developed at each stage of the process with different gasification options, natural gas conversion routes, hydrocarbon production, and upgrading methods. Simultaneous heat, power, and water integration is introduced for the optimal usage of the utilities in the proposed plants. The global optimization framework with a branch-and-bound approach is utilized to determine the optimal process out of numerous alternatives that would give the maximum plant profit. The optimal topologies obtained suggest that the best possible process depends on the liquid fuels and olefins to be produced. Parametric analysis on different chemicals production levels suggests that both the profit and net present value (NPV) increases substantially at higher chemicals production levels. Economies of scale are present as the case studies at higher capacities result in higher profits and higher net present values. The results suggest that the proposed refineries with coproduction of liquid fuels and olefins are economically viable because of their high and positive NPVs. Furthermore, higher olefins production levels can make the plants more favorable economically

Thermochemical Conversion of Duckweed Biomass to Gasoline, Diesel, and Jet Fuel: Process Synthesis and Global Optimization

Duckweed biomass is gasified in a thermochemical-based superstructure to produce gasoline, diesel, and kerosene using a synthesis gas intermediate. The superstructure includes multiple pathways for conversion of the synthesis gas to liquid hydrocarbons via Fischer-Tropsch synthesis or intermediate methanol synthesis. Low-temperature and high-temperature Fischer-Tropsch processes are examined using both iron and cobalt based catalysts. Methanol may be converted to hydrocarbons via the methanol-to-gasoline or methanol-to-olefins processes. The hydrocarbons will be refined into the final liquid products using ZSM-5 catalytic conversion, oligomerization, alkylation, isomerization, hydrotreating, reforming, and hydrocracking. A process synthesis framework is outlined to select the refining pathway that will produce the liquid fuels as the lowest possible cost. A rigorous deterministic branch-and-bound global optimization strategy will be incorporated to theoretically guarantee that the overall cost of the solution chosen by the synthesis framework is within a small fraction of the best possible value. A heat, power, and water integration is incorporated within the process synthesis framework to ensure that the cost of utility production and wastewater treatment are simultaneously included with the synthesis of the core refining processes. The proposed process synthesis framework is demonstrated using four case studies which determine the effect of refinery capacity and liquid fuel composition on the overall system cost, the refinery topological design, the process material/energy balances, and the life cycle greenhouse gas emissions.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000323536000021&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, ChemicalSCI(E)EI33ARTICLE3311436-114505

PILOT_PROTEIN: Identification of Unmodified and Modified Proteins via High-Resolution Mass Spectrometry and Mixed-Integer Linear Optimization

A novel protein identification framework, PILOT_PROTEIN, has been developed to construct a comprehensive list of all unmodified proteins that are present in a living sample. It uses the peptide identification results from the PILOT_SEQUEL algorithm to initially determine all unmodified proteins within the sample. Using a rigorous biclustering approach that groups incorrect peptide sequences with other homologous sequences, the number of false positives reported is minimized. A sequence tag procedure is then incorporated along with the untargeted PTM identification algorithm, PILOT_PTM, to determine a list of all modification types and sites for each protein. The unmodified protein identification algorithm, PILOT_PROTEIN, is compared to the methods SEQUEST, InsPecT, X!Tandem, VEMS, and ProteinProspector using both prepared protein samples and a more complex chromatin digest. The algorithm demonstrates superior protein identification accuracy with a lower false positive rate. All materials are freely available to the scientific community at http://pumpd.princeton.edu