|
|
| (37 intermediate revisions by 2 users not shown) |
| Line 1: |
Line 1: |
| ==Eun-Hae "EK Kim, Ph.D.==
| |
| [[Image:ek.jpg|thumb|left|Eun-Hae "EK" Kim]]
| |
| '''''Mailing Address:'''''<br>
| |
| Dr. Eun-Hae Kim<br>
| |
| 1177 E Fourth St<br>
| |
| Tucson, AZ 85721-0038
| |
|
| |
|
| or
| |
|
| |
| P.O. Box 210038<br>
| |
| Tucson, AZ 85721-0038
| |
|
| |
| '''''Physical Address:'''''<br>
| |
| Saguaro Hall Rm 315<br>
| |
| 1110 E. South Campus <br>
| |
| Tucson, AZ 85721
| |
|
| |
| '''''Laboratory:'''''<br>
| |
| Saguaro Hall Rm 301
| |
|
| |
| '''Email: ''eunhae.kim at arizona dot edu'''''
| |
|
| |
| ==Education==
| |
|
| |
| '''Ph.D., Environmental Science, Biochemistry'''
| |
| :University of Arizona<br>
| |
| :Dept of Biochemistry and Molecular Biophysics and Soil, Water, and Environmental Science<br>
| |
| :''Integrating an interdisciplinary approach of comparative genomics, molecular microbiology,'' <br>
| |
| :''and biochemistry to better understand mechanisms of metal transport systems in bacteria.''
| |
|
| |
| '''M.S., Microbiology'''
| |
| :University of Nevada, Las Vegas<br>
| |
| :School of Life Sciences<br>
| |
| :''Elucidation of the roles and regulation of virulence factors in bacterial intracellular pathogens by''<br>
| |
| :''employing biochemical and genetic methods.''
| |
|
| |
| '''B.S., Biological Sciences'''
| |
| :University of Southern California<br>
| |
| :Wrigley Institute of Environmental Studies<br>
| |
| :''Characterization of microbial communities in aquatic and terrestrial environments on Santa Catalina'' <br>
| |
| :''Island utilizing 16S rRNA genes as a phylogenetic marker.''
| |
|
| |
| ==Research interests==
| |
| <!-- Feel free to add brief descriptions to your research interests as well -->
| |
| I graduated from the University of Southern California with a B.S. degree in Biological Sciences.
| |
|
| |
| I was afforded the opportunity to do some really awesome field research at the USC Wrigley Institute for Environmental Studies where I studied phylogenetics and phylogeography of microbial populations around Catalina Island.
| |
|
| |
| I then moved to the city that never sleeps, Las Vegas, NV where I obtained my Masters of Science degree in Microbiology. It was at UNLV where my work was extended from molecular biology to honing the skills necessary for employing biochemical methodologies. The focus of my research was analyzing virulence factors of the bacterial pathogen, Shigella.
| |
|
| |
| I had a passion for creative and critical thinking and decided to continue my graduate career by obtaining a Ph.D. On an interview at the University of Arizona in the great Sonoran desert, I had arrived at an opportune time during monsoon season, which instantly made me fall in love with Tucson. I obtained my Doctorate degree at the University of Arizona in Environmental Science with a focus in Biochemistry. As a Ph.D. student, my research integrated a multidisciplinary approach of comparative genomics, molecular biology, and biochemistry to better understand mechanisms of metal homeostasis in microorganisms.
| |
|
| |
| These acquired biochemical tools now have led me to the incredible field of proteomics, specifically community proteomics. My research focuses on how microbial communities impact biogeochemistry and global change.
| |
|
| |
| I use the techniques of molecular microbial ecology and biochemistry via metagenomics and metaproteomics to examine microbial community interactions within populations and their environment, specifically in critical terrestial environments. To gain a systems-level understanding of these communities and processes, I collaborate with biogeochemists, modelers, and others.
| |
|
| |
| A driving question of my research is: What is the role microbes play in carbon gas emissions from thawing permafrost?
| |
|
| |
| ==Publications==
| |
| <!-- Replace the PubMed ID's ("pmid=#######") below with the PubMed ID's for your publications. You can add or remove lines as needed -->
| |
| <biblio>
| |
|
| |
| #Paper1 pmid=22267509
| |
| #Paper2 pmid=22176720
| |
| #Paper3 pmid=21398536
| |
| // Selected as high impact publication by ASM Press and included in Journal Highlights section in Microbe Magazine, June 2011
| |
| #Paper5 pmid=20497225
| |
| #Paper6 pmid=20442961
| |
| #Paper7 pmid=19895645
| |
|
| |
| </biblio>
| |
|
| |
| ==Useful links==
| |
| *[http://rc.arizona.edu/hpc-htc/using-systems Using the HPC]
| |
| *[[Help|OpenWetWare help pages]]
| |
|
| |
| ==Proteomics Links==
| |
| *[http://en.wikipedia.org/wiki/Mass_spectrum_analysis Mass Spectrometry Analysis]
| |
| *[http://en.wikipedia.org/wiki/Mass_spectrometry_software Mass Spectrometry Software]
| |
| *[http://en.wikipedia.org/wiki/Mass_spectrometry_data_format Mass Spectrometry Data Format]
| |
|
| |
|
| |
| ==Proteomic Tools==
| |
| *[http://www.proteomesoftware.com/products/free-viewer Scaffold Download]
| |
|
| |
| ==Search Engines==
| |
| *[http://thegpm.org/tandem/ X!Tandem]
| |
| *[http://thegpm.org/tandem/api/ XTandem Parameters]
| |
|
| |
| ==Proteomic References==
| |
| General Label-Free Statistics<br>
| |
| (1) '''Detecting Differential and Correlated Protein Expression in Label-Free Shotgun Proteomics'''
| |
| <biblio>#Paper1 pmid=17081042</biblio>
| |
| (2) '''Significance analysis of spectral count data in label-free shotgun proteomic'''s
| |
| <biblio>#Paper2 pmid=18644780 </biblio>
| |
| (3) '''Mass spectrometry-based label-free quantitative proteomics'''
| |
| <biblio>#Paper3 pmid=19911078 </biblio>
| |
| (4) '''Less label, more free: Approaches in label‐free quantitative mass spectrometry'''
| |
| <biblio>#Paper5 pmid=21243637</biblio>
| |
| (5) '''Statistical similarities between transcriptomics and quantitative shotgun proteomics data'''
| |
| <biblio>#Paper6 pmid=18029349 </biblio>
| |
| (6) '''PatternLab for proteomics: a tool for differential shotgun proteomics'''
| |
| <biblio>#Paper7 pmid=18644148</biblio>
| |
| (7) '''Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments'''
| |
| <biblio>#Paper8 pmid=17905794</biblio>
| |
|
| |
| BIG ONE
| |
| (8) The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS
| |
|
| |
| (9) Peek a peak: a glance at statistics for quantitative label-free proteomics
| |
|
| |
|
| |
| (10) Relative, label-free protein quantitation: spectral counting error statistics from nine replicate MudPIT samples
| |
|
| |
|
| |
| (11) An assessment of false discovery rates and statistical significance in label-free quantitative proteomics with combined filters
| |
|
| |
|
| |
| (12) PepC: proteomics software for identifying differentially expressed proteins based on spectral counting
| |
|
| |
|
| |
| (13) Quantitative mass spectrometry in proteomics: a critical review
| |
|
| |
|
| |
| (14) The Spectra Count Label-free Quantitation in Cancer Proteomics
| |
|
| |
|
| |
| PROBABLY VERY GOOD
| |
| (15) Refinements to label free proteome quantitation: how to deal with peptides shared by multiple proteins
| |
|
| |
|
| |
| (16) Significance analysis of spectral count data in label-free shotgun proteomics
| |
|
| |
|
| |
| (17) Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis
| |
|
| |
|
| |
|
| |
| HERE IS FIRST PAPER ON SPECTRAL COUNTS!!! Must reference this
| |
| (18) A model for random sampling and estimation of relative protein abundance in shotgun proteomics
| |
|
| |
|
| |
| other papers on Spectral Counting including NSAF
| |
| (19) Role of spectral counting in quantitative proteomics
| |
|
| |
|
| |
| NSAF PAPER MUST REFERENCE:
| |
| (20) Analyzing chromatin remodeling complexes using shotgun proteomics and normalized spectral abundance factors
| |
|
| |
|
| |
| the first very good paper comparing methods for label free quant
| |
| (21) Comparison of label-free methods for quantifying human proteins by shotgun proteomics
| |
|
| |
|
| |
|
| |
| APPLICATIONS:
| |
| (22) Statistical Analysis of Membrane Proteome Expression Changes in Saccharomyces c erevisiae
| |
|
| |
| (23) A label free quantitative proteomic analysis of the< i> Saccharomyces cerevisiae</i> nucleus
| |
|
| |
|
| |
| (24) Differential quantitative proteomics of Porphyromonas gingivalis by linear ion trap mass spectrometry
| |
|
| |
|
| |
| (25) Community genomic and proteomic analyses of chemoautotrophic iron-oxidizing “Leptospirillum rubarum”(group II) and “Leptospirillum ferrodiazotrophum”(group III)
| |
|
| |
|
| |
| (26) Proteogenomic basis for ecological divergence of closely related bacteria in natural acidophilic microbial communities
| |
|
| |
|
| |
| (27) Shotgun metaproteomics of the human distal gut microbiota
| |
|
| |
|
| |
| (28) Metaproteomics of a gutless marine worm and its symbiotic microbial community reveal unusual pathways for carbon and energy use
| |
|
| |
| Instrument concerns:
| |
| (29) Effect of dynamic exclusion duration on spectral count based quantitative proteomics
| |
|
| |
| =Mass Spectrum Analysis=
| |
|
| |
| === Basic peaks ===
| |
| Electron ionization mass spectra have several distinct sets of peaks: the molecular ion, isotope peaks, fragmentation peaks, and metastable peaks.
| |
|
| |
| In the mass spectra the molecular ion peak is often most intense, but can be weak or missing. The molecular ion is a radical cation (M+.) as a result of removing one electron from the molecule. Identification of the molecular ion can be difficult. Examining organic compounds, the relative intensity of the molecular ion peak diminishes with branching and with increasing mass in a homologous series. In the spectrum for [[toluene]] for example, the molecular ion peak is located at 92 m/z corresponding to its molecular mass. Molecular ion peaks are also often preceded by a M-1 or M-2 peak resulting from loss of a hydrogen radical or dihydrogen.
| |
|
| |
| The peak with the highest intensity is called the base peak which is not necessarily the molecular ion.
| |
|
| |
| More peaks may be visible with m/z ratios larger than the molecular ion peak due to isotope distributions, called isotope peaks. The value of 92 in the toluene example corresponds to the monoisotopic mass of a molecule of toluene entirely composed of the most abundant isotopes (1H and 12C). The so-called M+1 peak corresponds to a fraction of the molecules with one higher isotope incorporated (2H or 13C) and the M+2 peak has two higher isotopes. The natural abundance of the higher isotopes is low for frequently encountered elements such as hydrogen, carbon and nitrogen and the intensity of isotope peaks subsequently low. In halogens on the other hand, higher isotopes have a large abundance which results in a specific mass signature in the mass spectrum of halogen containing compounds.
| |
|
| |
| Peaks with mass less than the molecular ion are the result of fragmentation of the molecule. Many reaction pathways exist for fragmentation, but only newly formed cations will show up in the mass spectrum, not radical fragments or neutral fragments.
| |
|
| |
| Metastable peaks are broad peaks with low intensity at non-integer mass values. These peaks result from ions with lifetimes shorter than the time needed to traverse the distance between ionization chamber and the detector.
| |
|
| |
| === Fragmentation ===
| |
| The fragmentation pattern of the spectra beside the determination of the molar weight of an unknown compound also suitable to give structural information, especially in combination with the calculation of the degree of unsaturation from the molecular formula (when available). Neutral fragments frequently lost are carbon monoxide, ethylene, water, ammonia, and hydrogen sulfide.
| |
|
| |
| fragmentations arise from:
| |
| * homolysis (chemistry)|homolysis processes. An example is the cleavage of carbon-carbon bonds next to a heteroatom
| |
| :[[Image:HeteroatomFragmentation.svg|fragmentation at heteroatom]]
| |
| : In this depiction single-electron movements are indicated by a [[Radical (chemistry)#Depicting radicals in chemical reactions|single-headed arrow]].
| |
| * Rearrangement reactions, for example a retro Diels-Alder reaction extruding neutral ethylene:
| |
| :[[Image:Unsaturated ring fragmentation.svg|Unsaturated ring fragmentation]]
| |
| :or the [[McLafferty rearrangement]]. As it is not always obvious where a lone electron resides in a radical cation a square bracket notation is often used.
| |
| * [[Ion-neutal complex]] formation. This pathway involves bond homolysis or bond heterolysis, in which the fragments do not have enough kinetic energy to separate and, instead, reaction with one another like an ion-molecule reaction.
| |
|
| |
| Some general rules:
| |
| * A useful aid is the nitrogen rule: if the m/z ratio is an even number, the compound contains no nitrogen or an even number of nitrogens.
| |
| * Cleavage occurs at alkyl substituted carbons reflecting the order generally observed in carbocations.
| |
| * Double bonds and arene compound|arene fragments tend to resist fragmentation.
| |
| * Allylic cations are stable and resist fragmentation.
| |
| * the even-electron rule stipulates that even-electron species (cations but not radical ions) will not fragment into two odd-electron species but rather to another cation and a neutral molecule.
| |
|
| |
| ===Isotope effects===
| |
| Isotope peaks within a spectra can help in structure elucidation. Compounds containing halogens (especially chlorine and bromine) can produce very distinct isotope peaks. The mass spectrum of methylbromide has two prominent peaks of equal intensity at m/z 94 (M) and 96 (M+2) and then two more at 79 and 81 belonging to the bromine fragment.
| |
|
| |
| Even when compounds only contain elements with less intense isotope peaks (carbon or oxygen), the distribution of these peaks can be used to assign the spectrum to the correct compound. For example, two compounds with identical mass of 150 Da, C<sub>8</sub>H<sub>12</sub>N<sub>3</sub><sup>+</sup> and C<sub>9</sub>H<sub>10</sub>O<sub>2</sub><sup>+</sup>, will have two different M+2 intensities which makes it possible to distinguish between them.
| |
|
| |
| ===Natural abundance of some elements===
| |
| The next table gives the isotope distributions for some elements. Some elements like phosphorus and fluorine only exist as a single isotope, with a natural abundance of 100%.
| |
|
| |
| {| class="wikitable"
| |
| |+'''Natural abundance of some elements'''
| |
| |-
| |
| ! ''Isotope'' || % nat. abundance !! atomic mass
| |
| |-
| |
| | <sup>1</sup>H || 99.985 || 1.007825
| |
| |-
| |
| | <sup>2</sup>H || 0.015 || 2.0140
| |
| |-
| |
| | <sup>12</sup>C || 98.89 || 12 (definition)
| |
| |-
| |
| | [[Carbon-13|<sup>13</sup>C]] || 1.11 || 13.00335
| |
| |-
| |
| | <sup>14</sup>N || 99.64 || 14.00307
| |
| |-
| |
| | <sup>15</sup>N || 0.36 || 15.00011
| |
| |-
| |
| | <sup>16</sup>O || 99.76 || 15.99491
| |
| |-
| |
| | <sup>17</sup>O || 0.04||
| |
| |-
| |
| | <sup>18</sup>O || 0.2|| 17.99916
| |
| |-
| |
| | <sup>28</sup>Si || 92.23 || 27.97693
| |
| |-
| |
| | <sup>29</sup>Si || 4.67 || 28.97649
| |
| |-
| |
| | <sup>30</sup>Si || 3.10 || 29.97376
| |
| |-
| |
| | <sup>32</sup>S || 95.0 || 31.97207
| |
| |-
| |
| | <sup>33</sup>S || 0.76 || 32.97146
| |
| |-
| |
| | <sup>34</sup>S || 4.22 || 33.96786
| |
| |-
| |
| | <sup>37</sup>Cl || 24.23 ||
| |
| |-
| |
| | <sup>35</sup>Cl || 75.77 || 34.96885
| |
| |-
| |
| | <sup>79</sup>Br || 50.69 || 78.9183
| |
| |-
| |
| | <sup>81</sup>Br || 49.31 || 80.9163
| |
| |}
| |
