Biomedical subjects

Kenneth A Marx

Publications and source records attributed to Kenneth A Marx.

13 recordsLinked to original sources

PubMed2006

DNA deformability changes of single base pair mutants within CDE binding sites in S. Cerevisiae centromere DNA correlate with measured chromosomal loss rates and CDE binding site symmetries.

BACKGROUND: The centromeres in yeast (S. cerevisiae) are organized by short DNA sequences (125 bp) on each chromosome consisting of 2 conserved elements: CDEI and CDEIII spaced by a CDEII region. CDEI and CDEIII are critical sequence specific protein binding sites necessary for correct centromere formation and following assembly with proteins, are positioned near each other on a specialized nucleosome. Hegemann et al. BioEssays 1993, 15: 451-460 reported single base DNA mutants within the critical CDEI and CDEIII binding sites on the centromere of chromosome 6 and quantitated centromere loss of function, which they measured as loss rates for the different chromosome 6 mutants during cell division. Olson et al. Proc Natl Acad Sci USA 1998, 95: 11163-11168 reported the use of protein-DNA crystallography data to produce a DNA dinucleotide protein deformability energetic scale (PD-scale) that describes local DNA deformability by sequence specific binding proteins. We have used the PD-scale to investigate the DNA sequence dependence of the yeast chromosome 6 mutants' loss rate data. Each single base mutant changes 2 PD-scale values at that changed base position relative to the wild type. In this study, we have utilized these mutants to demonstrate a correlation between the change in DNA deformability of the CDEI and CDEIII core sites and the overall experimentally measured chromosome loss rates of the chromosome 6 mutants. RESULTS: In the CDE I and CDEIII core binding regions an increase in the magnitude of change in deformability of chromosome 6 single base mutants with respect to the wild type correlates to an increase in the measured chromosome loss rate. These correlations were found to be significant relative to 10(5) Monte Carlo randomizations of the dinucleotide PD-scale applied to the same calculation. A net loss of deformability also tends to increase the loss rate. Binding site position specific, 4 data-point correlations were also created using the wild type sequence and the 3 associated alternate base mutants at each binding site position. These position specific slope magnitudes, or sensitivities, correlated with and reflected the underlying position symmetry of the DNA binding sequences. CONCLUSION: These results suggest the utility of correlating quantitative aspects of sequence specific protein-DNA complex single base mutants with changes in the easily calculated PD-deformability scale of the individual DNA sequence mutants. Using this PD approach, it may be possible in the future to understand the magnitude of biological or energetic functional effects of specific DNA sequence mutants within DNA-protein complexes in terms of their effect on DNA deformability.

Base Pairing↗

PubMed2006

Evidence for long poly(dA).poly(dT) tracts in D. discoideum DNA at high frequencies and their preferential avoidance of nucleosomal DNA core regions.

The eukaryote, Dictyostelium discoideum, has one of the most (A+T) rich genomes studied to date. Isolated nuclear D. discoideum DNA (AX3 strain) was used to qualitatively determine the frequency and length distribution of long (dA).(dT) homopolymer tracts in this genome, in comparison to the less (A+T) rich calf thymus and Schistosoma mansoni DNAs that had few observable long tracts. These experimental data accurately reflect the significantly elevated frequencies of long tracts found computationally within the D. discoideum intron and flanking sequences, but not exons. PCR amplification of long (dA).(dT) homopolymer tract containing sequences was carried out. Then experimental biotinylated (dT)18 probe hybridization to the PCR amplified DNA showed that the long (dA).(dT) homopolymer tracts were enriched in D. discoideum sequences only hundreds of base pair in length, under conditions where no equivalent hybridization was observed to S. mansoni DNA or calf DNA sequences. Similar probe hybridization to DNA isolated following micrococcal nuclease digestion of D. discoideum chromatin demonstrated that long (dA).(dT) homopolymer tracts were more highly enriched in nucleosomal DNA lengths that included the internucleosomal linker as compared to shorter linker free mononucleosomal lengths. This observation is in agreement with the frequency of tract spacing results calculated from GenBank sequence data. These frequency data indicate that adjacent long tracts plus the intervening spacer DNA are found at peak lengths (average 42 bp), exactly characteristic of the internucleosomal spacer region of D. discoideum chromatin and are in sufficient number to be found in nearly half of all nucleosomes. Compared to shuffled tract sequence controls, these lengths of adjacent long tracts plus the intervening spacer DNA were found to be significantly enriched. Lesser enrichments are observed at lengths corresponding to adjacent tracts being separated by nucleosomal core length DNA sequences (145-185 bp). These data strongly suggest that adjacent long tracts occur spaced at selected lengths so as to avoid the central core regions of nucleosomes and instead are found localized within internucleosomal DNA linker and core edge regions in D. discoideum chromatin.

Animals↗

PubMed2005

Quartz crystal microbalance biosensor study of endothelial cells and their extracellular matrix following cell removal: Evidence for transient cellular stress and viscoelastic changes during detachment and the elastic behavior of the pure matrix.

A quartz crystal microbalance (QCM) cell biosensor utilizing living endothelial cells (ECs) or human breast cancer cells (MCF-7) adhering to the gold QCM surface was used to study the relative contributions of the cells and their underlying extracellular matrix (ECM) to the measured QCM Deltaf and DeltaR shifts. The ECM represents a natural biomaterial that is synthesized by the cells to enable their attachment to surfaces. We followed the detachment of the ECs or MCF-7 cells from their ECM using a nonproteolytic method and were able to apportion the total frequency, Deltaf, decrease of the biosensor into contributions from cell attachment and from the intact underlying ECM. We also demonstrated that the Deltaf shift remaining after EC removal corresponds to ECM as determined by light microscopic visualization of the stained protein. During the process of cell detachment, we observed a novel transient increase in viscoelastic behavior expressed as a transient increase in the motional resistance, DeltaR, parameter. Then we showed via a simulation experiment using ECs stained with fluorescent rhodamine-labeled phalloidin, an actin stain, that the transient viscoelastic increase correlated with cellular stress exhibited by the cells during removal with ethylene glycol bis(2-aminoethyl ether)-N,N,N',N'- tetraacetic acid. Prior to cells lifting from their ECM, the attached ECs rearrange their actin microfilaments first into peripheral stress fibers and second into internal aggregates, to maintain cell-cell connectivity, retain their spread morphology, and attempt to adhere more tightly to their underlying ECM. The decrease in DeltaR following its transient rise corresponds to cells finally losing their attachment focal points and lifting from the ECM. We also characterized the normalized f shifts, -Delta(Deltaf)(ECM)/attached cell and -Delta(Deltaf)(cells)/attached cell, as a function of varying the number of adherent cells. Finally, we demonstrate that the underlying native ECM biomaterial, from which all cells have been removed, does not exhibit any significant level of energy dissipation, in contrast to the cells when they are attached to the ECM.

Biosensing Techniques↗

PubMed2005

Detection of apoptosis and drug resistance of human breast cancer cells to taxane treatments using quartz crystal microbalance biosensor technology.

Taxanes are used for the treatment of many human cancers, as first- and second-line chemotherapeutics. In the course of treatment many patients develop resistance or hypersensitivity to one form of taxane and require a different taxane to rescue the therapeutic benefit of the drug. There is currently no method to reliably predict tumor responses to taxanes prior to therapy or when resistance or hypersensitivity develops. We adapted the quartz crystal microbalance (QCM) biosensor technique to study responses of human mammary epithelial tumor cells to taxanes. Studies indicate that stable frequency and resistance levels are reached at 24 h. Cells in the QCM can then be treated with taxanes and responses monitored in real time via frequency and resistance changes reflecting alterations of cell mass distribution and viscoelastic properties. Distinct shifts in frequency and resistance accurately predicted apoptosis or resistance to treatment, as determined in parallel convention assays. QCM analysis accurately predicted docetaxel was more effective than paclitaxel and MCF-7 cells were more resistant to taxanes compared to MDA-MB-231 cells. These studies suggest "signature" patterns for taxane responsivity could be compared to those of patient biopsy samples to predict therapy outcome prior to treatment for initial therapy or to rescue therapy efficacy.

Antineoplastic Agents↗

PubMed2004

Homopolymer tract length dependent enrichments in functional regions of 27 eukaryotes and their novel dependence on the organism DNA (G+C)% composition.

BACKGROUND: DNA homopolymer tracts, poly(dA).poly(dT) and poly(dG).poly(dC), are the simplest of simple sequence repeats. Homopolymer tracts have been systematically examined in the coding, intron and flanking regions of a limited number of eukaryotes. As the number of DNA sequences publicly available increases, the representation (over and under) of homopolymer tracts of different lengths in these regions of different genomes can be compared. RESULTS: We carried out a survey of the extent of homopolymer tract over-representation (enrichment) and over-proportional length distribution (above expected length) primarily in the single gene documents, but including some whole chromosomes of 27 eukaryotics across the (G+C)% composition range from 20 - 60%. A total of 5.2 x 10(7) bases from 15,560 cleaned (redundancy removed) sequence documents were analyzed. Calculated frequencies of non-overlapping long homopolymer tracts were found over-represented in non-coding sequences of eukaryotes. Long poly(dA).poly(dT) tracts demonstrated an exponential increase with tract length compared to predicted frequencies. A novel negative slope was observed for all eukaryotes between their (G+C)% composition and the threshold length N where poly(dA).poly(dT) tracts exhibited over-representation and a corresponding positive slope was observed for poly(dG).poly(dC) tracts. Tract size thresholds where over-representation of tracts in different eukaryotes began to occur was between 4 - 11 bp depending upon the organism (G+C)% composition. The higher the GC%, the lower the threshold N value was for poly(dA).poly(dT) tracts, meaning that the over-representation happens at relatively lower tract length in more GC-rich surrounding sequence. We also observed a novel relationship between the highest over-representations, as well as lengths of homopolymer tracts in excess of their random occurrence expected maximum lengths. CONCLUSIONS: We discuss how our novel tract over-representation observations can be accounted for by a few models. A likely model for poly(dA).poly(dT) tract over-representation involves the known insertion into genomes of DNA synthesized from retroviral mRNAs containing 3' polyA tails. A proposed model that can account for a number of our observed results, concerns the origin of the isochore nature of eukaryotic genomes via a non-equilibrium GC% dependent mutation rate mechanism. Our data also suggest that tract lengthening via slip strand replication is not governed by a simple thermodynamic loop energy model.

AT Rich Sequence↗

PubMed2004

Coding and non-coding DNA thermal stability differences in eukaryotes studied by melting simulation, base shuffling and DNA nearest neighbor frequency analysis.

The melting of the coding and non-coding classes of natural DNA sequences was investigated using a program, MELTSIM, which simulates DNA melting based upon an empirically parameterized nearest neighbor thermodynamic model. We calculated T(m) results of 8144 natural sequences from 28 eukaryotic organisms of varying F(GC) (mole fraction of G and C) and of 3775 coding and 3297 non-coding sequences derived from those natural sequences. These data demonstrated that the T(m) vs. F(GC) relationships in coding and non-coding DNAs are both linear but have a statistically significant difference (6.6%) in their slopes. These relationships are significantly different from the T(m) vs. F(GC) relationship embodied in the classical Marmur-Schildkraut-Doty (MSD) equation for the intact long natural sequences. By analyzing the simulation results from various base shufflings of the original DNAs and the average nearest neighbor frequencies of those natural sequences across the F(GC) range, we showed that these differences in the T(m) vs. F(GC) relationships are largely a direct result of systematic F(GC)-dependent biases in nearest neighbor frequencies for those two different DNA classes. Those differences in the T(m) vs. F(GC) relationships and biases in nearest neighbor frequencies also appear between the sequences from multicellular and unicellular organisms in the same coding or non-coding classes, albeit of smaller but significant magnitudes.

Base Composition↗

PubMed2004

Applications of machine learning and high-dimensional visualization in cancer detection, diagnosis, and management.

Recent technical advances in combinatorial chemistry, genomics, and proteomics have made available large databases of biological and chemical information that have the potential to dramatically improve our understanding of cancer biology at the molecular level. Such an understanding of cancer biology could have a substantial impact on how we detect, diagnose, and manage cancer cases in the clinical setting. One of the biggest challenges facing clinical oncologists is how to extract clinically useful knowledge from the overwhelming amount of raw molecular data that are currently available. In this paper, we discuss how the exploratory data analysis techniques of machine learning and high-dimensional visualization can be applied to extract clinically useful knowledge from a heterogeneous assortment of molecular data. After an introductory overview of machine learning and visualization techniques, we describe two proprietary algorithms (PURS and RadViz) that we have found to be useful in the exploratory analysis of large biological data sets. We next illustrate, by way of three examples, the applicability of these techniques to cancer detection, diagnosis, and management using three very different types of molecular data. We first discuss the use of our exploratory analysis techniques on proteomic mass spectroscopy data for the detection of ovarian cancer. Next, we discuss the diagnostic use of these techniques on gene expression data to differentiate between squamous and adenocarcinoma of the lung. Finally, we illustrate the use of such techniques in selecting from a database of chemical compounds those most effective in managing patients with melanoma versus leukemia.

Artificial Intelligence↗

PubMed2003

Poly: a quantitative analysis tool for simple sequence repeat (SSR) tracts in DNA.

BACKGROUND: Simple sequence repeats (SSRs), microsatellites or polymeric sequences are common in DNA and are important biologically. From mononucleotide to trinucleotide repeats and beyond, they can be found in long (> 6 repeating units) tracts and may be characterized by quantifying the frequencies in which they are found and their tract lengths. However, most of the existing computer programs that find SSR tracts do not include these methods. RESULTS: A computer program named Poly has been written not only to find SSR tracts but to analyze the results quantitatively. CONCLUSIONS: Poly is significant in its use of non-standard, quantitative methods of analysis. And, with its flexible object model and data structure, Poly and its generated data can be used for even more sophisticated analyses.

Algorithms↗

PubMedDate not supplied

Quartz crystal microbalance: a useful tool for studying thin polymer films and complex biomolecular systems at the solution-surface interface.

The quartz crystal microbalance (QCM) is a simple, cost effective, high-resolution mass sensing technique, based upon the piezoelectric effect. As a methodology, the QCM evolved a solution measurement capability in largely analytical chemistry and electrochemistry applications due to its sensitive solution-surface interface measurement capability. The technique possesses a wide detection range. At the low mass end, it can detect monolayer surface coverage by small molecules or polymer films. At the upper end, it is capable of detecting much larger masses bound to the surface. These can be complex arrays of biopolymers and biomacromolecules, even whole cells. In addition, the QCM can provide information about the energy dissipating properties of the bound surface mass. Another important and unique feature of the technique is the ability to measure mass and energy dissipation properties of films while simultaneously carrying out electrochemistry on solution species or upon film systems bound to the upper electrode on the oscillating quartz crystal surface. These measurements can describe the course of electropolymerization of a film or can reveal ion or solute transport within a film during changes in the film environment or state, including the oxidation state for an electroactive film driven by the underlying surface potential. The past decade has witnessed an explosive growth in the application of the QCM technique to the study of a wide range of molecular systems at the solution-surface interface, in particular, biopolymer and biochemical systems. In this report, we start with a brief historical and technical overview. Then we discuss the application of the QCM technique to measurements involving micellar systems, self-assembling monolayers and their phase transition behavior, molecularly imprinted polymers, chemical sensors, films formed using the layer-by-layer assembly technique, and biopolymer films and point out the utility of the electrochemical capabilities of the technique to characterizing film properties, especially electroactive polymer films. We also describe the wide range of surface chemistries and attachment strategies used by investigators to bring about surface attachment and multi-layer interactions of these thin film systems. Next we review the wide range of recent applications of the technique to: studies of complex biochemical and biomimetic systems, the creation of protein and nucleic acid biosensors, studies of attached living cells and whole cell biosensor applications. Finally, we discuss future technical directions and applications of the QCM technique to areas such as drug discovery.

Biopolymers↗

PubMedDate not supplied

Electropolymerized films formed from the amphiphilic decyl esters of D- and L-tyrosine compared to L-tyrosine using the electrochemical quartz crystal microbalance.

Using the electrochemical quartz crystal microbalance (EQCM), we compared thin films formed on Pt by electropolymerization of l-tyrosine to that of the amphiphilic monomers, decyl esters of d- and l-tyrosine (DEDT and DELT). Mass build-up and film properties were determined as a function of monomer concentration via frequency, f, motional resistance, R, and charge passage, Q, measurements. Films were found to occur by a combination of monomer electropolymerization and adsorption for DEDT and DELT, but only by electropolymerization for l-tyrosine. This difference in film formation process for the monomers is reflected in the net mass build-up for each film, as represented by calculated df/dQ values. For the adsorbing monomers DEDT and DELT, films possessed concentration dependent df/dQ values, more than 100-fold greater than that for l-tyrosine film formation under equivalent electropolymerization conditions. During the entire film growth process, all three films exhibited no significant energy dissipation properties (DeltaR invariant). Concentration dependent adsorption of significant levels of unpolymerized but self-assembled DEDT and DELT monomers account for the subsequent time dependent mass loss observed from the films maintained in buffer in the absence of monomer. Contact angle measurements demonstrated a pH dependent increase in the surface hydrophilicity of films electropolymerized from the DEDT, DELT, and l-tyrosine monomers but not films formed from phenol and 3-nitrophenol monomers. This behavior is consistent with the monomers' known changes in titration/charge state properties with increasing pH. This study provided insight into the film formation, stability, and surface hydrophilicity resulting from electropolymerization of these related tyrosine based monomers. This information is critical to assessing the utility these films may have in the development of new biomaterials and as biological macromolecule or cell immobilization strategies in biosensors.

Electrochemistry↗

PubMedDate not supplied

Enzymatic copolymerization alters the structure of unpolymerized mixtures of the biomimetic monomers: the amphiphilic decyl ester of L-tyrosine and L-tyrosineamide--an AFM investigation of nano- to micrometer-scale structure differences.

Previously, we have shown that the amphiphilic decyl esters of both D- and L-tyrosine (DELT) self-assemble in aqueous solution above their critical micelle concentration values to form long rodlike structures that can be enzymatically polymerized. In the current study, we have examined the self-assembled structures of unpolymerized and enzymatically (horseradish peroxidase) copolymerized 1:1 molar mixtures of DELT with the nonamphiphilic comonomer L-tyrosineamide. The structures were examined following adsorption to gold-coated mica surfaces using optical microscopy and scanning electron microscopy, but primarily noncontact atomic force microscopy. Both unpolymerized and copolymerized 1:1 comonomer mixture aggregates produced amorphous to spherical shaped structures, exhibiting increased flexibility that contrasted with our previous observations of the more highly ordered long rodlike structures seen with the pure DELT. The unpolymerized comonomer aggregates were amorphous and of varying size. Interestingly, they contained occasional novel structures-smooth, sharp, nipplelike features that rose hundreds of nanometers above the smooth aggregate surface. However, upon enzymatic copolymerization, the structures are altered, forming nearly hemispherical aggregates in contact with each other on the surface. These structures possessed diameters of 1.51 +/- 0.24 microm. The copolymerized structures lacked any evidence of the sharp nipplelike features observed in the unpolymerized sample, but they did exhibit nanometer-scale detailed surface features, indicative of a higher degree of internal organization. The measured surface roughness of the copolymerized comonomer mixture was more than 10 times greater than the surface roughness of the unpolymerized comonomer mixture.

Biomimetic Materials↗

PubMedDate not supplied

Quartz crystal microbalance study of endothelial cell number dependent differences in initial adhesion and steady-state behavior: evidence for cell-cell cooperativity in initial adhesion and spreading.

The quartz crystal microbalance (QCM) technique has been applied to the real time monitoring of endothelial cell (EC) adhesion and spreading on the QCM gold surface. We previously showed that the measured QCM Deltaf and DeltaR shifts were due to cells adhering to the gold crystal surface, requiring proteolytic enzyme treatment to be removed from the surface, in order for the Deltaf and DeltaR shifts to return to zero. In the present report, we demonstrate the quantitative dependence and saturation of the measured Deltaf and DeltaR shifts on the number of firmly attached ECs as measured by electronic counting of the cells. We demonstrate through a light microscope simulation experiment that the different Deltaf and DeltaR regions of the QCM temporal response curve correspond to the incident ECs contacting the surface, followed by their adhesion and spreading, which reflect cellular mass distribution and cytoskeletal viscoelasticity changes. Also, we demonstrate that the dose response curve of Deltaf and DeltaR values versus attached EC number is more sensitive and possesses less scatter for the hydrophilically treated surface compared to the native gold surface of the QCM. For both surfaces, a Deltaf and DeltaR versus trypsinized, attached EC number plot 1 h post-seeding exhibits a sigmoid curve shape whereas a similar plot 24 h post-seeding exhibits a hyperbolic curve shape. This number dependence suggests cell-cell cooperativity in the initial cell adhesion and spreading processes. These QCM data and our interpretation are corroborated by differences in cell appearance and spreading behavior we observed for ECs in a light microscope fluorescence simulation experiment of the cell density effect. For a stably attached EC monolayer at 24 h post-addition, steady-state Deltaf and DeltaR values are higher and exhibit saturation behavior for both the hydrophilically treated gold surface as compared to the untreated surface. The steady-state 24 h Deltaf and DeltaR values of stably attached ECs are shifted from the 1 h attached ECs. The 24 h values are characteristic of a more energy-dissipative structure. This is consistent with the time-dependent elaboration of surface contacts in anchorage-dependent ECs via the attachment of intregrins to underlying extracellular matrix. It is also in agreement with the known energy dissipation function of the ECs that cover the interior of blood vessels and are exposed to continuous pulsatile blood flow.

Animals↗

PubMedDate not supplied

Data mining the NCI cancer cell line compound GI(50) values: identifying quinone subtypes effective against melanoma and leukemia cell classes.

Using data mining techniques, we have studied a subset (1400) of compounds from the large public National Cancer Institute (NCI) compounds data repository. We first carried out a functional class identity assignment for the 60 NCI cancer testing cell lines via hierarchical clustering of gene expression data. Comprised of nine clinical tissue types, the 60 cell lines were placed into six classes-melanoma, leukemia, renal, lung, and colorectal, and the sixth class was comprised of mixed tissue cell lines not found in any of the other five classes. We then carried out supervised machine learning, using the GI(50) values tested on a panel of 60 NCI cancer cell lines. For separate 3-class and 2-class problem clustering, we successfully carried out clear cell line class separation at high stringency, p < 0.01 (Bonferroni corrected t-statistic), using feature reduction clustering algorithms embedded in RadViz, an integrated high dimensional analytic and visualization tool. We started with the 1400 compound GI(50) values as input and selected only those compounds, or features, significant in carrying out the classification. With this approach, we identified two small sets of compounds that were most effective in carrying out complete class separation of the melanoma, non-melanoma classes and leukemia, non-leukemia classes. To validate these results, we showed that these two compound sets' GI(50) values were highly accurate classifiers using five standard analytical algorithms. One compound set was most effective against the melanoma class cell lines (14 compounds), and the other set was most effective against the leukemia class cell lines (30 compounds). The two compound classes were both significantly enriched in two different types of substituted p-quinones. The melanoma cell line class of 14 compounds was comprised of 11 compounds that were internal substituted p-quinones, and the leukemia cell line class of 30 compounds was comprised of 6 compounds that were external substituted p-quinones. Attempts to subclassify melanoma or leukemia cell lines based upon their clinical cancer subtype met with limited success. For example, using GI(50) values for the 30 compounds we identified as effective against all leukemia cell lines, we could subclassify acute lymphoblastic leukemia (ALL) origin cell lines from non-ALL leukemia origin cell lines without significant overlap from non-leukemia cell lines. Based upon clustering using GI(50) values for the 60 cancer cell lines laid out by the RadViz algorithm, these two compound subsets did not overlap with clusters containing any of the NCI's 92 compounds of known mechanism of action, a few of which are quinones. Given their structural patterns, the two p-quinone subtypes we identified would clearly be expected to possess different redox potentials/substrate specificities for enzymatic reduction in vivo. These two p-quinone subtypes represent valuable information that may be used in the elucidation of pharmacophores for the design of compounds to treat these two cancer tissue types in the clinic.

Algorithms↗