986 resultados para Methods: laboratory: molecular
Resumo:
The molecular dynamics (MD) simulations play a very important role in science today. They have been used successfully in binding free-energy calculations and rational design of drugs and vaccines. MD simulations can help visualize and understand structures and dynamics at an atomistic level when combined with molecular graphics programs. The molecular and atomistic properties can be displayed on a computer in a time-dependent way, which opens a road toward a better understanding of the relationship of structure, dynamics, and function. In this chapter, the basics of MD are explained, together with a step-by-step description of setup and running an MD simulation.
Resumo:
The specific transporters involved in maintenance of blood pH homeostasis in cephalopod molluscs have not been identified to date. Using in situ hybridization and immuno histochemical methods, we demonstrate that Na+/K+-ATPase (soNKA), a V-type H+-ATPase (soV-HA), and Na+/HCO3- cotransporter (soNBC) are co-localized in NKA-rich cells in the gills of Sepia officinalis. mRNA expression patterns of these transporters and selected metabolic genes were examined in response to moderately elevated seawater pCO2 (0.16 and 0.35 kPa) over a time-course of six weeks in different ontogenetic stages. The applied CO2 concentrations are relevant for ocean acidification scenarios projected for the coming decades. We determined strong expression changes in late stage embryos and hatchlings, with one to three log2-fold reductions in soNKA, soNBCe, socCAII and COX. In contrast, no hypercapnia induced changes in mRNA expression were observed in juveniles during both short- and long-term exposure. However a transiently increased demand of ion regulatory demand was evident during the initial acclimation reaction to elevated seawater pCO2. Gill Na+/K+-ATPase activity and protein concentration were increased by approximately 15% in during short (2-11 day), but not long term (42 day) exposure. Our findings support the hypothesis that the energy budget of adult cephalopods is not significantly compromised during long-term exposure to moderate environmental hypercapnia. However, the down regulation of ion-regulatory and metabolic genes in late stage embryos, taken together with a significant reduction in somatic growth, indicates that cephalopod early life stages are challenged by elevated seawater pCO2.
Resumo:
AIMS: Mutation detection accuracy has been described extensively; however, it is surprising that pre-PCR processing of formalin-fixed paraffin-embedded (FFPE) samples has not been systematically assessed in clinical context. We designed a RING trial to (i) investigate pre-PCR variability, (ii) correlate pre-PCR variation with EGFR/BRAF mutation testing accuracy and (iii) investigate causes for observed variation. METHODS: 13 molecular pathology laboratories were recruited. 104 blinded FFPE curls including engineered FFPE curls, cell-negative FFPE curls and control FFPE tissue samples were distributed to participants for pre-PCR processing and mutation detection. Follow-up analysis was performed to assess sample purity, DNA integrity and DNA quantitation. RESULTS: Rate of mutation detection failure was 11.9%. Of these failures, 80% were attributed to pre-PCR error. Significant differences in DNA yields across all samples were seen using analysis of variance (p
Resumo:
Membrane proteins, which reside in the membranes of cells, play a critical role in many important biological processes including cellular signaling, immune response, and material and energy transduction. Because of their key role in maintaining the environment within cells and facilitating intercellular interactions, understanding the function of these proteins is of tremendous medical and biochemical significance. Indeed, the malfunction of membrane proteins has been linked to numerous diseases including diabetes, cirrhosis of the liver, cystic fibrosis, cancer, Alzheimer's disease, hypertension, epilepsy, cataracts, tubulopathy, leukodystrophy, Leigh syndrome, anemia, sensorineural deafness, and hypertrophic cardiomyopathy.1-3 However, the structure of many of these proteins and the changes in their structure that lead to disease-related malfunctions are not well understood. Additionally, at least 60% of the pharmaceuticals currently available are thought to target membrane proteins, despite the fact that their exact mode of operation is not known.4-6 Developing a detailed understanding of the function of a protein is achieved by coupling biochemical experiments with knowledge of the structure of the protein. Currently the most common method for obtaining three-dimensional structure information is X-ray crystallography. However, no a priori methods are currently available to predict crystallization conditions for a given protein.7-14 This limitation is currently overcome by screening a large number of possible combinations of precipitants, buffer, salt, and pH conditions to identify conditions that are conducive to crystal nucleation and growth.7,9,11,15-24 Unfortunately, these screening efforts are often limited by difficulties associated with quantity and purity of available protein samples. While the two most significant bottlenecks for protein structure determination in general are the (i) obtaining sufficient quantities of high quality protein samples and (ii) growing high quality protein crystals that are suitable for X-ray structure determination,7,20,21,23,25-47 membrane proteins present additional challenges. For crystallization it is necessary to extract the membrane proteins from the cellular membrane. However, this process often leads to denaturation. In fact, membrane proteins have proven to be so difficult to crystallize that of the more than 66,000 structures deposited in the Protein Data Bank,48 less than 1% are for membrane proteins, with even fewer present at high resolution (< 2Å)4,6,49 and only a handful are human membrane proteins.49 A variety of strategies including detergent solubilization50-53 and the use of artificial membrane-like environments have been developed to circumvent this challenge.43,53-55 In recent years, the use of a lipidic mesophase as a medium for crystallizing membrane proteins has been demonstrated to increase success for a wide range of membrane proteins, including human receptor proteins.54,56-62 This in meso method for membrane protein crystallization, however, is still by no means routine due to challenges related to sample preparation at sub-microliter volumes and to crystal harvesting and X-ray data collection. This dissertation presents various aspects of the development of a microfluidic platform to enable high throughput in meso membrane protein crystallization at a level beyond the capabilities of current technologies. Microfluidic platforms for protein crystallization and other lab-on-a-chip applications have been well demonstrated.9,63-66 These integrated chips provide fine control over transport phenomena and the ability to perform high throughput analyses via highly integrated fluid networks. However, the development of microfluidic platforms for in meso protein crystallization required the development of strategies to cope with extremely viscous and non-Newtonian fluids. A theoretical treatment of highly viscous fluids in microfluidic devices is presented in Chapter 3, followed by the application of these strategies for the development of a microfluidic mixer capable of preparing a mesophase sample for in meso crystallization at a scale of less than 20 nL in Chapter 4. This approach was validated with the successful on chip in meso crystallization of the membrane protein bacteriorhodopsin. In summary, this is the first report of a microfluidic platform capable of performing in meso crystallization on-chip, representing a 1000x reduction in the scale at which mesophase trials can be prepared. Once protein crystals have formed, they are typically harvested from the droplet they were grown in and mounted for crystallographic analysis. Despite the high throughput automation present in nearly all other aspects of protein structure determination, the harvesting and mounting of crystals is still largely a manual process. Furthermore, during mounting the fragile protein crystals can potentially be damaged, both from physical and environmental shock. To circumvent these challenges an X-ray transparent microfluidic device architecture was developed to couple the benefits of scale, integration, and precise fluid control with the ability to perform in situ X-ray analysis (Chapter 5). This approach was validated successfully by crystallization and subsequent on-chip analysis of the soluble proteins lysozyme, thaumatin, and ribonuclease A and will be extended to microfluidic platforms for in meso membrane protein crystallization. The ability to perform in situ X-ray analysis was shown to provide extremely high quality diffraction data, in part as a result of not being affected by damage due to physical handling of the crystals. As part of the work described in this thesis, a variety of data collection strategies for in situ data analysis were also tested, including merging of small slices of data from a large number of crystals grown on a single chip, to allow for diffraction analysis at biologically relevant temperatures. While such strategies have been applied previously,57,59,61,67 they are potentially challenging when applied via traditional methods due to the need to grow and then mount a large number of crystals with minimal crystal-to-crystal variability. The integrated nature of microfluidic platforms easily enables the generation of a large number of reproducible crystallization trials. This, coupled with in situ analysis capabilities has the potential of being able to acquire high resolution structural data of proteins at biologically relevant conditions for which only small crystals, or crystals which are adversely affected by standard cryocooling techniques, could be obtained (Chapters 5 and 6). While the main focus of protein crystallography is to obtain three-dimensional protein structures, the results of typical experiments provide only a static picture of the protein. The use of polychromatic or Laue X-ray diffraction methods enables the collection of time resolved structural information. These experiments are very sensitive to crystal quality, however, and often suffer from severe radiation damage due to the intense polychromatic X-ray beams. Here, as before, the ability to perform in situ X-ray analysis on many small protein crystals within a microfluidic crystallization platform has the potential to overcome these challenges. An automated method for collecting a "single-shot" of data from a large number of crystals was developed in collaboration with the BioCARS team at the Advanced Photon Source at Argonne National Laboratory (Chapter 6). The work described in this thesis shows that, even more so than for traditional structure determination efforts, the ability to grow and analyze a large number of high quality crystals is critical to enable time resolved structural studies of novel proteins. In addition to enabling X-ray crystallography experiments, the development of X-ray transparent microfluidic platforms also has tremendous potential to answer other scientific questions, such as unraveling the mechanism of in meso crystallization. For instance, the lipidic mesophases utilized during in meso membrane protein crystallization can be characterized by small angle X-ray diffraction analysis. Coupling in situ analysis with microfluidic platforms capable of preparing these difficult mesophase samples at very small volumes has tremendous potential to enable the high throughput analysis of these systems on a scale that is not reasonably achievable using conventional sample preparation strategies (Chapter 7). In collaboration with the LS-CAT team at the Advanced Photon Source, an experimental station for small angle X-ray analysis coupled with the high quality visualization capabilities needed to target specific microfluidic samples on a highly integrated chip is under development. Characterizing the phase behavior of these mesophase systems and the effects of various additives present in crystallization trials is key for developing an understanding of how in meso crystallization occurs. A long term goal of these studies is to enable the rational design of in meso crystallization experiments so as to avoid or limit the need for high throughput screening efforts. In summary, this thesis describes the development of microfluidic platforms for protein crystallization with in situ analysis capabilities. Coupling the ability to perform in situ analysis with the small scale, fine control, and the high throughput nature of microfluidic platforms has tremendous potential to enable a new generation of crystallographic studies and facilitate the structure determination of important biological targets. The development of platforms for in meso membrane protein crystallization is particularly significant because they enable the preparation of highly viscous mixtures at a previously unachievable scale. Work in these areas is ongoing and has tremendous potential to improve not only current the methods of protein crystallization and crystallography, but also to enhance our knowledge of the structure and function of proteins which could have a significant scientific and medical impact on society as a whole. The microfluidic technology described in this thesis has the potential to significantly advance our understanding of the structure and function of membrane proteins, thereby aiding the elucidation of human biology, the development of pharmaceuticals with fewer side effects for a wide range of diseases. References (1) Quick, M.; Javitch, J. A. P Natl Acad Sci USA 2007, 104, 3603. (2) Trubetskoy, V. S.; Burke, T. J. Am Lab 2005, 37, 19. (3) Pecina, P.; Houstkova, H.; Hansikova, H.; Zeman, J.; Houstek, J. Physiol Res 2004, 53, S213. (4) Arinaminpathy, Y.; Khurana, E.; Engelman, D. M.; Gerstein, M. B. Drug Discovery Today 2009, 14, 1130. (5) Overington, J. P.; Al-Lazikani, B.; Hopkins, A. L. Nat Rev Drug Discov 2006, 5, 993. (6) Dauter, Z.; Lamzin, V. S.; Wilson, K. S. Current Opinion in Structural Biology 1997, 7, 681. (7) Hansen, C.; Quake, S. R. Current Opinion in Structural Biology 2003, 13, 538. (8) Govada, L.; Carpenter, L.; da Fonseca, P. C. A.; Helliwell, J. R.; Rizkallah, P.; Flashman, E.; Chayen, N. E.; Redwood, C.; Squire, J. M. J Mol Biol 2008, 378, 387. (9) Hansen, C. L.; Skordalakes, E.; Berger, J. M.; Quake, S. R. P Natl Acad Sci USA 2002, 99, 16531. (10) Leng, J.; Salmon, J.-B. Lab Chip 2009, 9, 24. (11) Zheng, B.; Gerdts, C. J.; Ismagilov, R. F. Current Opinion in Structural Biology 2005, 15, 548. (12) Lorber, B.; Delucas, L. J.; Bishop, J. B. J Cryst Growth 1991, 110, 103. (13) Talreja, S.; Perry, S. L.; Guha, S.; Bhamidi, V.; Zukoski, C. F.; Kenis, P. J. A. The Journal of Physical Chemistry B 2010, 114, 4432. (14) Chayen, N. E. Current Opinion in Structural Biology 2004, 14, 577. (15) He, G. W.; Bhamidi, V.; Tan, R. B. H.; Kenis, P. J. A.; Zukoski, C. F. Cryst Growth Des 2006, 6, 1175. (16) Zheng, B.; Tice, J. D.; Roach, L. S.; Ismagilov, R. F. Angew Chem Int Edit 2004, 43, 2508. (17) Li, L.; Mustafi, D.; Fu, Q.; Tereshko, V.; Chen, D. L. L.; Tice, J. D.; Ismagilov, R. F. P Natl Acad Sci USA 2006, 103, 19243. (18) Song, H.; Chen, D. L.; Ismagilov, R. F. Angew Chem Int Edit 2006, 45, 7336. (19) van der Woerd, M.; Ferree, D.; Pusey, M. Journal of Structural Biology 2003, 142, 180. (20) Ng, J. D.; Gavira, J. A.; Garcia-Ruiz, J. M. Journal of Structural Biology 2003, 142, 218. (21) Talreja, S.; Kenis, P. J. A.; Zukoski, C. F. Langmuir 2007, 23, 4516. (22) Hansen, C. L.; Quake, S. R.; Berger, J. M. US, 2007. (23) Newman, J.; Fazio, V. J.; Lawson, B.; Peat, T. S. Cryst Growth Des 2010, 10, 2785. (24) Newman, J.; Xu, J.; Willis, M. C. Acta Crystallographica Section D 2007, 63, 826. (25) Collingsworth, P. D.; Bray, T. L.; Christopher, G. K. J Cryst Growth 2000, 219, 283. (26) Durbin, S. D.; Feher, G. Annu Rev Phys Chem 1996, 47, 171. (27) Talreja, S.; Kim, D. Y.; Mirarefi, A. Y.; Zukoski, C. F.; Kenis, P. J. A. J Appl Crystallogr 2005, 38, 988. (28) Yoshizaki, I.; Nakamura, H.; Sato, T.; Igarashi, N.; Komatsu, H.; Yoda, S. J Cryst Growth 2002, 237, 295. (29) Anderson, M. J.; Hansen, C. L.; Quake, S. R. P Natl Acad Sci USA 2006, 103, 16746. (30) Hansen, C. L.; Sommer, M. O. A.; Quake, S. R. P Natl Acad Sci USA 2004, 101, 14431. (31) Lounaci, M.; Rigolet, P.; Abraham, C.; Le Berre, M.; Chen, Y. Microelectron Eng 2007, 84, 1758. (32) Zheng, B.; Roach, L. S.; Ismagilov, R. F. J Am Chem Soc 2003, 125, 11170. (33) Zhou, X.; Lau, L.; Lam, W. W. L.; Au, S. W. N.; Zheng, B. Anal. Chem. 2007. (34) Cherezov, V.; Caffrey, M. J Appl Crystallogr 2003, 36, 1372. (35) Qutub, Y.; Reviakine, I.; Maxwell, C.; Navarro, J.; Landau, E. M.; Vekilov, P. G. J Mol Biol 2004, 343, 1243. (36) Rummel, G.; Hardmeyer, A.; Widmer, C.; Chiu, M. L.; Nollert, P.; Locher, K. P.; Pedruzzi, I.; Landau, E. M.; Rosenbusch, J. P. Journal of Structural Biology 1998, 121, 82. (37) Gavira, J. A.; Toh, D.; Lopez-Jaramillo, J.; Garcia-Ruiz, J. M.; Ng, J. D. Acta Crystallogr D 2002, 58, 1147. (38) Stevens, R. C. Current Opinion in Structural Biology 2000, 10, 558. (39) Baker, M. Nat Methods 2010, 7, 429. (40) McPherson, A. In Current Topics in Membranes, Volume 63; Volume 63 ed.; DeLucas, L., Ed.; Academic Press: 2009, p 5. (41) Gabrielsen, M.; Gardiner, A. T.; Fromme, P.; Cogdell, R. J. In Current Topics in Membranes, Volume 63; Volume 63 ed.; DeLucas, L., Ed.; Academic Press: 2009, p 127. (42) Page, R. In Methods in Molecular Biology: Structural Proteomics - High Throughput Methods; Kobe, B., Guss, M., Huber, T., Eds.; Humana Press: Totowa, NJ, 2008; Vol. 426, p 345. (43) Caffrey, M. Ann Rev Biophys 2009, 38, 29. (44) Doerr, A. Nat Methods 2006, 3, 244. (45) Brostromer, E.; Nan, J.; Li, L.-F.; Su, X.-D. Biochemical and Biophysical Research Communications 2009, 386, 634. (46) Li, G.; Chen, Q.; Li, J.; Hu, X.; Zhao, J. Anal Chem 2010, 82, 4362. (47) Jia, Y.; Liu, X.-Y. The Journal of Physical Chemistry B 2006, 110, 6949. (48) RCSB Protein Data Bank. http://www.rcsb.org/ (July 11, 2010). (49) Membrane Proteins of Known 3D Structure. http://blanco.biomol.uci.edu/Membrane_Proteins_xtal.html (July 11, 2010). (50) Michel, H. Trends Biochem Sci 1983, 8, 56. (51) Rosenbusch, J. P. Journal of Structural Biology 1990, 104, 134. (52) Garavito, R. M.; Picot, D. Methods 1990, 1, 57. (53) Kulkarni, C. V. 2010; Vol. 12, p 237. (54) Landau, E. M.; Rosenbusch, J. P. P Natl Acad Sci USA 1996, 93, 14532. (55) Pebay-Peyroula, E.; Rummel, G.; Rosenbusch, J. P.; Landau, E. M. Science 1997, 277, 1676. (56) Cherezov, V.; Liu, W.; Derrick, J. P.; Luan, B.; Aksimentiev, A.; Katritch, V.; Caffrey, M. Proteins: Structure, Function, and Bioinformatics 2008, 71, 24. (57) Cherezov, V.; Rosenbaum, D. M.; Hanson, M. A.; Rasmussen, S. G. F.; Thian, F. S.; Kobilka, T. S.; Choi, H. J.; Kuhn, P.; Weis, W. I.; Kobilka, B. K.; Stevens, R. C. Science 2007, 318, 1258. (58) Cherezov, V.; Yamashita, E.; Liu, W.; Zhalnina, M.; Cramer, W. A.; Caffrey, M. J Mol Biol 2006, 364, 716. (59) Jaakola, V. P.; Griffith, M. T.; Hanson, M. A.; Cherezov, V.; Chien, E. Y. T.; Lane, J. R.; IJzerman, A. P.; Stevens, R. C. Science 2008, 322, 1211. (60) Rosenbaum, D. M.; Cherezov, V.; Hanson, M. A.; Rasmussen, S. G. F.; Thian, F. S.; Kobilka, T. S.; Choi, H. J.; Yao, X. J.; Weis, W. I.; Stevens, R. C.; Kobilka, B. K. Science 2007, 318, 1266. (61) Wacker, D.; Fenalti, G.; Brown, M. A.; Katritch, V.; Abagyan, R.; Cherezov, V.; Stevens, R. C. J Am Chem Soc 2010, 132, 11443. (62) Höfer, N.; Aragão, D.; Caffrey, M. Biophys J 2010, 99, L23. (63) Li, L.; Ismagilov, R. F. Ann Rev Biophys 2010. (64) Pal, R.; Yang, M.; Lin, R.; Johnson, B. N.; Srivastava, N.; Razzacki, S. Z.; Chomistek, K. J.; Heldsinger, D. C.; Haque, R. M.; Ugaz, V. M.; Thwar, P. K.; Chen, Z.; Alfano, K.; Yim, M. B.; Krishnan, M.; Fuller, A. O.; Larson, R. G.; Burke, D. T.; Burns, M. A. Lab Chip 2005, 5, 1024. (65) Jayashree, R. S.; Gancs, L.; Choban, E. R.; Primak, A.; Natarajan, D.; Markoski, L. J.; Kenis, P. J. A. J Am Chem Soc 2005, 127, 16758. (66) Wootton, R. C. R.; deMello, A. J. Chem Commun 2004, 266. (67) McPherson, A. J Appl Crystallogr 2000, 33, 397.
Resumo:
Streptococcus pneumoniae is a human pathobiont that colonizes the nasopharynx. S. pneumoniae is responsible for causing non-invasive and invasive disease such as otitis, pneumonia, meningitis, and sepsis, being a leading cause of infectious diseases worldwide. Due to similarities with closely related species sharing the same niche, it may be a challenge to correctly distinguish S. pneumoniae from its relatives when using only non-culture based methods such as real time PCR (qPCR). In 2007, a molecular method targeting the major autolysin (lytA) of S. pneumoniae by a qPCR assay was proposed by Carvalho and collaborators to identify pneumococcus. Since then, this method has been widely used worldwide. In 2013, the gene encoding for the ABC iron transporter lipoprotein PiaA, was proposed by Trzcinzki and collaborators to be used in parallel with the lytA qPCR assay. However, the presence of lytA gene homologues has been described in closely related species such as S. pseudopneumoniae and S. mitis and the presence of piaA gene is not ubiquitous between S. pneumoniae. The hyaluronate lyase gene (hylA) has been described to be ubiquitous in S. pneumoniae. This gene has not been used so far as a target for the identification of S. pneumoniae. The aims of our study were to evaluate the specificity, sensitivity, positive predicted value (PPV) and negative predicted value (NPV) of the lytA and piaA qPCR methods; design and implement a new assay targeting the hylA gene and evaluate the same parameters above described; analyze the assays independently and the possible combinations to access what is the best approach using qPCR to identify S. pneumoniae. A total of 278 previously characterized strains were tested: 61 S. pseudopneumoniae, 37 Viridans group strains, 30 type strains from other streptococcal species and 150 S. pneumoniae strains. The collection included both carriage and disease isolates. By Mulilocus Sequence Analysis (MLSA) we confirmed that strains of S. pseudopneumoniae could be misidentified as S. pneumoniae when lytA qPCR assay is used. The results showed that as a single target, lytA had the best combination of specificity, sensitivity, PPV and NPV being, 98.5%, 100.0%, 98.7% and 100.0% respectively. The combination of targets with the best values of specificity, sensibility, PPV and NPV were lytA and piaA, with 100.0%, 93.3%, 97.9% and 92.6%, respectively. Nonetheless by MLSA we confirmed that strains of S. pseudopneumoniae could be misidentified as S. pneumoniae and some capsulated (23F, 6B and 11A) and non-capsulated S. pneumoniae were not Identified using this assay. The hylA gene as a single target had the lowest PPV. Nonetheless it was capable to correctly identify all S. pneumoniae.
Resumo:
A wide range of studies have shown that liposomes can act as suitable adjuvants for a range of vaccine antigens. Properties such as their amphiphilic character and biphasic nature allow them to incorporate antigens within the lipid bilayer, on the surface, or encapsulated within the inner core. However, appropriate methods for the manufacture of liposomes are limited and this has resulted in issues with cost, supply, and wider scale application of these systems. Within this chapter we explore manufacturing processes that can be used for the production of liposomal adjuvants, and we outline new manufacturing methods can that offer fast, scalable, and cost-effective production of liposomal adjuvants.
Resumo:
The present Thesis reports on the various research projects to which I have contributed during my PhD period, working with several research groups, and whose results have been communicated in a number of scientific publications. The main focus of my research activity was to learn, test, exploit and extend the recently developed vdW-DFT (van der Waals corrected Density Functional Theory) methods for computing the structural, vibrational and electronic properties of ordered molecular crystals from first principles. A secondary, and more recent, research activity has been the analysis with microelectrostatic methods of Molecular Dynamics (MD) simulations of disordered molecular systems. While only very unreliable methods based on empirical models were practically usable until a few years ago, accurate calculations of the crystal energy are now possible, thanks to very fast modern computers and to the excellent performance of the best vdW-DFT methods. Accurate energies are particularly important for describing organic molecular solids, since they often exhibit several alternative crystal structures (polymorphs), with very different packing arrangements but very small energy differences. Standard DFT methods do not describe the long-range electron correlations which give rise to the vdW interactions. Although weak, these interactions are extremely sensitive to the packing arrangement, and neglecting them used to be a problem. The calculations of reliable crystal structures and vibrational frequencies has been made possible only recently, thanks to development of some good representations of the vdW contribution to the energy (known as “vdW corrections”).
Resumo:
This chapter provides a short review of quantum dots (QDs) physics, applications, and perspectives. The main advantage of QDs over bulk semiconductors is the fact that the size became a control parameter to tailor the optical properties of new materials. Size changes the confinement energy which alters the optical properties of the material, such as absorption, refractive index, and emission bands. Therefore, by using QDs one can make several kinds of optical devices. One of these devices transforms electrons into photons to apply them as active optical components in illumination and displays. Other devices enable the transformation of photons into electrons to produce QDs solar cells or photodetectors. At the biomedical interface, the application of QDs, which is the most important aspect in this book, is based on fluorescence, which essentially transforms photons into photons of different wavelengths. This chapter introduces important parameters for QDs' biophotonic applications such as photostability, excitation and emission profiles, and quantum efficiency. We also present the perspectives for the use of QDs in fluorescence lifetime imaging (FLIM) and Förster resonance energy transfer (FRET), so useful in modern microscopy, and how to take advantage of the usually unwanted blinking effect to perform super-resolution microscopy.
Resumo:
Fluorescence Correlation Spectroscopy (FCS) is an optical technique that allows the measurement of the diffusion coefficient of molecules in a diluted sample. From the diffusion coefficient it is possible to calculate the hydrodynamic radius of the molecules. For colloidal quantum dots (QDs) the hydrodynamic radius is valuable information to study interactions with other molecules or other QDs. In this chapter we describe the main aspects of the technique and how to use it to calculate the hydrodynamic radius of quantum dots (QDs).
Resumo:
Proteins containing PilZ domains are widespread in Gram-negative bacteria and have recently been shown to be involved in the control of biofilm formation, adherence, aggregation, virulence-factor production and motility. Furthermore, some PilZ domains have recently been shown to bind the second messenger bis(3'-> 5') cyclic diGMP. Here, the cloning, expression, purification and crystallization of PilZ(XAC1133), a protein consisting of a single PilZ domain from Xanthomonas axonopodis pv. citri, is reported. The closest PilZ(XAC1133) homologues in Pseudomonas aeruginosa and Neisseria meningitidis control type IV pilus function. Recombinant PilZ(XAC1133) containing selenomethionine was crystallized in space group P6(1). The unit-cell parameters were a = 62.125, b = 62.125, c = 83.543 angstrom. These crystals diffracted to 1.85 angstrom resolution and a MAD data set was collected at a synchrotron source. The calculated Matthews coefficient suggested the presence of two PilZ(XAC1133) molecules in the asymmetric unit.
Resumo:
LipL32 is a major surface protein that is expressed during infection by pathogenic Leptospira. Here, the crystallization of recombinant LipL32(21-272), which corresponds to the mature LipL32 protein minus its N-terminal lipid-anchored cysteine residue, is described. Selenomethionine-labelled LipL32(21-272) crystals diffracted to 2.25 angstrom resolution at a synchrotron source. The space group was P3(1)21 or P3(2)21 and the unit-cell parameters were a = b = 126.7, c = 96.0 angstrom.
Resumo:
Maltose-binding protein is the periplasmic component of the ABC transporter responsible for the uptake of maltose/maltodextrins. The Xanthomonas axonopodis pv. citri maltose-binding protein MalE has been crystallized at 293 Kusing the hanging-drop vapour-diffusion method. The crystal belonged to the primitive hexagonal space group P6(1)22, with unit-cell parameters a = 123.59, b = 123.59, c = 304.20 angstrom, and contained two molecules in the asymetric unit. It diffracted to 2.24 angstrom resolution.
Resumo:
Glutathione S-transferases (GSTs) form a group of multifunctional isoenzymes that catalyze the glutathione-dependent conjugation and reduction reactions involved in the cellular detoxification of xenobiotic and endobiotic compounds. GST from Xylella fastidiosa (xfGST) was overexpressed in Escherichia coli and purified by conventional affinity chromatography. In this study, the crystallization and preliminary X-ray analysis of xfGST is described. The purified protein was crystallized by the vapour-diffusion method, producing crystals that belonged to the triclinic space group P1. The unit-cell parameters were a = 47.73, b = 87.73, c = 90.74 angstrom, alpha = 63.45, beta = 80.66, gamma = 94.55 degrees. xfGST crystals diffracted to 2.23 angstrom resolution on a rotating-anode X-ray source.
Resumo:
The filamentous fungus Trichoderma harzianum has a considerable cellulolytic activity that is mediated by a complex of enzymes which are essential for the hydrolysis of microcrystalline cellulose. These enzymes were produced by the induction of T. harzianum with microcrystalline cellulose (Avicel) under submerged fermentation in a bioreactor. The catalytic core domain (CCD) of cellobiohydrolase I (CBHI) was purified from the extracellular extracts and submitted to robotic crystallization. Diffraction-quality CBHI CCD crystals were grown and an X-ray diffraction data set was collected under cryogenic conditions using a synchrotron-radiation source.
Resumo:
Interleukin-22 (IL-22) is a pleiotropic cytokine that is involved in inflammatory responses. Human IL-22 was incubated with its soluble decoy receptor IL-22BP (IL-22 binding protein) and the IL-22 -IL-22BP complex was crystallized in hanging drops using the vapour-diffusion method. Suitable crystals were obtained from polyethylene glycol solutions and diffraction data were collected to 2.75 angstrom resolution. The crystal belonged to the tetragonal space group P41, with unit-cell parameters a = b = 67.9, c = 172.5 angstrom, and contained two IL-22-IL- 22BP complexes per asymmetric unit.