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1.
《Current opinion in cell biology》2000,12(5):525-535
A selection of interesting papers that were published in the two months before our press date in major journals most likely to report significant results in cell biology.
Contents (chosen by) | |||||||||
525 | Cytoskeleton (Desai and Holleran) | ||||||||
526 | Cell regulation (Roche, Servant and Weiner) | ||||||||
528 | Nucleus and gene expression (Aasland and Weinzierl) | ||||||||
529 | Membranes and sorting (Ponnambalam) | ||||||||
530 | Membrane permeability (Slesinger) | ||||||||
531 | Cell-to-cell contact and extracellular matrix (Pfaff) | ||||||||
533 | Cell differentiation (van Roessel, Kaltschmidt, Tsang and Huckriede) | ||||||||
534 | Cell multiplication (Sclafani) |
Mean (%) | ||||
Type of colonies | t Score | P Value | Unfrozen | Frozen |
Erythrocytic | 26.283 | 14.100 | 2.09 | 0.059 |
Granulocytic | 23.741 | 32.917 | 1.45 | 0.173 |
Mixed | 49.321 | 52.700 | 0.55 | 0.59 |
- a
- . the presence of pluripotent hemopoietic precursor cells in cryopreserved 0-, 3-, 6-, 9-, and 12-hr postmortem murine bone marrow cells. Apparently, the erythropoietic precursor cells are more sensitive to freezing injury as compared to granulopoietic precursor cells.
3.
Recent development of titratable coions has paved the way for realizing all-atom molecular dynamics at constant pH. To further improve physical realism, here we describe a technique in which proton titration of the solute is directly coupled to the interconversion between water and hydroxide or hydronium. We test the new method in replica-exchange continuous constant pH molecular dynamics simulations of three proteins, HP36, BBL, and HEWL. The calculated pKa values based on 10-ns sampling per replica have the average absolute and root-mean-square errors of 0.7 and 0.9 pH units, respectively. Introducing titratable water in molecular dynamics offers a means to model proton exchange between solute and solvent, thus opening a door to gaining new insights into the intricate details of biological phenomena involving proton translocation.Solution pH is an important factor in biology. Although neutral pH in extracellular medium accounts for balanced electrostatics and proper folding of protein structures, pH gradients across cell membranes induce large conformational changes that are necessary for biological functions, such as ATP synthesis and efflux of small molecules out of the cell. To gain detailed insights into pH-dependent conformational phenomena, several constant pH molecular dynamics (pHMD) methods, based on either discrete or continuous titration coordinates, have been developed in the last decade (1–4). In the continuous pHMD (CpHMD) framework (2,4), a set of titration coordinates {λi} are simultaneously propagated along with the conformational degrees of freedom. Although the original CpHMD method based on the generalized Born (GB) implicit-solvent models (2,4) offers quantitative prediction of pKa values and pH dependence of folding and conformational dynamics of proteins (5), its accuracy and applicability to highly charged systems and those with dominantly hydrophobic regions are limited due to the approximate nature of the underlying implicit-solvent models.Motivated by the above-mentioned need, three groups have made efforts to develop a CpHMD method using exclusively the explicit-solvent models (6–8). In our development, the titration of acidic and basic sites is coupled with that of coions to level the total charge of the system (8). To further improve physical realism, here we replace the coions by titratable water molecules, which not only absorb the excess charge but also enable direct modeling of solute-solvent proton exchange in classical molecular dynamics simulations.To illustrate the utility of the new methodology, we applied it to the titration simulations of three proteins that were previously used to benchmark the GB-based CpHMD. Although this work does not explore specific interactions between titratable waters and proteins, the methodology can be further tested or improved to provide a rigorous way for modeling proton transfer in molecular dynamics, which is a computationally efficient alternative to the empirical valence-bond theory-based methodologies (9,10).We define titration of water as:
Open in a separate windowaTaken from Wallace and Shen (12). The pKa''s of BBL were recalculated.bSampling time per pH replica.Breaking the simulations in two halves, we noticed that the second 5-ns sampling gave better agreement with experiment. The RMS deviation is reduced from 1.2 to 0.9 pH units, while the average absolute deviation is reduced from 1.0 to 0.6 pH units. The linear regression against experimental data is also improved, with the slope decreasing from 1.4 to 1.1 although R2 remains the same. Comparing these second-half results with the GB-based simulations, we find that the RMS and average absolute deviations are about the same as the GB-CpHMD results; however, the all-atom simulations show a small systematic overestimation (regression slope >1), whereas GB simulations show a systematic underestimation (regression slope <1).The improvement in the second halves of the simulations are seen mainly for residues involved in attractive electrostatic interactions, including Asp44 and Asp46 of HP36, Asp129 of BBL, and Asp48, Asp66, and Asp87 of HEWL. These residues are initially locked in salt-bridges or hydrogen bonds. However, in the second 5 ns, the attractive interactions weakened, leading to a decrease in the calculated pKa shifts relative to the model values and better agreement with experiment. For instance, Asp44 was initially in a salt-bridge distance from Arg55. However, the salt-bridge positions were sampled less often in the second 5 ns (see Fig. S5), which explains the 1-unit reduction in the calculated pKa shift. Significant fluctuation in ion-pair interactions was also observed in the work by Alexov (11). The carboxyl oxygen of Asp46 was a hydrogen-bond acceptor with both the backbone amide and hydroxyl of Ser43. These hydrogen bonds were less frequently sampled in the second 5 ns (see Fig. S6), leading to a decrease of the pKa shift for Asp46 by 1.3 units. These results indicate that extensive conformational sampling is necessary to give an accurate estimate of the ratio between the charged and neutral populations.Limited conformational sampling is also a contributing factor to the overestimation of the pKa shifts for buried residues (Fig. S7 and Fig. S8). The increase in SASA is correlated with the more frequent sampling of the states with λ close to 1, i.e., the deprotonated form (see Fig. S9). However, because Glu35 was buried in the starting conformation and the transition between buried and exposed states is slow compared to the simulation length, the exposed state may not be sufficiently sampled, leading to overestimation of the pKa shift.In contrast to Glu35, the SASA of Asp52 in HEWL is almost identical for both protonation states. The lack of conformational fluctuation is due to the strong hydrogen bonding with the side-chain amino group of Asn46 and Asn59 (data not shown). Overestimation of the pKa shifts for buried residues can also be attributed to the limitation of the additive force field which underestimates dielectric response in protein environment (more discussion see Supporting Material) of the pKa shifts for buried residues.Finally, to ascertain if the presence of hydroxide/hydronium introduces artifacts, we studied the interaction between hydroxide/hydronium and the titratable sites/ions. Comparing the hydroxide/hydronium with respective chloride/sodium ions, we find that the spatial distributions are nearly identical (see plots of distance distributions and radial distribution functions in Figs. S10–S13). However, the relative occupancy of the hydroxide around the neutral Asp/Glu, positive histidine, or sodium ion is 2–3 times as that of a chloride. The water-bridged interaction between sodium and chloride ions becomes much weaker when chloride is replaced by hydroxide or sodium is replaced by hydronium. By contrast, the occupancy of the hydronium around the solute is similar to that of the sodium. Furthermore, similar pKa results for these proteins were obtained when coions were used instead of titratable waters (data not shown). Thus, we believe that potential artifacts related to the ionized forms of water are negligible. Work is underway to further understand the limitations of the methodology and to explore applications to protein dynamics coupled to proton transfer.In summary, we have developed and tested titratable water models for use in all-atom CpHMD simulations. Although the benchmark pKa calculations indicate a comparable accuracy as the GB-CpHMD method, the all-atom method offers physical rigor and most importantly, it is applicable to systems that cannot be studied with GB-based simulations such as lipids and nucleic acids. We anticipate that the accuracy of this methodology can be further improved by incorporating the new-generation force fields that account for polarization. The coupling between proton titration of water and solute offers a computationally efficient way to model proton transfer in molecular mechanics simulations. 相似文献
- 1.Loss of a proton to give a negatively charged hydroxide,
- 2.Gain of a proton to give a positively charged hydronium,
Table 1
Calculated and experimental pKa values of three proteinsResidue | Experimenta | GBa | All-atom CpHMD | ||
---|---|---|---|---|---|
Time (ns)b | 0–1 | 0–5 | 5–10 | 0–10 | |
HP36 | |||||
Asp44 | 3.10 (0.01) | 3.2 (0.1) | 2.0 | 3.0 | 2.6 (0.5) |
Glu45 | 3.95 (0.01) | 3.5 (0.1) | 4.3 | 4.5 | 4.4 (0.1) |
Asp46 | 3.45 (0.12) | 3.5 (0.1) | 2.4 | 3.7 | 3.1 (0.6) |
Glu72 | 4.37 (0.03) | 3.5 (0.1) | 4.4 | 4.4 | 4.4 (0.0) |
BBL | |||||
Asp129 | 3.88 (0.02) | 3.2 (0.0) | 2.2 | 3.2 | 2.7 (0.5) |
Glu141 | 4.46 (0.04) | 4.3 (0.0) | 4.0 | 4.4 | 4.2 (0.2) |
His142 | 6.47 (0.04) | 7.1 (0.0) | 5.9 | 5.8 | 5.8 (0.0) |
Asp145 | 3.65 (0.04) | 2.8 (0.2) | 3.0 | 3.1 | 3.1 (0.0) |
Glu161 | 3.72 (0.05) | 3.6 (0.3) | 4.2 | 3.9 | 4.0 (0.2) |
Asp162 | 3.18 (0.04) | 3.4 (0.3) | 2.9 | 3.5 | 3.2 (0.3) |
Glu164 | 4.50 (0.03) | 4.5 (0.1) | 5.7 | 4.6 | 5.2 (0.6) |
His166 | 5.39 (0.02) | 5.4 (0.1) | 4.4 | 4.4 | 4.4 (0.0) |
HEWL | |||||
Glu7 | 2.6 (0.2) | 2.6 (0.1) | 3.6 | 3.4 | 3.5 (0.1) |
His15 | 5.5 (0.2) | 5.3 (0.5) | 5.1 | 5.1 | 5.1 (0.0) |
Asp18 | 2.8 (0.3) | 2.9 (0.0) | 2.5 | 3.3 | 2.9 (0.4) |
Glu35 | 6.1 (0.4) | 4.4 (0.2) | 8.5 | 8.7 | 8.6 (0.1) |
Asp48 | 1.4 (0.2) | 2.8 (0.2) | −0.1 | 1.1 | 0.6 (0.6) |
Asp52 | 3.6 (0.3) | 4.6 (0.0) | 5.4 | 5.6 | 5.5 (0.1) |
Asp66 | 1.2 (0.2) | 1.2 (0.4) | −0.6 | 0.8 | 0.3 (0.7) |
Asp87 | 2.2 (0.1) | 2.0 (0.1) | 0.8 | 2.1 | 1.5 (0.7) |
Asp101 | 4.5 (0.1) | 3.3 (0.3) | 6.1 | 5.7 | 5.9 (0.2) |
Asp119 | 3.5 (0.3) | 2.5 (0.1) | 3.0 | 3.3 | 3.2 (0.1) |
Maximum absolute deviation | 1.8 | 2.4 | 2.6 | 2.5 | |
Average absolute deviation (RMS deviation) | 0.5 (0.7) | 1.0 (1.2) | 0.6 (0.9) | 0.7 (0.9) | |
Linear fit R2 (slope) | 0.7 (0.8) | 0.8 (1.4) | 0.7 (1.1) | 0.8 (1.2) |
4.
5.
6.
Joel M. Goodman 《Journal of lipid research》2009,50(11):2148-2156
Cytosolic lipid droplets were considered until recently to be rather inert particles of stored neutral lipid. Largely through proteomics is it now known that droplets are dynamic organelles and that they participate in several important metabolic reactions as well as trafficking and interorganellar communication. In this review, the role of droplets in metabolism in the yeast Saccharomyces cerevisiae, the fly Drosophila melanogaster, and several mammalian sources are discussed, particularly focusing on those reactions shared by these organisms. From proteomics and older work, it is clear that droplets are important for fatty acid and sterol biosynthesis, fatty acid activation, and lipolysis. However, many droplet-associated enzymes are predicted to span a membrane two or more times, which suggests either that droplet structure is more complex than the current model posits, or that there are tightly bound membranes, particularly derived from the endoplasmic reticulum, which account for the association of several of these proteins.Cytosolic lipid droplets, originally thought to be simply coalesced neutral lipids waiting for lipolysis at metabolic demand, are now known to be considerably more complicated both structurally and functionally. There is general agreement that droplets are comprised of a core of neutral lipids, principally triglycerides and steryl esters, surrounded by a leaflet of phospholipids into which are embedded a specific subset of cellular proteins, the most abundant of which are members of the PAT family (see below) in animal cells (1). However, this model is probably too simple; there is evidence from physical probes of droplets isolated from yeast mutants unable to synthesize triglycerides or steryl esters that these two molecular families are partially segregated within the core, with thin shells of steryl esters forming concentric hollow spheres around an inner core composed principally of triglycerides (2).The next layer of complexity is the functional inhomogeneity of droplets. Subsets of droplets within the same cells exist with different populations of PAT proteins, differentiating among different sizes, ages, and levels of metabolic activity (3, 4). Perhaps most surprisingly, droplets may be comprised, at least in some cases, not of the layered core-phospholipid shell architecture at all but a knot of tightly woven endoplasmic reticulum (ER) surrounded by secreted neutral lipid, itself encased with a single leaflet. Such a model is based on electron microscopic thin sections (5), freeze fracture-immunogold evidence (6), immunohistochemical studies of ER luminal proteins within the droplet (7), and the identification of these proteins, notably ER chaperones, in several proteomic studies. Although certainly, such a complex structure must obey physical laws governing aqueous interactions with hydrophobic lipids and artifacts in processing for electron microscopy do occur, it may be best at present to keep an open mind and consider that droplets may not have the same structure among tissues and that they may take multiple physical forms in rapid order as they dynamically perform their functions.What are these functions? The most obvious one is lipid metabolism, namely the biogenesis and breakdown of the neutral lipids contained within the droplet. Although this conclusion predates proteomic studies (8), these recent studies have revealed the breadth and conservation of metabolic reactions that occur at or near the droplet surface, the subject of this review. Moreover, proteomics has demonstrated the surprising fact that droplets are likely to be very active in organellar communication because they are replete in rab proteins and other trafficking molecules. Our knowledge from proteomic studies of droplet trafficking and communication is discussed separately in this thematic review series.A major caveat must be kept in mind when evaluating droplet proteomics data: besides droplet trafficking through transient interactions with vesicles or target organelles such as early endosomes (9), droplets make extensive, tight, and long-lasting synapses with the endoplasmic reticulum, mitochondria, and peroxisomes (10, 11). The fact that ER, mitochondrial, peroxisomal, and a few plasma membrane proteins are found with such high frequency in the droplet proteome probably reflects these tight interorganellar interactions, perhaps similar to the mitochondrially associated membranes (MAMs) that link mitochondria with ER (12). The molecular basis for droplet-mediated synapses are not yet known. Besides the frequent occurrence of specific nondroplet organelle proteins in the droplet proteome, adventitious contamination of droplets is unlikely in view of the unique density of droplets that allow their flotation to the top of aqueous buffers and density gradients after centrifugation while all other cell components sink (which also permits several washes with high recovery), and the nonrandom coisolation of subsets of proteins from other organelles, such as the β-oxidation peroxisomal enzymes (10), which suggests specialized regions for metabolically-productive droplet interactions at the synapses.Droplet-ER interactions are a special case; it is the rule rather than the exception that enzymes of lipid metabolism that are found in the droplet proteome are also found to varying extents in the ER. This has been well documented in yeast through genome-wide green fluorescent protein (GFP)-tagging (13, 14). Erg6p, an enzyme in the latter part of the ergosterol biosynthetic pathway, is the only droplet protein in the pathway with a near-exclusive droplet localization in yeast; Erg1p, Erg7p, and Erg 27p are dually localized, and the pattern changes depending on metabolic state. Whether this general rule is specific for yeast, in which droplets remain on the ER surface (15), is not yet clear. However, several examples already exist in mammalian cells: cytochrome b5 reductase (DT diaphorase) and various sterol dehydrogenases (see 12).
Open in a separate window*Non proteomics screens.(a) (29).*(b) (GFP screen) (13).*(c) (GFP screen) (14).(d) (10).(e) (73).(f) (74).(g) (23).(h) (75).(i) (76).(j) (24).(k) (77).(l) (78).(m) (79).(n) (40).(o) (5).The metabolic functions of droplets, as revealed or confirmed by proteomic studies, can be grouped into fatty acid synthesis and activation, sterol biosynthesis, triglyceride biosynthesis, and fatty acid mobilization from sterol esters and triglycerides. 相似文献
TABLE 1.
Metabolic functions of droplets as revealed by proteomicsProtein | Reference(s) | Comments |
---|---|---|
Fatty Acid Synthesis | ||
ATP citrate lyase | (e) | Generates acetyl-CoA |
Acetyl-CoA carboxylase/ACC1 | (i) (j) (n) (o)(e) | Generates malonyl CoA |
3-Oxoacyl(ACP) synthase | (e) | Drosophila; early step in FA synthesis |
Fatty acid synthase | (e) | Drosophila |
Diaphorase 1/Cytochrome b5 reductase | (g)(h)(j) (l) (n) (o) | Redox carrier in FA elongation and many others |
Fatty acid desaturase 2 | (e) (m) | Many hydrophobic spans likely |
Fatty Acid Activation | ||
Acyl-CoA synthetase/ACSL1 | (g) (n) | Fatty acid-CoA ligase |
Acyl-CoA synthetase/ACSL3 | (g)(h)(i) (j) (l) (n) (o) | Fatty acid-CoA ligase |
Acyl-CoA synthetase/ACSL4 | (g)(h) (j) (l) (n) | Fatty acid-CoA ligase |
Acyl-CoA synthetase/ACSL5 | (m) | LACS2 |
Acyl-CoA synthetases/FAA1, FAA4, FAT1 | (a) (d) | Yeast enzymes; FAT1 is a FA transporter; may have synthetase activity |
Steroid Synthesis | ||
Squalene epoxidase/ERG1 | (a) (i) (j) (o)(d) | |
Lanosterol synthase/ERG7 | (a)(g) (h) (i) (j) (m) (o)(d) | |
NAD(P) steroid dehydrogenase like (NSDHL)/ERG26 | (g)(h) (i)(m) (o) | Sterol synthesis |
3-keto reductase 17 βHSD7/ERG27 | (b)*(c)*(g) (j)(n) (o)(d) | Sterol synthesis |
C24-methyltransferase/ERG6 | (a) (c)* (d) | Specific to ergosterol synthesis in fungi |
17 β-HSD11 (retinal short chain dehydrogenase) | (h) (i) (j) (l) (m) (n) (o) (e) | Testosterone biosynthesis; steroid metabolism |
17 β-HSD4 | (l) | Bile salt snthesis |
17 β-HSD13 | (m) | A short-chain dehydrogenase |
17 β-HSD3 | (m) | Steroid metabolism |
Triglyceride Synthesis | ||
AcylDHAP reductase/AYR1 | (d) | Determined early biochemically (68) |
LysoPA acyltransferase/SLC1 | (d) | Determined earlier biochemically (69) |
DAG acyltransferase/DGA1 | Determined biochemically in yeast (70) | |
Lipolysis | ||
Hormone-sensitive lipase | (f)(g) | Diglyceride lipase [first characterized in (71)] |
Fat-specific gene 27 | (g) | Lipase activity |
ATGL | (n) (o) | Triglyceride lipase |
Monoglyceride lipase | (m) | |
Tgl3, Tgl4, Tgl5 | (a) | Yeast triglyceride lipases [for Tgl4 and 5 see (60)] |
Tgl1p, Yeh1p | (a) | Yeast steryl ester lipases; Yeh1 localized in (62) |
PLC α | (n) | |
Phospholipase A1 | (n) | |
Lipase Modulators | ||
Perilipin | (g) | PAT family |
ADRP | (g)(h) (i) (k) (l) (m) (n) (o) | PAT family |
TIP47 | (g)(h) (l) (m) (o) | PAT family |
S3-12 | (g) | PAT family |
LSD2 | (e)(f) | PAT family (Drosophila) |
CGI-58 | (g) (i) (n) (o) (f) | Regulator of ATGL; has endogenous acyltransferase activity (72) |
Caveolin 1 | (g) (m) (n) | May bridge perilipin with PKA to stimulate lipolysis |
Other Redox Enzymes | ||
Cytochrome p450 | (e) | Mostly in ER |
Cytochrome b5 | (e) | Mostly in ER |
Alcohol dehydrogenase 4 | (j) (m)(n) (e) | Most in cytoplasm. Broad specificity, including retinols, aliphatic alcohols, and steroids |
Aldehyde dehydrogenase /ALDH3B1 | (g) | Can oxidize medium and long chain aldehydes |
Glyceraldehyde phosphate dehydrogenase | (a)(h) (l) (m) (n) (o) (e) | Cytosolic glycolytic enzyme, but often found with droplets |
Xanthine oxidoreductase | (k) | Identified in mammary tissue only |
Gulonolactone oxidase | (m) | Drosophila; missing in humans. Role in ascorbic acid synthesis |
Short-chain dehydrogenase/reductase member 1 | (g) (j) (n)(e) | Unknown substrate |
Other Enzymes | ||
Acyl-CoA:ethanol o-acyltransferase /EHT1 | (a)(d) | Generation of medium-chain ethyl esters |
SCCPDH (CGI49) | (h)(n) (o) | Degradation of lysine |
PI4 phosphatase/SAC1 | (n) | |
Serine palmitoyltransferase subunit 1 isoform a | (n) | Sphingolipid synthesis |
SAM-dependent methyltransferase | (j) | Biosynthesis of phosphatidylcholine |
Possible Contamination | ||
Sterol carrier protein 2-related form | (l) (e) | May have thiolase activity. Peroxisomal contamination? |
Palmitoyl-protein thioesterase | (j) (n) | Lysosomal contamination? |
ER carboxyesterase | (k) | Mammary; used to make triglyc for lipooproteins |
ATPsynthase2 | (g) | Mitochondrial contamination |
Carbamoyl P Synthetase 1 | (m) | Mitochondrial contamination |
Pyruvate carboxylase | (g)(k)(e) | Mitochondrial contamination? |
Fatty acid translocase/CD36 | (g) | Plasma membrane contamination? |
Lipoprotein lipase (LPL) | (g) | Plasma membrane contamination |
7.
S Mironescu 《Cryobiology》1978,15(2):178-191
Correlated studies on volume distributions and cation (Na+ and K+) content of CHO cells in suspension were carried out after various exposures to hypertonic NaCl or sucrose (500–7550 mOsm in both the presence and absence of DMSO (5–20%; ). The effects superimposed by ouabain (10?2–10?4m), amphotericin B (6–18 μg/ml), and glutaraldehyde (1.25%) on the above-mentioned parameters were also investigated. Volumetric analysis of CHO cells with the Coulter Channelyzer indicated a biphasic dose-dependent response to hypertonic media, the duration of the
TABLE 2. Correlation between Volume, Survival, and Cation Content of CHO Cells Exposed to Hypertonic Media in Suspension
Osmolality mOsm | Exposure (min) | Hypertonic agent | |||||||
NaCl | Sucrose | ||||||||
Na+ | K+ | V | Na+ | K+ | S | ||||
1000 | 60 or less | Small | High | High | High | Normal | Low | High | High |
1500–2000 | 60 or less | Small | High | Low | Low | Normal | Low | High | High |
2000 or over | 60 or more | Small or largec | High | Very low | Very low | Small | Very low | Very low | Very low |
U1‐bef | U1‐aft | U2‐bef | U2‐aft | E‐bef | E‐aft | ||
---|---|---|---|---|---|---|---|
Achnanthes biasolettiana Grunow | ABIA | 1.1 | 1.2 | 0.4 | 0.1 | 5.4 | 0.7 |
Achnanthes lanceolata (Bréb.) Grunow | ALAN | 7.2 | 1.3 | 5.7 | 7.1 | 7.3 | 2.2 |
Achnanthes minutissima Kütz. | AMIN | 56.2 | 55.0 | 81.2 | 71.4 | 52.2 | 34.5 |
Achnanthes lanceolata v. frequentissima Lange‐Bert. | ALFR | 0.0 | 0.1 | 0.1 | 0.9 | 1.0 | 0.0 |
Amphora inariensis Krammer | AINA | 1.9 | 2.0 | 0.3 | 0.1 | 1.0 | 1.4 |
Amphora ovalis (Kütz.) Kütz. | AOVA | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.3 |
Amphora pediculus (Kütz.) Grunow | APED | 0.9 | 2.2 | 0.1 | 0.6 | 3.3 | 1.3 |
Cocconeis pediculus Ehrenb. | CPED | 0.1 | 0.2 | 0.0 | 0.1 | 0.2 | 1.7 |
Cocconeis placentula Ehrenb. | CPLA | 13.7 | 20.3 | 1.8 | 8.4 | 12.3 | 32.4 |
Cymbella silesiaca Bleisch in Rabenh. | CSLE | 0.0 | 0.2 | 0.0 | 0.1 | 0.0 | 0.1 |
Diploneis oblongella (Nägeli) Cleve‐Euler | DOBL | 0.6 | 0.0 | 0.9 | 0.2 | 0.0 | 0.0 |
Fragilaria capucina var. gracilis (Øestrup) Hustedt | FCGP | 0.3 | 1.0 | 0.1 | 0.0 | 0.1 | 3.5 |
Fragilaria capucina var. capitellata (Grunow) Lange‐Bert. | FCCP | 0.0 | 0.2 | 0.0 | 0.1 | 0.4 | 0.6 |
Fragilaria ulna (Nitzsch) Lange‐Bert. | FULN | 0.2 | 1.1 | 0.1 | 0.1 | 0.0 | 1.4 |
Gomphonema angustatum (Kütz.) Rabenh. | GADI | 1.6 | 0.6 | 1.6 | 1.8 | 1.0 | 0.8 |
Gomphonema angustum C. Agardh | GANT | 0.2 | 0.1 | 0.6 | 1.2 | 1.4 | 0.1 |
Gomphonema minutum (C. Agardh) C. Agardh | GMIN | 0.2 | 0.0 | 0.3 | 0.1 | 0.3 | 0.5 |
Gomphonema pumilum (Grunow) E. Reichardt et Lange‐Bert. | GPUM | 1.7 | 0.0 | 2.0 | 1.4 | 1.1 | 0.0 |
Meridion circulare (Grev.) C. Agardh | MCIR | 0.0 | 0.1 | 1.5 | 1.7 | 0.4 | 0.2 |
Navicula antonii Lange‐Bert. | NANT | 0.8 | 0.1 | 0.1 | 0.2 | 0.8 | 0.2 |
Navicula accomoda Hust. | NARB | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Navicula capitatoradiata H. Germ. | NCPR | 0.3 | 0.0 | 0.1 | 0.1 | 0.0 | 0.3 |
Navicula cryptocephala Kütz. | NCRY | 0.5 | 0.1 | 0.1 | 0.3 | 0.5 | 0.2 |
Nitzschia linearis (C. Agardh) W. Sm. | NLIN | 0.2 | 0.0 | 0.0 | 0.2 | 0.0 | 0.1 |
Nitzschia palea (Kütz.) W. Sm. | NPAL | 0.0 | 0.0 | 0.3 | 0.2 | 0.5 | 0.2 |
Reimeria sinuata (W. Greg.) Kociolek et Stoermer | RSIN | 3.4 | 2.0 | 0.6 | 1.2 | 4.9 | 2.8 |
Rhoicosphenia abbreviata (C. Agardh) Lange‐Bert. | RABB | 8.1 | 5.0 | 0.2 | 0.4 | 3.6 | 9.9 |
Citing Literature
Volume 44 , Issue 3 June 2008
Pages 564-572 相似文献
10.
The activity levels of DNA polymerases α and β have been measured by autoradiography in squash preparations from rat testis of sexually mature animals. Similar results were obtained with ‘fixed’ samples (dipped in acetone: ethanol for 5 min at 25 °C) or ‘unfixed’ samples (frozen in liquid nitrogen and freeze-dried). The activities of DNA polymerases α and β in situ were distinguished by differential assay conditions and by selective inhibition with compounds such as N-ethylmaleimide and aphidicolin. Using the endogenous chromatin as template, maximal activity for both enzymes was obtained in the presence of all four deoxyribonucleoside triphosphates, MgCl2 and ethylene glycol. When DNA polymerase activities in several predominant testicular cell types (pre-leptotene primary spermatocytes, pachytene primary spermatocytes, round spermatids and elongated spermatids) were quantitatively compared, on a per cell basis, the following percentage distribution was observed:
Pre-leptotene primary spermatocyte % | Pachytene primary spermatocyte % | Round spermatid % | Elongated spermatid % | ||||
DNA polymerase α | 25 | 42 | 30 | 3 | |||
DNA polymerase β | 29 | 34 | 36 | 1 |
Component | Role in the pathway | PDB ID |
---|---|---|
Sgt2 | Component of the pretargeting complex that delivers TA proteins to Get3; dimer interacts with Get4/Get5, contains TPR repeats that interact with Hsps | 3SZ7 |
Get5 | Component of the pretargeting complex that delivers TA proteins to Get3; dimer interacts with Get4 via amino-terminal domain and with Sgt2 via its ubiquitin-like domain | 2LNZ 3VEJ 2LO0 |
Get4 | Component of the pretargeting complex that delivers TA proteins to Get3; interacts with Get3 via amino-terminal domain and with Get4 via carboxy-terminal domain | 3LPZ 3LKU 3WPV |
Get3 | ATPase that binds the TA protein; dimer interacts with the pretargeting complex in the cytosol, and with Get1/2 at the ER membrane | Table 2 |
Get1 | ER receptor for Get3; integral ER membrane protein, three TMDs; forms a complex with Get2 | 3SJA, 3SJB 3SJC, 3ZS8 3VLC, 3B2E |
Get2 | ER receptor for Get3; integral ER membrane protein, three TMDs; forms a complex with Get1 | 3SJD 3ZS9 |
Table 2.
An itemized list of published Get3 structures with associated nucleotides and conformation nomenclatureOrganism | Nucleotide | Conformation | PDB ID | References |
---|---|---|---|---|
Get3 | ||||
Schizosaccharomyces pombe | None | Open | 2WOO | Mateja et al. 2009 |
Saccharomyces cerevisiae | None | Open | 3H84 | Hu et al. 2009 |
3A36 | Yamagata et al. 2010 | |||
Aspergillus fumigatus | ADP | Open | 3IBG | Suloway et al. 2009 |
S. cerevisiae | ADP | Open | 3A37 | Yamagata et al. 2010 |
Debaryomyces hansenii | ADP | Closed | 3IO3 | Hu et al. 2009 |
Chaetomium thermophilum | AMPPNP-Mg2+ | Closed | 3IQW | Bozkurt et al. 2009 |
C. thermophilum | ADP-Mg2+ | Closed | 3IQX | Bozkurt et al. 2009 |
S. cerevisiae | ADP•AlF4−-Mg2+ | Fully closed | 2WOJ | Mateja et al. 2009 |
Methanothermobacter thermautotrophicus | ADP•AlF4−-Mg2+ | Fully closed | 3ZQ6 | Sherill et al. 2011 |
Methanococcus jannaschii | ADP•AlF4−-Mg2+ | Tetrameric | 3UG6 | Suloway et al. 2012 |
3UG7 | ||||
Get3/Get2cyto | ||||
S. cerevisiae | ADP-Mg2+ | Closed | 3SJD | Stefer et al. 2011 |
S. cerevisiae | ADP•AlF4−-Mg2+ | Closed | 3ZS9 | Mariappan et al. 2011 |
Get3/Get1cyto | ||||
S. cerevisiae | None | Semiopen | 3SJC | Stefer et al. 2011 |
S. cerevisiae | ADP | Semiopen | 3VLC | Kubota et al. 2012 |
S. cerevisiae | None | Open | 3SJA | Stefer et al. 2011 |
3SJB | Stefer et al. 2011 | |||
3ZS8 | Mariappan et al. 2011 | |||
ADP | Open | 3B2E | Kubota et al. 2012 |
12.
Many plant species can be induced to flower by responding to stress factors. The short-day plants Pharbitis nil and Perilla frutescens var. crispa flower under long days in response to the stress of poor nutrition or low-intensity light. Grafting experiments using two varieties of P. nil revealed that a transmissible flowering stimulus is involved in stress-induced flowering. The P. nil and P. frutescens plants that were induced to flower by stress reached anthesis, fruited and produced seeds. These seeds germinated, and the progeny of the stressed plants developed normally. Phenylalanine ammonialyase inhibitors inhibited this stress-induced flowering, and the inhibition was overcome by salicylic acid (SA), suggesting that there is an involvement of SA in stress-induced flowering. PnFT2, a P. nil ortholog of the flowering gene FLOWERING LOCUS T (FT) of Arabidopsis thaliana, was expressed when the P. nil plants were induced to flower under poor-nutrition stress conditions, but expression of PnFT1, another ortholog of FT, was not induced, suggesting that PnFT2 is involved in stress-induced flowering.Key words: flowering, stress, phenylalanine ammonia-lyase, salicylic acid, FLOWERING LOCUS T, Pharbitis nil, Perilla frutescensFlowering in many plant species is regulated by environmental factors, such as night-length in photoperiodic flowering and temperature in vernalization. On the other hand, a short-day (SD) plant such as Pharbitis nil (synonym Ipomoea nil) can be induced to flower under long days (LD) when grown under poor-nutrition, low-temperature or high-intensity light conditions.1–9 The flowering induced by these conditions is accompanied by an increase in phenylalanine ammonia-lyase (PAL) activity.10 Taken together, these facts suggest that the flowering induced by these conditions might be regulated by a common mechanism. Poor nutrition, low temperature and high-intensity light can be regarded as stress factors, and PAL activity increases under these stress conditions.11 Accordingly, we assumed that such LD flowering in P. nil might be induced by stress. Non-photoperiodic flowering has also been sporadically reported in several plant species other than P. nil, and a review of these studies suggested that most of the factors responsible for flowering could be regarded as stress. Some examples of these factors are summarized in 12–14
Open in a separate window 相似文献
Table 1
Some cases of stress-induced floweringStress factor | Species | Flowering response | Reference |
high-intensity light | Pharbitis nil | induction | 5 |
low-intensity light | Lemna paucicostata | induction | 29 |
Perilla frutescens var. crispa | induction | 14 | |
ultraviolet C | Arabidopsis thaliana | induction | 23 |
drought | Douglas-fir | induction | 30 |
tropical pasture Legumes | induction | 31 | |
lemon | induction | 32–35 | |
Ipomoea batatas | promotion | 36 | |
poor nutrition | Pharbitis nil | induction | 3, 4, 13 |
Macroptilium atropurpureum | promotion | 37 | |
Cyclamen persicum | promotion | 38 | |
Ipomoea batatas | promotion | 36 | |
Arabidopsis thaliana | induction | 39 | |
poor nitrogen | Lemna paucicostata | induction | 40 |
poor oxygen | Pharbitis nil | induction | 41 |
low temperature | Pharbitis nil | induction | 9, 12 |
high conc. GA4/7 | Douglas-fir | promotion | 42 |
girdling | Douglas-fir | induction | 43 |
root pruning | Citrus sp. | induction | 44 |
Pharbitis nil | induction | 45 | |
mechanical stimulation | Ananas comosus | induction | 46 |
suppression of root elongation | Pharbitis nil | induction | 7 |
13.
14.
A commercially available tissue culture medium has been proven capable of preserving dog kidney function for at least 24 hr after simple cooling. The advantages of using tissue culture medium as preservation fluid instead of plasma or albumin solutions from the infectious and immunological points of view are obvious. An in vitro study was completed using the tissue
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1.
Code (animal No.) | Perfusion time (br) | Perfusion pressure mm/Hg | Flow ml/min | Weight gain | pH | pO2 mm/Hg | Histological appearance |
1 | 24 | 70-60 systolic | 96 | 35 | 7.3 | 150–180 | Grossly normal |
2 | 24 | 45-40 diastolic | 108 | 30 | |||
3 | 24 | 96 | 30 | ||||
4 | 48 | 70-60 systolic | 80 | 35 | 7.3 | 150–180 | Grossly normal |
5 | 48 | 45-40 diastolic | 120 | 40 | 7.4 | ||
6 | 48 | 100 | 40 | ||||
7 | 72 | 70-60 systolic | 115 | 40 | 7.4 | 150–180 | Slight vacuolization of the tubular cells |
8 | 72 | 45-40 diastolic | 96 | 40 | |||
9 | 72 | 80 | 40 | ||||
10 | 24 | 70-60 systolic | 110 | 35 | 7.3 | 150–180 | Used for transplantation |
11 | 24 | 45-40 diastolic | 120 | 35 | |||
12 | 24 | 140 | 40 | ||||
13 | 24 | 100 | 30 | ||||
14 | 24 | 96 | 30 | ||||
Reese-Ellsworth (RE) Classification For Intraocular Retinoblastoma | |||||||
GROUP I | a. Solitary tumor, less than 4 disc diameters in size, at or behind the equator | ||||||
b. Multiple tumors, none over 4 disc diameters in size, all at or behind the equator | |||||||
GROUP II | a. Solitary tumor, less than 4 to 10 disc diameters in size, at or behind the equator | ||||||
b. Multiple tumors, none over 4 to 10 disc diameters in size, all at or behind the equator | |||||||
GROUP III | a. Any lesion anterior to the equator | ||||||
b. Solitary tumors larger than 10 disc diameters behind the equator | |||||||
GROUP IV | a. Multiple tumors, some larger than 10 disc diameters | ||||||
b. Any lesion extending anteriorly to the ora serrata | |||||||
GROUP V | a . Massive tumors involving over half the retina | ||||||
b . Vitreous seeding |
Table 2
International Classification for Retinoblastoma (ICRB) Scheme.International Classification for Intraocular Retinoblastoma (ICRB) | |
Group A | Small intraretinal tumors away from foveola and disc |
* All tumors are 3 mm or smaller in greatest dimension, confined to the retina and * All tumors are located further than 3 mm from the foveola and 1.5 mm from the optic disc | |
Group B | All remaining discrete tumors confined to the retina |
* All other tumors confined to the retina not in Group A * Tumor-associated subretinal fluid less than 3 mm from the tumor with no subretinal seeding | |
Group C | Discrete Local disease with minimal subretinal or vitreous seeding |
* Tumor(s) are discrete * Subretinal fluid, present or past, without seeding involving up to ¼ retina * Local fine vitreous seeding may be present close to discrete tumor * Local subretinal seeding less than 3 mm (2DD) from the tumor | |
Group D | Diffuse disease with significant vitreous or subretinal seeding |
* Tumor(s) may be massive or diffuse * Subretinal fluid, present or past without seeding, involving up to total retinal detachment * Diffuse or massive vitreous disease may include “greasy” seeds or avascular tumor masses * Diffuse subretinal seeding may include subretinal plaques or tumor nodules | |
Group E | Presence of any one or more of these poor prognosis features |
* Tumor touching the lens * Tumor anterior to anterior vitreous face involving ciliary body or anterior segment * Diffuse infiltrating retinoblastoma * Neovascular glaucoma * Opaque media from hemorrhage * Tumor necrosis with aseptic orbital cellulites * Phthisis bulbi |
Conclusions/Significance
Ophthalmic artery chemosurgery for retinoblastoma that was Reese-Ellsworth I, II and III (or International Classification B or C) was associated with high success (100% of treatable eyes were retained) and limited toxicity with results that equal or exceed conventional therapy with less toxicity. 相似文献18.
19.
We have studied the integrity of lysosomes in isolated rat livers perfused for 3, 4, or 6 hr at 35 °C with BSA (40 g/l) in Krebs Ringer bicarbonate buffer. The latency and sedimentability of β-glucuronidase in homogenates of these livers was well maintained even after 6 hr. The latency and sedimentability of acid phosphatase remained at about control levels during the first 4 hr of perfusion but decreased between 4 and 6 hr. These decreases in latency and sedimentability correlated with a decrease in bile production and an increase in the rate of release of GOT into the perfusate and could indicate either intracellular disruption of lysosomes
Latencies, Sedimentabilities, and Specific Activities of Acid Phosphatase and β-Glucuronidase in Homogenates of Rat Liver Prepared before or at Various Times after Exposure to 1.4 m Me2SO for 1 hr
Time (hr) | 0 | 3 | 4 | 6 |
Acid phosphatase | ||||
Latency (%) | 83.2 ± 0.8 | 64.7 ± 5.1 | 62.4 ± 7.9 | 68.9 ± 5.4 |
Sedimentability (%) | 81.7 ± 0.6 | 77.6 ± 3.1 | 81.0 ± 3.4 | 79.4 ± 5.1 |
Specific activity (mIU/mg protein) | 2.8 ± 0.4 | 2.8 ± 0.2 | 2.4 ± 0.4 | 1.6 ± 0.2 |
β-Glucuronidase | ||||
Latency (%) | 06.8 ± 1.5 | 71.3 ± 4.3 | 74.2 ± 2.5 | 63.3 ± 4.5 |
Sedimentability (%) | 69.5 ± 0.3 | 75.4 ± 3.2 | 75.0 ± 1.1 | 74.6 ± 2.0 |
Specific activity (mIU/mg protein) | 1.8 ± 0.1 | 1.6 ± 0.1 | 1.6 ± 0.2 | 1.6 ± 0.2 |
No Vertigo | Improved | Unchanged | |
Number of patients | 7 | 5 | 3 |
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