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1.
In this short report, the genome-wide homologous recombination events were re-evaluated for classical swine fever virus (CSFV) strain AF407339. We challenged a previous study which suggested only one recombination event in AF407339 based on 25 CSFV genomes. Through our re-analysis on the 25 genomes in the previous study and the 41 genomes used in the present study, we argued that there should be possibly at least two clear recombination events happening in AF407339 through genome-wide scanning. The reasons for identifying only one recombination event in the previous study might be due to the limited number of available CSFV genome sequences at that time and the limited usage of detection methods. In contrast, as identified by most detection methods using all available CSFV genome sequences, two major recombination events were found at the starting and ending zones of the genome AF407339, respectively. The first one has two parents AF333000 (minor) and AY554397 (major) with beginning and ending breakpoints located at 19 and 607 nt of the genome respectively. The second one has two parents AF531433 (minor) and GQ902941 (major) with beginning and ending breakpoints at 8397 and 11,078 nt of the genome respectively. Phylogenetic incongruence analysis using neighbor-joining algorithm with 1000 bootstrapping replicates further supported the existence of these two recombination events. In addition, we also identified additional 18 recombination events on the available CSFV strains. Some of them may be trivial and can be ignored. In conclusion, CSFV might have relatively high frequency of homologous recombination events. Genome-wide scanning of identifying recombination events should utilize multiple detection methods so as to reduce the risk of misidentification.  相似文献   

2.
Containment strategies for outbreaks of invasive Neisseria meningitidis disease are informed by serogroup assays that characterize the polysaccharide capsule. We sought to uncover the genomic basis of conflicting serogroup assay results for an isolate (M16917) from a patient with acute meningococcal disease. To this end, we characterized the complete genome sequence of the M16917 isolate and performed a variety of comparative sequence analyses against N. meningitidis reference genome sequences of known serogroups. Multilocus sequence typing and whole-genome sequence comparison revealed that M16917 is a member of the ST-11 sequence group, which is most often associated with serogroup C. However, sequence similarity comparisons and phylogenetic analysis showed that the serogroup diagnostic capsule polymerase gene (synD) of M16917 belongs to serogroup B. These results suggest that a capsule-switching event occurred based on homologous recombination at or around the capsule locus of M16917. Detailed analysis of this locus uncovered the locations of recombination breakpoints in the M16917 genome sequence, which led to the introduction of an ∼2-kb serogroup B sequence cassette into the serogroup C genomic background. Since there is no currently available vaccine for serogroup B strains of N. meningitidis, this kind capsule-switching event could have public health relevance as a vaccine escape mutant.  相似文献   

3.
The cannabinoid 1 (CB1) allosteric modulator, 5-chloro-3-ethyl-1H-indole-2-carboxylic acid [2-(4-piperidin-1-yl-phenyl)-ethyl]-amide) (ORG27569), has the paradoxical effect of increasing the equilibrium binding of [3H](−)-3-[2-hydroxyl-4-(1,1-dimethylheptyl)phenyl]-4-[3-hydroxylpropyl]cyclohexan-1-ol (CP55,940, an orthosteric agonist) while at the same time decreasing its efficacy (in G protein-mediated signaling). ORG27569 also decreases basal signaling, acting as an inverse agonist for the G protein-mediated signaling pathway. In ligand displacement assays, ORG27569 can displace the CB1 antagonist/inverse agonist, N-(piperidiny-1-yl)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide(SR141716A). The goal of this work was to identify the binding site of ORG27569 at CB1. To this end, we used computation, synthesis, mutation, and functional studies to identify the ORG27569-binding site in the CB1 TMH3-6-7 region. This site is consistent with the results of K3.28192A, F3.36200A, W5.43279A, W6.48356A, and F3.25189A mutation studies, which revealed the ORG27569-binding site overlaps with our previously determined binding site of SR141716A but extends extracellularly. Additionally, we identified a key electrostatic interaction between the ORG27569 piperidine ring nitrogen and K3.28192 that is important for ORG27569 to act as an inverse agonist. At this allosteric site, ORG27569 promotes an intermediate conformation of the CB1 receptor, explaining ORG27569''s ability to increase equilibrium binding of CP55,940. This site also explains ORG27569''s ability to antagonize the efficacy of CP55,940 in three complementary ways. 1) ORG27569 sterically blocks movements of the second extracellular loop that have been linked to receptor activation. 2) ORG27569 sterically blocks a key electrostatic interaction between the third extracellular loop residue Lys-373 and D2.63176. 3) ORG27569 packs against TMH6, sterically hindering movements of this helix that have been shown to be important for receptor activation.  相似文献   

4.
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5.
We analyzed the temporal and spatial diversity of the microbiota in a low-usage and a high-usage hospital tap. We identified a tap-specific colonization pattern, with potential human pathogens being overrepresented in the low-usage tap. We propose that founder effects and local adaptation caused the tap-specific colonization patterns. Our conclusion is that tap-specific colonization represents a potential challenge for water safety.Humans are exposed to and consume large amounts of tap water in their everyday life, with the tap water microbiota representing a potent reservoir for pathogens (8). Despite the potential impact, our knowledge about the ecological diversification processes of the tap water microbiota is limited (4, 11).The aim of the present work was to determine the temporal and spatial distribution patterns of the planktonic tap water microbiota. We compared the summer and winter microbiota from two hospital taps supplied from the same water source. We analyzed 16S rRNA gene clone libraries by using a novel alignment-independent approach for operational taxonomic unit (OTU) designation (6), while established OTU diversity and richness estimators were used for the ecological interpretations.Tap water samples (1 liter) from a high-usage kitchen and a low-usage toilet cold-water tap in Akershus University Hospital, Lørenskog, Norway, were collected in January and July 2006. The total DNA was isolated and the 16S rRNA gene PCR amplified and sequenced. Based on the sequences, we estimated the species richness and diversity, we calculated the distances between the communities, and trees were constructed to reflect the relatedness of the microbiota in the samples analyzed. Details about these analytical approaches are given in the materials and methods section in the supplemental material.Our initial analysis of species composition was done using the RDPII hierarchical classifier. We found that the majority of pathogen-related bacteria in our data set belonged to the class Gammaproteobacteria. The genera encompassed Legionella, Pseudomonas, and Vibrio (Table ​(Table1).1). We found a significant overrepresentation of pathogen-related bacteria in the toilet tap (P = 0.04), while there were no significant differences between summer and winter samples. Legionella showed the highest relative abundance for the pathogen-related bacteria. With respect to the total diversity, we found that Proteobacteria dominated the tap water microbiota (representing 86% of the taxa) (see Table S1 in the supplemental material). There was, however, a large portion (56%) of the taxa that could not be assigned to the genus level using this classifier.

TABLE 1.

Cloned sequences related to human pathogensa
Sampling placeSampling timePathogenNCBI accession no.Identity (%)
ToiletSummerEscherichia coliEF41861499
ToiletSummerEscherichia sp.EF07430799
ToiletSummerLegionella sp.AY92415595
ToiletSummerLegionella sp.AY92415395
ToiletSummerLegionella sp.AY92415396
ToiletWinterLegionella sp.AY92406196
ToiletWinterLegionella sp.AY92415897
ToiletWinterLegionella sp.AY92415897
KitchenWinterLegionella sp.AY92399697
ToiletSummerPseudomonas fluorescensEF41307398
ToiletSummerPseudomonas fluorescensEF41307398
KitchenSummerPseudomonas fluorescensDQ20773199
ToiletWinterVibrio sp.DQ40838898
ToiletWinterVibrio sp.AB27476098
KitchenWinterVibrio sp.DQ40838898
KitchenWinterVibrio lentusAY29293699
KitchenWinterVibrio sp.AM18376597
ToiletWinterStenotrophomonas maltophiliaAY83773099
KitchenWinterStenotrophomonas maltophiliaDQ42487098
ToiletWinterStreptococcus suisAF28457898
ToiletWinterStreptococcus suisAF28457898
Open in a separate windowaThe relatedness between the cloned sequences and potential pathogens was determined by BLAST searches of the NCBI database, carried out using default settings.To obtain a better resolution of the uncharacterized microbiota, we analyzed the data using a clustering approach that is not dependent on a predefined bacterial group (see the materials and methods section in the supplemental material for details). These analyses showed that there were three relatively tightly clustered groups in our data set (Fig. ​(Fig.1A).1A). The largest group (n = 590) was only distantly related to characterized betaproteobacteria within the order Rhodocyclales. We also identified another large betaproteocaterial group (n = 320) related to Polynucleobacter. Finally, a tight group (n = 145) related to the alphaproteobacterium Sphingomonas was identified.Open in a separate windowFIG. 1.Tap water microbiota diversity, determined by use of a principal component analysis coordinate system. (A) Each bacterium is classified by coordinates, with the following color code: brown squares, kitchen summer; red diamonds, toilet summer; green triangles, kitchen winter; and green circles, toilet winter. (B and C) Each square represents a 1 × 1 (B) or 5 × 5 (C) OTU. PC1, first principal component; PC2, second principal component.The tap-specific distributions of the bacterial groups were investigated using density distribution analyses. A dominant population related to Polynucleobacter was identified for the toilet summer samples, while for the winter samples there was a dominance of the Rhodocyclales-related bacteria. The kitchen summer samples revealed a dominance of Sphingomonas. The corresponding winter samples did not reveal distinct high-density bacterial populations (see Table S2 in the supplemental material).Hierarchical clustering for the 1 × 1 OTU density distribution confirmed the relatively low overlap for the microbiota in the samples analyzed (Fig. ​(Fig.2).2). We found that the microbiota clustered according to tap and not season.Open in a separate windowFIG. 2.Hierarchical clustering for the density distribution of the tap water microbiota. The density of 1 × 1 OTUs was used as a pseudospecies for hierarchical clustering. The tree for the Cord distance matrix is presented, while the distances calculated using the three distance matrices Cord, Brad Curtis, and Sneath Sokal, respectively, are shown for each branch.We have described the species diversity and richness of the microbiota in Table S3 in the supplemental material. For the low taxonomic level, these analyses showed that the diversity and species richness were greater for the winter samples than for the summer samples. Comparing the two taps, the diversity and richness were greater in the kitchen tap than in the toilet tap. In particular, the winter sample from the kitchen showed great richness and diversity. The high taxonomic level, however, did not reveal the same clear differences as did the low level, and the distributions were more even. Rarefaction analyses for the low taxonomic level confirmed the richness and diversity estimates (see Fig. S1 in the supplemental material).Our final analyses sought to fit the species rank distributions to common rank abundance curves. Generally, the rank abundance curves were best fitted to log series or truncated log normal distributions (see Table S4 in the supplemental material). The log series distribution could be fit to all of the samples except the kitchen summer samples at the low taxonomic level, while the truncated log normal distribution could not be fit to the kitchen samples at the high taxonomic level. Interestingly, however, the kitchen winter sample was best fit to a geometric curve at both the high and the low taxonomic level.Diversifying, adaptive biofilm barriers have been documented for tap water bacteria (7), and it is known that planktonic bacteria can interact with biofilms in an adaptive manner (3). On the other hand, tap usage leads to water flowthrough and replacement of the global with the local water population by stochastic founder effects (1).Therefore, we propose that parts of the local diversity observed can be explained by local adaptation (10) and parts by founder effects (9).Most prokaryote diversity measures assume log normal or log series OTU dominance density distributions (5). The kitchen winter sample, however, showed deviations from these patterns by being correlated to geometric distributions (in addition to the log series and truncated log normal distributions for the high taxonomic level). This sample also showed a much greater species richness than the other samples. A possible explanation is that the species richness of the tap water microbiota can be linked to usage and that the kitchen tap is driven toward a founder microbiota by high usage.Since our work indicates an overrepresentation of Legionella in the low-usage tap, it would be of high interest to determine whether the processes for local Legionella colonization can be related to tap usage. Understanding the ecological forces affecting Legionella and other pathogens are of great importance for human health. At the Akerhus University Hospital, this was exemplified by a Pseudomonas aeruginosa outbreak in an intensive care unit, where the outbreak could be traced back to a single tap (2).  相似文献   

6.
Our previous work using a melanoma progression model composed of melanocytic cells (melanocytes, primary and metastatic melanoma samples) demonstrated various deregulated genes, including a few known lncRNAs. Further analysis was conducted to discover novel lncRNAs associated with melanoma, and candidates were prioritized for their potential association with invasiveness or other metastasis‐related processes. In this sense, we found the intergenic lncRNA U73166 (ENSG00000230454) and decided to explore its effects in melanoma. For that, we silenced the lncRNA U73166 expression using shRNAs in a melanoma cell line. Next, we experimentally investigated its functions and found that migration and invasion had significantly decreased in knockdown cells, indicating an essential association of lncRNA U73166 for cancer processes. Additionally, using naïve and vemurafenib‐resistant cell lines and data from a patient before and after resistance, we found that vemurafenib‐resistant samples had a higher expression of lncRNA U73166. Also, we retrieved data from the literature that indicates lncRNA U73166 may act as a mediator of RNA processing and cell invasion, probably inducing a more aggressive phenotype. Therefore, our results suggest a relevant role of lncRNA U73166 in metastasis development. We also pointed herein the lncRNA U73166 as a new possible biomarker or target to help overcome clinical vemurafenib resistance.  相似文献   

7.
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8.
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9.
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10.
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11.
(±) SKF83959, like many other arylbenzazepines, elicits powerful neuroprotection in vitro and in vivo. The neuroprotective action of the compound was found to partially depend on its D1-like dopamine receptor agonistic activity. The precise mechanism for the (±) SKF83959-mediated neuroprotection remains elusive. We report here that (±) SKF83959 is a potent blocker for delayed rectifier K+ channel. (±) SKF83959 inhibited the delayed rectifier K+ current (I K) dose-dependently in rat hippocampal neurons. The IC 50 value for inhibition of I K was 41.9±2.3 µM (Hill coefficient = 1.81±0.13, n = 6), whereas that for inhibition of I A was 307.9±38.5 µM (Hill coefficient = 1.37±0.08, n = 6). Thus, (±) SKF83959 is 7.3-fold more potent in suppressing I K than I A. Moreover, the inhibition of I K by (±) SKF83959 was voltage-dependent and not related to dopamine receptors. The rapidly onset of inhibition and recovery suggests that the inhibition resulted from a direct interaction of (±) SKF83959 with the K+ channel. The intracellular application of (±) SKF83959 had no effects of on I K, indicating that the compound most likely acts at the outer mouth of the pore of K+ channel. We also tested the enantiomers of (±) SKF83959, R-(+) SKF83959 (MCL-201), and S-(−) SKF83959 (MCL-202), as well as SKF38393; all these compounds inhibited I K. However, (±) SKF83959, at either 0.1 or 1 mM, exhibited the strongest inhibition on the currents among all tested drug. The present findings not only revealed a new potent blocker of I K , but also provided a novel mechanism for the neuroprotective action of arylbenzazepines such as (±) SKF83959.  相似文献   

12.
We have previously shown that Fhit tumor suppressor protein interacts with Hsp60 chaperone machinery and ferredoxin reductase (Fdxr) protein. Fhit-effector interactions are associated with a Fhit-dependent increase in Fdxr stability, followed by generation of reactive oxygen species and apoptosis induction under conditions of oxidative stress. To define Fhit structural features that affect interactions, downstream signaling, and biological outcomes, we used cancer cells expressing Fhit mutants with amino acid substitutions that alter enzymatic activity, enzyme substrate binding, or phosphorylation at tyrosine 114. Gastric cancer cell clones stably expressing mutants that do not bind substrate or cannot be phosphorylated showed decreased binding to Hsp60 and Fdxr and reduced mitochondrial localization. Expression of Fhit or mutants that bind interactor proteins results in oxidative damage and accumulation of cells in G2/M or sub-G1 fractions after peroxide treatment; noninteracting mutants are defective in these biological effects. Gastric cancer clones expressing noncomplexing Fhit mutants show reduction of Fhit tumor suppressor activity, confirming that substrate binding, interaction with heat shock proteins, mitochondrial localization, and interaction with Fdxr are important for Fhit tumor suppressor function.Fhit protein is a powerful tumor suppressor that is frequently lost or reduced in cancer cells because of rearrangement of the exquisitely DNA damage-sensitive fragile FHIT gene. Restoration of Fhit expression suppresses tumorigenicity of cancer cells of various types, and the ability to induce apoptosis in cancer cells in vitro is reduced by specific Fhit mutations (1, 2).Through studies of signal pathways affected by Fhit expression, by searches for Fhit protein effectors, and by in vitro analyses of Fhit activity, we and others have defined Fhit enzymatic activity in vitro (3), apoptotic activity in cells and tumors (4–6), and most recently identification of a Fhit protein complex that affects Fhit stability, mitochondrial localization, and interaction with ferredoxin reductase (Fdxr)5 (7). The complex includes Hsp60 and Hsp10 that mediate Fhit stability and may affect import into mitochondria, where Fhit interacts with Fdxr, which is responsible for transferring electrons from NADPH to cytochrome P450 via ferredoxin. Virally mediated Fhit restoration in Fhit-deficient cancer cells increases production of intracellular reactive oxygen species (ROS), followed by increased apoptosis of cancer cells under oxidative stress conditions; conversely, Fhit-negative cells escape apoptosis, likely carrying oxidative DNA damage that contributes to accumulation of mutations.The Fhit protein sequence, showing high homology to the histidine triad (HIT) family of proteins, suggested that the protein product would hydrolyze diadenosine tetraphosphate or diadenosine triphosphate (Ap3A) (8), and in vitro studies showed that Ap3A was cleaved into ADP and AMP by Fhit. The catalytic histidine triad within Fhit was essential for catalytic activity (3), and a Fhit mutant that substituted Asn for His at the central histidine (H96N mutant) was catalytically inactive, although it bound substrate well (3). Early tumor suppression studies showed that cancer cells stably transfected with wild type (WT) or H96N mutant Fhit were suppressed for tumor growth in nude mice. This suggested the hypothesis that the Fhit-substrate complex sends the tumor suppression signal (9, 10). To test this hypothesis, a series of FHIT alleles was designed to reduce substrate-binding and/or hydrolytic rates and was characterized by quantitative cell-death assays on cancer cells virally infected with each allele. The allele series covered defects as great as 100,000-fold in kcat and increases as large as 30-fold in Km. Mutants with 2–7-fold increases in Km had significantly reduced apoptotic indices and the mutant with a 30-fold increase in Km retained little apoptotic function. Thus, the proapoptotic function of Fhit, which is likely associated with tumor suppressor function, is limited by substrate binding and is unrelated to substrate hydrolysis (11).Fhit, a homodimeric protein of 147 amino acids, is a target of tyrosine phosphorylation by the Src family protein kinases, which can phosphorylate Tyr-114 of Fhit in vitro and in vivo (12). After co-expression of Fhit with the Elk tyrosine kinase in Escherichia coli to generate phosphorylated forms of Fhit, unphosphorylated, mono-, and diphosphorylated Fhit were purified, and enzyme kinetics studies showed that monophosphorylated Fhit exhibited monophasic kinetics with Km and kcat values ∼2- and ∼7-fold lower, respectively, than for unphosphorylated Fhit. Diphosphorylated Fhit exhibited biphasic kinetics; one site had Km and kcat values ∼2- and ∼140-fold lower, respectively, than for unphosphorylated Fhit; the second site had a Km ∼60-fold higher and a kcat ∼6-fold lower than for unphosphorylated Fhit (13). Thus, it was possible that the alterations in Km and kcat values for phosphorylated forms of Fhit might favor formation and lifetime of the Fhit-Ap3A complex and enhance tumor suppressor activity (see
Fhit forms
Kinetic parameters
% Sub-G1
Direct binding
Subcellular location
Co-IP in vivo
8-OHdG
Apoptosis
Tumor suppressor
Km (mm)kcat (s–1)A549MKN74Hsp60FdxrHsp60Fdxr
Fhit WT 1.6 +/– 0.19 2.7 +/– 0.95 43 24 Yes Yes Cyt & mito Yes Yes Yes Yes Yes
Catalyt mutants
   H96D Up 2-fold Down >2 × 104 29 NT NT NT Cyt & mito Yes Yes NT Yes NT
   H96N Up 2-fold Down >5 × 105 31 14.4 NT NT Cyt & mito Yes Yes Yes Yes Yes
Loop mutants
   Y114A Up 23-fold Down 2-fold 3.7 NT NT NT Cyt +/– +/– +/– No No
   Y114D NT NT 2.9 6 NT NT Cyt +/– +/– – No –/+
   Y114E NT NT NT NT NT NT Cyt & mito –/+ –/+ – No NT
   Y114F Up 5-fold Up 1.1-fold 11.5 3 NT NT Cyt & mito –/+ –/+ – No No
   Y114W Up 5-fold Up 1.4-fold NT NT NT NT Cyt & mito –/+ – – NT NT
   del113–117 Up 10-fold Down 38-fold 5 NT NT NT NT NT NT – No NT
Other mutants
   L25W Up 7-fold Down 4-fold 15 NT NT NT Cyt – – – NT –/+
   I10W,L25W Up 32-fold Down 6-fold 11 NT NT NT NT NT NT NT NT NT
   F5W Up 3.3 fold NT NT 5 NT NT NT NT NT +/– No NT
Purified pFhit
   pFhit Down 0.4-fold Down 7-fold NA NA –/+ Yes NA NA NA NA NA NA
   ppFhit Down 0.4-fold Down > 100-fold NA NA –/+ Yes NA NA NA NA NA NA
Up 60-fold Down 6-fold
Open in a separate windowTo explore the in vivo importance of the Tyr-114 phosphorylation site and define Fhit-mediated signaling events, Semba et al. (14) compared the differential biological effects of Ad-FHIT WT and Ad-FHIT Tyr-114 mutant expression in human lung cancer cells. Caspase-dependent apoptosis was effectively induced only by WT Fhit protein. However, the biological significance of phosphorylation at Tyr-114 has been difficult to study because the endogenous phosphorylated forms have very short half-lives; activation of epidermal growth facto receptor family members induces Fhit phosphorylation by Src and proteasome degradation of phosphorylated Fhit (15).Although there are possible connections among the various pathways known to be altered in Fhit-deficient cells, apoptosis, DNA damage-response checkpoint activation, ROS production, and related biological effects of Fhit loss or overexpression, details of the pathway(s) leading from Fhit overexpression to cell death and tumor suppression have not been delineated. Now that a Fhit signaling complex has been identified, we set out to examine which structural features of Fhit protein might participate in individual steps of the pathway leading from Fhit overexpression through complex formation, subcellular localization, interaction with mitochondrial Fdxr, DNA damage induction, cell cycle changes, apoptosis, and ultimately tumor suppression. The underlying hypotheses were as follows: substrate-binding mutants would behave similarly to WT; nonsubstrate-binding mutants would be defective in some step of the pathway, perhaps complexing with heat shock proteins or Fdxr or perhaps induction of DNA damage; and Tyr-114 mutants, which also affect formation or stability of the enzyme-substrate complex, would also be defective in executing some step of the Fhit overexpression pathway to cell death. One goal was to identify specific mutants that exhibited deficiency in specific steps of the pathway, so that such mutants could be used to dissect each step in more detail. Using in vitro Fhit and Fhit-effector protein interactions, we aimed to determine the following: 1) which proteins of the complex interact directly with Fhit, and 2) the biological role of these interactions in vivo. Using cancer cells expressing exogenous WT and mutant Fhit proteins, we were able to examine the structural features of Fhit that affect the direct interaction with its effectors, participate in ROS production, and are necessary for tumor suppression activity.  相似文献   

13.
Unsuitability of Quantitative Bacteroidales 16S rRNA Gene Assays for Discerning Fecal Contamination of Drinking Water     
Paul W. J. J. van der Wielen  Gertjan Medema 《Applied and environmental microbiology》2010,76(14):4876-4881
Bacteroidales species were detected in (tap) water samples from treatment plants with three different PCR assays. 16S rRNA gene sequence analysis indicated that the sequences had an environmental rather than fecal origin. We conclude that assays for Bacteroidales 16S rRNA genes are not specific enough to discern fecal contamination of drinking water in the Netherlands.Drinking water in many countries is routinely monitored for recent fecal contamination by testing for fecal indicator organisms Escherichia coli, thermotolerant coliforms, and/or intestinal enterococci to demonstrate microbial safety (13, 21, 42). Although these indicator organisms have been used for many decades, they have some limitations: the number of E. coli/coliform/enterococcus bacteria in feces is relatively low (18, 38), and they sometimes might be able to grow in the environment (10, 11, 14, 27). Consequently, scientists have been searching for alternative indicator organisms to determine fecal contamination of water. In 1967, bacteria belonging to the genus Bacteroides were suggested as alternative indicator organisms (26). Bacteroides spp. might have some advantages over the traditional indicator organisms. The numbers of Bacteroides spp. in the intestinal tract of humans and animals are 10 to 100 times higher than the numbers of E. coli or intestinal enterococci (1, 2, 12, 26). However, the use of Bacteroides spp. as indicator organisms was hampered by the complex cultivation conditions required (1, 2). The introduction of molecular methods made it possible to detect bacterial species that belong to the order Bacteroidales, an order that includes the genus Bacteroides, without cultivation. As a result, real-time PCR methods were developed for the quantitative detection of Bacteroidales in surface and recreation water and the potential of Bacteroidales species as an indication of fecal contamination of recreational waters was demonstrated (6, 12, 16, 19, 20, 29). Bacteroidales species might be useful indicator organisms for fecal contamination of drinking water as well. However, methods to detect fecal contamination in drinking water should be more sensitive, because people ingest more drinking water and the quality assessments and standards for fecal contamination are stricter than for bathing water. Studies exploring real-time PCR for the detection of Bacteroidales genes in drinking water have not been published to our knowledge. The objective of our study was, therefore, to determine if assays for the detection of Bacteroidales 16S rRNA genes can be used to detect fecal contamination in drinking water.Unchlorinated tap water samples were obtained in November 2007 and February 2010 from one or more locations in the distribution systems of nine different drinking water treatment plants (plants A to I; Table ​Table1)1) that produced unchlorinated drinking water from confined (plants B, C, E, F, and G) and unconfined (plants A, D, H, and I) groundwater. The treatment plants are located in the central part of the Netherlands within 90 km of each other. In addition, untreated groundwater from extraction wells and/or untreated raw groundwater (mixture of groundwater from different extraction wells) was sampled in March 2008 (Table ​(Table1).1). Water samples (100 ml) were filtered over a 25-mm polycarbonate filter (0.22-μm pore size, type GTTP; Millipore, Netherlands) and a DNA fragment was added as internal control to determine the recovery efficiency of DNA isolation and PCR analysis (2a, 40). DNA was isolated using a FastDNA spin kit for soil (Qbiogene, United States) according to the supplier''s protocol. Primer sets AllBac 296f and AllBac 412r, resulting in a PCR product of 108 bp, were used in combination with TaqMan probe AllBac375Bhqr to quantitatively determine the number of Bacteroidales 16S rRNA gene copies in the water samples using a real-time PCR instrument (20). The PCR cycle after which the fluorescence signal of the amplified DNA was detected (threshold cycle [CT]) was used to quantify the concentration of 16S rRNA gene copies. Quantification was based on comparison of the sample CT value with the CT values of a calibration curve graphed using known copy numbers of the Bacteroidales 16S rRNA gene, as previously described (12, 20). The correlation coefficient of the calibration curve was 0.99, and the efficiency of the PCR 95 to 105%. Finally, the Bacteroidales cell number was calculated by using the recovery rate of the internal standard and assuming five 16S rRNA gene copy numbers per cell (5). The detection limit of this gene assay was 50 Bacteroidales cells 100 ml−1 (corresponding to 10 16S rRNA gene copies per reaction mixture). Furthermore, the 16S rRNA genes that were obtained from several water samples from treatment plant C with the AllBac and TotBac (12) primer sets were sequenced, and the nearest relatives were obtained from the GenBank database using BLAST searches.

TABLE 1.

Numbers of Bacteroidales cells in extraction wells, raw groundwater, and unchlorinated tap water of nine different groundwater plants in the Netherlandsa
PlantSource of sampleNo. (100 ml−1) of Bacteroidales cells in:
200720082010
ATap water 1b5,948 ± 950
Tap water 22,682 ± 1,4591,254 ± 216
Tap water 34,362 ± 947439 ± 136
Raw water96 ± 15
BTap water 13,553 ± 9815,302 ± 2,952
Tap water 24,487 ± 3912,119 ± 1,367
Tap water 37,862 ± 4,5883,896 ± 3,003
Raw water3,209 ± 833
CTap water 1661 ± 75386 ± 199
Tap water 21,051 ± 626
Tap water 3831 ± 584
Tap water 41,254 ± 216
Extraction well 11,126 ± 262
Extraction well 22,666 ± 51
Extraction well 3<50
Raw water90 ± 44
DTap water1,103 ± 291,254 ± 216
Raw water48 ± 16
ETap water1,302 ± 2221,254 ± 216
Extraction well 1671 ± 97
FTap water1,317 ± 198
Raw water<50
GTap water 1675 ± 92439 ± 300
Tap water 2216 ± 65249 ± 98
Tap water 3154 ± 6322 ± 137
Raw water<50
HTap water7,073 ± 845
Raw water511 ± 254
ITap water1,577 ± 176
Raw water420 ± 66
Open in a separate windowaValues are the average results and standard deviations from replicate PCRs on the same water sample using the AllBac primer set (20). In November 2007, the distribution systems (tap water) of plants A, B, and G were sampled at three different locations, whereas for the other plants, one location in the distribution system was sampled. In March 2008, raw water of plants A to G was sampled, as well as one (plant E) or three (plant C) different extraction wells. Finally, in February 2010, the distribution systems of plants A, B, C, D, E, and G were sampled again.bMore than one tap water sample from a treatment plant means that samples were taken at different locations in the distribution system.The Bacteroidales 16S rRNA gene, quantified with the AllBac primer set, was detected in all tap water samples in November 2007 and February 2010. The number of cells varied between 154 and 7,862 Bacteroidales cells 100 ml−1, and the numbers in tap water of each plant were similar in 2007 and 2010 (Table ​(Table1).1). The Bacteroidales counts were high compared to the number of E. coli that are occasionally observed in fecally contaminated drinking water (17a) but low compared to numbers observed in surface water (4, 20, 22). Water from the extraction wells and raw water used for unchlorinated drinking water production were analyzed, and Bacteroidales species were detected in 10 out of 15 samples (Table ​(Table1).1). These results would imply that the extracted groundwater, raw water, and tap water were fecally contaminated. According to the Dutch drinking water decree (2b), both raw and tap water from the nine different treatment plants are regularly analyzed for fecal contamination by monitoring for E. coli, F-specific RNA phages, and somatic coliphages. For at least the last 10 years, these indicator organisms have not been detected in these waters.Additional qualitative PCR analyses using TotBac and BacUni primer sets (12, 19) targeting other parts of the Bacteroidales 16S rRNA gene were performed to confirm the presence of Bacteroidales species in the water samples of November 2007 and March 2008. Nine or 10 of the 11 samples that were positive with the AllBac primer set were also positive with the TotBac and BacUni primer sets (data not shown). The BacUni primer set has a higher detection limit (30 gene copies per PCR; 19), which could explain the difference from the results with the AllBac primer set. The TotBac primer set has the same detection limit as the AllBac primer set (12), but small differences in PCR efficiencies might have resulted in different results, since some water samples showed Bacteroidales 16S rRNA gene copy numbers around the detection limit (Table ​(Table1).1). Nevertheless, the additional PCR analyses demonstrated that the detection of Bacteroidales species in tap, raw, and extracted well water with the AllBac primer set was not an artifact. The primer sets used were developed in three different studies (12, 19, 20) but have been applied in a number of recent studies to detect fecal contamination of surface water (3, 4, 16, 22, 33, 34). The results from most of these studies showed that 16S rRNA genes of Bacteroidales were present in all surface water samples tested. Only Sinigalliano et al. (34) observed that 2 out of 4 water samples were negative with the TotBac primer set. However, the detection limit of the assay was not specified in that study.The nine different treatment plants tested in our study produce unchlorinated drinking water from groundwater, which is considered to be of high hygienic quality. In addition, the extraction wells are protected from fecal contamination by a protection zone where no activities related to human waste or animal manure are allowed. In the Netherlands, this protection zone is based on a 60-day residence time of the water. Previous studies have demonstrated that a residence time of 60 days is highly effective in removing fecal bacteria and viruses (30, 31, 39). Moreover, the Bacteroidales numbers in tap water in November 2007 were significantly higher than the numbers in raw groundwater in March 2008 (Mann-Whitney U test; P < 0.01). Because the recovery efficiency of the internal control was the same between raw water and tap water samples, this result demonstrates that Bacteroidales cell numbers increased during treatment and/or drinking water distribution. This result could suggest that the water was fecally contaminated during drinking water treatment and/or distribution. However, it is unlikely that the integrity of nine different treatment trains and/or supply systems was affected in the sampling period. The statutory monitoring did not show the presence of E. coli at these sites. Another hypothesis is that the increase of Bacteroidales cell numbers in tap water was caused by the growth of Bacteroidales species in (drinking) water systems. In summary, it is unexpected that the majority of the tap water, raw water, and extracted groundwater samples were fecally contaminated. These unexpected observations raise the question of whether the PCR methods detect only fecal Bacteroidales species and, thus, if the gene assays are suitable to discern fecal contamination in drinking water in the Netherlands.Sequence analyses of the Bacteroidales 16S rRNA genes were performed to determine the relatedness of sequences from the different sampling sites to sequences from the nearest relatives in the GenBank database. All sequences contained the primer regions, indicating that nonspecific amplification had not occurred in the PCRs. Because the PCR product from the AllBac primer set was small (108 bp), many 16S rRNA gene sequences (100 to 5,000) in the GenBank database were identical to the Bacteroidales 16S rRNA gene sequences obtained from groundwater and unchlorinated tap water samples from plant C. These identical 16S rRNA gene sequences were in general obtained from fecal sources, but some of them came from environmental rather than fecal sources (Table ​(Table2).2). The AllBac 16S rRNA gene sequences from tap water and groundwater had relative high similarities (96.3 to 100%) to sequences from bacterial species of the genera Bacteroides, Prevotella, and Tannerella (Table ​(Table2),2), which all belong to the order Bacteroidales.

TABLE 2.

Nearest relatives in GenBank to the Bacteroidales 16S rRNA gene sequences obtained from groundwater and unchlorinated tap water from plant C using different primer setsa
Primer set used, source of sample, and OTUsbGenBank sequence accession no.Source of sequence (GenBank sequence accession no.)SimilaritycNearest cultivated bacterium in GenBank (sequence accession no.)Similarity
AllBac
    Extraction well 1 (3/6)GQ169588Rhizosphere (EF605968)108/108Prevotella oralis (AY323522)105/108
    Extraction well 1 (3/6)GQ169589Water from watershed (DQ886209)108/108Tannerella forsythia(AB035460)107/108
    Extraction well 2 (1/6)GQ169590Phyllosphere Brazilian forest (DQ221468)108/108Tannerella forsythia(AB035460)106/108
    Extraction well 2 (5/6)GQ169591Bovine rumen (EU348207)108/108Tannerella forsythia(AB035460)106/108
    Extraction well 3 (1/6)GQ169592Phyllosphere Brazilian forest (DQ221468)108/108Prevotella oralis (AY323522)104/108
    Extraction well 3 (5/6)GQ169593Prevotella corporis (L16465)108/108Prevotella corporis (L16465)108/108
    Raw water (3/6)GQ169594Spitsbergen permafrost (EF034756)108/108Tannerella forsythia(AB035460)106/108
    Raw water (3/6)GQ169595Hindgut beetle larvae (FJ374179)108/108Tannerella forsythia(AB035460)107/108
    Tap water (6/6)GQ169596Prevotella timonensis (DQ518919)108/108Prevotella timonensis (DQ518919)108/108
    Prevotella buccalis (L16476)Prevotella buccalis (L16476)
    Prevotella ruminicola (AF218617)Prevotella ruminicola (AF218617)
    Bacteroides vulgatus (NC_009614)Bacteroides vulgatus (NC_009614)
TotBac
    Extraction well 1 (1/10)GQ169597Deep subsurface groundwater (AB237705)339/369Salinimicrobium terrae (EU135614)315/370
    Extraction well 1 (1/10)GQ169598Songhuajiang River sediment (DQ444125)363/377Paludibacter propionicigenes (AB078842)357/376
    Extraction well 1 (4/10)GQ169599Freshwater pond sediment (DQ676447)352/360Paludibacter propionicigenes (AB078842)313/372
    Extraction well 1 (4/10)GQ169600Pine River sediment (DQ833352)364/371Bacteroides oleiciplenus (AB490803)334/375
    Extraction well 2 (4/10)GQ169601Groundwater (AF273319)364/371Xanthobacillum maris (AB362815)338/375
    Extraction well 2 (6/10)GQ169602Human saliva (AB028385)381/382Prevotella intermedia (AY689226)380/382
    Extraction well 3 (1/10)GQ169603Pig manure (AY816766)354/377Bacteroides thetaiotaomicron (AE015928)311/380
    Extraction well 3 (3/10)GQ169604Pig manure (AY816867)371/376Butyricimonas virosa (AB443949)307/379
    Extraction well 3 (6/10)GQ169605Swedish lake (AY509350)343/362Parabacteroides distasonis (AB238927)320/374
    Raw water (10/10)GQ169606Prevotella timonensis (AF218617)378/379Prevotella timonensis (AF218617)378/379
    Tap water (1/10)GQ169607Deep subsurface groundwater (AB237705)338/369Salinimicrobium terrae (EU135614)312/370
    Tap water (2/10)GQ169608Yukon River, AK(FJ694652)367/372Psychroserpens burtonensis (U62913)312/375
    Tap water (7/10)GQ169609Deep subsurface groundwater (AB237705)341/369Salinimicrobium terrae (EU135614)315/370
Open in a separate windowaPrimer sets AllBac (20) and TotBac (12) were used in PCRs of samples, and GenBank was searched for relatives using BLAST.bOTUs are indicated by the values in parentheses (number of sequences belonging to the OTU/total number of sequences analyzed).cNumber of base pairs identical in both sequences/total number of base pairs in sequences.16S rRNA gene sequences obtained with the TotBac primer set were longer (∼370 bp) and did not show 100% similarity with the nearest relatives in the GenBank database (Table ​(Table2).2). Sequences from the GenBank database that showed the highest similarity (91.6% to 99.7%) with the 16S rRNA gene sequences from tap water and groundwater from plant C were in general isolated from environmental sources (Table ​(Table2).2). The 16S rRNA gene sequences from cultivated bacterial species that showed the highest similarity to the 16S rRNA gene sequences obtained in our study belonged to different genera (Table ​(Table2).2). Some of these genera (Salinimicrobium, Xanthobacillum, and Psychroserpens) did not belong to the order Bacteroidales. However, the 16S rRNA gene sequences from bacterial species of these genera showed low similarities with the sequences obtained in this study (83.2% to 90.1%) and six mismatches to the TotBac primers. Thus, it is unlikely that DNA from bacterial species belonging to Salinimicrobium, Xanthobacillum, and Psychroserpens was amplified in the gene assay. More importantly, the majority of the nearest environmental clone sequences retrieved from the GenBank database showed no or a single mismatch with the AllBac and TotBac primer and probe sequences. Thus, these primer sets are capable of amplifying 16S rRNA genes from bacteria that have been observed in ecosystems outside the intestinal tract of humans and animals.16S rRNA gene sequences related to Prevotella species were commonly observed in extracted groundwater, raw water, and tap water (Table ​(Table2).2). The isolation of Prevotella paludivivens from rice roots in a rice field soil (35) demonstrated the environmental nature of some Prevotella species. In addition, primer sequences developed for the detection of fecal Bacteroidales species (8, 12, 19, 20, 25, 29) showed no or a single mismatch with 16S rRNA gene sequences from P. paludivivens, Xylanibacterium oryzae, Paludibacter propionicigenes, Proteiniphilum acetatigenes, and Petrimonas sulfuriphila that are present in the GenBank database. These five Bacteroidales species have all been isolated from ecosystems other than the gastrointestinal tract. Consequently, primer sets for 16S rRNA genes of Bacteroidales species cannot always be used to discern fecal contamination in water.A number of 16S rRNA gene sequences observed in groundwater and tap water fell in the genus Bacteroides. The presence of Bacteroides 16S rRNA gene sequences in groundwater and tap water might also suggest that some Bacteroides species are capable of growth in the environment. However, until now, type strains of Bacteroides species growing outside the animal intestinal tract have not been published. Another possible explanation is that the observed 16S rRNA gene sequences originate from Bacteroides species that inhabit the anoxic intestinal tract of insects. Previous studies have shown that bacterial species belonging to the genus Bacteroides are common inhabitants of the hindguts of insects (15, 23, 24, 28, 32). Some of the 16S rRNA gene sequences obtained with the AllBac primer set in our study showed 100% similarity to 16S rRNA gene sequences from the hindgut of insects. Moreover, a number of 16S rRNA gene sequences isolated from the hindguts of insects (15, 23, 24, 32) showed no or a single mismatch with the TotBac and AllBac primer and probe sequences. In conclusion, these primer sets are capable of detecting Bacteroides species from the hindgut of insects as well. Water insects are normal inhabitants of groundwater and drinking water distribution systems (7, 41) and might be a source of Bacteroides species in water. Bacteroides species from insect feces do not indicate fecal pollution by warm-blooded animals, and insects do not normally shed human fecal pathogenic microorganisms. Bacteroides species from insect feces, therefore, can hamper Bacteroides gene assays developed for the detection of water fecally contaminated by warm-blooded animals. Additional cultivation techniques in combination with molecular tools are required to demonstrate the persistence or growth of Bacteroides bacteria in groundwater and drinking water or whether Bacteroides bacteria are present in water insects. However, these experiments were beyond the scope of our study.The three extraction wells of plant C are located close to each other and extract water from the same aquifer. Subsequently, extracted water from the three wells is mixed and enters the treatment plant as raw water. We hypothesize that if a fecal source in the vicinity of the extraction field of plant C contaminated the groundwater, water from the extraction wells and raw water should (partly) have the same Bacteroidales species. Although a relatively limited amount of clones was sequenced per sample (16), the diversity of Bacteroidales operational taxonomic units (OTU) within a sample was low (Table ​(Table2).2). In contrast, unique 16S rRNA gene sequences were observed between the different water types (e.g., extracted groundwater, raw water, and tap water) and sequence overlap between water types was low. These results demonstrate that the Bacteroidales 16S rRNA gene sequences at the sampling locations were not from the same fecal source and imply once again that Bacteroidales species were environmental rather than fecal.Finally, we hypothesized that if the Bacteroidales species observed in tap water were of nonfecal origin, human- and/or bovine-specific Bacteroidales strains should not be present in tap water. We tested for the presence of human- or bovine-specific Bacteroidales strains by using source-specific 16S rRNA gene assays (5) on tap water samples from February 2010. The results showed that human- and bovine-specific Bacteroidales 16S rRNA genes could not be detected in tap water, whereas a PCR product was always detected with the positive control. Again, these results indicate that the Bacteroidales species observed in tap water were of nonfecal origin.Overall, the results from our study indicate that gene assays for Bacteroidales detected environmental rather than fecal Bacteroidales species in groundwater and tap water from treatment plants in the Netherlands. First, Bacteroidales 16S rRNA gene sequences obtained from water samples taken at plant C showed (high) similarity to clone sequences that were isolated from environmental sources. The majority of these clone sequences and several Bacteroides clone sequences from the hindguts of insects showed no or a single mismatch with AllBac, TotBac, and BacUni primer and probe sequences. Second, the primer and probe sequences used for the gene assays have no or a single mismatch with 16S rRNA gene sequences of environmental Bacteroidales species P. paludivivens, X. oryzae, P. propionicigenes, P. acetatigenes, and/or P. sulfuriphila (9, 17, 35-37). Third, Bacteroidales 16S rRNA gene sequences from raw water and water from extraction wells were unique, and sequence overlap between water types was low. It is expected that in the case of fecal contamination of groundwater, different water types from the same groundwater area have similar Bacteroidales species. Fourth, the quantitative assays for Bacteroidales 16S rRNA genes commonly used to detect fecal contamination (3, 4, 12, 16, 19, 20, 22, 33, 34) detected Bacteroidales species in deep groundwater and tap water that have no history of fecal contamination. Fifth, Bacteroidales gene copy numbers were significantly higher in tap water than in raw groundwater, demonstrating an increase or growth of Bacteroidales species during the treatment and/or distribution of drinking water. Finally, human- and bovine-specific Bacteroidales strains were not detected in tap water. Consequently, (quantitative) assays for general Bacteroidales 16S rRNA genes are not suitable to discern fecal contamination in groundwater and unchlorinated drinking water in the Netherlands.Nucleotide sequence accession numbers.The 16S rRNA gene sequences obtained in this study were deposited in the GenBank database under accession numbers GQ169588 to GQ169609.  相似文献   

14.
MitoMiner, an Integrated Database for the Storage and Analysis of Mitochondrial Proteomics Data     
Anthony C. Smith  Alan J. Robinson 《Molecular & cellular proteomics : MCP》2009,8(6):1324-1337
  相似文献   

15.
Splitting the BLOSUM Score into Numbers of Biological Significance     
Francesco Fabris  Andrea Sgarro  Alessandro Tossi 《EURASIP Journal on Bioinformatics and Systems Biology》2007,2007(1):31450
Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]  相似文献   

16.
Genetic diversity in relation to heterosis and combining ability in spring wheat   总被引：3，自引：0，他引：3  
A. K. M. Shamsuddin 《TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik》1985,70(3):306-308
Summary Genetic diversity among ten varieties of spring wheat used as parents in a diallel cross was assessed through multivariate analysis (D2-statistics) and then related to heterosis and SCA effects of their hybrids. The parents fell into three groups. Group I contained the varieties, Nobre, Girua and Carazinho; group II contained Sonalika, Lyallpur and Pitic 62 and group III contained Indus 66, Balaka, Sonora 64rs and MSl. The varieties of group I were good general combiners, while the varieties of group III were poor combiners. Significant heterotic and SCA effects for yield and yield components were observed in the hybrids of the parents belonging to different groups but not in the same group. Genetic divergence between the parents had a positive relationship with heterosis and SCA effects of the hybrids.  相似文献   

17.
Stability of Murine Cytomegalovirus Genome after In Vitro and In Vivo Passage     
Tammy P. Cheng  Mark C. Valentine  Jian Gao  Jeanette T. Pingel  Wayne M. Yokoyama 《Journal of virology》2010,84(5):2623-2628
  相似文献   

18.
Le syndrome de Klinefelter chez l'enfant     
Ch. Sultan  J. M. Lobaccaro  S. Lumbroso  S. Missov  Ch. Belon  M. Bost  R. Dumas 《Andrologie》1994,4(3):283-287
Klinfelter syndrome was first described in adult males with gynecomastia, azoospermia and hypergonadotropic hypogonadism. Children with the 47, XXY karyotype demonstrate few clinical findings so Klinefelter syndrome is rarely diagnosed until adult life. Besides children who have been diagnosed during prenatal genetic testing, in infancy a male with 47, XXY (or variants: 46, XY-47, XXY; 48, XXXY; 48, XXYY, 49, XXXXY) may be found while undergoing evaluation of micropenis, hypospadias, cryptorchidism or facial anomalies. The older child may present with learning disabilities, behavior disorders or tall stature. At the time of puberty, the clinical picture includes small testes, gynecomastia and an eunuchoid habitus. Early diagnosis of Klinefelter syndrome must be performed since it has been demonstrated that early treatment with androgens may ameliorate many aspects of the clinical symptoms and attenuate or prevent behavioral and psychiatric disorders associated with 47, XXY males.  相似文献   

19.
Bacterial regeneration of ammonium and phosphate as affected by the carbon:nitrogen:phosphorus ratio of organic substrates   总被引：10，自引：2，他引：8  
Yasuhiko Tezuka 《Microbial ecology》1990,19(3):227-238
The effect of carbonnitrogenphosphorus (CNP) ratio of organic substrates on the regeneration of ammonium and phosphate was investigated by growing natural assemblages of freshwater bacteria in mineral media supplemented with the simple organic C, N, and P sources (glucose, asparagine, and sodium glycerophosphate, respectively) to give 25 different substrate CNP ratios. Both ammonium and phosphate were regenerated when CN and NP atomic ratios of organic substrates were 101 and 161, respectively. Only ammonium was regenerated when CN and NP ratios were 101 and 10–201, respectively. On the other hand, neither ammonium nor phosphate was regenerated when CN and NP ratios were 151 and 51, respectively. In no case was phosphate alone regenerated. As bacteria were able to alter widely the CNP ratio of their biomass, the growth yield of bacteria appeared primarily dependent on the substrate carbon concentration, irrespective of a wide variation in the substrate CNP ratio.  相似文献   

20.
Immunoreactivity for alpha-smooth muscle actin characterizes a potentially aggressive subgroup of little basal cell carcinomas     
L. Pilloni  P. Bianco  C. Manieli  G. Senes  P. Coni  L. Atzori  N. Aste  G. Faa 《European journal of histochemistry : EJH》2009,53(2)
Basal cell carcinoma (BCC) is a very common malignant skin tumor that rarely metastatizes, but is often locally aggressive. Several factors, like large size (more than 3 cm), exposure to ultraviolet rays, histological variants, level of infiltration and perineural or perivascular invasion, are associated with a more aggressive clinical course. These morphological features seem to be more determinant in mideface localized BCC, which frequently show a significantly higher recurrence rate. An immunohistochemical profile, characterized by reactivity of tumor cells for p53, Ki67 and alpha-SMA has been associated with a more aggressive behaviour in large BCCs. The aim of this study was to verify if also little (<3 cm) basal cell carcinomas can express immunohistochemical markers typical for an aggressive behaviour.Basal cell carcinoma (BCC) is a very common malignant skin tumor that rarely metastatizes, even If Is often locally aggressive. Several factors, like large size (more than 3 cm), face localization, exposure to ultraviolet rays, histological variants, infiltration level and perineural or perivascular invasion, are associated with a more aggressive clinical course. In particular, the incidence of metastasis and/or death correlates with tumors greater than 3 cm in diameter in which setting patients are said to have 1–2 % risk of metastases that increases to 20–25% in lesions greater than 5 cm and to 50% in lesions greater than 10 cm in diameter (Snow et al., 1994). Histologically morpheiform, keratotic types and infiltrative growth of BCC are also considered features of the most aggressive course (Crowson, 2006). This can be explained by the fact that both the superficial and nodular variants of BCC are surrounded by a continuous basement membrane zone comprising collagens type IV and V admixed with laminin, while the aggressive growth variants (i.e. morpheiform, metatypical, and infiltrative growth subtypes) manifest the absence of basement membrane (Barsky et al., 1987).The molecular markers which characterize aggressive BCC include: increased expression of stromolysin (MMP-3) and collagenase-1 (MMP-1) (Cribier et al., 2001), decreased expression of syndecan-1 proteoglycan (Bayer-Garner et al., 2000) and of anti-apoptotic protein bcl-2 (Ramdial et al., 2000; Staibano et al., 2001).C-ras , c-fos (Urabe et al., 1994; Van der Schroeff et al., 1990) and p53 tumor supressor gene mutations (Auepemikiate et al., 2002) are indicative of an aggressive course.Focusing upon bcl-2 and p53 expression in BCC, there have been numerous studies documenting the utility of bcl-2 as a marker of favourable clinical behaviour while p53 expression may be a feature of a more aggressive outcome (Ramdial et al., 2000; Staibano et al., 2001; Bozdogan et al., 2002).An increased expression of cytoskeletal microfilaments like α–smooth muscle actin, frequently found in invasive BCC subtypes (Jones JCR et al., 1989), may explain an enhanced tumor mobility and deep tissue invasion through the stroma. (Cristian et al., 2001; Law et al., 2003). The aim of this preliminary study was to verify if also little (<3 cm) basal cell carcinomas may express aggressive immunohistochemical markers like p53, Ki67 and alpha-SMA. We used 31 excisional BCCs with tumor size less than 2 cm (ranging from 2 up to 20 mm) and with different skin localization (19 in the face, 6 in the trunk and 6 in the body extremities). All cases were immunostained for p53, BCL2, Ki67 and alpha-smooth muscle actin (α-SMA) (AgeSexLocationHystotypeMax.DimDepthUlcEssInfp53Bcl-2Ki67AML161MExtrKeratotic10×81No+++URD+++++-261MFaceAdenoid10×94No+URD+++---364MExtrSup mult11×130.8No+DRD+---473MFaceNodular10×82Yes+DRD+++++++++584MFaceNodular9×122Yes+DRD----684MFaceAdenoid50.8No+URD+++---784MExtrNodular13×103No+DRD+++++-852FFaceNodular40.8No+URD+++-976FFaceAdenoid10×44No+DRD+++-++-1077FFaceMorph8×61Yes+++DRD+++---1186MFaceMorph81Yes+DRD+++-++1263FFaceAdenoid41No+URD+++++1376FFaceNodular71.5No+DRD++++++-1484MFaceNodular114Yes+++DRD+--+1563FFaceKeratotic10×61.8No++DRD-+++-1668FTrunkSup mult10×60.7No++URD++--1767MFaceSup mult12×60.4No+URD+-+-1867MExtrSup mult4×30.3No+URD+++++-1932FExtrSup mult1×30.4No+URD+++-2045MTrunkNodular7×52Yes+++URD+++-2162MTrunkSup mult11×70.9No++URD-++-++2265MTrunkAdenoid7×61.5No+URD+++++-2372MTrunkNodular12×61No+URD+++-++2486FFaceKeratotic20×113.1No++DRD+++-2585MFaceNodular0.51.3No++DRD++++-2674FExtrNodular4×40.9No+URD--+-2771MFaceNodular6×121.7No+DRD--+-2864FTrunkSup mult1.3×1.50.4No++URD+++---2978FFaceNodular4×31.5No++DRD+++-+++3080MFaceKeratotic4×41.6Yes+DRD--++++Open in a separate window Our data show that p53 (75%), Bcl2 (50%) and Ki67 (63%) positivity was generally diffuse in the majority of cases. On the contrary, cytoplasmatic α-SMA expression was present only in 8 out of 31 cases (25,8%). All these 8 α-SMA positive BCCs, prevalently found in the mideface (6 out of 8), were characterized by an initial invasion beyond the dermis. Among these 6 face-localized α-SMA positive BCCs, 1 showed a sclerosing aggressive histotype, 1 a keratotic type and 4 a nodular histotype.These 8 little α-SMA-positive BCCs, compared to the others 23 α-SMA negative samples, all showed a major aggressiveness features: facial location, ulceration, morpheiform histotype and deeper infiltration into the dermis (Location
Histotype
Local aggressiveness
Immunohistochemistry
FaceKeratoticMorpheiformDepht of invasion Mean value(mm)UlcerationInfiltration of the dermisP53Bcl-2Ki678 α-SMA Positive cases75%12%12%1.650%63%75%50%63%23 α-SMA Negative cases56%13%4%1.413%48%78%43%65%Open in a separate windowGiven the absence of a specific difference between α-SMA positive cases and α-SMA negative cases in the expression of aggressive immunohistochemical markers, except for a light reduction of bcl-2 in the α-SMA positive group (​and2).2). By the analysis of the data, we selected the combination that could better define an aggressive behaviour even for little BCC: α-SMA, p53, Ki67 positivity and bcl-2 negativity. We considered p53 and ki67 markers of proliferation and cell-cycle alteration, combined with a loss of apoptotic activity expressed by Bcl-2 negativity, quite characteristic of aggressiveness; moreover α-SMA positivity probably reflects invasive potential and acquired mobility by neoplastic cells.This immunohistochemical profile (α-SMA, p53, Ki67 positivity and bcl-2 negativity) in our cases of BCC is present in two of them; one is a morpheiform BCC, that is an aggressive variant, while the other one is a nodular subtype (less aggressive).Therefore, our preliminary data suggest that only α-SMA positivity should be considered as an early diagnostic marker of potential aggressiveness in little BCC: all α-SMA positive little BCC in fact showed clinical and histological features of aggressiveness. Invasive potential is probably acquired by some BCCs not only when they reach large size, but it is probably present also when they have still little size, and can be revealed by α-SMA positivity in the neoplastic cells. Open in a separate windowFigure 1BCC, nodular type, HE, 10×. Open in a separate windowFigure 2BCC, nodular type, α-SMA positivity, 10×.  相似文献   

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