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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.
DNA sequencing has been revolutionized by the development of high-throughput sequencing technologies. Plummeting costs and the massive throughput capacities of second and third generation sequencing platforms have transformed many fields of biological research. Concurrently, new data processing pipelines made rapid de novo genome assemblies possible. However, high quality data are critically important for all investigations in the genomic era. We used chloroplast genomes of one Oryza species (O. australiensis) to compare differences in sequence quality: one genome (GU592209) was obtained through Illumina sequencing and reference-guided assembly and the other genome (KJ830774) was obtained via target enrichment libraries and shotgun sequencing. Based on the whole genome alignment, GU592209 was more similar to the reference genome (O. sativa: AY522330) with 99.2% sequence identity (SI value) compared with the 98.8% SI values in the KJ830774 genome; whereas the opposite result was obtained when the SI values in coding and noncoding regions of GU592209 and KJ830774 were compared. Additionally, the junctions of two single copies and repeat copies in the chloroplast genome exhibited differences. Phylogenetic analyses were conducted using these sequences, and the different data sets yielded dissimilar topologies: phylogenetic replacements of the two individuals were remarkably different based on whole genome sequencing or SNP data and insertions and deletions (indels) data. Thus, we concluded that the genomic composition of GU592209 was heterogeneous in coding and non-coding regions. These findings should impel biologists to carefully consider the quality of sequencing and assembly when working with next-generation data. 相似文献
3.
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.
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.
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
TABLE 1.
Numbers of Bacteroidales cells in extraction wells, raw groundwater, and unchlorinated tap water of nine different groundwater plants in the Netherlandsa| Plant | Source of sample | No. (100 ml−1) of Bacteroidales cells in: | ||
|---|---|---|---|---|
| 2007 | 2008 | 2010 | ||
| A | Tap water 1b | 5,948 ± 950 | ||
| Tap water 2 | 2,682 ± 1,459 | 1,254 ± 216 | ||
| Tap water 3 | 4,362 ± 947 | 439 ± 136 | ||
| Raw water | 96 ± 15 | |||
| B | Tap water 1 | 3,553 ± 981 | 5,302 ± 2,952 | |
| Tap water 2 | 4,487 ± 391 | 2,119 ± 1,367 | ||
| Tap water 3 | 7,862 ± 4,588 | 3,896 ± 3,003 | ||
| Raw water | 3,209 ± 833 | |||
| C | Tap water 1 | 661 ± 75 | 386 ± 199 | |
| Tap water 2 | 1,051 ± 626 | |||
| Tap water 3 | 831 ± 584 | |||
| Tap water 4 | 1,254 ± 216 | |||
| Extraction well 1 | 1,126 ± 262 | |||
| Extraction well 2 | 2,666 ± 51 | |||
| Extraction well 3 | <50 | |||
| Raw water | 90 ± 44 | |||
| D | Tap water | 1,103 ± 29 | 1,254 ± 216 | |
| Raw water | 48 ± 16 | |||
| E | Tap water | 1,302 ± 222 | 1,254 ± 216 | |
| Extraction well 1 | 671 ± 97 | |||
| F | Tap water | 1,317 ± 198 | ||
| Raw water | <50 | |||
| G | Tap water 1 | 675 ± 92 | 439 ± 300 | |
| Tap water 2 | 216 ± 65 | 249 ± 98 | ||
| Tap water 3 | 154 ± 6 | 322 ± 137 | ||
| Raw water | <50 | |||
| H | Tap water | 7,073 ± 845 | ||
| Raw water | 511 ± 254 | |||
| I | Tap water | 1,577 ± 176 | ||
| Raw water | 420 ± 66 | |||
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 OTUsb | GenBank sequence accession no. | Source of sequence (GenBank sequence accession no.) | Similarityc | Nearest cultivated bacterium in GenBank (sequence accession no.) | Similarity |
|---|---|---|---|---|---|
| AllBac | |||||
| Extraction well 1 (3/6) | GQ169588 | Rhizosphere (EF605968) | 108/108 | Prevotella oralis (AY323522) | 105/108 |
| Extraction well 1 (3/6) | GQ169589 | Water from watershed (DQ886209) | 108/108 | Tannerella forsythia(AB035460) | 107/108 |
| Extraction well 2 (1/6) | GQ169590 | Phyllosphere Brazilian forest (DQ221468) | 108/108 | Tannerella forsythia(AB035460) | 106/108 |
| Extraction well 2 (5/6) | GQ169591 | Bovine rumen (EU348207) | 108/108 | Tannerella forsythia(AB035460) | 106/108 |
| Extraction well 3 (1/6) | GQ169592 | Phyllosphere Brazilian forest (DQ221468) | 108/108 | Prevotella oralis (AY323522) | 104/108 |
| Extraction well 3 (5/6) | GQ169593 | Prevotella corporis (L16465) | 108/108 | Prevotella corporis (L16465) | 108/108 |
| Raw water (3/6) | GQ169594 | Spitsbergen permafrost (EF034756) | 108/108 | Tannerella forsythia(AB035460) | 106/108 |
| Raw water (3/6) | GQ169595 | Hindgut beetle larvae (FJ374179) | 108/108 | Tannerella forsythia(AB035460) | 107/108 |
| Tap water (6/6) | GQ169596 | Prevotella timonensis (DQ518919) | 108/108 | Prevotella 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) | GQ169597 | Deep subsurface groundwater (AB237705) | 339/369 | Salinimicrobium terrae (EU135614) | 315/370 |
| Extraction well 1 (1/10) | GQ169598 | Songhuajiang River sediment (DQ444125) | 363/377 | Paludibacter propionicigenes (AB078842) | 357/376 |
| Extraction well 1 (4/10) | GQ169599 | Freshwater pond sediment (DQ676447) | 352/360 | Paludibacter propionicigenes (AB078842) | 313/372 |
| Extraction well 1 (4/10) | GQ169600 | Pine River sediment (DQ833352) | 364/371 | Bacteroides oleiciplenus (AB490803) | 334/375 |
| Extraction well 2 (4/10) | GQ169601 | Groundwater (AF273319) | 364/371 | Xanthobacillum maris (AB362815) | 338/375 |
| Extraction well 2 (6/10) | GQ169602 | Human saliva (AB028385) | 381/382 | Prevotella intermedia (AY689226) | 380/382 |
| Extraction well 3 (1/10) | GQ169603 | Pig manure (AY816766) | 354/377 | Bacteroides thetaiotaomicron (AE015928) | 311/380 |
| Extraction well 3 (3/10) | GQ169604 | Pig manure (AY816867) | 371/376 | Butyricimonas virosa (AB443949) | 307/379 |
| Extraction well 3 (6/10) | GQ169605 | Swedish lake (AY509350) | 343/362 | Parabacteroides distasonis (AB238927) | 320/374 |
| Raw water (10/10) | GQ169606 | Prevotella timonensis (AF218617) | 378/379 | Prevotella timonensis (AF218617) | 378/379 |
| Tap water (1/10) | GQ169607 | Deep subsurface groundwater (AB237705) | 338/369 | Salinimicrobium terrae (EU135614) | 312/370 |
| Tap water (2/10) | GQ169608 | Yukon River, AK(FJ694652) | 367/372 | Psychroserpens burtonensis (U62913) | 312/375 |
| Tap water (7/10) | GQ169609 | Deep subsurface groundwater (AB237705) | 341/369 | Salinimicrobium terrae (EU135614) | 315/370 |
4.
The purpose of this table is to provide the community with a citable record of publications of ongoing genome sequencing projects that have led to a publication in the scientific literature. While our goal is to make the list complete, there is no guarantee that we may have omitted one or more publications appearing in this time frame. Readers and authors who wish to have publications added to subsequent versions of this list are invited to provide the bibliographic data for such references to the SIGS editorial office.
Phylum Euryarchaeota
- Halococcus hamelinensis, sequence accession PRJNA80845 [1]
- “Methanocella conradii” HZ254, sequence accession CP003243 [2]
- Thermococcus litoralis NS-C, sequence accession AHVB00000000 [3]
Phylum Crenarchaeota
- Candidatus Nitrosopumilus salaria” BD31, sequence accession AEXL00000000 [4]
- Candidatus Nitrosoarchaeum limnia, sequence accession AHJG00000000 [5]
Phylum Deinococcus-Thermus
Phylum Proteobacteria
- Aggregatibacter actinomycetemcomitans strain ANH9381, sequence accession CP003099 [7]
- Alishewanella jeotgali, sequence accession AHTH00000000 [8]
- Enterobacter aerogenes KCTC 2190, sequence accession CP002824 [9]
- Escherichia coli O104:H4, sequence accession AFOB02000092 [10]
- Helicobacter pylori strains 17874, sequence accession PRJNA76569 [11]
- Helicobacter pylori strains P79, sequence accession PRJNA76567 [11]
- Janthinobacterium sp. Strain PAMC 25724, sequence accession AHHB00000000 [12]
- Klebsiella oxytoca KCTC 1686, sequence accession CP003218 [13]
- Klebsiella pneumoniae subsp. pneumoniae HS11286, sequence accession CP003200 (chromosome), CP003223 (plasmid pKPHS1), CP003224 (plasmid pKPHS2), CP003225 (plasmid pKPHS3), CP003226 (plasmid pKPHS4), CP003227 (plasmid pKPHS5), CP003228 (plasmid pKPHS6) [14]
- Oceanimonas sp. GK1, sequence accession CP003171 [15]
- “Pseudogulbenkiania ferrooxidans” Strain 2002, sequence accession NZ_ACIS01000000 [16]
- Pseudomonas extremaustralis 14-3b, sequence accession AHIP00000000 [17]
- Pseudomonas sp. Strain PAMC 25886, sequence accession AHHC00000000 [18]
- Psychrobacter, sequence accession AHVZ00000000 [19]
- Rahnella sp. Strain Y9602, sequence accession CP002505 [20]
- Rhizobium sp. Strain PDO1-076, sequence accession AHZC00000000 [21]
- Rhodospirillum photometricum DSM122, sequence accession HE663493 [22]
- “Rickettsia sibirica sibirica”, sequence accession AHIZ00000000 [23]
- Rickettsia sibirica subsp. mongolitimonae strain HA-91, sequence accession AHZB00000000 [24]
- Salmonella enterica subsp. enterica Serotype Enteritidis Strain LA5, sequence accession [25]
- Salmonella enterica subsp. enterica Serotype Senftenberg Strain SS209, sequence accession CAGQ00000000 [26]
- Salmonella enterica subsp. enterica Serovar Typhi P-stx-12, sequence accession CP003278 (chromosome) and CP003279 (plasmid) [27]
- Sphingomonas echinoides ATCC 14820, sequence accession AHIR00000000 [28]
- Strain HIMB55, sequence accession AGIF00000000 [29]
- Vibrio harveyi CAIM 1792, sequence accession AHHQ00000000 [30]
- Wolbachia Strain wAlbB, sequence accession CAGB01000001 to CAGB01000165 [31]
- Xanthomonas axonopodis pv. punicae Strain LMG 859, sequence accession CAGJ01000001 to CAGJ01000217 [32]
Phylum Tenericutes
Phylum Firmicutes
- Bacillus subtilis, sequence accession BGSCID 3A27 through BGSCID 28A4 [34]
- Clostridium difficile Strain CD37, sequence accession AHJJ00000000 [35]
- Clostridium perfringens, sequence accession AFES00000000 [36]
- Lactobacillus fructivorans KCTC 3543, sequence accession AEQY00000000 [37]
- Lactococcus lactis IO-1, sequence accession AP012281 [38]
- Lactobacillus plantarum strain NC8, sequence accession AGRI00000000 [39]
- Paenibacillus dendritiformis C454, sequence accession AHKH00000000 [40]
- Paenibacillus sp. Strain Aloe-11, sequence accession AGFI00000000 [41]
- “Peptoniphilus rhinitidis” 1-13T, sequence accession BAEW01000001 to BAEW01000056 [42]
- Streptococcus macedonicus ACA-DC 198, sequence accession HE613569 and HE613570 [43]
- Staphylococcus aureus VC40, sequence accession CP003033 [44]
- Streptococcus infantarius subsp. infantarius Strain CJ18, sequence accession CP003295 (chromosome), CP003296 (plasmid) [45]
- Streptococcus macedonicus ACA-DC 198, sequence accession HE613569 (chromosome), HE613570 (plasmid pSMA198) [46]
Phylum Actinobacteria
- Actinoplanes sp. SE50/110, sequence accession CP003170 [47]
- Amycolatopsis sp. Strain ATCC 39116, sequence accession [48]
- Nocardia cyriacigeorgica GUH-2, sequence accession FO082843 [49]
- Salinibacterium sp., sequence accession AHWA00000000 [50]
- Streptomyces acidiscabies 84-104, sequence accession AHBF00000000 [51]
Non-Bacterial genomes
- Bluetongue Virus Serotype 2, sequence accession AJ783905 (Seg-6) and JQ681257 (Seg-1), JQ681257 (Seg-1), JQ681258 (Seg-2), JQ681259 (Seg-3), JQ681260 (Seg-4), JQ681261 (Seg-5), JQ681262 (Seg-7), JQ6812563 (Seg-8), JQ6812564 (Seg-9), to JQ681265 (Seg-10) [52]
- Virus Serotype 1, sequence accession AJ585111 (Seg-2), AJ586659 (Seg-6), JQ282770 (Seg-1), JQ282771 (Seg-3), JQ282772 (Seg-4), JQ282773 (Seg-5), JQ282774 (Seg-7), JQ282775 (Seg-8), JQ282776 (Seg-9), and JQ282777 (Seg-10) [52]
- Chloroplast genome of Erycina pusilla, sequence accession JF_746994 [53]
- Danio rerio, sequence accession JQ434101 [54]
- Enterococcal Bacteriophage SAP6, sequence accession JF731128 [55]
- Eubenangee virus, sequence accession JQ070376 through JQ070385 [56]
- Fujian/411-like viruses, sequence accession CY087969 to CY088568 [57]
- Hantavirus Variant of Rio Mamoré Virus, Maripa Virus, sequence accession JQ611712 (segment S), JQ611713 (segment M), and JQ611714 (segment L) [58]
- Pata virus, sequence accession JQ070386 through JQ070395 [59]
- Porcine Circovirus 2, sequence accession JQ413808 [60]
- Porcine Reproductive and Respiratory Syndrome Virus, sequence accession JQ326271 [61]
- Streptococcus mutans Phage M102AD, sequence accession DQ386162 [62]
- Tilligery virus, sequence accession JQ070366 through JQ070375 [63]
5.
Lavanya Rishishwar Lee S. Katz Nitya V. Sharma Lori Rowe Michael Frace Jennifer Dolan Thomas Brian H. Harcourt Leonard W. Mayer I. King Jordan 《Journal of bacteriology》2012,194(20):5649-5656
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
6.
The purpose of this table is to provide the community with a citable record of publications of ongoing genome sequencing projects that have led to a publication in the scientific literature. While our goal is to make the list complete, there is no guarantee that we may have omitted one or more publications appearing in this time frame. Readers and authors who wish to have publications added to subsequent versions of this list are invited to provide the bibliographic data for such references to the SIGS editorial office.
- Phylum Crenarchaeota
- Thermoproteus tenax, strain Kra1, DSM 2078T sequence accession FN869859 [1]
- Phylum Euryarchaeota
- Haloarcula hispanica CGMCC 1.2049, sequence accession CP002921 (chromosome I), CP002922 (chromosome II), and CP002923 (plasmid pHH400) [2]
- Methanococcus maripaludis, strain X1 (unculturable) sequence accession CP002913 [3]
- Phylum Proteobacteria
- Acinetobacter baumannii strain 1656-2, sequence accession CP001921 [4]
- Arcobacter butzleri strain ED-1, sequence accession AP012047, AP012048, and AP012049 [5]
- Brucella suis strain 1330, sequence accession CP002997 and CP002998 [6]
- Campylobacter fetus subsp. venerealis NCTC 10354, sequence accession AFGH01000000 [7]
- “Chromobacterium sp.” strain C-61, sequence accession CAEE01000001 to CAEE01001118 [8]
- Cronobacter sakazakii strain E899, sequence accession AFMO00000000 [9]
- “Desulfovibrio sp.” strain A2, sequence accession AGFG01000000 [10]
- “Erythrobacter sp.” strain NAP1, sequence accession NZ_AAMW00000000 [11]
- Escherichia coli strain XH140A, sequence accession AFVX01000000 [12]
- Escherichia coli strain XH001, sequence accession AFYG01000000 [13]
- Haemophilus haemolyticus strain M19107, sequence accession AFQN00000000 [14]
- Haemophilus haemolyticus strain M19501, sequence accession AFQO00000000 [14]
- Haemophilus haemolyticus strain M21127, sequence accession AFQP00000000 [14]
- Haemophilus haemolyticus strain M21621, sequence accession AFQQ00000000 [14]
- Haemophilus haemolyticus strain M21639, sequence accession AFQR00000000 [14]
- Idiomarina sp.” strain A28L, sequence accession AFPO01000001 to AFPO01000028 [15]
- Ketogulonicigenium vulgare” strain WSH-001, sequence accession CP002018 (chromosome), CP002019 (plasmid pKVU_100), and CP002020 (plasmid pKVU_200) [16]
- Methylobacter tundripaludum strain SV96, sequence accession AEGW00000000 [17]
- Pseudogulbenkiania sp.” strain NH8B, sequence accession AP012224 [18]
- Pseudomonas aeruginosa NCGM1179, sequence accession DF126593 through DF126613 [19]
- Pseudomonas putida strain B001, sequence accession CAED01000001 to CAEE01000262 [20]
- Pseudomonas putida strain B6-2, sequence accession AGCS01000000 [21]
- Pseudomonas stutzeri CGMCC 1.1803, sequence accession CP002881 [22]
- Ralstonia solanacearum phylotype IB, strain Y45, sequence accession AFWL01000000 [23]
- Rheinheimera sp.” strain A13L, sequence accession AFHI01000001 through AFHI01000072 [24]
- Sphingobium yanoikuyae strain XLDN2-5, sequence accession AFXE01000000 [25]
- Vibrio cholerae strain Amazonia, sequence accession AFSV01000000 [26]
- Phylum Firmicutes
- Bacillus coagulans strain XZL4, sequence accession AFWM01000000 [27]
- Bacillus megaterium strain WSH-002, sequence accession CP003017 (chromosome), plasmids CP003018 (plasmid pBME_100), CP003019 (plasmid pBME_200), and CP003020 (plasmid pBME_300) [28]
- Bacillus pumilus strain S-1, sequence accession AGBY00000000 [29]
- “Desulfosporosinus sp.” strain OT, sequence accession AGAF01000000 [30]
- Lentibacillus jeotgali strain Grbi, sequence accession AGAV01000000 [31]
- Leuconostoc carnosum KCTC 3525, sequence accession BACM01000000 [32]
- Listeria ivanovii subsp. ivanovii strain PAM 55, sequence accession FR687253 [33]
- Paenibacillus riograndensis strain SBR5, sequence accession AGBD01000000 [34]
- Sporolactobacillus inulinus strain CASD, sequence accession AFVQ00000000 [35]
- Streptococcus pseudopneumoniae strain IS7493, sequence accession CP002925 and CP002926 [36]
- Streptococcus salivarius strain 57.I, sequence accession CP002888 and CP002889 [37]
- Streptococcus salivarius strain M18, sequence accession AGBV01000000 [38]
- Streptococcus suis SS12, sequence accession CP002640 [39]
- Streptococcus suis D9, sequence accession CP002641 [39]
- Streptococcus suis D12, sequence accession CP002644 [39]
- Streptococcus suis ST1, sequence accession CP002651 [39]
- Weissella thailandensis strain fsh4-2, sequence accession HE575133 through HE575182 [40]
- Phylum Tenericutes
- Mycoplasma anatis strain 1340, sequence accession AFVJ00000000 [41]
- Mycoplasma capricolum subsp. capripneumoniae strain M1601, sequence accession AENG01000000 [42]
- Mycoplasma putrefaciens Type strain KS1, sequence accession CP003021 [43]
- Corynebacterium pseudotuberculosis strain PAT10, sequence accession CP002924 [44]
- Phylum Actinobacteria
- Bifidobacterium animalis subsp. lactis strain BLC1, sequence accession CP003039 [45]
- Bifidobacterium breve strain DPC 6330, sequence accession AFXX01000000 [46]
- Brachybacterium squillarum strain M-6-3, sequence accession AGBX01000000 [47]
- “Citricoccus sp.” strain CH26A, sequence accession AFXQ01000000 [48]
- Corynebacterium glutamicum strain S9114, sequence accession AFYA01000000 [49]
- Dietzia alimentaria strain 72, sequence accession AGFF01000000 [50]
- Mycobacterium colombiense CECT 3035, sequence accession AFVW00000000 [51]
- Mycobacterium tuberculosis NCGM2209, sequence accession DF126614 and DF126615 [52]
- Rhodococcus erythropolis strain XP, sequence accession AGCF01000000 [53]
- Serinicoccus profundi MCCC 1A05965T, sequence accession AFYF00000000 [54]
- Phylum Spirochaetes
- Leptospira interrogans, sequence accession CP001221 (CI), CP001222 (CII) [55]
- Phylum Bacteroidetes
- Bacteroides faecis Type strain MAJ27T, sequence accession AGDG01000000 [56]
- Bizionia argentinensis, Type strain JUB59T sequence accession AFXZ01000000 [57]
- Flavobacterium branchiophilum strain FL-15, sequence accession FQ859183 [58]
- “Flavobacteriaceae” strain S85, sequence accession AFPK00000000 [59]
- Phylum Thermotogae
- “Thermotoga sp.” strain RQ2, sequence accession CP000969 [60]
Non-Bacterial genomes
- Aspergillus kawachii IFO 4308, sequence accession DF126447 through DF126592, BACL01000001 through BACL01001641, AP012272 [61]
- Cajanus cajan pigeonpea, sequence accession PRJNA72815 [62]
- Coxsackievirus A22, sequence accession JN542510 [63]
- Gordonia phage GRU1, sequence accession JF923797 [64]
- Gordonia phage GTE5, sequence accession JF923796 [64]
- Heterocephalus glaber naked mole rat, sequence accession AFSB00000000, AFSB01000000 [65]
- Human Adenovirus Prototype 17, sequence accession HQ910407 [66]
- Macaca mulatta lasiota rhesus macaque, sequence accession AEHL00000000 [67]
- Macaca mulatta mulatta rhesus macaque, sequence accession AEHK00000000 [67]
- Porcine epidemic diarrhea virus, sequence accession JN547228 [68]
7.
Lyubomir G. Nashev Anna Vuorinen Lukas Praxmarer Boonrat Chantong Diego Cereghetti Rahel Winiger Daniela Schuster Alex Odermatt 《PloS one》2012,7(10)
Background
Impaired corticosteroid action caused by genetic and environmental influence, including exposure to hazardous xenobiotics, contributes to the development and progression of metabolic diseases, cardiovascular complications and immune disorders. Novel strategies are thus needed for identifying xenobiotics that interfere with corticosteroid homeostasis. 11β-hydroxysteroid dehydrogenase 2 (11β-HSD2) and mineralocorticoid receptors (MR) are major regulators of corticosteroid action. 11β-HSD2 converts the active glucocorticoid cortisol to the inactive cortisone and protects MR from activation by glucocorticoids. 11β-HSD2 has also an essential role in the placenta to protect the fetus from high maternal cortisol concentrations.Methods and Principal Findings
We employed a previously constructed 3D-structural library of chemicals with proven and suspected endocrine disrupting effects for virtual screening using a chemical feature-based 11β-HSD pharmacophore. We tested several in silico predicted chemicals in a 11β-HSD2 bioassay. The identified antibiotic lasalocid and the silane-coupling agent AB110873 were found to concentration-dependently inhibit 11β-HSD2. Moreover, the silane AB110873 was shown to activate MR and stimulate mitochondrial ROS generation and the production of the proinflammatory cytokine interleukin-6 (IL-6). Finally, we constructed a MR pharmacophore, which successfully identified the silane AB110873.Conclusions
Screening of virtual chemical structure libraries can facilitate the identification of xenobiotics inhibiting 11β-HSD2 and/or activating MR. Lasalocid and AB110873 belong to new classes of 11β-HSD2 inhibitors. The silane AB110873 represents to the best of our knowledge the first industrial chemical shown to activate MR. Furthermore, the MR pharmacophore can now be used for future screening purposes. 相似文献8.
damo Davi Digenes Siena Isabela Ichihara de Barros Camila Baldin Storti Carlos Alberto Oliveira de Biagi Júnior Larissa Anastacio da Costa Carvalho Silvya Stuchi Maria&#x;Engler Josane de Freitas Sousa Wilson Araújo Silva Jr 《Journal of cellular and molecular medicine》2022,26(3):671
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
9.
G Yu W Yao J Wang X Ma W Xiao H Li D Xia Y Yang K Deng H Xiao B Wang X Guo W Guan Z Hu Y Bai H Xu J Liu X Zhang Z Ye 《PloS one》2012,7(8):e42377
Background
Long noncoding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. They are aberrantly expressed in many types of cancers. In this study, we described lncRNAs profiles in 6 pairs of human renal clear cell carcinoma (RCCC) and the corresponding adjacent nontumorous tissues (NT) by microarray.Methodology/Principal Findings
With abundant and varied probes accounting 33,045 LncRNAs in our microarray, the number of lncRNAs that expressed at a certain level could be detected is 17157. From the data we found there were thousands of lncRNAs that differentially expressed (≥2 fold-change) in RCCC tissues compared with NT and 916 lncRNAs differentially expressed in five or more of six RCCC samples. Compared with NT, many lncRNAs were significantly up-regulated or down-regulated in RCCC. Our data showed that down-regulated lncRNAs were more common than up-regulated ones. ENST00000456816, X91348, BC029135, NR_024418 were evaluated by qPCR in sixty-three pairs of RCCC and NT samples. The four lncRNAs were aberrantly expressed in RCCC compared with matched histologically normal renal tissues.Conclusions/Significance
Our study is the first one to determine genome-wide lncRNAs expression patterns in RCCC by microarray. The results displayed that clusters of lncRNAs were aberrantly expressed in RCCC compared with NT samples, which revealed that lncRNAs differentially expressed in tumor tissues and normal tissues may exert a partial or key role in tumor development. Taken together, this study may provide potential targets for future treatment of RCCC and novel insights into cancer biology. 相似文献10.
11.
The purpose of this table is to provide the community with a citable record of publications of ongoing genome sequencing projects that have led to a publication in the scientific literature. While our goal is to make the list complete, there is no guarantee that we may have omitted one or more publications appearing in this time frame. Readers and authors who wish to have publications added to subsequent versions of this list are invited to provide the bibliographic data for such references to the SIGS editorial office.
Phylum Crenarchaeota
Phylum Deinococcus-Thermus
Phylum Proteobacteria
- “Achromobacter arsenitoxydans” SY8, sequence accession AGUF00000000 [3]
- Acidovorax sp. Strain NO1, sequence accession AGTS00000000 [4]
- Acinetobacter baumannii AB4857, sequence accession AHAG00000000 [5]
- Acinetobacter baumannii AB5075, sequence accession AHAH00000000 [5]
- Acinetobacter baumannii AB5256, sequence accession AHAI00000000 [5]
- Acinetobacter baumannii AB5711, sequence accession AHAJ00000000 [5]
- Aeromonas salmonicida, sequence accession AGVO00000000 [6]
- Aggregatibacter actinomycetemcomitans RHAA1, sequence accession AHGR00000000 [7]
- Agrobacterium tumefaciens 5A, sequence accession AGVZ00000000 [8]
- Azoarcus sp. Strain KH32C, sequence accession AP012304, AP012305 [9]
- Burkholderia sp. Strain YI23, sequence accession CP003087 (Chromosome 1), CP003088 (Chromosome 2), CP003089 (Chromosome 3), CP003090 (plasmid BYI23_D), CP003091 (plasmid BYI23_E) CP003092 (plasmid BYI23_F) [10]
- Brucella suis VBI22, sequence accession CP003128, CP003129 [11]
- Comamonas testosteroni ATCC 11996, sequence accession AHIL00000000 [12]
- “Commensalibacter intestini” A911T, sequence accession AGFR00000000 [13]
- Edwardsiella ictaluri, sequence accession CP001600.1 [14]
- Enterobacter cloacae subsp. dissolvens SDM, sequence accession AGSY00000000 [15]
- “Gluconobacter morbifer” G707T, sequence accession AGQV00000000 [16]
- Legionella dumoffii TEX-KL, sequence accession AGVT00000000 [17]
- Legionella dumoffii NY-23, sequence accession AGVU00000000 [17]
- Legionella pneumophila serogroup 12 Strain 570-CO-H, sequence accession CP003192 [18]
- Marinobacterium stanieri S30, sequence accession AFPL00000000 [19]
- “Marinobacter manganoxydans” MnI7-9, sequence accession CP001978 to CP001980 [20]
- Mesorhizobium alhagi CCNWXJ12-2T, sequence accession AHAM00000000 [21]
- Mesorhizobium amorphae, sequence accession AGSN00000000 [22]
- Methylomicrobium alcaliphilum 20Z, sequence accession FO082060 and FO082061 [23]
- Mitsuaria sp. Strain H24L5A, sequence accession CAFG01000001 to CAFG01000607 [24]
- Novosphingobium pentaromativorans US6-1, sequence accession AGFM00000000 [25]
- Pantoea ananatis B1-9, sequence accession CAEI01000001 to CAEI01000169 [26]
- Pantoea ananatis LMG 5342, sequence accession HE617160 (chromosome), HE617161 (pPANA10) [27]
- Pantoea ananatis Strain PA13, sequence accession CP003085 and CP003086 [28]
- Pseudomonas aeruginosa, sequence accession AFXI00000000 [29]
- Pseudomonas aeruginosa, sequence accession AFXJ00000000 [29]
- Pseudomonas aeruginosa, sequence accession AFXK00000000 [29]
- Pseudomonas chlororaphis GP72, sequence accession AHAY01000000 [30]
- Pseudomonas fluorescens F113, sequence accession CP003150 [31]
- Pseudomonas fluorescens Wayne 1R, sequence accession CADX01000001 to CADX01000090 [32]
- Pseudomonas fluorescens Wood1R, sequence accession CAFF01000001 to CAFF01001437 [32]
- Pseudomonas psychrotolerans L19, sequence accession AHBD00000000 [33]
- Pseudoalteromonas rubra ATCC 29570T, sequence accession AHCD00000000 [34]
- Pseudomonas stutzeri SDM-LAC, sequence accession AGSX00000000 [35]
- Pseudoxanthomonas spadix BD-a59, sequence accession CP003093 [36]
- Rickettsia slovaca, sequence accession CP002428 [37]
- Salmonella enterica serovar Pullorum RKS5078, sequence accession CP003047 [38]
- Sinorhizobium meliloti CCNWSX0020, sequence accession AGVV00000000 [39]
- Sphingobium sp. Strain SYK-6, sequence accession AP012222 and AP012223 [40]
- Sphingomonas sp. Strain PAMC 26605, sequence accession AHIS00000000 [41]
- Stenotrophomonas maltophilia RR-10, sequence accession AGRB00000000 [42]
- Strain HIMB30, sequence accession AGIG00000000 [43]
- Taylorella equigenitalis, sequence accession CP003059 [44]
- Vibrio campbellii DS40M4, sequence accession AGIE00000000 [45]
- Vibrio fischeri SR5, sequence accession AHIH00000000 [46]
- Yersinia enterocolitica, sequence accession AGQO00000000 [47]
Phylum Tenericutes
- Candidatus Mycoplasma haemominutum, sequence accession HE613254 [48]
- Mycoplasma haemocanis strain Illinois, sequence accession CP003199 [49]
- Mycoplasma iowae, sequence accession AGFP00000000 [50]
- Mycoplasma pneumoniae Type 2a Strain 309, sequence accession AP012303 [51]
Phylum Firmicutes
- Bacillus cereus F837/76, sequence accession CP003187 (chromosome) CP003188 (pF837_55kb), CP003189 (pF837_10kb) [52]
- Brevibacillus laterosporus Strain GI-9, sequence accession CAGD01000001 to CAGD01000061 [53]
- Clostridium sporogenes PA 3679, sequence accession AGAH00000000 [54]
- Enterococcus mundtii CRL1656, sequence accession AFWZ00000000.1 [55]
- Geobacillus thermoleovorans CCB_US3_UF5, sequence accession CP003125 [56]
- Lactobacillus curvatus Strain CRL705, sequence accession AGBU01000000 [57]
- Lactobacillus rhamnosus ATCC 8530, sequence accession CP003094 [58]
- Lactobacillus rhamnosus R0011, sequence accession AGKC00000000 [59]
- Lactococcus garvieae TB25, sequence accession AGQX01000000 [60]
- Lactococcus garvieae LG9, sequence accession AGQY01000000 [60]
- Lactococcus lactis subsp. cremoris A76, sequence accession CP003132 (chromosome), CP003136 (pQA505), CP003135 (PQA518), CP003134 (pQA549), CP003133 (pQA554) [61]
- Leuconostoc citreum LBAE C10, sequence accession CAGE00000000 [62]
- Leuconostoc citreum LBAE C11, sequence accession CAGF00000000 [62]
- Leuconostoc citreum LBAE E16, sequence accession CAGG00000000 [62]
- Leuconostoc mesenteroides subsp. mesenteroides Strain J18, sequence accession CP003101 [63]
- Paenibacillus peoriae Strain KCTC 3763T, sequence accession AGFX00000000 [64]
- Pediococcus acidilactici MA18/5M, sequence accession AGKB00000000 [65]
- Pediococcus claussenii ATCC BAA-344T, sequence accession CP003137 (chromosome), CP003138 (pPECL-1), CP003139 (pPECL-2), CP003140 (pPECL-3), CP003141 (pPECL-4), CP003142 (pPECL-5), CP003143 (pPECL-6), CP003144 (pPECL-7), CP003145 (pPECL-8) [66]
- Staphylococcus aureus M013, sequence accession CP003166 [67]
- Staphylococcus aureus subsp. aureus TW20, sequence accession FN433596 [68]
- Weissella confusa LBAE C39-2, sequence accession CAGH00000000 [69]
Phylum Actinobacteria
- Corynebacterium casei, sequence accession CAFW01000001 to CAFW01000106 [70]
- Corynebacterium glutamicum, sequence accession AGQQ00000000 [71]
- Leucobacter chromiiresistens, sequence accession AGCW00000000 [72]
- Mycobacterium abscessus, sequence accession AGQU00000000 [73]
- Propionibacterium acnes ST9, sequence accession CP003195 [74]
- Propionibacterium acnes ST22, sequence accession CP003196 [74]
- Propionibacterium acnes ST27, sequence accession CP003197 [74]
- Saccharomonospora azurea SZMC 14600, sequence accession AHBX00000000 [75]
- Streptomyces sp. Strain TOR3209, sequence accession AGNH00000000 [76]
- Streptomyces sp. Strain W007, sequence accession AGSW00000000 [77]
Phylum Spirochaetes
- Borrelia valaisiana VS116, sequence accession ABCY02000001 (chromosome), CP001439 (plasmid Ip17), CP001437 (Ip25), CP001440 (plasmid Ip 28-3), CP001442 (plasmid Ip28-8), CP001436 (Ip 36), CP001433 (plasmid Ip 54), CP001438 (plasmid cp9), CP001432 (plasmid cp26), CP001441 (plasmid cp32-5), CP001434 (plasmid cp32-7), CP001435 (plasmid cp32-10) [78]
- “Borrelia bissettii” DN127, sequence accession CP002746 (chromosome), CP002756 (plasmid Ip12), CP002757 (plasmid Ip25), CP002758 (plasmid 28-3), CP002759 (plasmid Ip 28-4), CP002760 (Ip28-7), CP002761 (plasmid Ip54), CP002762 (plasmid Ip56), CP002755 (plasmid cp9), CP002747 (plasmid cp26), CP002749 (plasmid cp32-3), CP002750 (plasmid cp32-4), CP002751 (plasmid 32-5), CP002752 (plasmid cp32-6), CP002753 (plasmid cp32-7), CP0027554 (plasmid cp32-9), CP002748 (plasmid cp32-11) [78]
- Borrelia spielmanii A14S, sequence accession ABKB02000001 (chromosome), CP001468 (plasmid Ip17), CP001471 (Ip28-3), CP001470 (plasmid Ip28-4), CP001465 (plasmid Ip28-2), CP001466 (plasmid Ip36), CP001464 (plasmid Ip38), CP001469 (plasmid Ip54), ABKB02000016, ABKB02000020 (plasmid cp9), CP001467 (plasmid cp26), ABKB02000026 (plasmid cp32-3), ABKB02000031 (plasmid 32-5), ABKB02000021 (plasmid cp32-12), ABKB02000014 (unidentified) [78]
Non-Bacterial genomes
- Aspergillus flavus, sequence accession GSE32177 [79]
- Bacteriophage SPN3UB, sequence accession JQ288021 [80]
- Bamboo mitochondria, sequence accession JQ235166 to JQ235179 [81]
- Boea hygrometrica chloroplast, sequence accession JN107811 [82]
- Boea hygrometrica mitochondrial, sequence accession JN107812 [82]
- Canine Picornavirus, sequence accession JN831356 [83]
- Chandipura virus (CHPV) CIN0327, sequence accession GU212856.1 [84]
- Chandipura virus (CHPV) CIN0451, sequence accession GU212857.1 [84]
- Chandipura virus (CHPV) CIN0751, sequence accession GU212858.1 [84]
- Chandipura virus (CHPV) CIN0755, sequence accession GU190711.1 [84]
- Chinese Porcine Parvovirus Strain PPV2010, sequence accession JN872448 [85]
- Common midwife toad megavirus, sequence accession JQ231222 [86]
- Dengue Virus Serotype 4, sequence accession JN983813 [87]
- Duck Tembusu Virus, sequence accession JF270480 [88]
- Duck Tembusu Virus, sequence accession JQ314464 [88]
- Duck Tembusu Virus, sequence accession JQ314465 [88]
- Emiliania huxleyi Virus 202, sequence accession HQ634145 [89]
- Emiliania huxleyi Virus EhV-88, sequence accession JF974310 [89]
- Emiliania huxleyi EhV-201, sequence accession JF974311 [89]
- Emiliania huxleyi EhV-207, sequence accession JF974317 [89]
- Emiliania huxleyi EhV-208, sequence accession JF974318 [89]
- Glarea lozoyensis, sequence accession GUE00000000 [90]
- Nannochloropis gaditana, sequence accession AGNI00000000 [91]
- Oryza sativa cv., sequence accession DRA000499 [92]
- Partetravirus, sequence accession JN990269 [93]
- Porcine Bocavirus PBoV5, sequence accession JN831651 [94]
- Porcine epidemic diarrhea virus, sequence accession JQ282909 [95]
- Pseudomonas aeruginosa lytic bacteriophage PA1Ø, sequence accession HM624080 [96]
- Pseudomonas fluorescens phage OBP, sequence accesssion JN627160 [97]
- RNA Virus from Avocado, sequence accession JN880414 [98]
- Salmonella enterica Serovar Typhimurium Bacteriophage SPN1S, sequence accession JN391180 [99]
- Schistosoma haematobium, sequence accession PRJNA78265 [100]
- Schistosoma mansoni, sequence accession ERP00038 [101]
- Stenopirates sp., sequence accession JN100019 [102]
- T7-Like Virus, sequence accession JN651747 [103]
- Vibrio harveyi siphophage VHS1, sequence accession JF713456 [104]
- Tyrolean ice man, sequence accession ERP001144 [105]
12.
Kang Wang Wei xing Guo Nan Li Chun fang Gao Jie Shi Yu fu Tang Feng Shen Meng chao Wu Shan rong Liu Shu qun Cheng 《PloS one》2015,10(12)
Background
Hepatocellular carcinoma (HCC) is a common malignancy that has a poor prognosis because there is lack of methods for early diagnosis. We aimed to utilize two serum long non-coding RNAs (lncRNAs), uc001ncr and AX800134, to diagnose hepatitis B virus (HBV)–positive HCC.Methods
lncRNA microarrays were utilized to measure the differential expression of lncRNAs between tumor tissues and corresponding non-tumor tissues in HBV-positive hapatocellular carcinoma. uc001ncr and AX800134 were selected as candidate lncRNAs and detected in three independent cohorts containing a total of 684 participants (healthy individuals and chronic HBV patients and HBV-positive HCC patients) who were recruited between March 2011 and December 2012. A logistic regression model was constructed using a training cohort (n = 353) and validated using an independent cohort (n = 181). The area under the receiver operating characteristic curve (AUC) was utilized to evaluate the diagnostic accuracy.Results
We determined that a panel based on the expression of uc001ncr and AX800134 accurately diagnosed HBV-positive HCC (AUC values of 0.9494 and 0.9491 for the training and validation cohorts, respectively). The diagnostic performance of the panel remained high in patients with AFP≤400 ng/ml (AUC values of 0.9371 and 0.9527 for the training and validation cohorts, respectively). The panel also diagnosed early HCC (AUC values of 0.9450 and 0.9564 for the training and validation cohorts, respectively).Conclusion
Our results indicated that the serum expression of uc001ncr and AX800134 has potential as novel potential biomarker for the diagnosis of HCC, especially in patients with AFP≤400 ng/ml or early-stage disease (BCLC 0+A). 相似文献13.
Nidiane D. R. Prado Soraya S. Pereira Michele P. da Silva Michelle S. S. Morais Anderson M. Kayano Leandro S. Moreira-Dill Marcos B. Luiz Fernando B. Zanchi André L. Fuly Maribel E. F. Huacca Cleberson F. Fernandes Leonardo A. Calderon Juliana P. Zuliani Luiz H. Pereira da Silva Andreimar M. Soares Rodrigo G. Stabeli Carla F. C. Fernandes 《PloS one》2016,11(3)
Antivenoms, produced using animal hyperimmune plasma, remains the standard therapy for snakebites. Although effective against systemic damages, conventional antivenoms have limited efficacy against local tissue damage. Additionally, the hypersensitivity reactions, often elicited by antivenoms, the high costs for animal maintenance, the difficulty of producing homogeneous lots, and the instability of biological products instigate the search for innovative products for antivenom therapy. In this study, camelid antibody fragments (VHH) with specificity to Bothropstoxin I and II (BthTX-I and BthTX-II), two myotoxic phospholipases from Bothrops jararacussu venom, were selected from an immune VHH phage display library. After biopanning, 28 and 6 clones recognized BthTX-I and BthTX-II by ELISA, respectively. Complementarity determining regions (CDRs) and immunoglobulin frameworks (FRs) of 13 VHH-deduced amino acid sequences were identified, as well as the camelid hallmark amino acid substitutions in FR2. Three VHH clones (KF498607, KF498608, and KC329718) were capable of recognizing BthTX-I by Western blot and showed affinity constants in the nanomolar range against both toxins. VHHs inhibited the BthTX-II phospholipase A2 activity, and when tested for cross-reactivity, presented specificity to the Bothrops genus in ELISA. Furthermore, two clones (KC329718 and KF498607) neutralized the myotoxic effects induced by B. jararacussu venom, BthTX-I, BthTX-II, and by a myotoxin from Bothrops brazili venom (MTX-I) in mice. Molecular docking revealed that VHH CDRs are expected to bind the C-terminal of both toxins, essential for myotoxic activity, and to epitopes in the BthTX-II enzymatic cleft. Identified VHHs could be a biotechnological tool to improve the treatment for snake envenomation, an important and neglected world public health problem. 相似文献
14.
15.
Yalamanchili N Syed R Chandra M Satti V Rao R Mohammed AH Nanne KM 《Indian journal of human genetics》2011,17(1):17-21
INTRODUCTION:
Designing a rapid, reliable and sensitive assay for detection of hepatitis B virus (HBV) variants by real-time PCR is challenging at best. A recent approach for quantifying the viral load using a sensitive fluorescent principle was brushed in this study.MATERIALS AND METHODS
: A total of 250 samples were collected from the outpatient unit, CLRD. Complete Human HBVDNA sequences (n = 944) were selected from the National Centre for Biotechnology Information (NCBI), primers and probes were designed and synthesized from the core, surface, and x region. Real-time based quantification was carried out using a standard kit and in-house generated standards and RT-PCR protocols.RESULTS AND DISCUSSION:
The standard calibration curve was generated by using serial dilution 102 to 108. The calibration curve was linear in a range from 102 to 108 copies/ml, with an R2 value of 0.999. Reproducibility as measured by dual testing of triplicates of serum samples was acceptable, with coefficients of variation at 6.5%, 7.5%, and 10.5%. Our results showed that amplification performance was good in the case of the x-region-based design (98%). Out of 100 negative samples screened by enzyme linked immunosorbent assay and the standard RT-PCR kit, one sample was detected as positive with the in-house developed RT-PCR assay, the positivity of the sample was confirmed by sequencing the amplified product, NCBI accession EU684022.CONCLUSION:
This assay is reproducible showing limited inter- and intra-assay variability. We demonstrate that the results of our assay correlated well with the standard kit for the HBV viral load monitor. 相似文献16.
Senbagam Duraisamy Fazal Husain Senthilkumar Balakrishnan Aswathy Sathyan Prabhu Subramani Prahalathan Chidambaram Selvaraj Arokiyaraj Wahidah H. Al-Qahtani Jothiramalingam Rajabathar Anbarasu Kumarasamy 《Current issues in molecular biology》2022,44(2):731
Breast milk is the combination of bioactive compounds and microflora that promote newborn’s proper growth, gut flora, and immunity. Thus, it is always considered the perfect food for newborns. Amongst their bioactives, probiotic communities—especially lactic acid bacteria (LAB)—are characterized from breast milk over the first month of parturition. In this study, seven LAB were characterized phenotypically and genotypically as Levilactobacillus brevis BDUMBT08 (MT673657), L. gastricus BDUMBT09 (MT774596), L. paracasei BDUMBT10 (MT775430), L. brevis BDUMBT11 (MW785062), L. casei BDUMBT12 (MW785063), L. casei BDUMBT13 (MW785178), and Brevibacillus brevis M2403 (MK371781) from human breast milk. Their tolerance to lysozyme, acid, bile, gastric juice, pancreatic juice, and NaCl and potential for mucoadhesion, auto-aggregation, and co-aggregation with pathogens are of great prominence in forecasting their gut colonizing ability. They proved their safety aspects as they were negative for virulence determinants such as hemolysis and biofilm production. Antibiogram of LAB showed their sensitivity to more than 90% of the antibiotics tested. Amongst seven LAB, three isolates (L. brevis BDUMBT08 and BDUMBT11, and L. gatricus BDUMBT09) proved their bacteriocin producing propensity. Although the seven LAB isolates differed in their behavior, their substantial probiotic properties with safety could be taken as promising probiotics for further studies to prove their in vivo effects, such as health benefits, in humans. 相似文献
17.
Beate Fuchs Markus Rupp Hossein A Ghofrani Ralph T Schermuly Werner Seeger Friedrich Grimminger Thomas Gudermann Alexander Dietrich Norbert Weissmann 《Respiratory research》2011,12(1):20
Background
Hypoxic pulmonary vasoconstriction (HPV) is an essential mechanism of the lung that matches blood perfusion to alveolar ventilation to optimize gas exchange. Recently we have demonstrated that acute but not sustained HPV is critically dependent on the classical transient receptor potential 6 (TRPC6) channel. However, the mechanism of TRPC6 activation during acute HPV remains elusive. We hypothesize that a diacylglycerol (DAG)-dependent activation of TRPC6 regulates acute HPV.Methods
We investigated the effect of the DAG analog 1-oleoyl-2-acetyl-sn-glycerol (OAG) on normoxic vascular tone in isolated perfused and ventilated mouse lungs from TRPC6-deficient and wild-type mice. Moreover, the effects of OAG, the DAG kinase inhibitor R59949 and the phospholipase C inhibitor U73122 on the strength of HPV were investigated compared to those on non-hypoxia-induced vasoconstriction elicited by the thromboxane mimeticum U46619.Results
OAG increased normoxic vascular tone in lungs from wild-type mice, but not in lungs from TRPC6-deficient mice. Under conditions of repetitive hypoxic ventilation, OAG as well as R59949 dose-dependently attenuated the strength of acute HPV whereas U46619-induced vasoconstrictions were not reduced. Like OAG, R59949 mimicked HPV, since it induced a dose-dependent vasoconstriction during normoxic ventilation. In contrast, U73122, a blocker of DAG synthesis, inhibited acute HPV whereas U73343, the inactive form of U73122, had no effect on HPV.Conclusion
These findings support the conclusion that the TRPC6-dependency of acute HPV is induced via DAG. 相似文献18.
Anusri Tripathi Sudip Kumar Dutta Monalisa Majumdar Lena Dhara Debolina Banerjee Krishnangshu Roy 《Indian journal of microbiology》2012,52(4):557-564
Pathogenic Klebsiella pneumoniae, resistant to beta-lactam and quinolone drugs, is widely recognized as important bacteria causing array of diseases. The resistance property is obtained by acquisition of plasmid encoded blaTEM, blaSHV, blaCTX-M, QNRA, QNRB and QNRS genes. The aim of this study was to document the prevalence and association of these resistant genes in K. pneumoniae infecting patients in India. Approximately 97 and 76.7 % of the 73 K. pneumoniae isolates showed resistance towards beta-lactam and quinolone drugs respectively. Bla genes were detected in 74 % of K. pneumoniae isolates; with prevalence in the following order: blaTEM > blaSHV > blaCTXM. QNR genes were detected in 67 % samples. Chi-square analysis revealed significant association between presence of bla and qnr genes in our study (P value = 0.000125). Sequence analysis of some blaTEM, blaSHV, blaCTX-M and QNRB PCR products revealed presence of blaTEM1 (GenBank accession: JN193522), blaTEM116 (JN193523 and JN193524), blaSHV11, blaCTXM72 variants (JF523199) and QNRB1 (JN193526 and JN193527) in our samples. 相似文献
19.
20.
Priyanka Banerjee Rajiv Kumar Mondal Madhuparna Nandi Sumantra Ghosh Mousumi Khatun Nabendu Chakraborty Swatilekha Bhattacharya Arindam RoyChoudhury Soma Banerjee Amal Santra Samir Sil Abhijit Chowdhury Pradip Bhaumik Simanti Datta 《PloS one》2014,9(10)