The detection of discrete spindles

and the event correlation histograms calculated across all spindle events (peaks and troughs) of all detected spindles clearly showed that those spindles detected during the stimulation were grouped by the up-phases of the oscillating stimulation signal. This observation not only corroborates the acute effectiveness of tSOS, but also strongly supports the conclusion that tSOS-induced SWA does indeed mimic physiologically normal conditions, because, also under natural conditions, endogenous slow oscillations drive spindle generation such that spindles occur preferentially during the slow oscillation up-phase (Mölle et al., 2002, 2011; Steriade, 2003; Steriade & Timofeev, 2003). On the other hand, this finding tempts us to speculate that phase-coupling of spindle activity might secondarily contribute Ponatinib to the enhancing effects of tSOS-induced slow oscillations on encoding. However spindle activity as such is unlikely to be an effective mediator

of the enhanced encoding capabilities after tSOS, as spindle activity as such did not differ between the stimulation and sham conditions, and was also not positively correlated in any way with measures Stem Cell Compound Library of encoding. The fact that induction of slow oscillations by tSOS prevents any direct measurement of endogenous slow oscillations is an obvious limitation of our approach. However, it is of importance in this context that, for tSOS, we chose the maximum current amplitude, such that it induced, in the underlying C1GALT1 neocortex, potential fields of a similar

amplitude as those naturally observed during SWA, thus closely mimicking endogenous slow oscillations (Steriade et al., 1996). Together, these observations justify the conclusion that the potential fields associated with the occurrence of slow oscillations and SWA do indeed play a causal role in the beneficial effect that these brain oscillations during sleep have on the encoding of information during succeeding wakefulness. The main finding of our study is that tSOS-induced slow oscillation activity during a nap consistently improved subsequent learning on different declarative tasks, whereas training of a procedural skill (finger sequence tapping) was completely unaffected. As training of finger sequence tapping skills is less dependent on hippocampal function than is learning of the declarative tasks, this pattern of findings suggests that SWA particularly benefits encoding in the hippocampus-dependent declarative memory system (Squire et al., 1993; Squire & Zola, 1996; Gais & Born, 2004; Debas et al., 2010). In fact, our pattern of findings is well in line with recent findings by Van Der Werf et al.

Second, strong support for this model was provided by a recent study by Pernia-Andrade et al. (2009) showing that CB1 receptors decrease GABA release from inhibitory interneurons in the dorsal horn, measured as inhibitory postsynaptic currents. The same study, using electron microscopic immunohistochemistry, selleck products found CB1 receptors in axon terminals forming inhibitory synapses in the superficial dorsal horn. Third, the experiment shown

in Fig. 9 confirmed our prediction that the inhibition produced by AM251 was caused by an increase in GABA and opioid release. Thus, inhibition by AM251 was reversed by GABAB and μ-opioid receptor antagonists. Interestingly, the GABAB antagonist CGP55845 reversed the inhibition by AM251 when the dorsal root was stimulated Selleck Protease Inhibitor Library at 1 Hz but not at 100 Hz. This

is consistent with our previous studies (Marvizon et al., 1999; Lao & Marvizon, 2005) showing that root stimulation at 1 Hz, but not at 100 Hz, induces the activation of GABAB receptors. The fact that CB1 receptors facilitate substance P release reveals an unexpected pronociceptive role of cannabinoids in the spinal cord. Because of the prominent role that substance P and NK1Rs play in the induction of central sensitization (Traub, 1996; Mantyh et al., 1997; De Felipe et al., 1998; Laird et al., 2000), an increase in substance P release would lead to sustained hyperalgesia. Furthermore, inasmuch as substance P release is an indicator of nociceptor activity (Hua & Yaksh, 2009), its facilitation could signal an increase in acute Sucrase nociception. Indeed, we show that CB1 receptors in the spinal cord increase acute thermal nociception (Fig. 8). Our findings are consistent with the study by Pernia-Andrade et al. (2009) showing pronociceptive effects of spinal CB1 receptors during hyperalgesia induced by cutaneous capsaicin injection. They found that spinal application of AM251 decreased neuronal firing evoked by stimuli delivered next to the capsaicin injection site. They also showed

that capsaicin-induced mechanical hyperalgesia in mice was decreased by intrathecal AM251 and knockout of the CB1 receptor gene, both global and restricted to the spinal cord. Importantly, CB1 receptor deletion restricted to primary afferents did not decrease capsaicin-induced hyperalgesia, showing that the pronociceptive effect is caused by CB1 receptors in dorsal horn neurons. Our results show that this pronociceptive effect of CB1 receptors is not limited to hyperalgesia but can also be detected during acute nociception. In conclusion, CB1 receptors in dorsal horn interneurons produce pronociceptive effects by decreasing the release of GABA and opioids next to primary afferent terminals. The resulting decrease in the activity of the GABAB and μ-opioid receptors in these terminals facilitates substance P release by producing disinhibition.

As a special case, the failure to detect HMMs in either orientation is a very strong indicator that the entry does not represent a 16S sequence to begin with, at least not one of good quality. This study

was supported by a grant to the Centre for Microbial Diversity and Evolution from the Tula Foundation and a grant from Genome British Columbia. We also acknowledge support from the Frontiers in Biodiversity Research Centre of Excellence (University of Tartu, Estonia). M.H. and C.G.H. contributed equally to this work. Fig. S1. blast output ABC294640 price screens for GenBank accessions BAAX01013497 (a), AB518927 (b), and DQ022163 (c). Panel a) represents an example of a reverse complementary LGK974 chimera, which is indicated by the black vertical line in the graphical overview (left) and shown by the pairwise alignment with the top hit in GenBank (right). Panel b) shows a representative example of the query sequence (the top BLAST hit is the query itself) containing a sequence segment of around 500 bp that does not match any of the top hits in GenBank. Panel c) shows a sequence (the top BLAST hit is the query itself) that features a high degree of chimeric anomaly indicated by

the fragmented matching of all top BLAST hits. Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article. “
“The filamentous fungi Monascus spp., which have been used in traditional fermented food in Asia for centuries, are well-known producers of a group

of bioactive metabolites that are widely used as food additives and nutraceutical supplements worldwide. However, its potential to produce the mycotoxin citrinin poses a threat to food safety. Here, a G-protein α-subunit-encoding gene, Mga1 (Monascus G-protein alpha-subunit 1), which encodes a protein showing a high degree of identity to Group I α-subunits of fungal heterotrimeric G-proteins, was cloned from Monascus ruber M7. An Mga1-disrupted strain was obtained by homologous recombination. The disruptant produced approximately nine times more citrinin and 71% more pigments Astemizole than the wild-type strain M7, indicating that the G-protein α-subunit encoded by Mga1 is involved in a signal transduction pathway regulating citrinin and pigment biosynthesis in M. ruber M7. Monascus spp. are mainly used for the production of red fermented rice (RFR), which has been used extensively for more than 1000 years as a food colorant and food preservative for meat and fish, as a folk medicine to promote cardiovascular health, as well as fermentation starters to brew rice wine and vinegar in Asia (Chen & Hu, 2005; Lin et al., 2008).

Further, the superoxide radical can act as a reducing agent towards metal ions in the Fenton reaction, leading to the production of hydroxide radicals (OH˙−, GDC-0449 in vitro Imlay & Linn, 1988). The hydroxide radical is a strong oxidizing agent and can cause lipid peroxidation and damage to proteins and other cell components (Mehdy, 1994). In plant defences, ROS not only act as toxins, able to directly kill or slow the

growth of the pathogen, but also as part of a signalling cascade which may lead to multifarious defences including the hypersensitive response (Tenhanken et al., 1995; Torres et al., 2005), cell wall modifications (e.g. Bradley et al., 1992) and changes in gene expression (Alvarez et al., 1998). The importance of oxidative signalling in defence is illustrated by a recent study showing that induction of the oxidative signal-inducible1 (OXI1) serine/threonine protein kinase correlates both spatially and temporally with the oxidative burst in Arabidopsis and that OXI1 null mutants

and overexpressor lines are more susceptible to Pseudomonas syringae (Petersen et al., 2009). A large literature is dedicated to the study of the methods used by plant pathogens to avoid detection by the plant immune system and thus escape the oxidative burst. In the case of plant pathogenic bacteria, such as P. syringae, the type three secretion system (T3SS), encoded by hrp genes, is used for this purpose. The T3SS allows C59 wnt the bacteria to deliver effector proteins [type III secreted effector proteins (T3SE)], some of which delay or inhibit the plant’s defence responses, including the production of ROS (Grant et al., 2006). Some T3SE localize to the chloroplasts and mitochondria (Bretz & Hutcheson, 2004), locations at which ROS may be generated. Further evidence that the T3SS may be

used in manipulating plant ROS-based defences has been provided by Navarro et al. (2004), who found that five genes involved in ROS production in Arabidopsis may be targeted by T3SE secreted by P. syringae pv. tomato and P. syringae pv. maculicola, both of which are able to cause disease on Arabidopsis. However, it is important to note that the production of ROS also occurs in compatible Ribociclib supplier reactions between plant and pathogen, in which T3SE are successfully deployed and disease develops (Kim et al., 1999; Santos et al., 2001), albeit to a lesser extent than during an incompatible, nonhost reaction. Moreover, a recent study by Block et al. (2010) indicates that the effector HopG1a of P. syringae targets mitochondrial function, leading to increased ROS production, rather than suppression of ROS. An additional and relatively unexplored role for ROS tolerance in plant–pathogen interactions is suggested by studies of bacterial cell death mechanisms in response to bactericidal antibiotics. Kohanski et al.

In fact, TAT, and particularly limb fat and SAT, but also VAT and trunk fat, all tended to increase regardless of the regimen, but only significantly so in those randomized to ATV/r. In the CASTLE study, a comparable increase in adipose tissue was observed 96 weeks after starting ritonavir-boosted

ATV [35]. A similar pattern was observed for lean body mass as well as total body mass changes. Early changes in body composition, after cART is first initiated, may at least partially reflect a restoration to normal health. Virological and immunological efficacy was similar in the two arms and therefore do not offer a likely explanation for the difference in body composition changes selleck screening library observed. The higher frequency of low-grade diarrhoea in the SQV/r arm may have contributed to the lower gain in lean body mass and adipose tissue. Another possible explanation is that, for six of the SQV/r-treated patients, but only one ATV/r-treated patient, only baseline and no follow-up DXA and CT scans were obtained. Given that missing values following baseline were imputed using a LOCF approach, this imbalance in available follow-up scans could have contributed to the apparent differences in fat gain buy RGFP966 between the arms in the ITT analysis, which seems to be supported by the reduced difference observed in the OT analysis of adipose tissue changes. Detrimental effects of SQV on adipocyte differentiation and metabolism

have been reported [36,37]. Whereas ATV by itself has not been clearly demonstrated to affect adipocytes in vitro [38,39], another in vitro study showed that treatment with ritonavir-boosted ATV resulted in decreased adipocyte differentiation and insulin sensitivity, and

promoted oxidative stress and inflammation for [40]. TDF has been associated with nephrotoxicity, the risk of which may be increased by concomitant use of ritonavir-boosted PIs [24,41], potentially by increasing TDF exposure [25]. There is little information about whether this effect differs between PIs. The CASTLE study did not reveal a difference between ATV/r and lopinavir/r, combined with TDF, in the change in eGFR, with only a minor decrease in eGFR in both regimens [42]. The decline in eGFR observed in our study was also minor, developing during the first 12–24 weeks with no changes thereafter, as reported previously [24,41,42]. Only when estimated by CG was the decline in eGFR significantly greater for patients randomized to SQV/r. As the CG (but none of the other estimations) includes weight, the significantly greater increase in weight in ATV/r-treated patients could explain these findings, similar to the suggestions of others [43]. GFR estimated by weight-independent equations such as MDRD or CKD-EPI may offer a more reliable assessment of GFR after the initiation of first-line cART, a period which may be accompanied by significant weight change. Clinically relevant proximal tubulopathy was not observed with either treatment regimen.

In fact, TAT, and particularly limb fat and SAT, but also VAT and trunk fat, all tended to increase regardless of the regimen, but only significantly so in those randomized to ATV/r. In the CASTLE study, a comparable increase in adipose tissue was observed 96 weeks after starting ritonavir-boosted

ATV [35]. A similar pattern was observed for lean body mass as well as total body mass changes. Early changes in body composition, after cART is first initiated, may at least partially reflect a restoration to normal health. Virological and immunological efficacy was similar in the two arms and therefore do not offer a likely explanation for the difference in body composition changes MLN0128 observed. The higher frequency of low-grade diarrhoea in the SQV/r arm may have contributed to the lower gain in lean body mass and adipose tissue. Another possible explanation is that, for six of the SQV/r-treated patients, but only one ATV/r-treated patient, only baseline and no follow-up DXA and CT scans were obtained. Given that missing values following baseline were imputed using a LOCF approach, this imbalance in available follow-up scans could have contributed to the apparent differences in fat gain INCB024360 between the arms in the ITT analysis, which seems to be supported by the reduced difference observed in the OT analysis of adipose tissue changes. Detrimental effects of SQV on adipocyte differentiation and metabolism

have been reported [36,37]. Whereas ATV by itself has not been clearly demonstrated to affect adipocytes in vitro [38,39], another in vitro study showed that treatment with ritonavir-boosted ATV resulted in decreased adipocyte differentiation and insulin sensitivity, and

promoted oxidative stress and inflammation else [40]. TDF has been associated with nephrotoxicity, the risk of which may be increased by concomitant use of ritonavir-boosted PIs [24,41], potentially by increasing TDF exposure [25]. There is little information about whether this effect differs between PIs. The CASTLE study did not reveal a difference between ATV/r and lopinavir/r, combined with TDF, in the change in eGFR, with only a minor decrease in eGFR in both regimens [42]. The decline in eGFR observed in our study was also minor, developing during the first 12–24 weeks with no changes thereafter, as reported previously [24,41,42]. Only when estimated by CG was the decline in eGFR significantly greater for patients randomized to SQV/r. As the CG (but none of the other estimations) includes weight, the significantly greater increase in weight in ATV/r-treated patients could explain these findings, similar to the suggestions of others [43]. GFR estimated by weight-independent equations such as MDRD or CKD-EPI may offer a more reliable assessment of GFR after the initiation of first-line cART, a period which may be accompanied by significant weight change. Clinically relevant proximal tubulopathy was not observed with either treatment regimen.

Type IV pili also function in bacterial conjugation (Proft & Baker, 2009), an active mechanism within biofilm cells, being responsible for the transference

of genetic material including genes of resistance against antibiotics (Molin & Tolker-Nielsen, 2003). Interestingly, the treatment of X. fastidiosa with gomesin upregulated the expression of plasmid genes, including one gene encoding a conjugal transfer protein (traG or virB11). Besides involvement in adhesion to substrata and cell-to-cell aggregation, Protein Tyrosine Kinase inhibitor bacterial biofilms are also involved in bacterial resistance to many antimicrobial agents (Mah & O’Toole, 2001). In addition to the upregulation of CDS related to biofilms, the treatment of X. fastidiosa with a sublethal concentration of gomesin indeed leads to an enhancement in biofilm production. This does not seem to be a general effect to all antimicrobial agents, because exposure of X. fastidiosa to a sublethal concentration of streptomycin showed no effects on biofilm production. It has been reported that bacteria treated with sublethal concentrations of antimicrobial agents can increase or diminish biofilm production (Drenkard & Ausubel, 2002; Overhage et al., 2008; Jones et al., 2009). In Neisseria meningitidis, a sublethal concentration of

LL-37, a human cathelicidin, induces the formation of the a polysaccharide capsule (Jones et al., 2009). Conversely, this same AMP was reported to inhibit the biofilm production by Pseudomonas aeruginosa (Overhage et al., 2008). On the other hand, conventional selleck kinase inhibitor antibiotics were reported to stimulate biofilm production by this same bacterium (Drenkard & Ausubel, 2002). These

results clearly demonstrate that the response of bacteria to a sublethal concentration of antimicrobial agents depends not only on the bacterial strain but also on the nature of the drug. When X. fastidiosa pre-exposed to 50 μM of gomesin was inoculated into tobacco plants, mafosfamide fewer plants displayed foliar lesions relative to control plants (inoculated with nontreated bacteria) 30 days after inoculation (Fig. 3). This result suggests that due to the enhancement in biofilm production, bacteria may be trapped to fewer vessels of the plant xylem, causing a delay in the appearance of symptoms. Indeed, the above-described mutants of the X. fastidiosa Temecula strain defective for the production of the hemagglutinin HxfA, despite having a reduced ability to adhere to a glass surface and also to form cell-to-cell aggregates, were surprisingly hypervirulent to grapevine, due to an increased number of infected vessels of the plant xylem (Guilhabert & Kirkpatrick, 2005). On the other hand, limiting bacteria to a few vessels of the plant could have the opposite effect, diminishing disease symptoms. Together, our results demonstrate that gomesin modulates the global gene expression of X. fastidiosa at a sublethal concentration, inducing genes involved in biofilm production, among others. Indeed, X.

Methylation of miR-129-2 is also related to MSI and hypermethylated hMLH1. Therefore, oncogene activation may be caused by methylation of a miRNA that has an inhibitory action on oncogene expression, in addition to direct promoter demethylation. Tsuruta et al.[90] similarly showed that expression of miR-152 is reduced by aberrant DNA methylation selleck products and can be recovered by the demethylating action of 5-aza-dC. Screening of methylation and expression showed that miR-152 is also a TS-miRNA in endometrial cancer. miR-152 methylation levels are also changed in acute lymphoblastic leukemia, gastrointestinal cancer and cholangiocarcinoma.[91-93] DNA methyltransferase

1 (DNMT1) is a well-known target of miR-152; and E2F3, MET and Rictor have been identified as new

targets. miR-152 inhibits expression of all of these genes. E2F3 is an E2F family transcriptional inhibitor and may be an oncogene;[94] MET is a cell surface receptor for hepatocyte growth factor and a known oncogene;[95] and Rictor is part of the mTOR complex 2 (mTORC2) and is important for cancer cell proliferation.[96, 97] In this review, we summarized new findings on the carcinogenic mechanisms of endometrial cancer. Carcinogenesis cannot be completely explained by endometrial proliferation due to estrogen and a single gene mutation. However, the core carcinogenic mechanisms of type I endometrial cancer are DNA methylation (an epigenetic change) and subsequent breakdown of the MMR system (Fig. 3). These actions cause Rucaparib nmr Thiamet G oncogene mutation, inactivation of tumor suppressor genes, and oncogene activation via TS-miRNA silencing, and contribute to chaotic cell proliferation, that is, carcinogenesis. Methylation patterns of MMR genes may be inherited over generations and may cause familial tumorigenesis, including Lynch syndrome, while estrogen may control both cell proliferation and MMR activity. However, the carcinogenic mechanisms remain

largely unknown, particularly with regard to de novo carcinogenesis of type II endometrial cancer. Improved diagnosis, risk assessment, and new treatment strategies targeting MMR genes will require establishment of the details of these mechanisms in endometrial cancer. The authors gratefully acknowledge grant support from the Japan Society for the Promotion of Science (JSPS) through a Grant-in-Aid for Scientific Research (KAKENHI), a Grant-in-Aid for Scientific Research (C) (22591866), and a Grant-in-Aid for Young Scientists (B) (24791718); the Medical Research Encouragement Prize of The Japan Medical Association; and the Keio Gijyuku Academic Development Fund. None disclosed. “
“The frequency of wound dehiscence after abdominal surgery has been reported to be approximately 4–29%, and that of surgical site infections is said to be of about 20%. We examined the effectiveness of the subcutaneous J-VAC drain (JVD) in the drainage of bleeding and exudates from surgical wounds.

The method is based on electroporation

of bifidobacterial cells, which were made competent by an optimized methodology LY294002 based on varying media and growth conditions. Furthermore, the transformation protocol was applied in order to design a PRL2010-derivative, which carries antibiotic resistance against chloramphenicol and which was used to monitor PRL2010 colonization in a murine model. Bifidobacteria are Gram-positive G+C%-rich, anaerobic/microaerophilic, fermentative bacteria, which are often Y- or V-shaped (Ventura et al., 2007). Bifidobacterium represents one of the most numerically abundant bacterial genera of the human gut microbiota in infants and is presumed to play a fundamental role in host health, which

drives their wide-spread use as probiotic bacteria in many functional foods. This commercial exploitation of probiotic bifidobacterial strains has fuelled scientific interest in these bacteria to identify the genomic traits that are responsible for the claimed beneficial activities. To exploit the full potential of these microorganisms for applications as probiotic ingredients, further knowledge is required on their molecular biology and genetics. However, molecular studies of Bifidobacterium are severely hampered by the absence of effective genetic tools, including efficient transformation protocols. So far, several Bifidobacterium strains, including members of Bifidobacterium www.selleckchem.com/products/BKM-120.html bifidum and Bifidobacterium asteroides, have been shown to be nontransformable or very poorly transformable (Argnani et al., 1996). Many factors may contribute to bifidobacterial recalcitrance

for acquiring exogenous DNA, such as the presence of a thick (multilayered) Thalidomide and complex cell wall (Fischer et al., 1987), intracellular restriction/modification barriers (Hartke et al., 1996; Schell et al., 2002; O’Connell Motherway et al., 2009), and sensitivity to environmental stresses, in particular oxygen, to which these strictly anaerobic bacteria are exposed to during the preparation of competent cells and transformation procedure. With the advent of the genomics era, many bifidobacterial genomes have been fully decoded (for reviews, see Turroni et al., 2011; Ventura et al., 2009), which has thus provided a huge amount of genetic data that can be exploited to study genome functionality. Such studies are needed to understand the molecular mechanisms sustaining the interaction of bifidobacteria with its host as well as with other members of the gut microbiota (Hartke et al., 1996; Schell et al., 2002; Sela et al., 2008; Ventura et al., 2009; Turroni et al., 2011). However, to perform such functional genomic investigations, it will be necessary to develop transformation protocols as well as to implement gene knock-out methodologies effective for bifidobacteria. In this report, we describe the development of a protocol for efficient and reproducible genetic transformation of B.

Colonies with an insert size greater than 500 bp were selected and grown in 5 mL of LB broth. They were purified using a Plasmid Mini Kit (Qiagen) and submitted to sequencing by Macrogen Inc. (Korea). The DNA PI3K Inhibitor Library sequence data were analyzed with softberry server software (http://linux1.softberry.com/berry.phtml) using

the FgenesB and Bprom algorithms. FgenesB is a suite of bacterial operon and gene prediction programs and is based on Markov chain models of coding regions and translation and termination sites (Tyson et al., 2004). Bprom is an algorithm that recognizes possible promoters in bacterial DNA sequences. The clc main workbench 5 is a versatile software for analyzing DNA, RNA and proteins with a graphical user interface (http://clcbio.com/); the software was used to complement the sequence analysis, specifically for alignments and to locate the different elements [ORF, promoters, inverted repeat sequences (IRs)]. The ORFs predicted by FgenesB were used in blastp, with the search limited to bacterial sequences (http://blast.ncbi.nlm.nih.gov), to determine their possible identities. A comparison with the most similar ISs from the IS6 family found in the ISFinder database (http://www-is.biotoul.fr/) was performed.

In order to determine the prevalence of the IS sequence in natural isolates, oligonucleotide primers were designed to amplify the putative IS already predicted by the sequence analysis. All PCR primers were designed as shown in Table 3, using the Oligo EX 527 nmr Calc tool (http://www.basic.northwestern.edu/bio-tools/oligocalc.html). The PCR reaction for the three fish isolates was performed

using the following primer set: (1) IR1-F and Tnp-PsaR2 yielded a PCR product of 427 bp and (2) Tnp-PsaF and IR2-R yielded a PCR product of 704 bp. The PCR conditions used were: 94 °C for 5 min, 35 cycles of 94 °C for 30 s, 58 °C for 30 s and 72 °C for 45 s, and a final extension of 72 °C for 5 min. The PCR products were visualized on a 1% agarose gel stained with GelRed™. Piscirickettsia salmonis DNA was partially digested with Sau3AI endonuclease. Because this enzyme has a 4-bp recognition site, excision occurs, on average, every 250 bp, thus generating DNA fragments smaller than 2000 bp (Fig. 1). Fragmented DNA was cloned into the vector pBluescript click here KS (+) and electroporated into E. coli, resulting in 4750 recombinant clones. PCR analysis of the cloned P. salmonis inserts yielded 200 clones with inserts larger than 500 bp, which were subsequently sequenced (data not shown). Sequence analysis of the 992-bp insert resulted in a unique 726-bp ORF with a putative in-frame protein of 242 amino acids, an upstream putative promoter containing the expected −10 and −35 regions, and two identical 16-bp IRs flanking the 726-bp ORF (Fig. 1). According to Blastp analysis, the new ORF encodes a putative transposase (Tnp-Psa) with high similarity to Bacillus thuringiensis IS240 protein.