brasilense (Burdman et al., 2000a), were present and participated in cell-to-cell aggregation and flocculation. The addition of 0.5 M arabinose to flocculating cultures of both mutant strains caused a significant reduction in the total amount of flocculation (Fig. 3a), suggesting that arabinose contributes to the structure and/or the stability of the flocs formed by these strains. In addition, we found that flocs selleck of the AB102 (ΔcheY1) strain were significantly more sensitive to the competitive addition of exogenous arabinose (Fig. 3a) than the flocs

of AB101. Similarly, high concentrations of glucose (0.5 M) reduced flocculation in both mutant strains and flocs formed by the AB102 (ΔcheY1) strain appeared to be more sensitive to the addition of glucose, with almost complete inhibition of flocculation after the addition of 0.5 M glucose (Fig. Depsipeptide clinical trial 3b). To further investigate differences in the extracellular matrix,

we used FITC-conjugated lentil lectin (LcH) (affinity for α-mannose and α-glucose) and lima bean lectin (LBL) (affinity for N-acetyl galactosamine) to probe for specific carbohydrates present on or around the cell surface. Wild-type cells did not show any significant binding of either lectin after 24 h of growth as determined by fluorescence imaging and statistical analysis (Fig. 4; Table S1). Both OSBPL9 lectins were found to stain AB101 (ΔcheA1) cells and the surrounding material (Fig. 4b and h). In comparison with AB101, AB102 (ΔcheY1) cells displayed reduced staining by both lectins (Fig. 4c and i). When normalized to the fluorescence signal of Syto61 that stains all cells (Fig. 4d–f and j–l), the lectin fluorescence signal detected for AB102 (ΔcheY1) floc structures was significantly (P=0.05) reduced for both lectins with respect to AB101 (Table S1). The lipopolysaccharides profiles of the mutant and wild-type strains grown under flocculating and nonflocculating conditions

were compared. Under conditions of growth in rich medium (TY), all strains had similar lipopolysaccharides profiles (Fig. 5). Differences in lipopolysaccharides profiles were detected between the strains as early as 24 h of incubation in flocculation medium, which corresponds to the time at which both mutant strains, but not the wild-type strain, flocculate. Under these conditions and compared with the lipopolysaccharides profile of the wild-type strain, a low-molecular-weight band (arrow 2, Fig. 5) is absent from the profile of both mutant strains while another low-molecular-weight band (arrow 3, Fig. 5) is significantly reduced. A higher molecular weight band (Fig. 5, arrow 1) is also clearly visible for all strains, but more abundant in the lipopolysaccharides profile of both mutant strains at 24 h.

Motor imagery of catching the ball, as compared with baseline, led to an increase in BOLD activity in cortical sensorimotor areas of the left

hemisphere and the right posterior cerebellum (Table 1). The cortical areas involved were the left supplementary motor area (SMA; Fig. 3A), the left IFG (Fig. 3B), the left posterior insula, the left postcentral gyrus, and the left IPL (Fig. 3B). In addition, the left anterior superior prefrontal cortex, the ventral ACC and the right inferior temporal cortex were activated (Table 1). To explore the BOLD changes found in the motor imagery condition in comparison with the action and observation conditions, regional analyses were performed across the following regions of interest: left ACC, left IFG, left SMA, and left IPL. We found a significantly higher degree of activation in the left SMA during ABT-199 cell line motor imagery than during active catching [T = −3.44, degrees of freedom (df) = 16, P = 0.003, Cohen's d = 0.8] and observation of catching [T = 3.57, df = 15, P = 0.003 (Fig. 4); pairwise t-tests with Bonferroni correction α = 0.003

and additional effect size Cohen's d]. The same pattern was observed for the left IFG (motor imagery vs. catching, T = −2.51, df = 16, P = 0.023, Cohen’s d = 0.6; motor imagery vs. observation, T = 2.26, df = 15, P = 0.039; Fig. 4) and left IPL find more (motor imagery vs. catching, T = −1.93, df = 16, P = 0.071, Cohen’s d = 0.5; motor imagery vs. observation, T = 1.84, df = 15, P = 0.086; Phosphatidylinositol diacylglycerol-lyase Fig. 4), although the medium effect as indicated by Cohen’s d was not statistically significant. Note that, in the left IFG and left IPL, there was no change in BOLD activity in the catching trial. No differences in the degree of activation were found when active catching and the observation of catching were compared within all regions of interest defined. In the current

fMRI study, as a first step to explore the neural correlates of RGS, we investigated in healthy volunteers whether actual or imagined catching of moving balls modulated the activity in candidate areas of the human mirror neuron system in frontal and parietal cortical areas. In order to address this question, we adapted the RGS to the fMRI environment, and compared active, passive and imaginary task conditions within a VR world. Similarly to the clinically used RGS, the MRI-adapted version simulated natural activities while maintaining action control by pressing of buttons to steer the avatar. In agreement with the working hypothesis behind the RGS, we observed the activation of a number of brain areas in the imagination condition, including the left SMA, the left IFG, the left posterior insula, the left postcentral gyrus, the left IPL, and the right cerebellum. These areas constitute a widespread circuit of sensorimotor areas including key cortical areas of the human mirror neuron system (Gallese et al., 1996; Iacoboni & Mazziotta, 2007; Sale & Franceschini, 2012).

The protein bands A and B were excised manually and in-gel digested, and then analyzed by LC-MS/MS. MS was analyzed with sequest

software. The lowest Xcorr values of the peptide were set to be 1.9 (+1 charge), 2.2 (+2 charge) and 3.75 (+3 charge), respectively, and ΔCn must be larger than 0.08 (Wang & Yuan, 2005). The matched peptides revealed that the protein A was InhA (Fig. 4b) protein B camelysin (Fig. 4c). To further support the results, shotgun analysis of the sporulated crystal cultures confirmed that the protein of InhA was not 5-Fluoracil order expressed in the camelysin-deficient strain. Grass et al. (2004) reported that the molecular mass of metalloproteinase camelysin was 21.569 kDa with a putative signal peptide of 27 amino acids from B. cereus. In the present study, the calY gene encoded a protein with a deduced size of 199 amino acids. signalp 3.0 server (http://www.cbs.dtu.dk/services/SignalP/) analysis showed that the deduced sequence contained a signal peptide. The prediction result revealed that the cleavage sites might be 31/32 (AFF-SD) and 29/30 (TFA-FF). clustalx analysis showed that there was a 99% homology of the camelysin protein between B. cereus and B. thuringiensis as well as homology of their calY gene sequence; the Alectinib homology between

Bacillus anthracis and B. thuringiensis was 95%. The high degree of homology of camelysin suggested that the genesis of B. thuringiensis camelysin had a close relationship with B. cereus

and B. anthracis, and that it was more closely related to B. cereus. This work demonstrated that the global expression Quinapyramine patterns of proteins differed between the wild-type and camelysin-deficient strain as determined by SDS-PAGE (Fig. 4a) associated with MS (Fig. 4b and c). Results of SDS-PAGE and LC-MS/MS suggested that there were many differences after knocking out the calY gene. It was obvious that the InhA was not expressed in the camelysin-deficient strain (Fig. 4a), and that the InhA reappeared in the complementation strain KCTFC (Fig. 4a). Previous studies reported that the inhA promoters of B. thuringiensis were a –35 (TTGAAA) and a –10 (TAAAAT) hexamer, which are highly similar to the σA promoter consensus (TTGACA 17-18N TATAAT) (Grandvalet et al., 2001). Our sequencing results showed that the transcriptional start site and ORF of the inhA gene remained intact after displacing the calY gene. Thus, it is suggested that there is a relationship between camelysin and InhA. InhA was synthesized during the stationary phase (Dalhammar & Steiner, 1984). It was suggested that the inhA transcription might depend on the complex regulatory mechanisms that control later growth development in Bacillus species (Grandvalet et al., 2001). It was previously reported that AbrB and SinR acted as repressors to prevent expression of InhA.

, 1987; Cardinale & Clark, 2005 and references cited therein). A possible exception to this statement is the

report that Salmonella within macrophages might be exposed to up to 10 μM NO (Raines et al., 2006). However, nitrite was a more effective inducer of Phcp expression than growth-inhibitory concentrations of 10 or 20 μM NO added repeatedly at 30 min intervals. The smaller and slower response to NO was not due to the rapid decomposition of NO by oxygen because separate experiments with an NO-sensitive electrode confirmed that NO was stable under the anaerobic conditions used. Note that the high pKa value of nitrous acid means that at physiological pH, nitrous acid diffuses across the cytoplasmic membrane, and nitrite can be transported by at least three mechanisms, NarK,

NarU and NirC (see, e.g. Jia et al., 2009). Three of the Z VAD FMK obvious possible explanations for the minimal response of the hcp promoter to external NO are that derepression of NsrR was counter-balanced check details by loss of transcription activation by FNR; that derepression of the NsrR regulon resulted in sufficient capacity to repair nitrosative damage to FNR as rapidly as it occurred or that the capacity of the bacteria to reduce NO was sufficient to prevent its cytoplasmic accumulation. Control experiments with the Nsr-independent promoter, FF-37.5::lacZ, eliminated the first possibility and hence, by inference also, the second explanation (Table 2). The results of these experiments also challenged claims that FNR can function as a physiologically relevant sensor of NO (Cruz-Ramos et al., 2002; Corker & Roole, 2003; Pullan et al., 2007). Although the periplasmic

nitrite reductase, NrfAB, was the obvious candidate to provide protection against externally added NO by catalysing its reduction to ammonia in the periplasm (as proposed by van Wonderen et al., 2008), externally added NO still did not induce Phcp::lacZ transcription in a nrfAB deletion mutant as effectively as nitrite. The 10-fold higher rates of NO reduction than nitrite reduction by strains defective in both NirB and NrfA suggest that E. coli has a greater capacity to reduce NO than to produce it from nitrite. We recently reported that even in the absence of all currently characterized Tolmetin NO reductase activities, anaerobic cultures of E. coli still reduce NO rapidly (Vine & Cole, 2011). The data in the current study therefore reinforce our previous conclusion that a significant NO reduction activity remains to be characterized. We favour the explanation that this activity prevents significant damage to cytoplasmic proteins by concentrations of externally generated NO relevant to pathogenicity. We thank Merve Yasa for help with some of the control experiments. “
“Institute of Microbiology, AS ČR, Praha 4-Krč, Czech Republic SpoIISAB is a toxin–antitoxin module encoded on the chromosomes of Bacillus subtilis and related Bacilli species.

, 1987; Cardinale & Clark, 2005 and references cited therein). A possible exception to this statement is the

report that Salmonella within macrophages might be exposed to up to 10 μM NO (Raines et al., 2006). However, nitrite was a more effective inducer of Phcp expression than growth-inhibitory concentrations of 10 or 20 μM NO added repeatedly at 30 min intervals. The smaller and slower response to NO was not due to the rapid decomposition of NO by oxygen because separate experiments with an NO-sensitive electrode confirmed that NO was stable under the anaerobic conditions used. Note that the high pKa value of nitrous acid means that at physiological pH, nitrous acid diffuses across the cytoplasmic membrane, and nitrite can be transported by at least three mechanisms, NarK,

NarU and NirC (see, e.g. Jia et al., 2009). Three of the selleckchem obvious possible explanations for the minimal response of the hcp promoter to external NO are that derepression of NsrR was counter-balanced CX-5461 chemical structure by loss of transcription activation by FNR; that derepression of the NsrR regulon resulted in sufficient capacity to repair nitrosative damage to FNR as rapidly as it occurred or that the capacity of the bacteria to reduce NO was sufficient to prevent its cytoplasmic accumulation. Control experiments with the Nsr-independent promoter, FF-37.5::lacZ, eliminated the first possibility and hence, by inference also, the second explanation (Table 2). The results of these experiments also challenged claims that FNR can function as a physiologically relevant sensor of NO (Cruz-Ramos et al., 2002; Corker & Roole, 2003; Pullan et al., 2007). Although the periplasmic

nitrite reductase, NrfAB, was the obvious candidate to provide protection against externally added NO by catalysing its reduction to ammonia in the periplasm (as proposed by van Wonderen et al., 2008), externally added NO still did not induce Phcp::lacZ transcription in a nrfAB deletion mutant as effectively as nitrite. The 10-fold higher rates of NO reduction than nitrite reduction by strains defective in both NirB and NrfA suggest that E. coli has a greater capacity to reduce NO than to produce it from nitrite. We recently reported that even in the absence of all currently characterized this website NO reductase activities, anaerobic cultures of E. coli still reduce NO rapidly (Vine & Cole, 2011). The data in the current study therefore reinforce our previous conclusion that a significant NO reduction activity remains to be characterized. We favour the explanation that this activity prevents significant damage to cytoplasmic proteins by concentrations of externally generated NO relevant to pathogenicity. We thank Merve Yasa for help with some of the control experiments. “
“Institute of Microbiology, AS ČR, Praha 4-Krč, Czech Republic SpoIISAB is a toxin–antitoxin module encoded on the chromosomes of Bacillus subtilis and related Bacilli species.

Here, eight aphasic persons with apraxia of speech underwent intensive language therapy in two different conditions: real bihemispheric anodic ipsilesional stimulation over the left Broca’s area and cathodic contralesional stimulation over the right homologue of Broca’s area, and a sham condition. In both conditions,

patients underwent concurrent language therapy for Pexidartinib concentration their apraxia of speech. The language treatment lasted 10 days (Monday to Friday, then weekend off, then Monday to Friday). There was a 14-day intersession interval between the real and the sham conditions. In all patients, language measures were collected before (T0), at the end of (T10) and 1 week after the end of (F/U) treatment. Results showed that after simultaneous excitatory stimulation to the left frontal hemisphere and inhibitory stimulation to the right frontal hemisphere regions, patients exhibited a significant recovery not only in terms of better accuracy and speed in articulating the treated stimuli but also in other language tasks (picture description, noun and verb naming, word repetition,

word reading) which persisted in the follow-up session. Taken together, these data suggest that bihemispheric anodic ipsilesional BMS-354825 cell line and cathodic contralesional stimulation in chronic aphasia patients may affect the treated function, resulting in a positive influence on different language tasks. Speech is probably one of the most complex and most intensively exercised motor skills of humans. In any language, the frequent use of always the same bundle of articulatory gestures participating in the construction of words transforms the recurring motor pattern into a stable, overlearned movement program represented onto the motor-cortical hard-disk that contains the human’s phonetic lexicon. From there it can be accessed rapidly and safely

whenever the words occur in an utterance (Levelt et al., 1999). Focal brain damage, such as a stroke in the left hemisphere, can cause a disorder in this alternation of movements, known as ‘apraxia of speech’. It is manifested as distortions of consonants and vowels that may be perceived as sound substitutions in the absence of reduced strength or tone (-)-p-Bromotetramisole Oxalate of muscles and articulators controlling phonation (McNeil et al., 2000; Duffy, 2005). Since Paul Broca in 1865, the hypothesis has been advanced that damage to the left inferior frontal gyrus (IFG; Broca’s area) might cause apraxia of speech disorders. Subsequent studies have suggested the involvement of the left anterior insula (Shuren, 1993; Dronkers, 1996; Donnan et al., 1997; Nestor et al., 2003), while others have confirmed that the most frequent area of damage in patients with apraxia of speech is Broca’s region (Hillis et al., 2004). Numerous treatments have been developed to remediate the apraxia speech disorder (Rosenbek et al., 1973; McNeil et al., 1997; Knock et al., 2000; Wambaugh, 2002).

Future studies should investigate the use of slower feedback update rates. Fourth, adjusting the relative contribution of attended and unattended pictures based on decoder output did not allow us to dissociate between the effect of neurofeedback and the effect of change in BOLD signal due to change in the perceptual input. Future neurofeedback designs should avoid changing object properties by using a more abstract neurofeedback such as adjusting the color of the background surrounding the hybrid picture depending on the results of the decoding. Finally, a decoder trained on separately presented pictures of faces and places might not be the optimal way of investigating

the effects of neurofeedback. This is because a decoder trained on faces and places will recruit only those regions that it finds useful for distinguishing between GSK2118436 price face and place pictures. Presenting decoder output as neurofeedback to the subjects may have little impact on their task performance because the regions that respond to neurofeedback may not be incorporated in the decoding model trained on just faces and places. Hence, even if the subject’s brain MDV3100 supplier is responding to neurofeedback, the decoder may be unable to detect it. Therefore, it is necessary that future studies using MVPA-generated neurofeedback could aim to incorporate the brain regions

responsible for processing feedback into the model. In case of whole-brain decoding, nine regions were consistently used by the classifier

to drive the predictions. Among these regions was the left fusiform gyrus, which is usually associated with reading and word processing (McCandliss et al., 2003; Hillis et al., 2005; Dehaene & Cohen, 2011). However, this area has also been suggested to be sensitive to the conjunction of object and background scene information (Goh et al., 2004). This view is strengthened by invasive studies in primates that also pointed to the Abiraterone presence of neurons in this area, which are responsive to the conjunction of object features (Baker et al., 2002; Brincat & Connor, 2004). The left fusiform gyrus may be showing more activity for place blocks than for face blocks because pictures of famous places in the stimulus set contained not only objects but also a wide variety of backgrounds. Pictures used in the face blocks rarely had objects in them. The right fusiform gyrus showed a preference for face blocks, whereas the left parahippocampal gyrus showed a preference for place blocks. These two regions have been implicated in many studies to be responsible for the processing of faces and places, respectively (Aguirre et al., 1996, 1998; Kanwisher et al., 1997; McCarthy et al., 1997; Epstein & Kanwisher, 1998). Furthermore, bilateral ligual gyri were also activated for place pictures. The lingual gyrus performs bottom-up perceptual analysis of a scene in order to recognize it.

Future studies should investigate the use of slower feedback update rates. Fourth, adjusting the relative contribution of attended and unattended pictures based on decoder output did not allow us to dissociate between the effect of neurofeedback and the effect of change in BOLD signal due to change in the perceptual input. Future neurofeedback designs should avoid changing object properties by using a more abstract neurofeedback such as adjusting the color of the background surrounding the hybrid picture depending on the results of the decoding. Finally, a decoder trained on separately presented pictures of faces and places might not be the optimal way of investigating

the effects of neurofeedback. This is because a decoder trained on faces and places will recruit only those regions that it finds useful for distinguishing between Trametinib mw face and place pictures. Presenting decoder output as neurofeedback to the subjects may have little impact on their task performance because the regions that respond to neurofeedback may not be incorporated in the decoding model trained on just faces and places. Hence, even if the subject’s brain CH5424802 purchase is responding to neurofeedback, the decoder may be unable to detect it. Therefore, it is necessary that future studies using MVPA-generated neurofeedback could aim to incorporate the brain regions

responsible for processing feedback into the model. In case of whole-brain decoding, nine regions were consistently used by the classifier

to drive the predictions. Among these regions was the left fusiform gyrus, which is usually associated with reading and word processing (McCandliss et al., 2003; Hillis et al., 2005; Dehaene & Cohen, 2011). However, this area has also been suggested to be sensitive to the conjunction of object and background scene information (Goh et al., 2004). This view is strengthened by invasive studies in primates that also pointed to the Flavopiridol (Alvocidib) presence of neurons in this area, which are responsive to the conjunction of object features (Baker et al., 2002; Brincat & Connor, 2004). The left fusiform gyrus may be showing more activity for place blocks than for face blocks because pictures of famous places in the stimulus set contained not only objects but also a wide variety of backgrounds. Pictures used in the face blocks rarely had objects in them. The right fusiform gyrus showed a preference for face blocks, whereas the left parahippocampal gyrus showed a preference for place blocks. These two regions have been implicated in many studies to be responsible for the processing of faces and places, respectively (Aguirre et al., 1996, 1998; Kanwisher et al., 1997; McCarthy et al., 1997; Epstein & Kanwisher, 1998). Furthermore, bilateral ligual gyri were also activated for place pictures. The lingual gyrus performs bottom-up perceptual analysis of a scene in order to recognize it.

baumannii infections (Boucher et al., 2009). Select antibiotic combinations reportedly show synergy, that is, significantly greater activity provided by two antibiotics combined than the sum of each antibiotic’s activity, against MDR A. baumannii infections (Rahal, 2006). Examples of such combinations include imipenem (IMP)–rifampin (RIF) (Tripodi et al., 2007; Song et al., 2009; Panchón-Ibáñez et al., 2010), carbapenem–colistin (COL) (Timurkaynak et al., 2006), COL–RIF (Hogg et al., 1998; Giamarellos-Bourboulis

et al., 2001; HIF-1 pathway Timurkaynak et al., 2006; Li et al., 2007; Tripodi et al., 2007), and COL–doxycycline (DOX) (Timurkaynak et al., 2006). Two small clinical studies showed very good and limited efficacy of COL–RIF and IMP–RIF combinations, respectively, for patients with A. baumannii infections (Motaouakkil et al., 2006; Saballs et al., 2006). The mechanism of synergy between antibiotic combinations against

MDR A. baumannii, however, is undetermined. For example, A. baumannii is intrinsically resistant to RIF, and we hypothesized that the reported synergistic effect of combinations containing RIF comes from RIF potentiating the other antibiotic by interfering with mRNA production. Acinetobacter baumannii strains infamously carry a multitude of antibiotic resistance determinants, either on their chromosome or on their plasmids (Perez et al., 2007), and it is conceivable that not all strains or even strains within the same clone respond to antibiotic combinations equally. During 2006 and 2007, Cedars-Sinai Medical see more Center in Los Angeles, CA, USA, experienced an outbreak of MDR A. baumannii. The outbreak was terminated by a ‘bundle approach’ of strict infection control measures (Murthy et al., 2008). To provide insight into approaches for treatment of MDR A. baumannii, we evaluated dual combinations of antibiotics for possible synergy against our outbreak strains of MDR A. baumannii using Etest. Abiraterone mouse Although the correlation between the Etest and time-kill methods for in vitro testing of antimicrobial combinations on A. baumannii

is reported as 72% (Bonapace et al., 2000), we chose Etest because it is less labor-intensive than time-kill assays and may facilitate rapid clinical decisions. Additionally, our study aimed to determine whether our clonal strains would respond to antibiotic combinations equally and to investigate the effects of β-lactamases (blas) and other antibiotic resistance determinants in select strains on their response to these antibiotic combinations. We screened for β-lactamase genes, including blaTEM, blaSHV, blaPER, blaADC, blaIMP, blaVIM, blaOXA-23,blaOXA-Ab (housekeeping gene belonging to the blaOXA-51/69 families), and blaOXA-58, and for the genes encoding aminoglycoside-modifying enzymes (AMEs) including aphA6, aadA1, aadB, aacC1, and aacC2 (Hujer et al., 2006).

Initial denaturation of DNA at 95 °C for 10 min

was followed by 40 cycles of amplification (95 °C for 15 s and 60 °C for 45 s), ending with a dissociation phase at 95 °C for 15 s, 60 °C for 60 s, 95 °C for 15 s, and 60 °C for 15 s. Primers were as follow: blaZ-F (ACGAAATCGGTGGAATCAAA) and blaZ-R (AGCAGCAGGCGTTGAAGTAT) for blaZ (product length, 115 bp); mecA1575 (AGGTTACGGACAAGGTGAAATACTG) and mecA1657 (TGTCTTTTAATAAGTGAGGTGCGTTAA) for mecA (product length, 106 bp); and 53D-F (CGACAAAAGGCATTCAACAA) buy AZD6738 and 53D-R (ACGTTCAAAAATCGCTTGCT) for the 4867-bp HindIII DNA fragment of bacteriophage φ53 cloned in the pUC18 vector (GenBank accession number, AF513856; product length, 139 bp) that is specific for all serogroup B phages (Doškař et al., 2000). The basis for calculating selleck inhibitor the unknown quantity of PCR product

is that the 10-fold difference in the amount of DNA in two samples will manifest in the difference in their quantification cycles with a value of 3.22 (Lee et al., 2006). By comparing quantities of the blaZ plasmid gene and mecA single-copy chromosome gene, the plasmid copy number (PCN) in the donor strain was determined, which is necessary to determine the number of transducing particles carrying the penicillinase plasmid in comparison with the standard consisting of genomic DNA. PCN was determined according to the equation PCN = [size of chromosomal DNA (bp) × amount of plasmid DNA (pg)]/[size of plasmid DNA (bp) × amount of genomic DNA (pg)] (Lee et al., 2006). To calculate the standard copy number (SCN), the following formula was used: SCN = (amount of DNA per reaction in ng)/(Mr/NA), where Mr = size of S. aureus USA300 genomic DNA × normalized weight of nucleotide base (650 Da),

and NA is the Avogadro constant. second The standard curves were repeatable, and amplification efficiency of PCR reactions ranged between 90% and 100%. Genotypic characteristics and plasmid content of clinical strains used as donors and/or recipients in transduction experiments are listed in Table 1. Ability to transduce plasmids from the USA300 strains was first confirmed using the φ80α phage. The prophageless, plasmidless, and restriction-deficient RN4220 strain was used as control recipient strain for the transductions. Transduction frequency in this system ranged from 3.9 × 10−6 CFU/PFU to 5.1 × 10−6 CFU/PFU for penicillinase plasmids and from 2.7 × 10−6 CFU/PFU to 3.4 × 10−6 CFU/PFU for tetracycline resistance plasmid pT181. Based upon successful transduction of penicillinase plasmids and the tetracycline resistance plasmid into RN4220, plasmids were transduced between the isolates from the USA300 clone by the φ80α phage and subsequently by the naturally occurring φJB prophage which in a number of our experiments demonstrated excellent transducing abilities (unpublished results).