, 2010) and largely determined

by indirect readout of a sequence-directed DNA bend selleck inhibitor occurring at an A-tract located between both subsites (O. Porrúa & F. Govantes, unpublished data). The role of ABS-3 as a repressor element and the involvement of a spontaneous DNA bend in recognition are new features of the ‘sliding dimer’ model that are likely to occur in other LTTR-activated promoters. In addition to sensing cyanuric acid, AtzR activates atzDEF transcription during nitrogen-limited growth in the absence of an inducer. Genetic evidence indicates that GlnK interacts directly with AtzR under nitrogen limitation and stimulates its activity. The nature of this interaction is currently unknown. The fact that it occurs only under nitrogen limitation indicates that the uridylylated form of GlnK is likely the physiologically

relevant form for this regulation. However, by constitutively producing a nonuridylylatable mutant of GlnK, it was shown that the nonuridylylated form partly retains the ability to stimulate Selleck Y27632 AtzR activity (García-González et al., 2009). Activation in response to nitrogen limitation is strictly dependent on AtzR interaction with the ABS-1 and ABS-2 subsites. However, the mechanism of activation appears to be different from the ‘sliding dimer’ model: rather than causing a stable rearrangement of the AtzR–DNA complex to the activation-proficient conformation, nitrogen limitation elicits transient shifts between the active and the inactive forms (Porrúa et al., 2010) (Fig. 4d). The difference between both mechanisms is evidenced in vivo by the phenotypes of the single subsite mutants: in the presence of cyanuric acid, atzDEF expression was not affected by inactivation of ABS-3 and only moderately diminished by mutations at ABS-1 and ABS-2, indicative

of a rigid architecture in which the protein is poised in the active conformation, interaction with ABS-3 is negated and a high affinity for ABS-1 and ABS-2 is not critical (Fig. 4c). In contrast, mutations at all three ABS subsites displayed strong phenotypes on activation in response Farnesyltransferase to nitrogen limitation alone, strongly suggesting that AtzR is not committed to a rigid architecture and likely wobbles between different conformations as a function of its relative affinity for each subsite (Porrúa et al., 2010) (Fig. 4d). This dual activation mechanism has not yet been described for any other protein in the LTTR family. Since its isolation in 1995 (Mandelbaum et al., 1995), Pseudomonas sp. strain ADP has become the best-characterized organism capable of mineralizing the widely used herbicide atrazine. The atrazine-degradative pathway of Pseudomonas sp. strain ADP has been the focus of intense biochemical and genetic characterization, including the landmark sequencing of the intriguing 108-kbp pADP-1 plasmid.

Adherent cells were stained with

0.25% safranin for 5 min. The wells were rinsed again with distilled water. After drying, 200 μL of a 0.9% NaCl solution was added to each well www.selleckchem.com/products/Metformin-hydrochloride(Glucophage).html and the A490 nm was determined using an enzyme-linked immunosorbent assay plate reader (BioTek ELx800, Vermont). The OD values were corrected by subtracting values from noninoculated negative controls. A strain was considered as biofilm positive if the average OD value obtained by safranin staining was higher than the average OD value of the negative control (S. epidermidis ATCC 12228; OD values >0.125). Strains with OD values between 0.126 and 0.9 were regarded as weak biofilm producers, whereas an OD≥1 indicated strong biofilm producers (Jain & Agarwal, 2009). Each assay was performed in quadruple in two separate experiments. Slime production was assessed on the basis of the color of staphylococcal colonies cultured on CRA according

to the criteria reported Selleckchem Regorafenib by Freeman et al. (1989). Briefly, S. epidermidis isolates were inoculated onto nutrient agar plates supplemented with sucrose (50 g L−1) and Congo red (0.8 g L−1), and then cultured for 20 h at 35 °C. Strains intensively producing slime formed black colonies with a metallic sheen, strains moderately producing slime formed dark-pink colonies and nonproducing slime strains formed light-pink colonies. DNA was isolated from 2 mL of overnight bacterial culture. Extraction was performed using the click here Genomic Mini Kit (A&A Biotechnology, Poland) according to a protocol for Gram-positive bacteria. After isolation, DNA was measured using

a BioPhotometer (Eppendorf, Germany) to determine the concentration and purity. All PCR reactions were performed on a Mastercycler ep gradient (Eppendorf). For the detection of icaA, the primers were as follows: 5′-AACAAGTTGAAGGCATCTCC and 5′-GATGCTTGTTTGATTCCCT (Tormo et al., 2005). The two primers for the detection of icaD were, respectively, 5′-CCGGAGTATTTTGGATGTATTG (forward primer) and 5′-TTGAAACGCGAGACTAAATGTA (reverse primer). According to Vandecasteele et al. (2003), for the detection of the aap gene, following primers were used: 5′-ATACAACTGGTGCAGATGGTTG (forward primer) and 5′-GTAGCCGTCCAAGTTTTACCAG (reverse primer). The cycling conditions were as follows: preheating for 4 min at 96 °C, followed by 35 cycles of denaturation at 96 °C for 30 s, annealing at 60 °C for 30 s, primer extension at 70 °C for 30 s and final extension at 70 °C for 4 min. DNA of the reference biofilm-negative S. epidermidis strain ATCC 12228 was used as a positive control for aap and as a negative control for the icaADBC operon. Amplified products were analyzed by agarose gel electrophoresis. Fisher’s exact test was used for statistical analyses of data using graphpad instat Software (La Jolla, CA). The differences with P lower than 0.05 were considered as statistically significant.

A random effects Poisson regression model was used to calculate incidence rates and accompanying incidence rate ratios (IRR). Incidence rate was defined as the number of symptom onsets divided by the sum of symptom-free days for all individuals during a specific time period. A random effects logistic regression model was used to calculate median number of symptomatic days and accompanying odds ratios Torin 1 (ORs). Median number of symptomatic days equals an individual’s probability to have a symptom per day. It was calculated to compare the disease burden between the travelers with diabetes and their controls. To express results in units per month, numbers per day were multiplied by 30. The random effects model

takes into account two levels of correlation: learn more (1) travelers with diabetes and their travel companions had more or less the same exposure, and thus are not independent; (2) for incidences, there may be repeated episodes of a symptom within an individual; for numbers of symptomatic days, presence of symptoms over the days within an individual are correlated. IDD and NIDD were analyzed separately. For estimation of the parameters, a Bayesian approach was used, starting with non-informative priors. Posterior distributions

were obtained by Markov Chain Monte Carlo methods, using the WinBUGS program.14,15 Three chains were generated, based on different sets of baseline values. Parameter estimates are the medians of the posterior distributions. The range from the 2.5% to the 97.5% quantile is used to

quantify the uncertainty in the parameter estimates. This range can be interpreted as a 95% confidence interval and will be referred to as such. If 1 is not included in the 95% confidence interval Adenosine triphosphate of a ratio, the ratio can be considered statistically significant (p < 0.05). During the study period, 210 persons with diabetes planning to travel with a non-immune-suppressed companion without diabetes were eligible for inclusion: 93 IDD and 117 NIDD. Of these 210 eligible pairs, 58 (28%) did not participate, citing lack of time (34%), lack of interest (57%), or reasons unspecified (9%). The remaining participants all provided a completed diary. The study sample comprised 70 IDD and their 70 controls, plus 82 NIDD and their 82 controls. Of these 152 pairs, 137 (90%) were included at the Public Health Service Amsterdam, and 15 (10%) at the University Medical Centre Leiden. Table 1 shows the characteristics per type of diabetes. Sixty-four IDD (91%) and 70 NIDD pairs (85%) matched for country of birth; only 8 IDD (11%) and 12 NIDD pairs (15%) matched for gender (data not shown). The IDD more often had cardiovascular disease and dyslipidemia than their controls (p < 0.05). There was no difference in the use of gastric acid inhibitors. The NIDD more often had non-ischemic cardiovascular disease and dyslipidemia than their controls (p < 0.05). Their use of gastric acid inhibitors seemed more frequent, but not significant.

, 2008). However, no international clone III isolates were identified in this study. Since bacterial motility is a known virulence factor in numerous bacterial species (Han et al., 2008; Alarcon et al., 2009; Proft & Baker, 2009), the motility potential of our 52 clinical isolates was examined. The motility phenotypes in this study were determined using the general classifications for both swarming and twitching (Semmler et al.,

1999; Kaiser, 2007). Our data revealed that all international clone I isolates showed significant twitching. A number of other twitching isolates, not part of this clonal lineage, had the ability to form well developed biofilms compared to the international clone I isolates (see below), Proteases inhibitor with the exception of A. baumannii strain D1279779. This relatively poor biofilm former (OD595 nm<1) also showed a small twitching zone (approximately 12 mm). Swarming motility was Selleck Venetoclax observed in three noninternational clone isolates, including A. baumannii ATCC 17978, a fully sequenced reference strain. Studies using MH and LB media showed that twitching and swarming phenotypes are largely medium dependent. Furthermore, twitching and swarming

were demonstrated to be distinct characteristics, as many twitchers did not swarm, and A. baumannii strain ATCC 17978 swarmed, but did not twitch. PilA showed a high degree of amino acid sequence conservation within twitching isolates, indicating that type IV pili may play a role in motility in this species. Examination of biofilm formation showed that there was a significant difference between international clone

I and II isolates, correlating with previously published data (de Breij et al., 2010). We also found a significant difference (P < 0.05) between international clone I and noninternational clone isolates, indicating that in general international clone I isolates are limited in their ability to form biofilms. We determined the adherence of selected A. baumannii isolates to eukaryotic cells of nasopharyngeal (Detroit 562) and alveolar (A549) origin. Not only were significant differences observed between strains, two selleck products isolates, D1279779 and ATCC 17978, showed significantly lower adherence to nasopharyngeal cells compared to lung epithelial cells. Comparison of the ability to form biofilms and eukaryotic cell adherence revealed no relationship between these two phenotypes in the strains tested. This suggests that the mechanism of adherence to either abiotic or biotic surfaces appears to be different and draws a parallel with the results from other studies (Lee et al., 2008; de Breij et al., 2010). Moreover, previous studies have shown that adherence to abiotic surfaces is in part mediated by the csu type I pili cluster in strain ATCC 19606 (Tomaras et al., 2003), however, in a subsequent study using the same csu knockout strain, no difference was observed in the ability to bind bronchial cells (de Breij et al., 2009).

Patients who are particularly susceptible include those who are neutropenic following chemotherapy, selleck kinase inhibitor transplant, surgical and ICU patients (Ben-Ami et al., 2009; Zilberberg & Shorr, 2009). Moreover, patients with genetic or functional abnormalities, particularly in the lungs such as those with cystic fibrosis (CF) or chronic obstructive pulmonary disease provide a natural environment that has a predilection for Aspergillus colonization and biofilm formation (Bakare et al., 2003; Ader et al.,

2009; Horre et al., 2010; Moss, 2010). Aspergillus produce small spores called conidia that have an average size of 2–3.5 μm. These are dispersed in the air and remain in the atmosphere for prolonged periods, and are inhaled into the respiratory tract in their hundreds

each day by humans and other mammals (Rivera et al., 2006). Aspergillus fumigatus can cause a spectrum of clinical disease, including allergic bronchopulmonary aspergillosis, an aspergilloma or invasive aspergillosis (IA) (Denning, 1998). Of these the aspergilloma, a localized infection consisting of a spherical mass of hyphae has clear biofilm characteristics. Aspergillomas can develop in immune competent hosts, but usually require a pre-existing cavity such as those resulting from prior tuberculosis. Some are asymptomatic; however, where symptoms exist, they commonly include a chronic cough and haemoptysis. Another form GPCR Compound Library of aspergillosis infection, aspergillary bronchitis, is characterized by bronchial casts containing mucus and mycelia, which are associated with pathological damage (Young et al., 1970). Compact masses are formed, which may be expectorated. Moreover, bronchoalveolar lavage (BAL) in some patients with aspergillosis reveals the presence of numerous hyphae in the form of a complex multicellular mycetoma

structure samples when examined histologically (Jayshree et al., 2006). In contrast, IA disease is more diffuse with multiple points of angioinvasion within the pulmonary tissue. Nevertheless, filamentous intertwined hyphae Glycogen branching enzyme are important to this process, as in other forms of aspergillosis (Mowat et al., 2007). Notably, antifungal treatment is often ineffectual, which may relate to the biofilm phenotype (Beauvais et al., 2007; Mowat et al., 2007, 2008b; Seidler et al., 2008; Fiori et al., 2011; Rajendran et al., 2011). Clearer evidence of Aspergillus biofilms is demonstrated in infections affecting other sites. Aspergilli can enter the host through alternative routes causing other serious biomaterial-related biofilm infections, including catheters, joint replacements, cardiac pace makers, heart valves and breast augmentation implants (Rosenblatt & Pollock, 1997; Langer et al., 2003; Escande et al., 2011; Jeloka et al., 2011). Aspergillus is also frequently associated with complex sinus infections, which in canines have been described as superficial mucosal fungal plaque (Grosjean & Weber, 2007; Day, 2009; Laury & Delgaudio, 2010; Sato et al., 2010).

In one series, all four tones were drawn from the same harmonic whereas in the other they alternated between an inharmonic and harmonic complex. The harmonic tone complex had a fundamental frequency of 100 Hz, whereas the inharmonic complex had the same fundamental frequency but with each component shifted by the same amount (Δf). A harmonic complex with a 100-Hz fundamental frequency was used as it consists of components

with frequencies around 1000 Hz, where frequency discrimination was measured in Experiment 1. Both complexes had the same harmonic envelope equal to a fundamental frequency of 100 Hz but with different TFS. In each trial, one interval, selected at random, contained the harmonic complex NVP-BEZ235 nmr and the other contained the inharmonic complex. Intervals were indicated by numbered Fostamatinib flashing boxes presented onscreen coincident with the presentation of the complexes. Subjects clicked with a computer mouse on the box corresponding to the interval containing the inharmonic tones. Following Moore & Sęk (2009), the duration of each complex was 200 ms and the two complexes were separated by a 300-ms interval. Feedback was given after each trial, with the selected observation period flashing either

green for correct or red for incorrect. At the start of each block, Δf was set at 50 Hz and was adapted according to response. Again following Moore & Sęk (2009), blocks were terminated following eight reversals, and the threshold for the block was taken as the arithmetic mean of Δf for the last six reversals. To prevent subjects discriminating on place coding, all components were passed through a fixed band-pass filter set centered at 900 Hz with a width of 110 Hz rolling on at 30 dB per octave. Threshold equalizing noise, presented 15 dB below stimulus presentation level (SPL) and extending from 50 to 11 050 Hz, was used to mask components of the complexes falling outside the band-pass filter.

Following Moore & Sęk (2009), SPL for the harmonic complex was set 20 dB SPL above each subject’s 70.7% absolute threshold measured using an adaptive 2I-2AFC staircase method for 900 Hz immediately prior to each session. The sampled point of the psychometric function of absolute threshold was changed from Experiment 2A for consistency with previously established measures of TFS. To give consistent performance, subjects AZD9291 price had one initial training session prior to testing where they practised the TFS task for ~45 min. There were two counterbalanced TFS testing sessions after training where either anodal or sham tDCS was applied, separated by a week to avoid any carry-over effects of stimulation. Subjects completed seven threshold procedures during the 20 min of either tDCS or sham stimulation. Each staircase lasted ~2 min, varying with the subject’s response times and number of trials needed for six reversals. The threshold for that session was taken as the arithmetic mean of the seven thresholds for the session, each of which lasted approximately 35 min.

The results indicated that amounts of IF1 are lower by ∼23% in the 30S fraction from E. coli cells coexpressing U791 ribosomes and IF1 than 3-MA manufacturer those expressing G791 ribosomes and IF1 (Fig.

2c). The composition of ribosomal proteins in both 30S fractions was similar (Fig. 2c), indicating that the U791 mutation does not affect assembly of ribosomal proteins to 16S rRNA. Considering that the proportion of mutant 30S subunits in the 30S peak from the sucrose gradient analysis is ∼40% (data not shown here), we conclude that the U791 mutation severely inhibits IF1 binding to the 30S ribosomal subunit. Overexpression of IF1 resulted in increased ribosomal subunit association, probably by stabilizing P-site-bound initiator tRNA, which is mediated by its cooperation with IF2 and its interaction with the initiation codon of the mRNA (Hartz et al., 1990; Wu & RajBhandary, 1997; Meinnel et al., 1999). Although no clear function has been assigned to initiation factor 1, considering that IF1 is known to aid IF2 and IF3 in translational initiation and increase the rate of both subunit association

and dissociation (Grunberg-Manago et al., 1975), and that IF1 footprinting mimics A-site-bound tRNA, a local Bcr-Abl inhibitor change in the A-site due to an increase in IF1 binding to the A-site may be transmitted to the P-site (790 loop), thus restoring the functional conformation of the P-site for initiator tRNA binding and consequent ribosomal subunit association. The crystal structures of ribosomes also support this hypothesis. The 790 loop interacts with the 900 region and the 900 region docks somewhere in the vicinity of residues at positions 1413–1418 and 1483–1487 (Cate et al., 1999; Clemons et al., 1999), which interact with find more IF1 (Carter et al., 2001). We thank Dr John W.B. Hershey for providing us with a monoclonal antibody to IF1. This research was supported by the Pioneer Research Center Program (20100002201) through the National Research Program of Korea and NRF grant (2010-0008539) funded by the Ministry of Education, Science

and Technology. “
“The limited information on the genetic differences among the 15 currently known serotypes of Actinobacillus pleuropneumoniae has significantly hampered the development of typing-based diagnostic methods and multivalent vaccines. In this study, we compared the genomic differences between A. pleuropneumoniae strains CVCC259 (serotype 1) and CVCC261 (serotype 3) by representational difference analysis. Of the eight differential DNA sequences in the CVCC259 strain and 11 differential DNA sequences in the CVCC261 strain that we identified, seven represent known virulent genes, 10 encode putative proteins, and two encode hypothetical proteins. We also investigated the distribution of these 19 sequences among the 15 serotypes, and each serotype showed a different distribution pattern. The autotransporter adhesin occurred as a novel putative virulence factor in serotypes 1, 5, 7, 8, 9, and 11.

“
“Reverse complementary DNA sequences – sequences that are inadvertently given backwards with all purines and pyrimidines transposed – can affect sequence analysis detrimentally unless taken into account. We present an open-source, high-throughput software tool –v-revcomp (http://www.cmde.science.ubc.ca/mohn/software.html) – to detect and reorient reverse complementary entries of the small-subunit rRNA (16S) gene from sequencing datasets, particularly from environmental sources. The software supports sequence lengths ranging from full length down to the short reads that are characteristic of next-generation sequencing technologies. We evaluated the reliability of Napabucasin clinical trial v-revcomp by screening all 406 781 16S sequences deposited

in release 102 of the curated SILVA database and demonstrated that the tool has a detection accuracy of virtually 100%. We subsequently used v-revcomp to analyse 1 171 646 16S sequences deposited in the International Cetuximab in vivo Nucleotide Sequence Databases and found that about 1% of these user-submitted sequences were reverse complementary. In addition, a nontrivial proportion of the entries were otherwise anomalous, including reverse complementary chimeras, sequences associated with wrong taxa, nonribosomal genes, sequences of poor quality or otherwise erroneous sequences without a reasonable match to any other entry in the database. Thus, v-revcomp is highly efficient in detecting and reorienting reverse

complementary 16S sequences of almost any length and can be used to detect various sequence anomalies. The bacterial and archaeal small-subunit rRNA (SSU rRNA, 16S) gene has emerged as the gold standard genetic marker for determining

the diversity and structure of prokaryotic communities in the environment and for the assessment of phylogenetic relationships within the microbial tree of life (reviewed in Tringe & Hugenholtz, 2008; Pace, 2009). Numerous international efforts to characterize microbial communities have led to an unparalleled accumulation of 16S sequences in the International Nucleotide Sequence Databases (INSDs, Sayers et al., 2010) and warranted the establishment of curated 16S reference databases such as SILVA Parvulin (Pruesse et al., 2007), RDP (Cole et al., 2007) and Greengenes (DeSantis et al., 2006). As per October 2010 release of SILVA version 104, close to 3 million 16S sequences are currently deposited in the INSDs, not counting the enormous number of short reads currently generated by massively parallel sequencing technologies (Margulies et al., 2005) and typically deposited as raw data in the Sequence Read Archive (Leinonen et al., 2011). The contribution of these data repositories to scientific progress is indisputable. However, as the number of public 16S sequences increases, so does the number of sequences exhibiting poor read quality, chimaerism and incomplete or incorrect taxonomic annotation (Bridge et al., 2003; Hugenholtz & Huber, 2003; Ashelford et al., 2005; Bidartondo et al.

Once the records had been reviewed, all unique identifiers associated with outbreaks and case reports were removed, including names, dates see more of birth, gender, countries of origin, job titles and duties on the vessel, vessel names, and cruise line names. Analysis was limited to varicella reports among crew members on cruise ships. Reports from cargo ships were not included since they do not carry trained medical personnel and follow different CDC recommendations

than those given to cruise ships. Passenger varicella cases and contacts were not included, since secondary cases associated with the index case would not be readily identified and only contact management information up to the time of disembarkation would be available. Categorical variables were described using frequencies and percentages, and continuous variables were described using ranges, means, and medians. This investigation was approved as non-research by the CDC Institutional Review Board. During 2005 to 2009, varicella reports comprised 357 (15%) of the total 2,305 maritime illness reports submitted to CDC during that period. Of the varicella reports, 278 (78%) were among cruise ship crew members. They were find protocol predominantly male (80%), their median age was 29 years (range 20–66), and three-quarters

new of the ill crew members were residents of Caribbean countries, Indonesia, the Philippines, or India. Excluding 2005, a partial reporting year, varicella was reported more commonly in the spring (28%) and winter (27%) months. During 2009, 94 cases of varicella among cruise ship crew members were reported to CDC Quarantine Stations. By manual review of each case report, 22 varicella clusters were identified. Four of the clusters were excluded because the cases were not considered epidemiologically linked. Therefore, after exclusion, 66/94 (70%) cases among crew members were associated with 18 outbreaks. The remaining 28 cases were considered isolated case reports.

Outbreak response by cruise ships reporting the 18 varicella outbreaks during 2009 included isolation of 66 (100%) of 66 cases, restriction of 66 (26%) of 255 close crew-contacts, and administration of post-exposure vaccine to 522 close contacts and other susceptible crew members (Table 2). No contacts received VZIG. The number of cases per outbreak ranged from 2 to 9. There were a total of 45 first-generation cases (range 1–6 per outbreak), 16 second-generation cases (range 0–4), and five additional-generation cases (range 0–2) (Figure 1). There was a slight but nonsignificant positive correlation between time to reporting and number of second- and additional-generation cases.

Gels were stained using Coomassie® G-250 Stain (SimplyBlue™ SafeStain, Invitrogen) for detection of proteins. For detection of heme-containing proteins, 3,3′,5,5′-tetramethylbenzidine was used for staining, as described previously

(Thomas et al., 1976). The appropriate fractions from gel filtration were pooled and concentrated by Amicon Ultra-15 Centrifugal Filter Units (Millipore) to ∼400 μL. The concentration of cytochrome c and content of heme was determined by pyridine hemochrome analysis (Berry & Trumpower, 1987). UV-VIS spectra were recorded on Shimadzu UV1601PC spectrophotometer. selleck products The molecular weight was determined by direct electrospray MS with an LTQ-Orbitrap Velos instrument. The purified protein was desalted, dried and dissolved in 0.1% formic acid in 50 : 50 water : acetonitrile. The MS analysis was performed by Proteomics Core Facility at University of Gothenburg, Sweden. Chlorate reductase was purified as described earlier (Thorell et al., 2003) with the modification that

cells were disrupted using a Bead beater (Biospec products) and that the polyethylene imine precipitation step was omitted. Protein concentration of chlorate reductase was determined by Pierce ®BCA Protein Assay Kit (Thermo Scientific). For kinetic studies, the purified cytochrome c-Id1 was reduced using a slight excess sodium dithionite. A stock solution containing nominally 6 mg dithionite mL−1, 17 mM NaOH and 4 μg mL−1 catalase was prepared using nitrogen-flushed water, and was standardized against horse heart cytochrome c. The reduction of cytochrome c-Id1 Selleck PLX 4720 was monitored spectrophotometrically (Shimadzu UV1601PC; ultra-micro cuvette, Hellma, Sigma-Aldrich Sweden AB, Stockholm). The reaction medium was bis-tris-propane (25 mM, pH 7.2) and the final concentration of cytochrome was varied between 4 and 0.6 μM. Samples were mixed with catalytic amount of chlorate reductase (final concentration MYO10 about 0.14 μM) and dithionite (final concentration 28 μM).

Reactions were initiated by addition of chlorate (final concentration 85 mM) and followed by repeated recordings of spectra at 580–530 nm at 1-min intervals. Purification of the cytochrome c from periplasm using hydrophobic interaction chromatography followed by gel filtration, as described above, resulted in the preparation analyzed in Fig. 1. Fractions from gel filtration were analyzed by SDS-PAGE and stained for protein (Fig. 1a) or heme (Fig. 1b). The fractions denoted by arrows were judged sufficiently pure for further characterization. According to the gel electrophoresis, an apparent molecular weight of 6 kDa was estimated. However, MS analysis results in a value of 9434.7 Da. Analysis of tryptic peptides from in-gel digestion confirms that the purified cytochrome is the target protein described and denoted as the 6-kDa cytochrome c in the previous paper (Bäcklund et al., 2009).