Relative to BA 44, BA 45 exhibited greater positive correlations with the pars orbitalis region of the inferior frontal gyrus where area 47/12 is located (see Petrides & Pandya, 1994), with the ventromedial prefrontal cortex and with the angular gyrus. Note that on the surface of the brain, this stronger RSFC appears to be restricted to the dorsal part of the angular gyrus, but this is

simply the result of the fact that much of the correlated activity lies just below the cortex selleck screening library and within the parietal extension of the superior temporal sulcus, which will not show on the surface of the brain, as can be seen in the appropriate coronal section in Fig. 2 (BA 45 > BA 44). BA 44 exhibited greater RSFC (relative to BA 45) with the premotor BA 6, the secondary somatosensory cortex within the upper bank of the Sylvian fissure and the caudal superior temporal gyrus (Fig. 1, Table 1). The above RSFC results were in excellent agreement with the predictions of connectivity from parietal and temporal cortex to the homologous ventrolateral regions in the macaque monkey based on the experimental anatomical study of these connections (Petrides & Pandya, 2009). However, there was also an apparent contradiction. In the study with the macaque monkey, the connections of area 45 with lateral

temporal cortex appeared to be more widespread than those of area 44 and to include a more ventral component of the selleck compound lateral temporal cortex. Comparison of the surface of the brain in Fig. 2 (compare panels BA 45 and BA 44) appears to confirm this greater activity in the lateral temporal cortex for BA 45 than for BA 44. However, this did not reach the accepted level of significance in the direct comparison BA 45 > BA 44. Given our prediction that differential RSFC would be observed, CHIR99021 we repeated the direct comparison between BA 44 and BA 45

RSFC, restricting our analysis to the left temporal lobe (Z > 2.3; cluster significance P < 0.05, corrected for a volume of 22 768 mm3). This restricted comparison did reveal significantly greater RSFC between BA 45 and the middle temporal gyrus, relative to BA 44 (Fig. 2). To examine the differences between BA 6 and BAs 44 and 45, direct contrasts were carried out between these ROIs. Relative to both BAs 44 and 45, BA 6 exhibited stronger RSFC with primary somatic and motor areas around the central sulcus, and the secondary somatosensory areas within the frontal and parietal opercula, and the insula. There were also stronger correlations between BA 6 and the superior parietal lobule and the anterior part of the supramarginal gyrus, relative to both BAs 44 and 45. There were stronger correlations between BA 6 and the supplementary motor region and the motor region in the central cingulate gyrus and sulcus, which probably correspond to the cingulate motor areas discovered in the macaque monkey (He et al., 1995) (Fig. 1, Table 1).

Contrary to our predictions, shock-associated tones did not evoke significant differential processing on an earlier AEF component between 20 and 50 ms after CS onset (P20–50 m). Results in two different behavioural tests measuring rather explicit learning effects suggested that subjects were not explicitly aware of the predictive CS–UCS relationship, owing to the large number

of complex tones and few learning instances. An indirect measure of acquired valence (affective priming), however, demonstrated an effect of emotional learning on behaviour. ALK inhibitor Human affective neuroscience research was rarely concerned with the auditory system in the past. Studies are mainly restricted

to physiological measures (e.g. skin conductance responses) and neuroimaging techniques such as functional MRI or positron emission tomography providing high spatial but rather low temporal resolution. These investigations showed affect-specific prioritised processing of emotionally salient auditory stimuli (Bradley & Lang, 2000) within a distributed network of emotion-related and sensory-specific cortical and subcortical brain regions, such as the amygdala, the medial geniculate nucleus of the thalamus and prefrontal and parietal cortex (Hugdahl et al., 1995; Morris et al., 1997; Royet et al., 2000; Sander & Scheich, 2001; Zald & Parvo, 2002). As these findings corresponded to results in vision (e.g. Lang et al., 1998a; Bradley et al., 2003; Junghöfer et al., 2005; Sabatinelli et al., 2005) http://www.selleckchem.com/products/GDC-0980-RG7422.html it was suggested that the same neural mechanisms might be relevant to affective processing in the two modalities

Carnitine palmitoyltransferase II (Bradley & Lang, 2000). However, only very few studies have investigated the temporal dynamics of auditory emotion processing with time-resolving neurophysiological measures, such as high-density EEG or whole-head MEG in the same way as in vision to further clarify this issue. Using a classical conditioning design with two different tones as CS and median nerve electric shock as US, Moses et al. (2010) demonstrated a so-called CR in the form of an enhanced CS+ beta-band desynchronisation in CS+ conditioning trials with omitted US. This CR was localised at somatosensory areas contralateral to the left or right stimulation side and was interpreted as reflecting the UCS association during CS processing. Although the CR in this study occurred rather late (150–350 ms after omitted shock presentation), previous electrophysiological studies revealed that CRs usually ‘…occur around the time that activation elicited by the US would be expected’ (Moses et al., 2010, p. 276). Non-CR effects were not reported by Moses and colleagues.

As with studies on other acidophilic methanotrophs, culture purity was Wortmannin concentration rigorously proven using a variety of microscopic and molecular analyses. Growth was greater on methane than on acetate (maximum OD410 nm of 0.8–1.0 and 0.25–0.30, respectively), as was the growth rate (μ=0.06 and 0.006 h−1, respectively). These data would suggest that methane is the preferred substrate of this strain. However, when both acetate and methane were used simultaneously, overall growth was enhanced, as first noted by Whittenbury et al. (1970) for other methanotrophs. Interestingly,

strain H2s was not found to grow significantly on any other organic acid or sugar (Table 1). With the finding of a facultative Methylocystis strain, Belova

et al. (2011) screened validly described Methylocystis species for facultative methanotrophic growth, and found that another acidophilic species with an optimal pH range of 5.8–6.2, Methylocystis heyeri H2, also grew significantly on acetate. Most mesophilic Methylocystis species (i.e. growth pH of 6.8) did not grow on acetate, with the exception of Methylocystis echinoides IMET10491 which grew in the presence of acetate Bleomycin from an initial OD410 nm of ∼0.03 to a final OD410 nm of 0.09 after 200 h of incubation. A second recent study supports the finding of facultative mesophilic Methylocystis species, with the characterization of Methylocystis strain SB2, a novel methanotroph that can only express pMMO (Im et al., 2011). This isolate, collected from a spring bog with an optimal growth pH of 6.8, was able to utilize methane, ethanol, or acetate as growth substrates. Growth was highest on methane followed by ethanol and acetate (maximum OD600 nm of 0.83, 0.45, and 0.26, respectively). Interestingly, growth on methane and ethanol followed standard exponential kinetics (μ=0.052 and 0.022 h−1, respectively), but growth on acetate

could be modeled as either exponential or linear growth. Such a finding supports the hypothesis that acetate is transported into Methylocystis strain SB2 as the undissociated acid, and at this growth pH, the proton-motive force is dissipated for acetate uptake (Axe & Bailey, 1995). Finally, as NADPH-cytochrome-c2 reductase with other investigations of facultative methanotrophy, culture purity was verified using a variety of microscopic and molecular techniques. The recent findings of facultative methanotrophy raises some very interesting questions. Particularly, is the MMO expressed when these strains are grown on multicarbon compounds in the absence of methane? Interestingly, acetate has been shown to repress MMO expression in some facultative methanotrophs, while others constitutively express MMO regardless of the growth substrate. Specifically, when using acetate as an alternative substrate, M. silvestris was clearly shown to repress expression of the sMMO (the only form of MMO it expresses) in either the absence or presence of methane (Theisen et al., 2005).

The STA-9090 datasheet present study does not limit the function of the Cls1 backup system to acute low-pH stress. This study was supported in part by the Program to Disseminate Tenure Tracking System, MEXT, Japan (to RLO). R.L.O. and K.K. contributed equally to the work. “
“5′-Methylthioadenosine/S-adenosylhomocysteine nucleosidase (MTAN) plays crucial roles in the production of autoinducers and methionine metabolism. Putative genes encoding MTAN and AdoHcyase from Burkholderia

thailandensis were cloned and characterized. The Km values of MTAN for 5′-methylthioadenosine (MTA) and S-adenosylhomocysteine (SAH) were 19 and 58 μM, respectively. The catalytic efficiency of MTAN for SAH was only 0.004% of the value for MTA, indicating an almost complete substrate preference of MTAN for MTA. The results of autoinducer-2 assay of B. thailandensis and recombinants indicated that LuxS enzyme activity was lacking in Burkholderia species. Instead, AdoHcyase hydrolysed SAH directly to homocysteine and adenosine in the activated methyl cycle. Meanwhile, the Km value of AdoHcyase for SAH was determined to be 40 μM. Sequence analysis revealed that MTAN had much higher diversity than AdoHcyase, which likely contributes to its substrate preference for MTA. Furthermore, the selleck chemical phylogenetic tree of MTAN sequences revealed that LuxS+ bacteria could be discriminated from LuxS− bacteria. These results suggested that the substrate preference of MTAN for MTA and SAH degradation

pathway evolved with the bacterial-activated methyl cycle. “
“The need for improved rapid diagnostic tests Flavopiridol (Alvocidib) for tuberculosis disease has prompted interest in the volatile organic compounds (VOCs) emitted by Mycobacterium tuberculosis complex bacteria. We have

investigated VOCs emitted by Mycobacterium bovis BCG grown on Lowenstein–Jensen media using selected ion flow tube mass spectrometry and thermal desorption-gas chromatography-mass spectrometry. Compounds observed included dimethyl sulphide, 3-methyl-1-butanol, 2-methyl-1-propanol, butanone, 2-methyl-1-butanol, methyl 2-methylbutanoate, 2-phenylethanol and hydrogen sulphide. Changes in levels of acetaldehyde, methanol and ammonia were also observed. The compounds identified are not unique to M. bovis BCG, and further studies are needed to validate their diagnostic value. Investigations using an ultra-rapid gas chromatograph with a surface acoustic wave sensor (zNose) demonstrated the presence of 2-phenylethanol (PEA) in the headspace of cultures of M. bovis BCG and Mycobacterium smegmatis, when grown on Lowenstein–Jensen supplemented with glycerol. PEA is a reversible inhibitor of DNA synthesis. It is used during selective isolation of gram-positive bacteria and may also be used to inhibit mycobacterial growth. PEA production was observed to be dependent on growth of mycobacteria. Further study is required to elucidate the metabolic pathways involved and assess whether this compound is produced during in vivo growth of mycobacteria.

The framework of our sorting method is schematically illustrated in Fig. 1. The

signals were recorded with multi-channel electrodes at the sampling frequency ωs of 20 kHz. They first underwent a band-pass filter to remove slowly changing local field potential and high-frequency fluctuations. In this study, we compared two types of band-pass filters. The classical window method (CWM) employed a finite impulse response filter that was derived by taking a difference between two sampling functions with different frequencies. We used finite impulse response filters rather than infinite impulse selleckchem response filters. The latter filters are generally faster than the former but they show frequency-dependent phase responses that make the accurate detection of spike peaks difficult. Figure 2A shows the CWM filter for the sampling rate ωs (inset) and its frequency–response property. The band-pass range, order and window function of the filter are 800 Hz–3 kHz, 50 and Hamming type, respectively. Figure 2B displays the frequency–response property of our finite impulse response filter constructed from a Mexican hat (MXH)-type wavelet for the same sampling frequency (inset). The filter

has band-pass frequencies around ωp = 2 kHz and the order is only 26. The wavelet is given as with s = 0.25 ×ωs/ωp, where s is the time length normalized by ωs and l is the sampling index (integer). As the two filters are symmetrical with respect to time 0, they do not show phase Talazoparib mw delays. We note that the MXH filter with 27 sampled values (including the origin) is computationally less costly than the CWM filter with 51 sampled values. Nevertheless, the MXH filter works

as ID-8 efficiently as the CWM filter in low-cut filtering. After the band-pass filtering, spikes were detected by amplitude thresholding. As the recorded spikes have negative peaks, the threshold was set to −4σ unless otherwise stated, where the SD of noise was estimated to be from the band-passed signal x (Hoaglin et al., 1983; Quiroga et al., 2004). The discrete spike waveform detected by each channel was interpolated with quadratic splines and the precise spike-firing time was defined as the time of the greatest negative peak among all detected spikes in all channels. A spike in general exhibits slightly different peak times at different channels. To avoid detecting the same spike more than once, the waveforms detected within a time window of 0.5 ms were regarded as the same spike. Spike detection is the first step in spike sorting and is considered to affect the quantity of sorted spikes. Lowering the detection threshold enables the detection of more spikes. However, most of the detected spikes with small amplitudes are finally grouped into a contaminated cluster, hence adding no valid spike trains. Therefore, detecting more spikes does not necessarily increase the number of spikes that are suitable for further analysis.

It is also a useful measure when they are asked at the end of the therapy to do the same and will often choose a different card. This again demonstrates the movement that has occurred during the course of counselling. Consent was obtained from all those referred by the counsellor for anonymised data to be used for evaluation of the service. We performed a retrospective check details analysis of data obtained for people referred to the service between June 2007 and June 2010, using measurements

made pre- and post-attendance at the course of counselling. We looked at effects on HbA1c as a measure of glycaemic control, and changes in scores from the Clinical Outcomes in Routine Evaluation (CORE) outcome measure questionnaire,7 a measure of feelings of anxiety and risk, to assess the effectiveness of the counselling. This system was chosen over specific diabetes evaluation measures because it related

to the person as a whole rather than their diabetes alone. As life events that result in anxiety have a detrimental effect on the ability to self-care, we used a measure encompassing their anxieties as a whole rather than focusing purely on the diabetes. Comparison of pre- and post-counselling GSK2118436 order values were made using chi-squared test for gender, Wilcoxon signed rank test for non-parametric data (HbA1c) and paired t-test for normally distributed data (age, CORE scores), with a 5% level of probability denoting significance. There were 79 people referred to the type 1 diabetes counselling service. The PDK4 average age was 40.1 years (SD 15.3), with 21 males and 58 females. Glycaemic control in the full cohort was sub-optimal (HbA1c pre-counselling [median (range)] 9.7% [5.8, 17.8]), and CORE scores revealed high levels of anxiety in these patients about their diabetes (CORE score pre-counselling [mean ± SD] 1.63±0.74). Of the 79 people referred, 17 did not complete the course of counselling. There was a trend towards these being more likely to be male (seven males and 10 females did not complete the counselling course; p=0.059), but there was no difference in age (completers [mean ± SD] 39.9±15.6 years, non-completers 39.3±13.8 years; p=0.883), glycaemic control (completers [median

(range)] 9.5% [6.2, 17.8], non-completers 10.6% [7.8, 13.7]; p=0.164) or CORE score (completers [mean ± SD] 1.60±0.71, non-completers 1.90±1.00; p=0.283). Of this group, seven did not start their counselling course despite referral, four did not complete the course after discussion with the counsellor, and six missed one or more sessions, so were not re-appointed. We did not explore the specific reasons why they did not complete the course, and the small numbers preclude further analysis of the different groups of non-completers. Data from the 62 people who completed the course were analysed to assess the impact of counselling. There was a reduction observed in both glycaemic control (HbA1c pre-counselling [median (range)] 9.5% [6.2, 17.8], post-counselling 9.3% [5.

UniFrac distances ranged from 0.298 to 0.607 and were higher between the initial and late stage samples. UniFrac tests have been previously used as a semi-quantitative determination of the similarities between the bacterial communities on the phyllosphere of Populus deltoides sampled at different times (Redford et al., 2010). According to our estimations, major changes

in the phenol-degrading bacterial community may occur between the initial and midterm stages of leaf decomposition. At the midterm, the greatest community richness and diversity was found and coincided with increasing phenol PD 332991 oxidase activity and maximum fungal biomass (Artigas et al., 2011). The LmPH sequences from this stage were scattered throughout the phylogenetic tree (in clusters A, B, C, and E), and their corresponding enzymes exhibit different kinetic properties. selleck inhibitor It is known that bacteria and fungi have complementary roles in leaf litter degradation. Bacteria are thought to increase their contribution only after leaf material has been partially broken down (Baldy et al., 1995), whereas fungi, especially

aquatic hyphomycetes, have been recognized as dominant, in terms of both activity and biomass, during early decomposition (Gulis & Suberkropp, 2003; Romaní et al., 2006). However, bacteria may make a greater contribution to leaf litter decomposition particularly when fungal activity is compromised by unfavorable conditions (Pascoal & Cassio, 2004; Kubartova et al., 2009). In conclusion, by analyzing the LmPH gene from different leaf decomposition stages, we have shown that the bacterial community changes significantly over the course of leaf litter degradation in streams. During Arachidonate 15-lipoxygenase early decomposition, the bacterial community is rather complex and potentially exhibits a low degree of metabolic

specialization in view of the deduced enzyme kinetics. As decomposition progresses, the phenol-degrading bacterial community is dominated by suspected low-Ks type bacteria, with a high similarity to Alcaligenes spp., Comamonas sp., and Ralstonia sp, suggesting a gradual selection of specialized phenol degraders as decomposition progressed. To the best of our knowledge, this work represents the first specific analysis of any functional gene marker and of bacterial and fungal origin, used for investigating microbial communities during the leaf litter decomposition process in streams. Time series analyses of bacterial and fungal communities in leaf litter decomposition have previously been performed using either DGGE or terminal-restriction fragment length polymorphism (T-RFLP) of amplified SSU rRNA fragments (Das et al., 2007; Marks et al., 2009; Kelly et al., 2010), although no general conclusions can be derived from these studies. The relative presence of general and specialized microorganisms on leaf surfaces during litter decomposition has been proposed as a major determinant of diversity (Das et al., 2007).

Paratyphi B. “
“The utility of specific strains of natural algicidal bacteria isolated from shallow wetland sediments was evaluated against several strains of algae with potential immediate or future commercial value. Two strains of bacteria, Pseudomonas pseudoalcaligenes AD6 and Aeromonas hydrophila AD9, were identified and demonstrated to have algicidal activity against the microalgae Neochloris oleoabundans and Dunaliella tertiolecta. These bacteria were further evaluated for the potential to improve lipid extraction using

a mild solvent extraction approach. Aeromonas hydrophila AD9 showed a nearly 12-fold increase in lipid extraction with D. tertiolecta, EPZ015666 order while both bacteria showed a sixfold improvement in lipid extraction with N. oleoabundans. “
“Although GlaxoSmithKline is on the way to launch the new vaccine candidate ‘RTS, S’, the search for suitable antimalarial drugs still remains an exceeding challenge because Plasmodium falciparum-mediated malaria is one of the most lethal diseases in the world. Novel innovative ideas are required to identify new potential molecular targets to be able to fight this lethal parasite efficiently. We

used an unconventional bioinformatics approach to analyze the entire genome and proteome of the Pf3D7 strain. Because the oxygen (O-) content is a decisive parameter that determines the function of a protein, we analyzed the entire Pf3D7 proteome based on O-containing amino acid expression. Our data disclose a total of four proteins encoded by chromosome (Chr)-4 and Chr-9 selleck monoclonal humanized antibody that have an outstanding O-controlled character. The identification of the biological significance of

these proteins could eventually lead to new vital drug targets. “
“Division of Crop Protection Central Plantation Crops Research Institute, Kerala, India Conventional and real-time PCR assays were developed for sensitive and specific detection of Phytophthora colocasiae, an oomycete pathogen that causes leaf blight and corm rot of taro. A set of three primer pairs was designed from regions of the RAS-related protein (Ypt1), G protein alpha-subunit (GPA1) and phospho-ribosylanthranilate isomerase (TRP1) genes. In conventional PCR, the lower limit of detection was 50 pg DNA, whereas in real-time PCR, Carbohydrate the detection limit was 12.5 fg for the primer based on Ypt1 gene. The cycle threshold values were linearly correlated with the concentration of the target DNA (range of R2 = 0.911–0.999). All the primer sets were successful in detecting P. colocasie from naturally infected leaves and tubers of taro. Phytophthora colocasiae was detected from artificially infested samples after 18 and 15 h of postinoculation in conventional and real-time PCR assay, respectively. The developed PCR assay proved to be a robust and reliable technique to detect P.

Probe labeling and hybridization were performed using the ECL Direct Nucleic Acid Labeling and Detection system (Amersham Bioscience) according to the manufacturer’s instructions. The membrane was exposed to Hyper Film™ ECL for visualization. The tester-specific clones were sequenced using M13F and/or M13R primers. Cycle sequencing was performed using the BigDye Terminator v3.1 Cycle Sequencing kit, and the sequencing reactions were analyzed on an automated DNA sequencer (model 3730; Applied

AZD6244 cell line Biosystems, Foster City, CA). The sequences generated from the automatic sequencer were edited by removing the vector and adaptor sequences. Sequence assembly and further editing were performed with the clustal_x 1.81 program (Thompson et al., 1994), and blastn, blastx, and tblastx analyses against the database of the National Center for Biotechnology Information (NCBI) were performed for each sequence to determine homology with other microorganisms and to annotate their functions.

The nucleotide sequences obtained in this study were deposited in the dbGSS (database of Genome Survey Sequences) of NCBI GenBank under accession numbers JM426692–JM426710 for SSH libraries of L. garvieae (Table 2). PCR primers were designed for the clones CAUF58 (garF58F, 5′-CGGAGTAGCCGATAATTCCA-3′ and garF58R, http://www.selleckchem.com/products/wnt-c59-c59.html 5′-GCAGGTACCCTGAAAAAGGA-3′) and CAUF64 (garF64F, 5′-GTGCTGAACGTCACCTTGAA-3′ and garF64R, 5′-CGTTTGCCATGATTTTTCCT-3′) using primer3 software (Rozen & Skaletsky, 2000). PCRs were performed with 100 ng genomic DNA template in 20-μL reaction mixtures containing 1 μM each primer, 2 μL 10× reaction buffer, 0.2 mM dNTPs, 1.5 mM MgCl2, and 2.5 U Taq polymerase. Amplification was carried out in a GeneAmp PCR system 9700 (Applied Biosystems) under the following conditions: initial denaturation at 94 °C for 5 min, followed by 30 cycles at 94 °C for 30 s, 58 °C for 30 s, and 72 °C for 40 s, with a final extension at 72 °C for 10 min. The primer specificities were evaluated using 12 L. garvieae, six other Lactococcus, 12 Streptococcus, and two Enterococcus strains and were compared with the specificities of previously reported Adenosine primers targeting

the 16S rRNA gene [pLG-1 and pLG-2 (Zlotkin et al., 1998), SA1B10-1-F and SA1B10-1-R (Aoki et al., 2000), and LcG-F and Lc-R (Odamaki et al., 2011)] using the published PCR conditions. After PCR amplification, 5 μL of each PCR product was resolved on a 1.2% Seakem LE agarose gel (FMC Bioproducts, Rockland, ME) and was visualized on the GelDoc xR image-analysis system (BioRad) after ethidium bromide staining. DNA signatures are nucleotide sequences that can be used to detect the presence of an organism and to distinguish that organism from all other species (Phillippy et al., 2007). In this study, the DNA signatures specific for L. garvieae were investigated through the identification of sequences present in L. garvieae but absent in a closely related species.

Table S1.Transcriptional profiles of Salmonella Typhimurium 4/74 nalR treated with INP0403 or DMSO (4657 gene dataset in

MS EXCEL XP format). Ratios of sample to reference (gDNA) are given as the average of three biological replicate hybridizations learn more after normalisation. Standard deviations are given for each gene. Table S2. Numerical data and P-values for INP0403-regulated genes presented in Fig. 1. Filtered for P-value < 0.05 and greater than 2-fold change. Table S3. Effect of INP0403 on transcription of known regulators of SPI-1. Data extracted from Table S1. a indicates a statistically-significant response to INP0403 (Table S2). 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 SP600125 clinical trial be directed to the corresponding author for the article. “
“Understanding the ecology of methanogens in natural and engineered environments is a prerequisite to predicting or managing methane emissions. In this study, a novel high-throughput fingerprint method was developed for determining methanogen diversity and relative abundance within environmental samples. The method described here, designated amplicon length heterogeneity PCR of the mcrA gene (LH-mcrA), is based on the natural length variation in the mcrA gene. The mcrA gene encodes the alpha-subunit of the methyl-coenzyme M reductase, which is involved in the terminal step of methane production by methanogens. The methanogenic communities from stored swine and dairy manures were distinct from

each other. To validate the method, methanogenic communities in a plug flow-type bioreactor (PFBR) treating swine manure were characterized using LH-mcrA method and correlated to mcrA gene clone libraries. The diversity and relative abundance of the methanogenic groups were assessed. Methanobrevibacter, Methanosarcinaceae, Methanoculleus, Methanogenium, Methanocorpusculum and one unidentified group were assigned to particular LH-mcrA amplicons. Particular phylotypes related to Methanoculleus MycoClean Mycoplasma Removal Kit were predominant in the last compartment of the PFBR where the bulk of methane was produced. LH-mcrA method was found to be a reliable, fast and cost-effective alternative for diversity assessment of methanogenic communities in microbial systems. Methanogenesis is a microbiological process of major environmental and industrial interest. Methane is, with CO2 and N2O, a major contributor to global warming (IPCC, 1996). On the other hand, methane produced from anaerobic digestion of organic wastes in engineered systems is a source of renewable energy (Lettinga, 1995). Therefore, it is important to improve our understanding of the ecology of bacteria and Archaea that together catalyse methanogenesis. Methanogenesis is carried out by complex anaerobic consortia of fermentative bacteria and methanogenic Archaea, or methanogens.