3a). At the CD8 T-cell level, a significant amount of AICD in effector memory and effector subsets was observed at baseline, while naïve and central memory subsets were less sensitive to AICD (Fig. 3b). Under ART, the amount of AICD decreased in all CD8 subsets from week 4 to week 24, while the expression of Ki67 in all subsets was low at baseline and slightly decreased under ART (Fig. 3b).

For unknown reasons, the amounts of AICD increased in most subsets at week 48, while immune activation was still suppressed. Altogether, taking into consideration the CHIR-99021 cost balance between priming for AICD and homeostatic proliferation, these observations may account for the differences in CD4 and CD8 T-cell subset kinetics of restoration under enfuvirtide therapy (Fig.

1a). The effect of enfuvirtide-based therapy on parameters affecting HIV entry, i.e. CCR5, chemokine (C-X-C chemokine) receptor 4 (CXCR4) and chemokines, was evaluated. A progressive decrease in the percentage of CCR5-expressing cells was detected in CD4 and CD8 T cells from all RP patients, affecting all four CD4 T-cell subsets and leading to very low CCR5 expression at week 48 in these subsets (Fig. 4a). The proportions of CXCR4-expressing CD4 and CD8 T cells were quite high at 5-Fluoracil datasheet baseline, slightly decreased until week 12 and then returned to baseline values at week 48. Considering the different subsets, CXCR4 expression was high in naïve and central memory CD4 T cells and did not change during the 48-week follow-up period. Regarding effector memory and effector CD4 T-cell

subsets, almost 40% expressed CXCR4 at baseline, and this percentage of CXCR4+ cells decreased until week 24 (Fig. 4b). Similar observations were obtained Astemizole for total CD8 T cells (Fig. 4b) and CD8 T-cell subsets (not shown). Importantly, the decrease in the proportion of CCR5-expressing CD4 T cells under enfuvirtide-based therapy was strongly correlated with, on the one hand, the activation state of CD4 T cells (i.e. CD38 or HLA-DR expression) and, on the other hand, plasma VL. Furthermore, the percentage of CCR5+ CD4 T cells was correlated with disease evolution, as estimated from CD4 cell counts (Fig. 4c). Regarding CXCR4 expression on CD4 T cells, no correlation was found with either the VL or CD4 T-cell numbers (Fig. 4c). To identify the key cytokines and chemokines modulated during enfuvirtide-based therapy, we used MAP technology on patients’ sera. Figure 5 shows that the levels of the CCR5 ligands macrophage inflammatory protein (MIP)-1α and MIP-1β dropped significantly from week 12. In contrast, the high levels of RANTES persisted. Circulating MIP-1α was correlated with the VL (r=0.43; P=0.007), but not with CD4 cell counts. Other chemokines, such as monocyte chemotactic protein (MCP)-1 and MIG, also dropped (Fig. 5), and their levels correlated positively with VL (P=0.02 and 0.

All isolates presented ADA activity, although we could not establish a relationship between isolate source and activity (Table S2). Herein, we described the biochemical properties of an ADA activity and two ADA-related sequences present on intact trophozoites of T. vaginalis. Cellular integrity was assessed, before and after the reactions, and the viability of the trophozoites was not affected by any of the conditions used in the assays. The influence of pH on the adenosine deamination in T. vaginalis was verified and the results demonstrated that the optimal pH for ADA activity reached at Opaganib molecular weight 7.5. It is known that vaginal pH in noninfected women is approximately 4.3, but can vary from

below 4 to pH 7.5 during the menstrual cycle (Stevens-Simon et al., 1994). In agreement, previous studies demonstrated that the optimal pH values for ADA activities from the camel tick, H. dromedarii,

and from the trematode F. gigantica were also 7.5 (Mohamed, 2006; Ali, 2008). Cation exposures (2.5 mM) were able to decrease the adenosine deamination in T. vaginalis in approximately 50%. Higher concentration of calcium (5.0 mM) completely abolished the enzyme activity and the presence of EDTA, a chelating agent, restored ADA activity. see more Previous data showed that zinc and other divalent cations are able to interact with other amino acid residues and induce an inhibition of the enzyme activity (Cooper et al., 1997; Mohamed, 2006; Rosemberg et al., 2008). Because zinc is toxic to PLEKHM2 T. vaginalis, we could not perform the experiments on the influence of this metal in ADA activity in intact trophozoites (Langley et al., 1987; Houang et al., 1997). Additional

studies are necessary to explain the relevance of the inhibition of ADA activity by calcium and magnesium in T. vaginalis physiology, because magnesium is the most abundant divalent cation in living cells, with a total cellular concentration between 14 and 20 mM (Schmitz et al., 2007). The substrate curve demonstrated that the apparent KM for adenosine was around 1.13 ± 0.07 mM and the estimated Vmax for adenosine deamination was 2.61 ± 0.054 NH3 min−1 mg−1 protein in T. vaginalis. The kinetic data obtained in this study are in accordance with other studies related to ADA activity, although there are some variations of KM among different ADA members. The KM value of H. dromedarii ADA2 was estimated to 0.5 mM adenosine (Mohamed, 2006), which is relatively close to several ADAs from different sources, such as rat brain (0.45 mM) (Centelles et al., 1988), bovine brain (0.4 mM) (Lupidi et al., 1992), human (0.46 mM) and chicken liver (0.33 mM) (Iwaki-Egawa & Watanabe, 2002). However, lower KM values were reported for ADA activity from mice intestine (0.023 mM) (Singh & Sharma, 2000) and from the sand fly Lutzomyia longipalpis (0.01 mM) (Charlab et al., 2000). Additional data on biochemical characterization revealed the strong preference of the T.

agalactiae PAGU 330T (=ATCC 13813T), Streptococcus suis PAGU 580T (=ATCC 43765T), S. dysgalactiae ssp. equisimilis PAGU 375T (=NCFB 1356T) and Streptococcus marimammalium PAGU 780T (=CCUG 48494T). All strains were grown on 5% defibrinated sheep blood agar plates at 37 °C and 5% CO2. Antigens were extracted using the Lancefield procedure (Slotved et al., 2002) and serologically grouped by a capillary precipitation test. Briefly, 0.1 mL of 0.2 N HCl was added to the bacteria pellet, and the acid suspension was placed in a water bath (100 °C) for 15 min. pH was adjusted to 7 by the addition of drops of 0.2 N NaOH. The suspension was centrifuged for 10 min at 1000 g

and the supernatant was transferred (acid antigen extract) to a test tube. When acid antigen extracts were mixed with equal amounts of the antiserum (Statens Serum Institut, Copenhagen, Denmark), they formed insoluble antigen–antibody Alectinib complexes MI-503 mouse visible as a precipitate in positive reactions. The organisms were biochemically characterized using the Streptogram (Wako Pure Chemical, Osaka, Japan) and Rapid ID 32 Strep (bioMérieux, Tokyo, Japan) systems, according to the manufacturers’ instructions.

Morphology and hemolysis of the colonies were determined after 24-h incubation on sheep blood agar at 37 °C and 5% CO2. PCR amplification of the 16S rRNA gene sequencing of the purified PCR products was carried out (Kawamura et al., 1999). After confirming amplicons of 16S rRNA gene on 1% agarose gels, the sequence was determined using a BigDye Terminator v3.1 Cycle Sequencing kit (Applied Biosystems, Tokyo, Japan). 16S rRNA gene (>1300 bases) sequences of both strands of the gene were determined using the 3130 Genetic Analyzer (Applied

Biosystems). The sequences of the other streptococci used for alignment and for calculating levels of homology were obtained from GenBank. Multiple find more sequence alignments of DNA sequences were performed using clustal x software (Thompson et al., 1997). Phylogenetic distances were calculated using the neighbor-joining method (Saitou & Nei, 1987). The phylogenetic tree was constructed using treeview software (Page, 1996). DNA–DNA hybridization was performed, as described by Ezaki et al. (1989). Briefly, purified DNA (100 μg mL−1) of each strain was heat denatured and then diluted to 10 μg mL−1 with phosphate-buffered saline (PBS) containing 0.1 M MgCl2. The diluted DNA solution was distributed onto a microplate (Nunc-Immunoplate, Roskilde, Denmark) at 100 μL per well, and the plate was incubated at 30 °C for 12 h. The solution was discarded and the plate was dried. DNA from group M strains and S. marimammalium CCUG 48494T were labeled with photobiotin (Vector Laboratories, CA). The plate was prehybridized for 30 min and then hybridized for 2 h at 30 °C (optimal conditions) and 40 °C (stringent conditions) using 2 × SSC containing 50% formamide.

agalactiae PAGU 330T (=ATCC 13813T), Streptococcus suis PAGU 580T (=ATCC 43765T), S. dysgalactiae ssp. equisimilis PAGU 375T (=NCFB 1356T) and Streptococcus marimammalium PAGU 780T (=CCUG 48494T). All strains were grown on 5% defibrinated sheep blood agar plates at 37 °C and 5% CO2. Antigens were extracted using the Lancefield procedure (Slotved et al., 2002) and serologically grouped by a capillary precipitation test. Briefly, 0.1 mL of 0.2 N HCl was added to the bacteria pellet, and the acid suspension was placed in a water bath (100 °C) for 15 min. pH was adjusted to 7 by the addition of drops of 0.2 N NaOH. The suspension was centrifuged for 10 min at 1000 g

and the supernatant was transferred (acid antigen extract) to a test tube. When acid antigen extracts were mixed with equal amounts of the antiserum (Statens Serum Institut, Copenhagen, Denmark), they formed insoluble antigen–antibody Erastin complexes Bioactive Compound Library cell line visible as a precipitate in positive reactions. The organisms were biochemically characterized using the Streptogram (Wako Pure Chemical, Osaka, Japan) and Rapid ID 32 Strep (bioMérieux, Tokyo, Japan) systems, according to the manufacturers’ instructions.

Morphology and hemolysis of the colonies were determined after 24-h incubation on sheep blood agar at 37 °C and 5% CO2. PCR amplification of the 16S rRNA gene sequencing of the purified PCR products was carried out (Kawamura et al., 1999). After confirming amplicons of 16S rRNA gene on 1% agarose gels, the sequence was determined using a BigDye Terminator v3.1 Cycle Sequencing kit (Applied Biosystems, Tokyo, Japan). 16S rRNA gene (>1300 bases) sequences of both strands of the gene were determined using the 3130 Genetic Analyzer (Applied

Biosystems). The sequences of the other streptococci used for alignment and for calculating levels of homology were obtained from GenBank. Multiple Farnesyltransferase sequence alignments of DNA sequences were performed using clustal x software (Thompson et al., 1997). Phylogenetic distances were calculated using the neighbor-joining method (Saitou & Nei, 1987). The phylogenetic tree was constructed using treeview software (Page, 1996). DNA–DNA hybridization was performed, as described by Ezaki et al. (1989). Briefly, purified DNA (100 μg mL−1) of each strain was heat denatured and then diluted to 10 μg mL−1 with phosphate-buffered saline (PBS) containing 0.1 M MgCl2. The diluted DNA solution was distributed onto a microplate (Nunc-Immunoplate, Roskilde, Denmark) at 100 μL per well, and the plate was incubated at 30 °C for 12 h. The solution was discarded and the plate was dried. DNA from group M strains and S. marimammalium CCUG 48494T were labeled with photobiotin (Vector Laboratories, CA). The plate was prehybridized for 30 min and then hybridized for 2 h at 30 °C (optimal conditions) and 40 °C (stringent conditions) using 2 × SSC containing 50% formamide.

Our study focused primarily on the suitability of single active ingredient analgesics; however, a number of fixed-dose combination this website analgesics are available in the OTC setting. From a suitability perspective their

use requires even more care, making it important to ensure that consumers are aware of the potential risks associated with both active ingredients when selecting these products. Our research found no significant public health issues associated with the OTC use of paracetamol, but it has shown that up to three in 10 regular users of OTC NSAIDs have current or prior medical conditions that warrant discussion with a healthcare professional prior to their use. It is important to note that

some of these consumers may already be acting upon such advice, reducing the potential risk. However, with a large proportion of regular users of OTC NSAIDs purchasing these products outside the pharmacy setting, the quality use of OTC NSAIDs is becoming increasing reliant on product labelling and the ability of consumers to understand and self-assess their own level of risk. A key theme emanating from our data and from other recent changes in the analgesics landscape both locally and globally is the continued need to ensure a high level of consumer education Daporinad concentration regarding the appropriate choice and use of analgesics. For the vast majority of consumers who have used these medications in the past the potential risks are minimal. However, consumers need to be aware that if their health status changes then this warrants a discussion with a healthcare professional to confirm the continued appropriateness of their OTC analgesic medication. Rather than placing the onus solely on the consumer to actively seek advice and hoping that this is undertaken a more practical approach would be to also reinforce with healthcare professionals

the need to proactively probe patients about the use of OTC analgesics and offer advice as to any changes that need be undertaken when they present with a new condition that puts them into an at-risk population. The safe and IMP dehydrogenase effective use of any OTC medication requires active participation and open communication between the user and healthcare professionals. Our study demonstrates that since ibuprofen has become available outside the pharmacy setting in Australia fewer people are using NSAIDs appropriately according to the label; compared to 2001, in 2009 10.2% more regular OTC analgesic users were using ibuprofen despite having contraindications, warnings, precautions or potential drug-interactions. The increasing use and wider availability of OTC NSAIDs may have led to a more relaxed attitude regarding the use of these medicines.

In order to validate the accuracy of the reason for discontinuation determined by the clinician, we repeated the analysis with the immunovirological and clinical endpoint,

defining discontinuation as a consequence of failure on the basis of the following: discontinuation Ceritinib supplier of ≥1 drug in the original regimen concomitant with (i) a single viral load >500 HIV-1 RNA copies/mL, or (ii) an increase in CD4 cell count <10% from the patient's pre-therapy value, or (iii) the occurrence of an AIDS-defining illness. A total of 3291 patients were included in the study: 28.2% were female and 39.9% were HCV antibody-positive; their median age was 36 years [interquartile range (IQR) 32–41 years]. Median

CD4 cell count at HAART initiation was 263 cells/μL (IQR 114–402 cells/μL), and median HIV RNA was 4.8 log10 copies/mL (IQR 4.2–5.3 log10 copies/mL). One hundred and thirty-eight patients (4.2%) initiated therapy with three NRTIs (of whom 117 initiated regimens including abacavir and 21 initiated regimens including tenofovir as the third drug), learn more 894 (27.2%) with an NNRTI-based regimen, 366 (11.1%) with a boosted PI, 1786 (54.3%) with a single PI, five (0.1%) with a combination of three other drugs (one NRTI+two PIs) and 102 (3.1%) with Glutamate dehydrogenase four or more drugs. Most patients

(52.6%) started HAART in the early period (1997–1999), 925 (28.1%) in the intermediate period (2000–2002) and 635 (19.3%) in the recent period (2003–2007) (Table 1). The median time of follow-up of patients was 12 (IQR 3–12) months; 288 patients (8.7% of the population) dropped out during the first year of follow-up; 14 of these died. During the first 12 months, 1189 (36.1%) patients discontinued ≥1 drug in their initial HAART. The main causes of discontinuation were intolerance/toxicity (696 of 1189 patients; 58.5%) and poor adherence (285 of 1189 patients; 24%); 126 patients (10.6%) discontinued because of immunovirological or clinical failure and 62 (5.2%) because of simplification strategies. Twenty patients (1.7%) interrupted temporarily or permanently all the ongoing drugs by clinician choice or patient wish. The Kaplan–Meier estimates of drug discontinuation for any reason in the first year were 39.5% (95% CI 37.1–41.9%) in those who initiated in 1997–1999, 35.6% (95% CI 32.3–38.9%) in those who initiated in 2000–2002, and 41.2% (95% CI 37.1–45.3%) in those who initiated in 2003–2007 (log-rank test P=0.06) (Fig. 1).

, 2010, 2011) have enabled these models to be generated in a high-throughput manner for tens of thousands of microbial genomes. This approach is becoming increasingly relevant as draft quality genomes of the most abundant organisms in a microbial community can be assembled from metagenomic data (Woyke et al., 2010; Hess et al., 2011; Mackelprang et al., 2011; Iverson et al., 2012; Luo et al., 2012). In particular, RXDX-106 nmr Mackelprang et al. (2011) found that the most abundant organism present in Alaskan permafrost soil was a novel methanogen and that modeling its metabolism from the assembled draft

genome provided direct insight into how the thawing permafrost will contribute methane, a powerful greenhouse gas, to the atmosphere. Microbial interaction models predict how the metabolisms of two or more microbial taxa interact with one another and their environment. Flux-balance models, which have been proven to be successful, are now being taken a step further to enable the development of simple interaction models between multiple individual flux-balance models for different genomes (Freilich et al., 2011). Individual-based models represent space as a discrete lattice, and each lattice element can contain microbial cells and measures of environmental

parameter levels. Each microbial cell in the PI3K inhibitor model is an individual and can have various capacities to interact with environmental parameters (O’Donnell et al., 2007). Applying individual-based methods to entire microbial communities requires highly detailed, very accurate information about microbial metabolism and the nature of the microenvironment (Ferrer et al., 2008;

Freilich et al., 2011). Fortunately, there are computational techniques for describing multiphase transport in complex, porous media like soil, such as the Lattice-Boltzmann method (i.e. Zhang et al., 2005), which is a class of computational fluid dynamics techniques. Using these methods, it may be possible to model the dynamic movement of soil and then overlay this with biological information regarding the dynamics of the microbiome in that system; however, this has not yet been validated. Because this form Liothyronine Sodium of modeling can be computationally intensive, some methodological innovations, such as the use of superindividuals, have been advocated (Scheffer et al., 1995). The first study using individual-based modeling to predict the behavior of a microbial community simulated the accumulation of nitrate by nitrifying bacteria in different soil types (Ginovart et al., 2005). Recently, Gras et al. (2010) modeled the metabolism and dynamics of organic carbon and nitrogen in three different types of Mediterranean soil. The model incorporated specific parameters for growth and decay of microbial biomass, temporal evolution of mineralized intermediate carbon and nitrogen, mineral nitrogen in ammonium and nitrate, carbon dioxide, and O2.

Injured travelers as well as medical tourists are directly concerned by this strategy. This article has been kindly proofread by Amy Whereat, Medical English Consultant. The authors state they have no conflicts of interest to declare. “
“A 34-year-old Nigerian man presented with nephrotic syndrome. Renal biopsy revealed chronic membranous glomerulopathy with focal segmental sclerosis. Blood Giemsa smear contained rare Plasmodium sp. trophozoites and small subunit

ribosomal RNA polymerase chain reaction amplification confirmed the presence of Plasmodium malariae. This case highlights the importance of obtaining even remote travel histories from ill immigrants and considering occult quartan malaria in patients from endemic locations with nephrotic syndrome. Although quartan ABT-737 nmr malaria comprises only a small portion of the global disease burden from malaria, Plasmodium this website malariae is unique among the plasmodia in which subclinical parasitemia may persist for decades with illness occurring more than 40 years after the last possible exposure.1 Additionally, chronic P malariae infection was linked to nephrotic syndrome in children in the 1960s and subsequently attributed to immune complex basement membrane nephropathy.2,3 We describe a case of P malariae-associated chronic membranous glomerulopathy and nephrotic

syndrome in a US Navy sailor 14 years after his last possible exposure to the risk of malaria. This case highlights the importance of obtaining remote travel histories from Phospholipase D1 immigrants presenting with illness, even decades after emigration from their country of origin. A 34-year-old US-born African American Navy sailor, who moved to Nigeria at the age of 1, migrated back to the United

States at the age of 21 and had not traveled home or to any malaria endemic locations during the ensuing 14 years. While at sea, he presented to his ship’s medical doctor with a 4-month history of bilateral lower extremity pitting edema and swelling of his face and a 5-month history of frothy urine. He was notably hypertensive with hyperlipidemia (total cholesterol 390 mg/dL, low density lipoprotein 305 mg/dL, triglycerides 230 mg/dL) and was placed on hydrochlorothiazide and simvastatin. Upon return to port, the patient was referred to Internal Medicine for suspected nephrotic syndrome. His past medical history was significant for sickle trait, treated latent tuberculosis, and childhood malaria. He denied a family or personal history of kidney disease. Laboratory studies were significant for a spot protein/creatinine ratio of 22.6, consistent with nephrotic syndrome. Additional abnormal laboratory findings included low serum albumin (1.8 g/dL), high serum creatinine (6.2 mg/dL), and a low glomerular filtration rate (14 mL/min).

This indicates that a classifier trained only on pictures of separately presented faces and places may not be the most optimal way of decoding object-based visual attention. Concluding, we have shown that real-time fMRI allows for online prediction of attention to objects belonging to different object categories. Prediction is based on distributed patterns of activity in multiple brain regions. The outlined methodology not only allows us to probe object-based attention in an online setting Selleckchem OSI 906 but also illustrates the potential to develop BCIs that are driven

by modulations of high-level cognitive states. The authors gratefully acknowledge the support of the BrainGain Smart Mix Programme of the Netherlands Ministry of Economic Affairs and the Netherlands Ministry of Education, Culture and Science. The first

author was supported by a UTS grant from the University of Twente. We thank Paul Gaalman for his technical support during the experimental setup and development of the real-time fMRI pipeline. We are very grateful to the editors and the anonymous reviewers for their encouraging and constructive comments on our manuscript. Abbreviations aMTG anterior medial temporal gyrus BCI brain–computer interface BOLD blood oxygen level-dependent FFA fusiform face area fMRI functional magnetic resonance imaging GLM general linear model MoCo motion-corrected MVA-C cluster-wise learn more multivariate analysis MVA-G GLM-restricted multivariate analysis MVA-T mean timeseries multivariate analysis MVA-W whole-brain multivariate analysis MVPA multivoxel pattern analysis OFA occipital face area PACE prospective acquisition correction TR repetition time

Fig. S1. A basis set of 15 face-place pairs used in decoding phase. Each pair was used twice in each condition, once with the face picture set as target and the other time with the place picture set as target. Note: Copyrighted pictures used in the original experiment have been replaced in the above graphic by their non-copyrighted look-alikes. Fig. S2. Graph-based visual saliency algorithm was used to select the face-place pairs. Saliency of the 50/50 hybrid and each of its constituents were Resveratrol observed and only those pairs were selected for which the 50/50 hybrid had an equal number of salient points for the face and place picture. Fig. S3. Stimulus timeline. (A) Example of an attend-face trial in non-feedback condition. (B) Example of an attend-place trial in feedback condition. After cues have been presented, the face-place hybrid image was updated every TR depending on classification result of the preceding TR. Fig. S4. List of all brain regions from which voxels were selected by the MVA-W classifier for training. Only regions that were activated across three or more subjects were used for further analyses. Fig. S5.

For mixed-strain competitions, hatchlings were exposed to an inoculum containing an ∼1 : 1 ratio of wild type and mutant. At 48-h postinoculation,

individual squid were homogenized and dilution plated on LBS. The resulting colonies were patched onto LBS with added trimethoprim to determine the ratio of strains in each animal. Inocula were similarly plated and patched to determine the starting ratio. The relative competitiveness index (RCI) was determined by dividing the mutant to wild-type ratio in each animal by the ratio of these strains in the inoculum. The Ibrutinib mean RCI was calculated from log-transformed data. blast searches (Altschul et al., 1990) of the V. fischeri ES114 genome revealed the similarity of ORFs VF1308 and VF1309 to the N and C termini of E. coli FNR, respectively (Fig. 1a). We MAPK Inhibitor Library nmr suspected that a sequencing error had led

to the misannotation of fnr as two genes, and we therefore cloned and sequenced the region spanning VF1308 and VF1309. We found five errors in the genome database, leading to an erroneously predicted truncation of VF1308, which we corrected in GenBank (Mandel et al., 2008). In the revised sequence, VF1308 encodes a protein that is the same length as, and shares 84% identity with, E. coli FNR. This ES114 FNR is identical to the previously deposited V. fischeri MJ1 FNR (accession no. CAE47558). Importantly, the residues necessary for interactions with RNA Molecular motor polymerase (Williams et al., 1997; Lonetto et al., 1998; Blake et al., 2002; Lamberg et al., 2002), 4Fe–4S center assembly (Spiro & Guest, 1988; Kiley & Beinert, 1998), and DNA recognition (Spiro et al., 1990) in E. coli are conserved in V. fischeri FNR. Using TransTermHP (Kingsford et al., 2007), we also found a likely Rho-independent transcriptional terminator downstream of fnr (Fig. 1a and b). Given the 142-bp spacing and strong putative terminator between fnr and VF1310 (Fig. 1b), it seems likely that these are expressed on separate transcripts. Using quantitative RT-PCR, we found that the fnr∷tmpR allele in mutants described

below did not affect the transcript levels for VF1310. We next generated mutants disrupted in the putative fnr in V. fischeri ES114 and MJ1. We did not observe any attenuation of these strains under aerobic growth conditions, consistent with the role of FNR in other bacteria. Escherichia coli fnr mutants do not grow anaerobically with nitrate or fumarate as an electron acceptor (Lambden & Guest, 1976), and we found that V. fischeri fnr mutants were similarly attenuated. Specifically, when grown with minimal medium under anaerobic conditions, ES114 and MJ1 displayed nitrate- or fumarate-dependent growth on a nonfermentable carbon source (glycerol) that was lacking in the fnr mutants (e.g. Fig. 1c).