For example, A. nidulans bglD (AN7915)

encodes a glucosidase present in the F9775 biosynthetic gene cluster (Additional file 2). In a cclAΔ strain background in which histone 3 lysine 4 methylation is impaired, the expression of cryptic secondary metabolite clusters, such as F9775, is activated [52]. The activation of bglD expression was observed along with other genes in the F9775 cluster and based on this pattern of coregulation, bglD is included as a member of this cluster [52]. It is unclear, however, whether bglD actually plays a role in F9775 biosynthesis. The gene encoding translation elongation factor 1 gamma, stcT, is a member of the ST gene cluster (stc) of A. nidulans. Its Gamma-secretase inhibitor inclusion in the stc cluster was based on its pattern of coregulation with 24 other genes, some of which have experimentally determined roles in A. nidulans

ST biosynthesis, or are orthologous to A. parasiticus proteins involved selective HDAC inhibitors in AF production, for which ST is a precursor [46]. We also observed a gene, AN2546, that is expressed, and is predicted to encode a glycosylphosphatidylinositol (GPI)-anchored protein [53], located in the emericellamide cluster (Additional file 2); however, an AN2546 deletion strain still produces emericellamide, thus its inclusion in the cluster is based on its genomic location and expression pattern rather than function. These examples indicate that some genes are located within clusters and yet may not contribute to secondary metabolite production. The frequency and significance of unrelated genes that have become incorporated into a secondary metabolism gene cluster remains unclear; experimental verification is needed to further assess these. Ribonuclease T1 In cases where the cluster synteny data were compelling, cluster synteny was given higher precedence than functional annotation in the delineation of the cluster boundaries. Increases in the distance between predicted boundary genes

and the gene directly adjacent to a boundary (which we refer to as intergenic distance) were frequently observed. An example with a large intergenic distance at the right boundary is shown in the A. fumigatus gliotoxin (gli) cluster (Figure 3). However, we found that more subtle increases in intergenic distance were only somewhat reliable when compared to boundaries with experimental evidence. We therefore only based a cluster boundary prediction on an increase in intergenic distance in a small number of cases where no other data were available (Table 9). Discussion AspGD provides high-quality manual and computational gene structure and function annotations for A. nidulans, A. fumigatus, A. niger and A. oryzae, along with sequence analysis and visualization resources for these and additional Aspergilli and related species. Among fungal databases, AspGD is the only resource performing comprehensive manual literature curation for Aspergillus species. AspGD contains curated data covering the entire corpus of experimental literature for A. nidulans, A. fumigatus, A.

3rd edition. John Wiley & Sons; 1998. Authors’ contributions JF carried out the transcriptional profiling studies and helped to draft the manuscript. LR made measurements of biofilm antibiotic susceptibility and protein synthetic activity. BP assisted with microscopy. FR performed the oxygen microelectrode see more measurements. GE participated in the design of the study and formulation of hypotheses. AP performed the statistical analyses. AM performed the bioinformatic analysis that generated Figure 4. PS conceived the

experimental and analytical approaches, supervised laboratory work and drafted the manuscript. All authors read and approved the final manuscript.”
“Background Most microbes in natural ecosystems exist in highly organized and functional interactive communities, which are composed of cells attached to surfaces and/or to each other either from a single species or multiple species [1–7]. Microbial communities confer a number of advantages for survival, such as nutrient availability with metabolic cooperation, acquisition of new genetic traits, and protection from the environment [4, 8]. The most common microbial communities are biofilms, which refer to assemblages of cell on solid biotic or abiotic surfaces. In recent years, the subject of microbial biofilms has drawn a lot of attention and numerous studies have provided important insights into the genetic basis of biofilm development [5, 7]. Pellicles, arising

from the interface between air and liquid and therefore frequently called air-liquid (A-L) XMU-MP-1 biofilms [9], have been well studied in an array of bacteria, such as Bacillus subtilis, Pseudomonas aeruginosa, and Vibrio parahaemolyticus [7, 10–12]. Pellicle formation consists of at least three distinctive

steps: (i) initial attachment of bacteria to the solid surface (wall of culture nearly device) at the interface between air and liquid, (ii) development of the monolayer pellicle initiated from the attached cells, and (iii) maturation of pellicles with characteristic three-dimensional architecture [1, 11]. In addition to cells, a variety of components, mainly extracellular polymeric substances (EPS), are needed for developing and maintaining the pellicle matrix. The most extensively studied EPS include exopolysaccharides, proteins, and extracellular DNA although contributions of these agents to the integrity of the pellicle matrix may vary [11]. While the pellicle is generally taken into account as a special form of biofilms [5, 7, 13], its distinguishing characteristics justify that this type of biofilm may serve as an independent research model [12–14]. Many factors, including extracellular organelles such as flagella and type IV pili, secreted proteins, and chemical agents supplemented in media such as iron and phosphate, have been shown to play important roles in biofilm formation [5]. However, effects of these factors on the biofilm formation process depend on the bacterium under study.

Many hospitals have created their own unique protocol to address this aspect of management, such as Vanderbilt University Medical Center, which has published their hospital’s guidelines: for the first round of transfusion, 10 units of non-irradiated, uncrossed packed red blood cells, 4 units of AB negative plasma and 2 units of single donor platelets are sent by the blood bank; then for continued hemorrhage, bundles of blood products are sent containing 6 units of non-irradiated PRBCs, 4 units of thawed plasma and 2 units of single donor platelets [18]. in obstetrical patients if transfusion

is needed before type specific C188-9 or crossmatched blood can be obtained, if possible type-O, Rh-negative blood should be utilized because of future risk of Rh sensitization; however if not readily available

Rh-positive blood should not be withheld if clinically required. The surgeon must be aware that hemolytic transfusion reactions with emergency non typed blood can reach up to 5% [19]. Escalated Medical Management If initial interventions fail to control postpartum hemorrhage, https://www.selleckchem.com/products/Belinostat.html a stepwise progression of medical therapy is available using uterotonics to facilitate contraction of the uterus. The first agent used is oxytocin. In the United States, oxytocin is typically administered after delivery of the placenta dosed at 10-20 units in 1000 mL of crystalloid solution, given intravenously (IV) and titrated to an in infusion

rate that achieves adequate uterine contractions. Less commonly, pheromone it can be given intramuscularly (IM) or intrauterine (IU). It is common practice to double the oxytocin in PPH, i.e., 40 units in 1 L, and safety/efficacy has been documented up to 80 units per liter of crystalloid [20]. Oxytocin is not bolused, as boluses can cause hypotension. Excessive oxytocin can cause water intoxication, as it resembles antidiuretic hormone. If there is not adequate uterine tone with oxytocin, the second line agent used will depend on the medications’ side effects and contraindications. Two classes of drugs are available: ergot alkaloids (methylergonovine) or prostaglandins (PGF2α, PGE1, and PGE2). Methylergonovine may be used, dosed as 0.2 mg IM and repeated 2-4 hrs later, as long as the patient does not have hypertension or preeclampsia. If the patient has contraindications to methylergonovine or if the hemorrhage is still non-responsive, 250 μg of 15-methylprostagandin F2α may be injected intramuscularly (IM) up to 3 times at 15-20 minute intervals (maximum dose 2 mg) [21]. Appropriate injection points include thigh, gluteal muscle or directly into the myometrium.

434    <26 30.58 ± 25.57      >26 26.02 ± 31.29

  AFP (ng/mL)   0.0001    <14.7 17.23 ± 10.39      ≥14.7 38.57 ± 36.52   LDH (IU/L)   0.092    <475 23.43 ± 24.61      >475 34.01 ± 34.09   hCG (mIU/mL)   0.0001    <25 18.27 ± 9.04      >25 37.93 ± 37.7   TNM        I selleck chemicals 23.84 ± 24.49 0.876 I vs. II    II 22.99 ± 18.49 0.024 I vs. III    III 41.49 ± 40.55 0.036 II vs. III Metastases (N or M)   0.103    Absent 23.31 ± 24.10      Present 32.88 ± 32.75   SD = standard deviation; AFP = alphafetoprotein; hCG = human chorionic gonadotropin; LDH = lactate dehydrogenase; TNM = tumor, nodes, metastasis. Table 4 Association of type of germ cell tumor with hCG levels and vascular density Variable hCG median (mIU/mL) ± SD p Vascular density ± SD p Seminoma 792.73 ± 2962.1 0.069 20.64 ± 20.14 0.016 Non-seminoma 26954 ± 96511.2   34.56 ± 33.70   hCG = human chorionic

gonadotropin; SD = standard deviation Table 5 Multivariate selleck kinase inhibitor analysis of factors associated with vascular density Variable Regression co-efficient p Histology (S vs. NS) 0.2 0.907 Metastatic disease 1.2 0.165 hCG 14 0.04 AFP 13.4 0.08 LDH 0.73 0.92 S = seminoma; NS = non-seminoma; hCG = human chorionic gonadotropin; AFP = alpha-fetoprotein; LDH = lactate dehydrogenase Figure 1 Relationship between tissue vascular density and human chorionic gonadotropin (hCG) serum levels. VEGF expression was determined in 57 biopsies due to insufficient Chloroambucil material. Its expression was present in 56% of the samples. Average percentage of expression was 19 ± 3% (minimum, 0%; maximum, 80%). Intensity was absent in 44%, mild in 48%, and moderate in 8%. Qualitative VEGF expression and expression intensity were not associated with either VD or hCG serum levels (Table 6). Table 6 Association of VEGF expression with hCG levels and vascular density Variable

hCG median (mIU/mL) ± SD p Vascular density median ± SD p VEGF   0.422   0.821    Absent 1840.7 ± 4444.0   25.44 ± 26.61      Present 16581.0 ± 85185.0   27.06 ± 23.72   VEGF intensity   NS   NS    Absent 1840.7 ± 4444.7   25.44 ± 26.61      Low 19337 ± 91973.8   28.43 ± 25.18      Moderate 47.35 ± 71.86   18.83 ± 9.85   VEGF = Vascular endothelial growth factor; hCG = human chorionic gonadotropin; SD = standard deviation Median follow-up time was 43 ± 27 months. Recurrence was observed in 7.5% and death in 11.5% of patients. Disease-free survival (DFS) at 2 and 5 years was 93.7% (95% CI, 88–98) and 83% (95% CI, 68–98), respectively. By analyzing DFS-related factors, only high international risk correlated with worse prognosis (p = 0.005). VD and VEGF expression were not associated with recurrence. Discussion hCG is considered an extremely sensitive and specific marker of germ cell testicular tumors. Its increased serum levels usually correlate with the existence of viable cancer cells and it is often associated with disease progression, recurrence, and a worse prognosis [7, 21, 22].

2002, 2005, 2011; Perski 2006). However, while one longitudinal study found that performance-based self-esteem was related to subsequent burnout (Blom 2012), another longitudinal study could not confirm

this association (Dahlin and Runeson 2007). To the best of our knowledge, Talazoparib a reversed causation has not been studied yet. Theoretically, the relationship between experienced imbalance between work and family demands and emotional exhaustion can be explained through the loss spiral assumption that is posed in the conservation of resources (COR) theory (Hobfoll 1989). According to this theory, a vicious circle with regard to the loss of resources is assumed, which is called the spiral loss hypothesis. Employees who may perceive a loss of resources in one domain (e.g. due to high work demands) are more likely to experience other subsequent resource losses in other domains (e.g. family domain, resulting in work–family conflict).

Over time less and less resources become available to deal with potential stressors, which can result in emotional exhaustion. This theory is also suitable to explain the relationship between performance-based self-esteem and work–family conflict. In order to maintain self-esteem, maximum effort and resources (i.e. time and energy) are invested in the work domain, which leads to a depletion of resources that otherwise could have been used in the non-work domain. Conflicts between the work and the family role might be especially stressful for individuals that value and need the work role for their feelings of self-worth (Innstrand et Smoothened inhibitor al. 2010). It can be speculated that individuals with high performance-based self-esteem have a need to perform well in both the work and the family sphere, which is likely to increase feelings of stress and deficiency. Stress in turn

may lead to feelings of conflict or imbalance. Also in the case of a potential relationship between performance-based self-esteem and emotional exhaustion, the COR theory’s spiral loss hypothesis could provide a useful theoretical explanation. The vulnerability through emotional exhaustion could make employees more sensitive to stress and the striving to maintain their self-worth through achievements in the work domain more dominant, which Y-27632 2HCl then increases performance-based self-esteem. Moreover, emotional exhaustion, which makes it harder to accomplish work, might be especially stressful for employees basing their self-esteem mainly on their work performance and evolving feelings of insufficiency might increase striving for success even more. Although in Sweden the labour market participation is more similar for men and women compared with other European countries (Eurostat 2010), there is still an imbalance in the distribution of family-related responsibilities.

Evaluating ulceration factor in S-subgroups 56% of S1, 40% of S2 and 83% of S3 patients had ulcerated lesions. Among the 11 patients who died for melanoma metastasis the ulceration factor was present in 9 (81%). It is interesting to note that inside the group of died patients 6 (55%) were classified as S3, 2 (18%) as S2 and 3 (27%) as S1. The analysis of S1 dead patients revealed that everyone presented peculiar characteristics: one patient had two different SLN compromised, another patient presented severe ulceration of the primary lesion, while the third patient had an high Breslow thickness, nodular type, primary

melanoma. These results outline the relevance of clinical biomarkers that can be useful, in correlation to the histological markers, to predict S1 patients clinical outcome. It should be reported,

that Reeves et al. [26] proposed the ratio size of metastases on SLN/ulceration (S/U score) as predictor factor of NSLNs status, LXH254 price while Frankel et al. [27] utilized the relation between the thickness of primary tumour and the surface area, measured in percentage, of the metastases on SLN. According with previous studies [2, 14, 16, 17, 27] and the recent study of Nagaraja [38], where it is shown a very accurate and extensive meta-analysis involving several predictive factors to determine the risk of lymph node metastasis, our data confirmed that about 20% of SLN positive patients undergone CLND present an additional Alisertib cell line lymphatic involvement. At the moment, according to the staging guidelines of the American Joint Committee on Cancer (AJCC) the most important prognostic factor in patients affected by melanoma is the SLN Orotic acid status [28–31]. The current standard treatment for SLN positive patients is the completion lymphatic node dissection. Within the last few years, several studies have been conducted to determine whether some patients could be classified as low risk of further nodal metastasis according to the type of involvement of the SLN. Furthermore, the overall

data published [11, 16, 21, 29] and the present study evidenced that the prognosis of patients is determined not only by the presence of melanoma cells in SLNs but also by a micro-morphometric characterization of SLNs according to the Starz classification. On these bases some Authors suggested the possibility to avoid the CLND to a subgroup of selected patients [30–34]. Already in few centres, patients with SLN tumour deposits <0.1mm in maximal dimension can choose if undergo CLND or clinical nodal follow-up [16, 18, 33–38]. In our report, using univariate analysis, we confirmed the prognostic relevance of Starz classification suggesting that patients classified as S1 could safely spare to the CLND. None of S1 patients presented CLND positivity, suggesting that the increased morbidity associated with complete nodal dissection could be avoided in this group of patients.

No obvious integrase genes are encoded by ϕE12-2, GI15, or PI-E264-2, which suggests these subgroup B Myoviridae use a different mechanism Bcr-Abl inhibitor of integration. Mu-like phages The ϕE255 genome shares ~ 90% nucleotide sequence identity with the genome of BcepMu, a Mu-like bacteriophage spontaneously

produced by Burkholderia cenocepacia strain J2315 [29]. Similar to BcepMu, the ϕE255 genome can be divided into functional clusters from the left end to the right end of the linear phage genome: replication and regulation, host lysis, head assembly, and tail assembly (Fig. 1D). ϕE255 encodes a transposase with a Rve integrase domain (gp40, PFAM PF00665) that allows transposition as a mechanism of replication. Following replicative transposition, DNA is packaged into the bacteriophage heads using a pac site at the left end of the bacteriophage genome which allows 200-2,000 bp of flanking host DNA to also be packaged [29]. The genomic Selleckchem GSI-IX sequence of ϕE255 (accession number NC_009237) contains 467 bp of host DNA sequence (Bm ATCC23344). The left and right ends of the linear ϕE255 genome contain 23-bp imperfect direct repeats that could be recognized by gp40 during replicative transposition (Fig. 1D). These repeats are similar to those found at the ends of the BcepMu genome [29] and the nucleotide differences are underlined in Fig. 1D. Three regions

of the ϕE255 genome are not present in the BcepMu genome and appear to be ϕE255-specific (gray shading in Fig. 1D). The unique regions are found at the left and right ends of the ϕE255 genome, which is consistent with the location Urease of unique sequences in BcepMu and other BcepMu-like prophages [29]. The two unique genes on the left side of the bacteriophage genome, gene41 and gene46, encode a conserved hypothetical protein and a lambda C1 repressor-like transcriptional regulator, respectively (Fig. 1D). These proteins are presumably involved in ϕE255 activation and/or replication. Five unique

genes are encoded on the extreme right end of the ϕE255 genome, including genes 26-30 (Fig. 1D). Gp26 encodes a putative tail fiber protein which presumably is required for attachment and probably provides host receptor specificity to this bacteriophage. It is interesting that this gene, and the downstream tail assembly chaperone protein (gp27), are the only tail assembly genes that are not conserved in BcepMu. This suggests that the BcepMu receptor(s) on B. cenocepacia is distinct from the ϕE255 receptor(s) on B. thailandensis and B. mallei. Furthermore, it suggests that the unique tail fiber protein and a tail assembly chaperone protein (gp27) were either acquired by ϕE255 via horizontal transfer or lost by BcepMu. Gp28 is a hypothetical protein with no functional prediction, but gp29 is a putative ABC (ATP-binding cassette) transporter protein (Fig. 1D). It is possible that ϕE255 gp29 is involved in the import of a nutrient or export of toxic metabolites that confers a selective advantage on the lysogen harboring it.

Leitner T, Korber B, Daniels M, Calef C, Foley B: HIV-1 subtype and circulating recombinant form (CRF) reference sequences, 2005. HIV sequence compendium 2005, 2005:41–48. 52. Carr JK, Foley BT, Leitner T, Salminen M, Korber B, McCutchan F: Reference sequences representing the principle genetic diversity of HIV-1 in the Pandemic. In Human retroviruses and AIDS 1998. Volume III. Edited by: Korber B, Kuiken CL, Foley B, Hahn B, McCutchan F, Mellors JW, Sodroski J. Los Alamos, NM: Theoretical Biology

and Biophysics Group, Los Alamos National Laboratory; 1998:10–19. 53. Robertson DL, MM-102 research buy Anderson JP, Bradac JA, Carr JK, Foley B, Funkhouser RK, Gao F, Hahn BH, Kuiken C, Learn GH, Leitner T, McCutchan F, Osmanov S, Peeters M, Pieniazek D, Kalish ML, Salminen M, Sharp PM, Wolinsky S, Korber B: HIV-1 nomenclature proposal. In Human Retroviruses and AIDS 1999. Edited by: Kuiken CL, Foley B, Hahn B, Korber B, McCutchan F, Marx PA, Mellors JW, Mullins JI, Sodroski

J, Wolinsky S. Los Alamos, NM: Theoretical Biology and Biophysics Group, Los Alamos National Laboratory; 1999:492–505. 54. Kuiken C, see more Korber B, Shafer RW: HIV sequence databases. AIDS reviews 2003,5(1):52–61.PubMed 55. Davies MN, Guan P, Blythe MJ, Salomon J, Toseland CP, Hattotuwagama C, Walshe V, Doytchinova IA, Flower DR: Using databases and data mining in vaccinology. Expert Opinion on Drug Discovery 2007,2(1):19–35.CrossRef 56. Frahm N, Linde C, Brander C: Identification of HIV-derived, HLA class I restricted CTL epitopes: insights into TCR repertoire, CTL escape and viral fitness. HIV molecular immunology 2006, 2007:3–28. 57. Korber B, Gnanakaran S: The implications of patterns in HIV diversity for neutralizing antibody induction and susceptibility. Current Opinion in HIV and AIDS 2009,4(5):408–417.PubMedCrossRef 58. Zolla-Pazner S, Cardozo T: Structure-function relationships of HIV-1 envelope sequence-variable ALOX15 regions refocus vaccine design. Nature Reviews Immunology 2010,10(7):527–535.PubMedCrossRef 59. Sette A, Peters B: Immune epitope mapping in the post-genomic era: lessons for vaccine development. Curr Opin Immunol 2007,19(1):106–110.PubMedCrossRef

60. Malherbe L: T-cell epitope mapping. Annals of Allergy, Asthma and Immunology 2009,103(1):76–79.CrossRef 61. Gorny MK, Gianakakos V, Sharpe S, Zolla-Pazner S: Generation of human monoclonal antibodies to human immunodeficiency virus. Proceedings of the National Academy of Sciences 1989,86(5):1624–1628.CrossRef 62. Grimison B, Laurence J: Immunodominant epitope regions of HIV-1 reverse transcriptase: correlations with HIV-1 serum IgG inhibitory to polymerase activity and with disease progression. JAIDS J Acquired Immune Defic Syndromes 1995,9(1):58–68. 63. Kanduc D, Serpico R, Lucchese A, Shoenfeld Y: Correlating low-similarity peptide sequences and HIV B-cell epitopes. Autoimmun Rev 2008,7(4):291–296.PubMedCrossRef 64.

3B)). The complemented ΔluxS Hp + cells were similar to wild-type, with nearly all cells possessing 3-4 normal long flagella at least one pole (95% ± 3%, n = 3) (Figure. 3C). Addition of DPD to ΔluxS Hp cells also converted them to a wild-type morphology, with the vast majority producing 3-4 wild-type length flagella usually present at a single pole (95% ± 3%, n = 3) (Figure. 3E). Addition of DPD to wild-type cells had little significant effect with check details nearly all remaining flagellate as before (95% ± 3%, n = 3) although more cells were seen with

a flagellum at both poles (Figure. 3D). Addition of DPD to the ΔluxS Hp + cells had a similar effect, with more cells with flagella at both poles (Figure. 3F). Figure 3 luxS Hp /DPD modulates flagellar morphogenesis. H. pylori cells were co-cultured with AGS cells. Cells were stained with 0.5% photungstate (PTA). Scale bars represent 2 μm. (A) wild-type, (B) ΔluxS Hp, (C) ΔluxS Hp +, (D) wild-type with DPD, (E) ΔluxS Hp with DPD and (F) ΔluxS Hp + with DPD. DPD was added after 10 h of incubation and once again after 18 h of incubation during co-cultures. Mutation of luxS Hp resulted in the decreased production of flagellar proteins FlaA and FlgE The reduced number and length of flagella in ΔluxS Hp cells

observed by electron microscopy could emanate from a number of different changes in the proteome. As previous work had suggested possible involvement of major flagella proteins, we investigated these first by immunoblotting whole

cell lysates. Cell lysates were adjusted so that protein from equivalent numbers see more of bacteria was loaded (see Materials and Methods), and probed with anti-flagellin (FlaA and FlaB) and anti-FlgE (hook protein) antiserum (Figure. 4). In practice, FlaB levels were very similar between all wild-type and mutant strains and were not shown to vary in our subsequent transcription analysis. Our main aim here was Cell Penetrating Peptide to compare ratios of flagella proteins between wild-types and mutants, so we expressed results of other flagella proteins (FlaA and FlgE) relative to FlaB levels within each strain. H. pylori wild-type 17874, and derived mutants (ΔflaA and ΔflgE) were used as positive and negative controls, respectively. In our experiments, four repetitions were included, when the reflective density (RD) of each protein band was measured using Quantity One 4.6.5 software (Biorad). Figure 4 Mutation of luxS Hp causes altered flagellin and hook protein production. Cell lysates of the strains indicated were subjected to immunoblotting with anti-flagellin (FlaA and FlaB) and anti-hook protein (FlgE) together [32]. The proteins were measured in wild-type, ΔluxS Hp, ΔluxS Hp + cultures grown in Brucella broth at 37°C for 24 h. H. pylori strain 17874 wild-type [29] served as the positive control.

For Gam complementation, E. coli C and E. coli C ∆agaS harboring the indicated plasmids were streaked out on Gam MOPS minimal agar plate with NH4Cl (B) and containing ampicillin and incubated at 30°C for 96 h. The strains with selleck various plasmids in the different sectors of the plates in A and B are shown below in C and and D, respectively. The panel on the right (E) describes the various plasmids used for complementation of ∆agaS mutants and summarizes the results from the plates (A and B). The

complementation results of EDL933 ∆agaS/pJFagaBDC are not shown in plates A and B. The agaS gene codes for Gam-6-P deaminase/isomerase Since agaI is not involved in the Aga/Gam pathway, the only step in the Aga/Gam pathway that does not have a gene assigned to it is the deamination and selleck screening library isomerization of Gam-6-P to tagatose-6-P. On the other hand, the agaS gene is the only gene that has not been linked to any step in the Aga/Gam pathway [1, 6]. It has been inferred that since the promoter specific for agaS is repressed by AgaR and agaS is inducible by Aga and Gam, AgaS must be involved in the catabolism

of Aga and Gam [11]. Our results with the ∆agaS mutants confirm this (Figure 7). The agaS gene is homologous to the C-terminal domain of GlcN-6-P synthase (GlmS) that has the ketose-aldose isomerase activity but does not have the N-terminal domain of GlmS that binds to glutamine [1]. The C-terminal domain of GlmS is found in a wide range of proteins that are involved in phosphosugar isomerization and therefore this has been named as the sugar isomerase (SIS) domain [22]. This SIS domain that is in AgaS has been shown to be present in prokaryotic, archaebacterial, and eukaryotic proteins [22]. Interestingly, a novel archaeal GlcN-6-P-deaminase which has been demonstrated to have deaminase activity is related to the isomerase

domain of GlmS and has the SIS domain [23]. Proteins with SIS domains have been classified in the Cluster of Orthologous Montelukast Sodium Group of proteins as COG222. It was proposed by Tanaka and co-workers that although AgaI has sequence homology to nagB encoded GlcNAc-6-P deaminase/isomerase and has been predicted to be the Gam-6-P deaminase/isomerase, AgaS which belongs to COG222 could be an additional Gam-6-P deaminase [23]. Based on these reports and our findings that neither agaI nor nagB has a role in Aga and Gam utilization, we propose that agaS codes for Gam-6-P deaminase/isomerase. In light of this proposal that agaS codes for Gam-6-P deaminase/isomerase, we tested if pJFnagB would complement E. coli C ∆agaS mutant for growth on Aga and similarly if pJFagaS would complement E. coli C ∆nagB mutant for growth on GlcNAc. In both cases, no complementation was observed even with 10, 50, and 100 μM IPTG (data not shown).