Molecular and Functional Characterization of Dihydrofolate Synthetase and Three Isoforms of Folylpolyglutamate Synthetase in Arabidopsis Thaliana
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Folic Acid Antagonists: Antimicrobial and Immunomodulating Mechanisms and Applications
International Journal of Molecular Sciences Review Folic Acid Antagonists: Antimicrobial and Immunomodulating Mechanisms and Applications Daniel Fernández-Villa 1, Maria Rosa Aguilar 1,2 and Luis Rojo 1,2,* 1 Instituto de Ciencia y Tecnología de Polímeros, Consejo Superior de Investigaciones Científicas, CSIC, 28006 Madrid, Spain; [email protected] (D.F.-V.); [email protected] (M.R.A.) 2 Consorcio Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, 28029 Madrid, Spain * Correspondence: [email protected]; Tel.: +34-915-622-900 Received: 18 September 2019; Accepted: 7 October 2019; Published: 9 October 2019 Abstract: Bacterial, protozoan and other microbial infections share an accelerated metabolic rate. In order to ensure a proper functioning of cell replication and proteins and nucleic acids synthesis processes, folate metabolism rate is also increased in these cases. For this reason, folic acid antagonists have been used since their discovery to treat different kinds of microbial infections, taking advantage of this metabolic difference when compared with human cells. However, resistances to these compounds have emerged since then and only combined therapies are currently used in clinic. In addition, some of these compounds have been found to have an immunomodulatory behavior that allows clinicians using them as anti-inflammatory or immunosuppressive drugs. Therefore, the aim of this review is to provide an updated state-of-the-art on the use of antifolates as antibacterial and immunomodulating agents in the clinical setting, as well as to present their action mechanisms and currently investigated biomedical applications. Keywords: folic acid antagonists; antifolates; antibiotics; antibacterials; immunomodulation; sulfonamides; antimalarial 1. -
1 SUPPLEMENTARY DATA Table S1
Electronic Supplementary Material (ESI) for Food & Function. This journal is © The Royal Society of Chemistry 2020 SUPPLEMENTARY DATA Table S1: Effects of catalase, protease, papain and pH treatments on the antimicrobial activity (%) of the CFS of S. thermophilus strain against G. vaginalis ATCC 14018. The antimicrobial activity of the strain was highest under acidic pH conditions. Remaining antimicrobial activity (%) Strains 5 mg mL-1 1 mg mL-1 1 mg mL-1 pH treatments catalase proteinase K papain 3.5 4.0 5.0 6.0 6.5 7.0 S. thermophilus KLDS 3.1003 90.49±0.62 100±0 100±0 100±0 100±0 67.02±0.08 6.35±0.03 0±0 0±0 All values were determined in triplicate Values were expressed as mean ± SD 1 Table S2: Weekly weights of study animals before and after S. aureus ATCC25923 infection. Significant variations (at P > 0.05) were observed in the weight of study animals during the study. Period C C C C Week 0 22.00b 23.57b 19.34e 23.24a 20.90d 22.84c 20.19d 22.60b 23.92a 23.70b 20.56c 23.78a 20.89d 23.10c 20.00d 23.51a Average 22.43 23.30 20.02 23.28 SD 1.29 0.40 0.51 0.51 C TST TSA TSTSA 24.92a 24.15a 21.19c 20.98c Week 1 23.34a 23.13c 20.26d 22.68b 21.98b 22.96d 20.85c 22.86b 22.60b 22.36d 24.28a 22.33b Average 23.21 23.15 21.65 22.21 SD 1.27 0.74 1.80 0.86 23.25a 24.28a 19.94d 20.39d Week 2 21.32c 22.09e 18.46f 20.35d 20.29d 21.82e 19.40e 16.68e 21.27c 22.89d 22.74b 20.09d Average 21.53 22.77 20.14 19.38 SD 1.24 1.10 1.84 1.80 Values with the same alphabet along the same column are not significantly different (P > 0.05) Composition of control and trial diets are given in Table 1. -
Roles of Vitamin Metabolizing Genes in Multidrug-Resistant Plasmids of Superbugs
bioRxiv preprint doi: https://doi.org/10.1101/285403; this version posted March 20, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Roles of Vitamin Metabolizing Genes in Multidrug-Resistant Plasmids of Superbugs Asit Kumar Chakraborty, Genetic Engineering Laboratory, Department of Biotechnology & Biochemistry, Oriental Institute of Science & Technology, Vidyasagar University, Midnapore 721102, West Bengal, India. Abstract Superbug crisis has rocked this world with million deaths due to failure of potent antibiotics. Thousands mdr genes with hundreds of mutant isomers are generated. Small integrons and R-plasmids have combined with F'-plasmids creating a space for >10-20 of mdr genes that inactivate antibiotics in different mechanisms. Mdr genes are created to save bacteria from antibiotics because gut microbiota synthesize >20 vitamins and complex bio-molecules needed for >30000 biochemical reactions of human metabolosome. In other words, mdr gene creation is protected from both sides, intestinal luminal cells and gut bacteria in a tight symbiotic signalling system. We have proposed, to avert the crisis all vitamin metabolizing genes will be acquired in MDR- plasmids if we continue oral antibiotics therapy. Therefore, we have checked the plasmid databases and have detected thiamine, riboflavin, folate, cobalamine and biotin metabolizing enzymes in MDR plasmids. Thus vit genes may mobilise recently into MDR-plasmids and are likely essential for gut microbiota protection. Analysis found that cob and thi genes are abundant and likely very essential than other vit genes. -
Letters to Nature
letters to nature Received 7 July; accepted 21 September 1998. 26. Tronrud, D. E. Conjugate-direction minimization: an improved method for the re®nement of macromolecules. Acta Crystallogr. A 48, 912±916 (1992). 1. Dalbey, R. E., Lively, M. O., Bron, S. & van Dijl, J. M. The chemistry and enzymology of the type 1 27. Wolfe, P. B., Wickner, W. & Goodman, J. M. Sequence of the leader peptidase gene of Escherichia coli signal peptidases. Protein Sci. 6, 1129±1138 (1997). and the orientation of leader peptidase in the bacterial envelope. J. Biol. Chem. 258, 12073±12080 2. Kuo, D. W. et al. Escherichia coli leader peptidase: production of an active form lacking a requirement (1983). for detergent and development of peptide substrates. Arch. Biochem. Biophys. 303, 274±280 (1993). 28. Kraulis, P.G. Molscript: a program to produce both detailed and schematic plots of protein structures. 3. Tschantz, W. R. et al. Characterization of a soluble, catalytically active form of Escherichia coli leader J. Appl. Crystallogr. 24, 946±950 (1991). peptidase: requirement of detergent or phospholipid for optimal activity. Biochemistry 34, 3935±3941 29. Nicholls, A., Sharp, K. A. & Honig, B. Protein folding and association: insights from the interfacial and (1995). the thermodynamic properties of hydrocarbons. Proteins Struct. Funct. Genet. 11, 281±296 (1991). 4. Allsop, A. E. et al.inAnti-Infectives, Recent Advances in Chemistry and Structure-Activity Relationships 30. Meritt, E. A. & Bacon, D. J. Raster3D: photorealistic molecular graphics. Methods Enzymol. 277, 505± (eds Bently, P. H. & O'Hanlon, P. J.) 61±72 (R. Soc. Chem., Cambridge, 1997). -
Product Sheet Info
Master Clone List for NR-19279 ® Vibrio cholerae Gateway Clone Set, Recombinant in Escherichia coli, Plates 1-46 Catalog No. NR-19279 Table 1: Vibrio cholerae Gateway® Clones, Plate 1 (NR-19679) Clone ID Well ORF Locus ID Symbol Product Accession Position Length Number 174071 A02 367 VC2271 ribD riboflavin-specific deaminase NP_231902.1 174346 A03 336 VC1877 lpxK tetraacyldisaccharide 4`-kinase NP_231511.1 174354 A04 342 VC0953 holA DNA polymerase III, delta subunit NP_230600.1 174115 A05 388 VC2085 sucC succinyl-CoA synthase, beta subunit NP_231717.1 174310 A06 506 VC2400 murC UDP-N-acetylmuramate--alanine ligase NP_232030.1 174523 A07 132 VC0644 rbfA ribosome-binding factor A NP_230293.2 174632 A08 322 VC0681 ribF riboflavin kinase-FMN adenylyltransferase NP_230330.1 174930 A09 433 VC0720 phoR histidine protein kinase PhoR NP_230369.1 174953 A10 206 VC1178 conserved hypothetical protein NP_230823.1 174976 A11 213 VC2358 hypothetical protein NP_231988.1 174898 A12 369 VC0154 trmA tRNA (uracil-5-)-methyltransferase NP_229811.1 174059 B01 73 VC2098 hypothetical protein NP_231730.1 174075 B02 82 VC0561 rpsP ribosomal protein S16 NP_230212.1 174087 B03 378 VC1843 cydB-1 cytochrome d ubiquinol oxidase, subunit II NP_231477.1 174099 B04 383 VC1798 eha eha protein NP_231433.1 174294 B05 494 VC0763 GTP-binding protein NP_230412.1 174311 B06 314 VC2183 prsA ribose-phosphate pyrophosphokinase NP_231814.1 174603 B07 108 VC0675 thyA thymidylate synthase NP_230324.1 174474 B08 466 VC1297 asnS asparaginyl-tRNA synthetase NP_230942.2 174933 B09 198 -
Supplementary Information
Supplementary information (a) (b) Figure S1. Resistant (a) and sensitive (b) gene scores plotted against subsystems involved in cell regulation. The small circles represent the individual hits and the large circles represent the mean of each subsystem. Each individual score signifies the mean of 12 trials – three biological and four technical. The p-value was calculated as a two-tailed t-test and significance was determined using the Benjamini-Hochberg procedure; false discovery rate was selected to be 0.1. Plots constructed using Pathway Tools, Omics Dashboard. Figure S2. Connectivity map displaying the predicted functional associations between the silver-resistant gene hits; disconnected gene hits not shown. The thicknesses of the lines indicate the degree of confidence prediction for the given interaction, based on fusion, co-occurrence, experimental and co-expression data. Figure produced using STRING (version 10.5) and a medium confidence score (approximate probability) of 0.4. Figure S3. Connectivity map displaying the predicted functional associations between the silver-sensitive gene hits; disconnected gene hits not shown. The thicknesses of the lines indicate the degree of confidence prediction for the given interaction, based on fusion, co-occurrence, experimental and co-expression data. Figure produced using STRING (version 10.5) and a medium confidence score (approximate probability) of 0.4. Figure S4. Metabolic overview of the pathways in Escherichia coli. The pathways involved in silver-resistance are coloured according to respective normalized score. Each individual score represents the mean of 12 trials – three biological and four technical. Amino acid – upward pointing triangle, carbohydrate – square, proteins – diamond, purines – vertical ellipse, cofactor – downward pointing triangle, tRNA – tee, and other – circle. -
The Metabolic Building Blocks of a Minimal Cell Supplementary
The metabolic building blocks of a minimal cell Mariana Reyes-Prieto, Rosario Gil, Mercè Llabrés, Pere Palmer and Andrés Moya Supplementary material. Table S1. List of enzymes and reactions modified from Gabaldon et. al. (2007). n.i.: non identified. E.C. Name Reaction Gil et. al. 2004 Glass et. al. 2006 number 2.7.1.69 phosphotransferase system glc + pep → g6p + pyr PTS MG041, 069, 429 5.3.1.9 glucose-6-phosphate isomerase g6p ↔ f6p PGI MG111 2.7.1.11 6-phosphofructokinase f6p + atp → fbp + adp PFK MG215 4.1.2.13 fructose-1,6-bisphosphate aldolase fbp ↔ gdp + dhp FBA MG023 5.3.1.1 triose-phosphate isomerase gdp ↔ dhp TPI MG431 glyceraldehyde-3-phosphate gdp + nad + p ↔ bpg + 1.2.1.12 GAP MG301 dehydrogenase nadh 2.7.2.3 phosphoglycerate kinase bpg + adp ↔ 3pg + atp PGK MG300 5.4.2.1 phosphoglycerate mutase 3pg ↔ 2pg GPM MG430 4.2.1.11 enolase 2pg ↔ pep ENO MG407 2.7.1.40 pyruvate kinase pep + adp → pyr + atp PYK MG216 1.1.1.27 lactate dehydrogenase pyr + nadh ↔ lac + nad LDH MG460 1.1.1.94 sn-glycerol-3-phosphate dehydrogenase dhp + nadh → g3p + nad GPS n.i. 2.3.1.15 sn-glycerol-3-phosphate acyltransferase g3p + pal → mag PLSb n.i. 2.3.1.51 1-acyl-sn-glycerol-3-phosphate mag + pal → dag PLSc MG212 acyltransferase 2.7.7.41 phosphatidate cytidyltransferase dag + ctp → cdp-dag + pp CDS MG437 cdp-dag + ser → pser + 2.7.8.8 phosphatidylserine synthase PSS n.i. cmp 4.1.1.65 phosphatidylserine decarboxylase pser → peta PSD n.i. -
Program Bound to Inspire
A PROGRAM BOUND TO INSPIRE Held in conjunction with Conference Program Feeling lucky? Stop by the ASBMB booth #1421 for your chance to win one of three $250 Amazon gift cards. To participate in the contest, you must update your ASBMB member profile or join the society for the first time. WWW.ASBMB.ORG Table of Contents 2 At-a-glance 10 Sunday oral program 20 Monday oral program 30 Tuesday oral program 39 Poster sessions Program at-a-glance At-a-glance Saturday April 6 Time Location Event Convention Center 8:30 AM – 4:30 PM ASBMB Graduate Student and Postdoctoral Researcher Travel W307ABC Awardee Career Development Event Convention Center 11:30 AM – 12:00 PM ASBMB Annual Meeting Orientation for Undergraduate W306AB Students Convention Center 11:30 AM – 6:00 PM ASBMB Undergraduate Poster Competition Judges' W303ABC Orientation Convention Center 1:00 PM – 4:30 PM W304 ASBMB Undergraduate Student Research Poster Competition Convention Center 1:15 PM – 2:45 PM Career Development Workshop for Grads and Postdocs: W305A Networking Skills Convention Center 1:15 PM – 2:45 PM Career Development Workshop for Grads and Postdocs: W307D Constructing Your Elevator Pitch Convention Center 1:15 PM – 2:45 PM Career Development Workshop for Grads and Postdocs: W305B Practical Tools for Navigating Your Career Path Evolution Convention Center 4:45 PM – 5:45 PM ASBMB Undergraduate Workshop: Exploring Careers Speed W306AB Networking Convention Center 7:00 PM – 8:30 PM Valencia Ballroom EB Welcome Reception with Science Outreach Poster Session ABCD GRANT WRITING WORKSHOP June 13–15 • Washington, D.C. -
Supplementary Informations SI2. Supplementary Table 1
Supplementary Informations SI2. Supplementary Table 1. M9, soil, and rhizosphere media composition. LB in Compound Name Exchange Reaction LB in soil LBin M9 rhizosphere H2O EX_cpd00001_e0 -15 -15 -10 O2 EX_cpd00007_e0 -15 -15 -10 Phosphate EX_cpd00009_e0 -15 -15 -10 CO2 EX_cpd00011_e0 -15 -15 0 Ammonia EX_cpd00013_e0 -7.5 -7.5 -10 L-glutamate EX_cpd00023_e0 0 -0.0283302 0 D-glucose EX_cpd00027_e0 -0.61972444 -0.04098397 0 Mn2 EX_cpd00030_e0 -15 -15 -10 Glycine EX_cpd00033_e0 -0.0068175 -0.00693094 0 Zn2 EX_cpd00034_e0 -15 -15 -10 L-alanine EX_cpd00035_e0 -0.02780553 -0.00823049 0 Succinate EX_cpd00036_e0 -0.0056245 -0.12240603 0 L-lysine EX_cpd00039_e0 0 -10 0 L-aspartate EX_cpd00041_e0 0 -0.03205557 0 Sulfate EX_cpd00048_e0 -15 -15 -10 L-arginine EX_cpd00051_e0 -0.0068175 -0.00948672 0 L-serine EX_cpd00054_e0 0 -0.01004986 0 Cu2+ EX_cpd00058_e0 -15 -15 -10 Ca2+ EX_cpd00063_e0 -15 -100 -10 L-ornithine EX_cpd00064_e0 -0.0068175 -0.00831712 0 H+ EX_cpd00067_e0 -15 -15 -10 L-tyrosine EX_cpd00069_e0 -0.0068175 -0.00233919 0 Sucrose EX_cpd00076_e0 0 -0.02049199 0 L-cysteine EX_cpd00084_e0 -0.0068175 0 0 Cl- EX_cpd00099_e0 -15 -15 -10 Glycerol EX_cpd00100_e0 0 0 -10 Biotin EX_cpd00104_e0 -15 -15 0 D-ribose EX_cpd00105_e0 -0.01862144 0 0 L-leucine EX_cpd00107_e0 -0.03596182 -0.00303228 0 D-galactose EX_cpd00108_e0 -0.25290619 -0.18317325 0 L-histidine EX_cpd00119_e0 -0.0068175 -0.00506825 0 L-proline EX_cpd00129_e0 -0.01102953 0 0 L-malate EX_cpd00130_e0 -0.03649016 -0.79413596 0 D-mannose EX_cpd00138_e0 -0.2540567 -0.05436649 0 Co2 EX_cpd00149_e0 -
Vitamin Biosynthesis As an Antifungal Target
Journal of Fungi Review Vitamin Biosynthesis as an Antifungal Target Zohar Meir and Nir Osherov * Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel-Aviv University, Ramat-Aviv, Tel-Aviv 69978, Israel; [email protected] * Correspondence: [email protected]; Tel.: +972-3-640-9599; Fax: +972-3-640-9160 Received: 29 May 2018; Accepted: 13 June 2018; Published: 17 June 2018 Abstract: The large increase in the population of immunosuppressed patients, coupled with the limited efficacy of existing antifungals and rising resistance toward them, have dramatically highlighted the need to develop novel drugs for the treatment of invasive fungal infections. An attractive possibility is the identification of possible drug targets within essential fungal metabolic pathways not shared with humans. Here, we review the vitamin biosynthetic pathways (vitamins A–E, K) as candidates for the development of antifungals. We present a set of ranking criteria that identify the vitamin B2 (riboflavin), B5 (pantothenic acid), and B9 (folate) biosynthesis pathways as being particularly rich in new antifungal targets. We propose that recent scientific advances in the fields of drug design and fungal genomics have developed sufficiently to merit a renewed look at these pathways as promising sources for the development of novel classes of antifungals. Keywords: antifungals; fungal vitamin metabolism; drug target; essential genes 1. Introduction The number of life-threatening fungal infections has risen dramatically over the last twenty years. Recent estimates have identified a global burden of almost two million patients with systemic and invasive fungal infections, including ~700,000 cases of invasive candidiasis, ~500,000 cases of Pneumocystis jirovecii pneumonia, ~250,000 cases of invasive aspergillosis, ~220,000 cases of cryptococcal meningitis, and ~100,000 cases of disseminated histoplasmosis [1,2]. -
Table 4. V. Cholerae Flexgene ORF Collection
Table 4. V. cholerae FLEXGene ORF collection Reference Clone protein PlasmID clone GenBank Locus tag Symbol accession identifier FLEX clone name accession Product name VC0001 NP_062585 VcCD00019918 FLH200476.01F DQ772770 hypothetical protein VC0002 mioC NP_062586 VcCD00019938 FLH200506.01F DQ772771 mioC protein VC0003 thdF NP_062587 VcCD00019958 FLH200531.01F DQ772772 thiophene and furan oxidation protein ThdF VC0004 yidC NP_062588 VcCD00019970 FLH200545.01F DQ772773 inner membrane protein, 60 kDa VC0005 NP_062589 VcCD00061243 FLH236482.01F DQ899316 conserved hypothetical protein VC0006 rnpA NP_062590 VcCD00025697 FLH214799.01F DQ772774 ribonuclease P protein component VC0007 rpmH NP_062591 VcCD00061229 FLH236450.01F DQ899317 ribosomal protein L34 VC0008 NP_062592 VcCD00019917 FLH200475.01F DQ772775 amino acid ABC transporter, ATP-binding protein VC0009 NP_062593 VcCD00019966 FLH200540.01F DQ772776 amino acid ABC transproter, permease protein VC0010 NP_062594 VcCD00019152 FLH199275.01F DQ772777 amino acid ABC transporter, periplasmic amino acid-binding portion VC0011 NP_062595 VcCD00019151 FLH199274.01F DQ772778 hypothetical protein VC0012 dnaA NP_062596 VcCD00017363 FLH174286.01F DQ772779 chromosomal DNA replication initiator DnaA VC0013 dnaN NP_062597 VcCD00017316 FLH174063.01F DQ772780 DNA polymerase III, beta chain VC0014 recF NP_062598 VcCD00019182 FLH199319.01F DQ772781 recF protein VC0015 gyrB NP_062599 VcCD00025458 FLH174642.01F DQ772782 DNA gyrase, subunit B VC0016 NP_229675 VcCD00019198 FLH199346.01F DQ772783 hypothetical protein -
Supplemental Material-PDF
List of supplementary tables and figures. Table S1 – Strains sequenced and assembly information (n=72) Table S2 – Genetic clusters obtained using BAPS Table S3 – Genes commonly found to be under positive selection in the three subspecies (n=14) Table S4 - Recombining genes in X. fastidiosa subsp. pauca strains 9a5c and U24D (Citrus) Table S5 – Recombination genes for X. fastidiosa 32 (Coffee) Table S6 - Genes found to be under selection in each subspecies Table S7 – Recombining genes for each X. fastidiosa subspecies Table S8 – Genes found in the accessory genome of each subspecies Figure S1 - Phylogeny of X. fastidiosa strains (n=72) and pan-genome visualization Figure S2 - Detection of temporal signal in the dataset Figure S3 - Rate comparison amongst subspecies. The boxplot (A) was constructed my merging the rate of evolution of each branch (internal and external) of the X. fastidiosa subsp. fastidiosa, pauca and multiplex clades together (obtained though rate-dating) as illustrated by the colored frames (B) Figure S4 - Comparison between clonalFrameML and FastGEAR. (A) ClonalFrameML output, (B) FastGEAR output, (C) comparison between the genes found to be recombining between the two algorithms that were mapped to the X. fastidiosa reference genome Table S1 – Strains sequenced and assembly information (n=72). Strain names in parentheses represent synonyms. Name N50 L50 Total length Country Host Subspecies Isolation date Accession CO33 176,135 6 2,681,926 Italy Coffea arabica ? 2015 SAMN04100274 MUL0034 2,642,186 1 2,666,577 USA Morus alba morus 2003 SAMN03081485 Mul-MD 134,146 6 2,520,555 USA Morus alba morus 2011 SAMN02630185 Ann-1 44,355 22 2,729,755 USA Nerium oleander sandyi SAMN03081476 Xf_ATCC_35879 500,648 2 2,522,328 USA Vitis vinifera fastidiosa 1987 SAMN02997312 DSM10026 89,916 11 2,431,652 USA Vitis vinifera fastidiosa 1987 SAMN05660380 EB92-1 44,355 22 2,729,755 USA Sambucus sp.