Mapping threats to arctic bird populations. The effect of infectious organisms and pollution on bird health. IPY #172 BirdHealth Project description Sveinn Are Hanssen, Geir Wing Gabrielsen, Tatiana Savinova, Kjetil Sagerup, Jan Ove Bustnes, Kjell Einar Erikstad, Ivar Folstad, Staffan Bensch, Dennis Hasselquist, Ron A M Fouchier, Olga Dolnik, Kjetil Aasbakk, Kirill Galaktionov and A
Suomen sivusto, jossa voit ostaa halvalla ja laadukas Viagra http://osta-apteekki.com/ toimitus kaikkialle maailmaan.
Erityisesti laatu viagra tästä kaupasta voi taata henkilökohtaisesti kamagra Paras laatu kehotan Teitä miellyttää.
Digital.csic.esFluorescence spectroscopy: a rapid tool for
assessing tetracycline resistance in
Mohammed Salim Ammor, Ana Belén Flórez, Abelardo Margolles, and Baltasar Mayo
Abstract: The tetracycline uptake kinetics of 35 Bifidobacterium longum strains isolated from the human gastrointestinal
tract were examined by fluorescence spectroscopy, and the suitability of the technique as a screening tool of tetracycline
resistance or susceptibility was determined. The strains were first grouped into three classes based on their corresponding
minimum inhibitory concentrations (MICs) of tetracycline, as established by the microdilution method: susceptible
(MICs ≤1 µg mL–1), semi-resistant (MICs between 1 and ≤32 µg mL–1), and resistant strains (MICs ≥32 µg mL–1).
The kinetics of tetracycline uptake for the strains in each resistance group were then analyzed over a 20 min period by
fluorescence spectroscopy (absorbance wavelength 524 nm, excitation wavelength 400 nm) in a buffer system containing
100 µg mL–1 tetracycline. Principal component analysis and factorial discriminant analysis of the results showed excellent
distinction among susceptible, semi-resistant, and resistant strains. The proposed method provides a powerful and convenient
means of rapidly screening tetracycline resistance in B. longum.
Key words: fluorescence spectroscopy, Bifidobacterium longum, antibiotic resistance, tetracycline uptake, multidimensionaldata analysis.
Résumé : Les cinétiques d’absorption de la tétracycline chez 35 souches de Bifidobacterium longum isolées du tractus
gastro-intestinal humain furent examinées par spectroscopie à fluorescence et la performance de cette technique comme
outil de criblage de la résistance ou susceptibilité à la tétracycline fut déterminée. Les souches furent d’abord groupées
en trois classes selon leurs concentrations inhibitrices minimales (CMI) à la tétracycline correspondantes telles que déter-
minées par la méthode de microdilution: souches susceptibles (CMI ≤1 µg mL–1), semi-resistante (CMI entre 1 et
≤32 µg mL–1) et résistantes (CMI ≥32 µg mL–1). Les cinétiques d’absorption de la tétracycline pour les souches danschacun des groupes de résistance furent par la suite analysée sur une durée de 20 minutes par spectroscopie à fluores-cence (longueur d’onde d’absorbance de 524 nm, longueur d’onde d’excitation de 400 nm) dans un système tamponnécontenant 100 µg mL–1 de tétracycline. Une analyse des composantes principales et une analyse factorielle du discrimi-nant des résultats ont démontré une excellente distinction entre les souches susceptibles, semi-résistantes et résistantes. Laméthode proposée fournit un moyen performant et pratique pour cribler rapidement la résistance à la tétracycline chezB. longum.
Mots clés : spectroscopie à fluorescence, Bifidobacterium longum, résistance aux antibiotiques, absorption de la tétracycline,analyse multidimensionnelle des données.
level as growth promoters in animal feeds (Wegener 2003).
However, this intensive and extensive use has caused tetra- Tetracyclines were discovered in the 1940s and shown to cycline resistance to spread to a large number of commensal, have activity against a wide range of microorganisms, including opportunistic, and pathogenic bacteria (Chopra and Roberts Gram-positive and -negative bacteria, chlamydiae, myco- 2001; Roberts 2005). This resistance is mostly acquired by plasmas, rickettsiae, and even protozoan parasites (Chopra the horizontal transmission of genes coding for energy- and Roberts 2001). These antibiotics have been extensively dependent efflux systems or for proteins that protect the bac- used in the prophylaxis and treatment of human and animal terial ribosomes from the blockage of protein synthesis (Chopra infections. They have also been used at the subtherapeutic Bifidobacterium longum is among the dominant bifido- bacterial species of the human gastrointestinal tract (GIT) Received 6 January 2006. Revision received 24 March 2006.
(Ventura et al. 2004), where it is thought to have several Accepted 27 March 2006. Published on the NRC Research health-promoting effects, including the prevention of diar- Press Web site at http://cjm.nrc.ca on 29 July 2006.
rhea in antibiotic-treated patients, the reduction of choles- M.S. Ammor,1 A.B. Flórez, A. Margolles, and B. Mayo.
terol levels, the alleviation of lactose intolerance symptoms, Instituto de Productos Lácteos de Asturias (CSIC), Carretera and the stimulation of the immune system (Ouwehand et al.
de Infiesto s/n, 33300 Villaviciosa, Asturias, Spain.
2002). Given these possible properties, this species is fre- 1Corresponding author (e-mail: firstname.lastname@example.org).
quently used as a probiotic in dairy products or is included Can. J. Microbiol. 52: (2006)
in dietary supplements (Tuohy et al. 2003). The selection of Table 1. Mean inhibitory concentration (MIC) of
suitable strains for this purpose is difficult, however, since tetracycline, as determined by microdilution using the key characteristics necessary for survival and competi- tion in the human GIT are poorly understood (O’Sullivan 2001). Nevertheless, agreement exists that the strains used in food systems should be free of potentially transferable deter-minants of antibiotic resistance (European Commission 2001).
Susceptible strains (MIC ≤1)
A few B. longum strains have already been characterized as (Delgado et al. 2005; Moubareck et al. 2005), and at least two tetracycline-resistant determinants in bifidobacterial species — tet(W) and tet(M) — have been characterized (Lacroix and Walker 1995; Scott et al. 2000). Thus, to avoid the spread of resistance via probiotics, systematic checking for antibiotic resistance (in particular to tetracycline) is es- The antibiotic resistance or susceptibility profiles of bifido- bacteria have been assessed by many methods, e.g., disk dif- fusion (Matteuzzi et al. 1983; Charteris et al. 1998), agar dilution (Lim et al. 1993), microdilution (Delgado et al.
2005), and the E-test (Charteris et al. 2001). However, more robust methods would facilitate large-scale screening in the Tetracycline fluoresces after excitation with light of at least 400 nm. Therefore, fluorescence spectroscopy can be used to monitor its uptake in bacterial cells, i.e., the influx of the antibiotic from the external environment to the cell interior. The aim of the present work was to use fluores- cence spectroscopy to follow tetracycline uptake in strains ofB. longum with different mean inhibitory concentrations Semi-resistant strains (1 < MIC < 32)
(MICs) for this antibiotic. The results show the suitability of this technique as a screening tool of tetracycline resistance Materials and methods
Strains and growth conditions
The bacteria used in this study were 35 B. longum isolates whose tetracycline MICs are known to be different (Delgado Resistant strains (MIC ≥32)
et al. 2005) (Table 1). The B. longum type strain LMG 13197T was included as a control in all analyses.
Frozen bacteria were subcultured twice in De Man – Rogosa – Sharpe (MRS) agar (Biokar Diagnostics, Beauvais, France) containing 0.25% cysteine (Sigma Chemical, St.
Louis, Missouri, USA) (MRS+C) prior to performing the assays. Isolated colonies were finally added to 10 mL of *Test strains; all others were used to construct the model.
MRS+C broth and cultured at 37 °C for 48 h in an anaerobicchamber (MAC500; Down Whitley Scientific, West York-shire, UK) containing an atmosphere of 85% N2, 10% H2,and 5% CO2.
Darmstadt, Germany) were added (approximate final bacterialconcentration 1 × 106 cfu mL–1). One hundred microlitres MICs of tetracycline
of this suspension was inoculated into each well of the The MICs of tetracycline for the different strains were Sensititre plates and incubated at 37 °C in anaerobic condi- determined with the Sensititre Anaero3 commercial system tions for 48 h. The growth of the strains was recorded by (Trek Diagnostic Systems, East Grinstead, UK), following the manufacturer’s recommendations. Briefly, colonies ofeach strain grown on solid media were used to make a 0.5 Fluorescence spectroscopy
McFarland suspension in Brucella Standard broth (TrekDiagnostic Systems, Cleveland, Ohio, USA), and 100 µL of Sample preparation
this suspension was then transferred to 10 mL of the same The strains were propagated in MRS+C agar for 24–48 h.
medium, to which haemin and vitamin K1 (Merck, VWR, One colony was placed in 10 mL of MRS+C broth and incu- Fig. 1. Spectra of tetracycline uptake kinetics recorded following excitation at 400 nm in dilute suspensions of Bifidobacterium longum
L46 (solid line) (MIC < 1 µg mL–1), L42 (heavy grey line) (MIC = 16 µg mL–1), and H67 (broken line) (MIC = 256 µg mL–1).
bated overnight (16–18 h). Ten millilitres of fresh MRS+C was added and incubation allowed to proceed for 10 min was inoculated (2%) with this overnight culture on the fol- (t5min–t15min); 20 mmol L–1 of glucose was finally added to lowing morning. The optical density (OD) of each culture energize the cells, and fluorescence was monitored for a fur- was determined at 600 nm using a Kontron spectro- ther 5 min (t15min–t20min).
photometer (Tegimenta AG, Rotkreuz, Switzerland). Whenan OD600 of 0.5 ± 0.1 was reached, 8 mL of the culture was Mathematical analysis of data
centrifuged at 7000 r/min (1 r = 2π rad; 6800g) for 2 min.
The spectral data were analyzed using XLStat pro 7.5 Cells were washed twice with 2 mL of 50 mmol L–1 potas- software (Addinsoft, Paris, France). Pearson principal com- sium phosphate buffer containing 2 mmol L–1 MgSO4 and ponent analysis (normed PCA) was performed to transform 2 mmol L–1 glucose (pH 7), and the pellet was resuspended the large number of potentially correlated factors into a in 0.5 mL of the same buffer. The volume of this suspension smaller number of uncorrelated factors (i.e., principal com- necessary to obtain a final OD600 of 0.5 was added to 2 mL ponents) and thus reduce the size of the data set. This of the buffer solution prior to the measurement of fluores- multivariate treatment allows score plots of the samples to cence. Three independent cultures were assayed for each be drawn representing the spectral patterns (Bertrand and Scotter 1992; Jollife 1986). Neighboring points on these scoreplots represent similar spectra.
The linearly independent principal components resulting The fluorescence spectra of the bacterial samples were from PCA were subjected to factorial discriminant analysis obtained using a Cary Eclipse fluorescence spectropho- (FDA) by examining the spectral fluorescence data. The aim tometer (Varian, Sydney, Australia) equipped with a thermostat- of this technique is to predict the likely belonging of an controlled, right-angled, single cuvette holder. Samples (2 mL) observation (spectrum data) to a previously defined qualita- were placed in a Teflon® cuvette and the kinetics of tetracy- tive group (Safar et al. 1994). Since the raw spectral data cline uptake measured over 20 min (λExc = 400 nm, λEmi = could not be used because of the strong correlations among 524 nm, slit width = 5 nm) at 37 °C. After a time period of variables (the measurement times), the uncorrelated princi- 5 min of preincubation (t5min), 100 µg mL–1 of tetracycline pal component resulting from PCA was employed.
Fig. 2. Discriminant analysis similarity map determined with discriminant factors 1 and 2 for the spectral data of the different tetracy-
cline resistance groups: ٗ, resistant strains (MIC ≥32 µg mL–1); ᭝, semi-resistant strains (1 µg mL–1 ≤ MIC < 32 µg mL–1); ᭺,
susceptible strains (MIC < 1 µg mL–1).
Results and discussion
fluorescence equilibrium soon after the addition of the anti-biotic, preceded by a peak of antibiotic uptake. Resistant MICs of tetracycline
strains were also characterized by a small increase in uptake Table 1 shows the MICs of tetracycline for the different after the cells received glucose. In contrast, susceptible strains. The results obtained agree well with those reported strains reached the equilibrium more slowly after the addi- by Delgado et al. (2005). Differences with respect to the tion of tetracycline and were characterized by a greater in- results of the latter authors were always less than two Log crease in uptake after the addition of glucose.
dilutions, which is normal for MICs obtained by the micro- Previous studies have shown that the movement of tetra- dilution method (Delgado et al. 2005; Flórez and Mayo cycline across the plasma membrane is an energy-dependent process driven by the ∆ pH component of proton motive A tetracycline resistance gene (tet(W)) was detected in all force (Nikaido and Thanassi 1993). The influx of the antibiotic the semi-resistant and resistant isolates (Flórez and Mayo is fast enough for fluorescence equilibrium to be reached in 2005). In fact, it has been reported in several B. longum just a few seconds. In contrast, when ribosome-binding strains (Moubareck et al. 2005; Scott et al. 2000) and seems proteins are present (which form stable complexes with ribo- to be the most common tetracycline resistance gene in other somes; Spahn et al. (2001)), fluorescence equilibrium is intestinal bacterial genera (Scott et al. 2000; Roberts 2005).
reached much later because the binding of the tetracycline tothe 30S subunit is inhibited (Nonaka et al. 2005). Based on Fluorescence spectroscopy
the present observations and given that all resistant strainsharbor the tet(W) gene (encoding a ribosomal protection Tetracycline uptake kinetics
protein), the fluorescence equilibrium may be affected by Figure 1 shows the spectra recorded for three representa- the efficiency of the binding of the antibiotic to the tive isolates of the different susceptibility groups. In general, ribosome. Since ribosomal binding sites are protected in no correlation was found among fluorescence intensity and resistant strains, tetracycline cannot bind to them, and the tetracycline resistance. However, the resistant strains reached equilibrium between the internalized tetracycline and the out- Table 2. Classification, membership probability, supplementary observation scores, and squared distances to group centroids.
Note: S, susceptible; SR, semi-resistant; R, resistant.
*The numbers 1, 2, and 3 refer to distinct replicate observations for every test strain.
Fig. 3. Discriminant analysis similarity map of principal (constructed model) and supplementary (test strains) data determined with dis-
criminant factors 1 and 2 for the spectral data of the different tetracycline resistance groups: ٗ, resistant strains, principal observations
(MIC ≥32 µg mL–1); ᭝, semi-resistant strains, principal observations (1 µg mL–1 ≤ MIC < 32 µg mL–1); ᭡, semi-resistant strains, sup-
plementary observations; ᭺, susceptible strains, principal observations (MIC <1 µg mL–1) ᭹, susceptible strains, supplementary observations.
side pool is quickly reached. In contrast, in the susceptible showing differences in tetracycline resistance should certainly strains, tetracycline binds to the ribosome and fluorescence equilibrium is reached later (Fig. 1: see t5min–t15min).
Tetracycline uptake was also found to be positively correlated Conclusions
in the presence of 2 mmol L–1 of MgSO4 was approximately The results show that fluorescence spectroscopy is a rapid 5-fold greater than in the presence of 0.4 mmol L–1 MgSO4.
and accurate method for screening B. longum strains for This agrees with previous observations suggesting that the resistance to tetracycline. Models similar to that constructed complexion of tetracycline with divalent metal ions, such as for B. longum could easily be developed for other bacterial Mg2+ or Ca2+, greatly increases fluorescence (Schneider et species. The method is amenable to semi-complete or com- plete automation; this should be useful in large-scale tetracy-cline resistance surveys, complementing or perhaps replacing Model building
the more expensive and time-consuming phenotypic assays To ensure robustness, the model was constructed using the results for 30 strains and validated with five test strains. Thespectral kinetics data obtained for the 30 B. longum strainswere pooled in one matrix and the data examined by PCA.
The linear independent factors resulting from the PCA were This work was supported by a project within the sixth then used as new variables to perform FDA based on the Framework Program of the EU (ACE-ART, ref. 506214).
defined group constituting the dependent variable.
M.S. Ammor was the recipient of a postdoctoral fellowship In a first step, the dependent variable was composed of 30 from the Secretaría de Estado de Universidades e Investi- groups representing the number of considered strains. The gación, Spanish Ministry of Education and Science (ref.
aim was to ensure that the results of the three replicate assays for each strain were attributed to the group formed bythe corresponding strain, thus confirming the reproducibilityof the method. The confusion matrix resulting from the FDA References
provided 100% correct classification of the results to thecorresponding strain. The first two discriminant factors were Bertrand, D., and Scotter, C.N.G. 1992. Application of multivariate able to explain more than 86.7% of the total variance (results analyses to NIR spectra of gelatinized starch. Appl. Spectrosc.
not shown), thus confirming reproducibility.
In a second step, the dependent variable was composed Charteris, W.P., Kelly, P.M., Morelli, L., and Collins, J.K. 1998.
of three groups according to the resistance level: susceptible Antibiotic susceptibility of potentially probiotic Bifidobacteriumisolates from the human gastrointestinal tract. Lett. Appl.
(MICs ≤1 µg mL–1), semi-resistant (MICs between 1 and Microbiol. 26: 333–337.
32 µg mL–1), and resistant (MICs ≥32 µg mL–1). The confusion Charteris, W.P., Kelly, P.M., Morelli, L., and Collins, J.K. 2001.
matrix of the FDA results indicated 100% correct classification Gradient diffusion antibiotic susceptibility testing of potentially of the strains in these groups (results not shown). Figure 2 probiotic lactobacilli. J. Food Prot. 64: 2007–2014.
shows the map defined by discriminant factors 1 and 2; Chopra, I., and Roberts, M. 2001. Tetracycline antibiotics: mode of these two factors explained 100% of the total variance. The action, applications, molecular biology, and epidemiology of model was therefore considered well constructed; validation bacterial resistance. Microbiol. Mol. Biol. Rev. 65: 232–260.
experiments were therefore performed.
Delgado, S., Florez, A.B., and Mayo, B. 2005. Antibiotic suscepti- bility of Lactobacillus and Bifidobacterium species from the Model validation
human gastrointestinal tract. Curr. Microbiol. 50: 202–207.
The spectral kinetics data for the five test strains were col- European Commission. 2001. Opinion of the Scientific Committee lected and pooled in a matrix. PCA was then applied to a on Animal Nutrition on the criteria for assessing the safety of model and validating data matrices. The model matrix pro- micro-organisms resistant to antibiotics of human clinical andveterinary importance [online]. Available from http://www.europa.
vided the principal observations and the validating matrix eu.int/comm/food/fs/sc/scan/out64_en.pdf [cited 18 April 2001].
provided the supplementary observations; thus, the supple- Flórez, A.B., and Mayo, B. 2005. Tetracycline resistance genes mentary observations did not contribute to the inertia of the from Bifidobacterium species of human origin. Proceedings of model. The linearly independent factors (principal and sup- the 3rd International Meeting on Probiotics, Prebiotics and New plementary data) were used as new variables (principal and Foods. Università Urbaniana, 4–6 September, 2005, Rome, Italy.
supplementary data) in FDA analysis. Although, 2 of the 15 Jollife, I.T. 1986. Principal component analysis. Springer, New observations corresponding to these supplementary observa- tions were misclassified (Table 2), all five test strains were Lacroix, J.M., and Walker, C.B. 1995. Detection and incidence of assigned a position close to other strains of their phenotypic the tetracycline resistance determinant tet(M) in the microflora group (Table 1). Both misclassified observations corre- associated with adult periodontitis. J. Periodontol. 66: 102–108.
sponded to the semi-resistant group (Fig. 3), but they did not Lim, K.S., Huh, C.S., and Baek, Y.J. 1993. Antimicrobial suscepti- invalidate the overall results. This misclassification might be bility of bifidobacteria. J. Dairy Sci. 76: 2168–2174.
explained by the small number of strains used in the con- Matteuzzi, D., Crociani, F., and Brigidi, P. 1983. Antimicrobial struction of the model. However, since more data can be susceptibility of Bifidobacterium. Ann. Microbiol. (Paris), 134:
added to the model, the analysis of new B. longum strains Moubareck, C., Gavini, F., Vaugien, L., Butel, M.J., and Doucet- Schneider, S., Schmitt, M.O., Brehm, G., Reiher, M., Matousek, P., Populaire, F. 2005. Antimicrobial susceptibility of bifido- and Towrie, M. 2003. Fluorescence kinetics of aqueous solu- bacteria. J. Antimicrob. Chemother. 55: 38–44.
tions of tetracycline and its complexes with Mg2+ and Ca2+.
Nikaido, H., and Thanassi, D.G. 1993. Penetration of lipophilic Photochem. Photobiol. Sci. 2: 1107–1117.
agents with multiple protonation sites into bacterial cells: tetra- Scott, K.P., Melville, C.M., Barbosa, T.M., and Flint, H.J. 2000.
cyclines and fluoroquinolones as examples. Antimicrob. Agents Occurrence of the new tetracycline resistance gene tet(W) in Chemother. 37: 1393–1399.
bacteria from the human gut. Antimicrob. Agents Chemother.
Nonaka, L., Connell, S.R., and Taylor, D.E. 2005. 16S rRNA muta- 44: 775–777.
tions that confer tetracycline resistance in Helicobacter pylori Spahn, C.M., Blaha, G., Agrawal, R.K., Penczek, P., Grassucci, decrease drug binding in Escherichia coli ribosomes. J. Bac- R.A., Trieber, C.A., Connell, S.R., Taylor, D.E., Nierhaus, K.H., teriol. 187: 3708–3712.
and Frank, J. 2001. Localization of the ribosomal protection O’Sullivan, D.J. 2001. Screening of intestinal microflora for effec- protein Tet(O) on the ribosome and the mechanism of tetracy- tive probiotic bacteria. J. Agric. Food Chem. 49: 1751–1760.
cline resistance. Mol. Cell, 7: 1037–1045.
Ouwehand, A.C., Salminen, S., and Isolauri, E. 2002. Probiotics: Tuohy, K.M., Probert, H.M., Smejkal, C.W., and Gibson, G.R.
an overview of beneficial effects. Antonie Leeuwenhoek, 82:
2003. Using probiotics and prebiotics to improve gut health.
Drug Discov. Today, 8: 692–700.
Roberts, M.C. 2005. Update on acquired tetracycline resistance Ventura, M., van Sinderen, D., Fitzgerald, G.F., and Zink, R. 2004.
genes. FEMS Microbiol. Lett. 245: 195–203.
Insights into the taxonomy, genetics and physiology of bifido- Safar, M., Bertrand, D., Robert, P., Devaux, M.F., and Genot, C.
bacteria. Antonie Leeuwenhoek, 86: 205–223.
1994. Characterization of edible oils, butters and margarines by Wegener, H.C. 2003. Antibiotics in animal feed and their role in fourier transform infrared spectroscopy with attenuated total re- resistance development. Curr. Opin. Microbiol. 6: 439–445.
flectance. J. Am. Oil Chem. Soc. 71: 371–377.
11° GRAND PRIX IUTA 2013 di ULTRAMARATONA Segnalare eventuali errori CLASSIFICA GENERALE FEMMINILE - FINALE e/o omissioni a: Aggiornamento Soci Iuta al 30\11\2013 SOCIETA' Migliori 9 ris. BELLATO Maria Applerun Team GARGANO Angela ASD Barletta Sportiva VERZELETTI Rossella ASD Runners Bergamo RAVANI Laura ASD Runners Bergamo PIASTRA Lorena