title: Modeling the acid-base properties of bacterial surfaces: A combined spectroscopic and potentiometric study of the gram-positive bacterium Bacillus subtilis.
abstract: In this study, macroscopic and spectroscopic data were combined to develop a surface complexation model that describes the acid-base properties of Bacillus subtilis. The bacteria were freeze-dried and then resuspended in 0.1 M NaCl ionic medium. Macroscopic measurements included potentiometric acid-base titrations and electrophoretic mobility measurements. In addition, ATR-FTIR spectra of wet pastes from suspensions of Bacillus subtilis at different pH values were collected. The least-squares program MAGPIE was used to generate a surface complexation model that takes into account the presence of three acid-base sites on the surface: tripple bond COOH, tripple bond NH+, and tripple bond PO-, which were identified previously by XPS measurements. Both potentiometric titration data and ATR-FTIR spectra were used quantitatively, and electrostatic effects at the charged bacterial surface were accounted for using the constant capacitance model. The model was calculated using two different approaches: in the first one XPS data were used to constrain the ratio of the total concentrations of all three surface sites. The capacitance of the double layer, the total buffer capacity, and the deprotonation constants of the tripple bond NH+, tripple bond POH, and tripple bond COOH species were determined in the fit. A second approach is presented in which the ratio determined by XPS of the total concentrations of tripple bond NH+ to tripple bond PO- sites is relaxed. The total concentration of tripple bond PO- sites was determined in the fit, while the deprotonation constant for tripple bond POH was manually varied until the minimization led to a model which predicted an isoelectric point that resulted in consistency with electrophoretic mobility data. The model explains well the buffering capacity of Bacillus subtilis suspensions in a wide pH range (between pH=3 and pH=9) which is of considerable environmental interest. In particular, a similar quantitative use of the IR data opens up possibilities to model other bacterial surfaces at the laboratory scale and help estimate the buffering capacity of carboxylate-containing compounds in natural samples.
authors.affiliation: Department of Chemistry, Umeå University, Umeå, Sweden. laura.leone@chem.umu.se
authors.forename: Laura
authors.initials: L
authors.lastname: Leone
authors.forename: Diego
authors.initials: D
authors.lastname: Ferri
authors.forename: Carla
authors.initials: C
authors.lastname: Manfredi
authors.forename: Per
authors.initials: P
authors.lastname: Persson
authors.forename: Andrei
authors.initials: A
authors.lastname: Shchukarev
authors.forename: Staffan
authors.initials: S
authors.lastname: Sjöberg
authors.forename: John
authors.initials: J
authors.lastname: Loring
mesh_terms: D000143:Acids / Q000737:chemistry*; D000468:Alkalies / Q000737:chemistry*; D001412:Bacillus subtilis / Q000737:chemistry* / Q000378:metabolism; D002462:Cell Membrane / Q000737:chemistry; D005612:Freeze Drying; D006863:Hydrogen-Ion Concentration; D008954:Models, Biological; D013052:Spectrometry, X-Ray Emission; D017550:Spectroscopy, Fourier Transform Infrared
chemical_list: D000143:Acids; D000468:Alkalies