Peteris Zikmanis

The effect of osmo-induced stress on product formation by Zymomonas mobilis on sucrose

The intensification of biosynthesis of fructooligosaccharides in the presence of high salt concentrations was observed during sucrose (10%) fermentation by Zymomonas mobilis 113S. A 0.6 M NaCl concentration led to an increase of oligosaccharide productivity by 3.5-fold. Sorbitol formation was increased in the presence of 0.16 M NaCl and was inhibited at highest salt concentrations. In a medium with high (65%, w/w) sucrose content the salts gave inhibitory effects on fructooligosaccharide production by lyophilised Z. mobilis cells. Influence of salts on gluconic acid and sorbitol formation under these conditions was studied. The ratio of oligosaccharides and gluconic acid productivity (Qolig./Qglucon.) was increased approximately 2 times at 1% KCl. Sorbitol formation was not significantly influenced in the presence of KCl (up to 2%).

Response of Zymomonas mobilis levansucrase activity to sodium chloride

An activation of levansucrase-catalysed levan formation by NaCl, KCl and Na2 SO4 (0.03–0.7 M) was observed using cell-free extract of Zymomonas mobilis. A sigmoidal response of the rate of levansucrase-catalysed reaction to the sucrose concentration was significantly reduced in the presence of salts the Hill coefficient 2.10 and 1.0–1.2 respectively), possibly, due to the heterotropic activation of levansucrase as an allosteric enzyme.

An Influence of Fructan Containing Concentrate from Jerusalem Artichoke Tubers on the Development of Probiotic Dairy Starters on Milk and Oat-based Substrates

Supplementation of milk and oat hydrolysate containing medium with Jerusalem artichoke concentrate (JAC) and subsequent fermentation with probiotic dairy starters resulted in substantial stimulation of probiotics Bifidobacterium lactis and Lactobacillus acidophilus as well as yogurt starter culture Lactobacillus bulgaricus development and acidification rate. The strain-specific responses of the general yogurt cultures, as well as probiotics to the addition of JAC, should be considered to achieve optimal composition of probiotic strains and conformable fermentation conditions. JAC is suggested to be perspective prebiotic additive for fermented synbiotic milks or oat-hydrolysate-based products.

Relationships between kinetic constants and the amino acid composition of enzymes from the yeast Saccharomyces cerevisiae glycolysis pathway

The kinetic models of metabolic pathways represent a system of biochemical reactions in terms of metabolic fluxes and enzyme kinetics. Therefore, the apparent differences of metabolic fluxes might reflect distinctive kinetic characteristics, as well as sequence-dependent properties of the employed enzymes. This study aims to examine possible linkages between kinetic constants and the amino acid (AA) composition (AAC) for enzymes from the yeast Saccharomyces cerevisiae glycolytic pathway. The values of Michaelis-Menten constant (K M), turnover number (k cat), and specificity constant (k sp = k cat/K M) were taken from BRENDA (15, 17, and 16 values, respectively) and protein sequences of nine enzymes (HXK, GADH, PGK, PGM, ENO, PK, PDC, TIM, and PYC) from UniProtKB. The AAC and sequence properties were computed by ExPASy/ProtParam tool and data processed by conventional methods of multivariate statistics. Multiple linear regressions were found between the log-values of k cat (3 models, 85.74% < R adj.2 <94.11%, p < 0.00001), K M (1 model, R adj.2 = 96.70%, p < 0.00001), k sp (3 models, 96.15% < R adj.2 < 96.50%, p < 0.00001), and the sets of AA frequencies (four to six for each model) selected from enzyme sequences while assessing the potential multicollinearity between variables. It was also found that the selection of independent variables in multiple regression models may reflect certain advantages for definite AA physicochemical and structural propensities, which could affect the properties of sequences. The results support the view on the actual interdependence of catalytic, binding, and structural residues to ensure the efficiency of biocatalysts, since the kinetic constants of the yeast enzymes appear as closely related to the overall AAC of sequences.

Influence of growth conditions on hydrophobicity of Lactobacillus acidophilus and Bifidobacterium lactis cells and characteristics by FT-IR spectra

In this study we have found, that the values of cell surface hydrophobicity (CSH) of L. acidophilus LA5 and B. lactis Bb12 cells change in response to varied growth conditions – phase of growth, concentration or type of carbon source, presence of oxygen. An evaluation of FT-IR spectra using cluster and quantitative analyses revealed substantial changes of the chemical composition depending on the CSH level of L. acidophilus LA5 and B. lactis Bb12 cells. Decrease of the carbohydrate level was observed in proportion to the increased CSH values alongside with the elevated protein content of more hydrophobic cells of both cultures. The results of present study could help to specify the appropriate physiological state and environment for L. acidophilus LA5 and B. lactis Bb12 to ensure their probiotic properties.

Model-based biotechnological potential analysis of Kluyveromyces marxianus central metabolism

The non-conventional yeast Kluyveromyces marxianus is an emerging industrial producer for many biotechnological processes. Here, we show the application of a biomass-linked stoichiometric model of central metabolism that is experimentally validated, and mass and charge balanced for assessing the carbon conversion efficiency of wild type and modified K. marxianus. Pairs of substrates (lactose, glucose, inulin, xylose) and products (ethanol, acetate, lactate, glycerol, ethyl acetate, succinate, glutamate, phenylethanol and phenylalanine) are examined by various modelling and optimisation methods. Our model reveals the organism’s potential for industrial application and metabolic engineering. Modelling results imply that the aeration regime can be used as a tool to optimise product yield and flux distribution in K. marxianus. Also rebalancing NADH and NADPH utilisation can be used to improve the efficiency of substrate conversion. Xylose is identified as a biotechnologically promising substrate for K. marxianus.

Search for a Minimal Set of Parameters by Assessing the Total Optimization Potential for a Dynamic Model of a Biochemical Network

Selecting an efficient small set of adjustable parameters to improve metabolic features of an organism is important for a reduction of implementation costs and risks of unpredicted side effects. In practice, to avoid the analysis of a huge combinatorial space for the possible sets of adjustable parameters, experience-, and intuition-based subsets of parameters are often chosen, possibly leaving some interesting counter-intuitive combinations of parameters unrevealed. The combinatorial scan of possible adjustable parameter combinations at the model optimization level is possible; however, the number of analyzed combinations is still limited. The total optimization potential (TOP) approach is proposed to assess the full potential for increasing the value of the objective function by optimizing all possible adjustable parameters. This seemingly unpractical combination of adjustable parameters allows assessing the maximum attainable value of the objective function and stopping the combinatorial space scanning when the desired fraction of TOP is reached and any further increase in the number of adjustable parameters cannot bring any reasonable improvement. The relation between the number of adjustable parameters and the reachable fraction of TOP is a valuable guideline in choosing a rational solution for industrial implementation. The TOP approach is demonstrated on the basis of two case studies.

Distinctive attributes for predicted secondary structures at terminal sequences of non-classically secreted proteins from proteobacteria

C- and N-terminal sequences (64 amino acid residues each) of 89 non-classically secreted type I, type III and type IV proteins (Swiss-Prot/TrEMBL) from proteobacteria were transformed into predicted secondary structures. Multivariate analysis of variance (MANOVA) confirmed the significance of location (C- or N-termini) and secretion type as essential factors in respect of quantitative representations of structured (a-helices, b-strands) and unstructured (coils) elements. The profiles of secondary structures were transcripted using unequal property values for helices, strands and coils and corresponding numerical vectors (independent variables) were subjected to multiple discriminant analysis with the types of secreted proteins as the dependent variables. The set of strong predictor variables (21 property values located at the region of 2–49 residues from the C-termini) was capable to classify all three types of non-classically secreted proteins with an accuracy of 93.3% for originally and 89.9% for cross-validated (leave-one-out procedure) grouped cases. The average error rate (0.137 ± 0.015) of k-fold (k = 3; 4; 6; 8; 10; 89) cross validation affirmed an acceptable prediction accuracy of defined discriminant functions with regard to the types of non-classically secreted proteins. The proposed prediction tool could be used to specify the secretome proteins from genomic sequences as well as to assess the compatibility between secretion pathways and secretion substrates of proteobacteria.

Discriminative features of type I and type III secreted proteins from Gram-negative bacteria

The amino acid composition of sequences and structural attributes (α-helices, β-sheets) of C-and N-terminal fragments (50 amino acids) were compared to annotated (SWISS-PROT/ TrEMBL) type I (20 sequences) and type III (22 sequences) secreted proteins of Gram-negative bacteria.The discriminant analysis together with the stepwise forward and backward selection of variables revealed the frequencies of the residues Arg, Glu, Gly, Ile, Met, Pro, Ser, Tyr, Val as a set of strong (1-P < 0.001) predictor variables to discriminate between the sequences of type I and type III secreted proteins with a cross-validated accuracy of 98.6–100 %. The internal and external validity of discriminant analysis was confirmed by multiple (15 repeats) test-retest procedures using a randomly split original set of proteins; this validation method demonstrated an accuracy of 100 % for 191 non-selected (retest) sequences.The discriminant analysis was also applied using selected variables from the propensities for β-sheets and polarity of C-terminal fragments. This approach produced the next highest and comparable cross-validated classification accuracy for randomly selected and retest proteins (85.4–86.0 % and 82.4–84.5 %, respectively).The proposed sets of predictor variables could be used to assess the compatibility between secretion substrates and secretion pathways of Gram-negative bacteria by means of discriminant analysis.

Distinctive amino acid residue periodicities in terminal sequences of type III and type I secreted proteins from proteobacteria

The Fourier transform (FT) method was applied to specify the distribution of 14 predefined groups of amino acids (64 residues) at both termini of annotated type III and type I secreted proteins from proteobacteria. Type I proteins displayed a higher occurrence of significant periodicities at both C-and N-termini, indicating potent features to discriminate between secretion types, particularly by the use of variables selected from the full periodicity profiles at 19 orders of FT. The Fishers linear discriminant analysis, together with the stepwise selection of variables throughout equal pairs of combinations for all predefined groups of residues, revealed the C-terminal harmonics of aromatic (HFWY) and aliphatic (VLIA) residues as a set of strong predictor variables to classify both types of secreted proteins with an accuracy of 100% for original grouped cases and 96.4% for cross-validated grouped cases. The prediction accuracy of proposed discriminant function was estimated by repeated k-fold cross-validation procedures where the original data set was randomly divided into k subsets, with one of the k-subsets serving as the test set and the remaining data forming the training set. The average error rate computed across all k-trials and repeats did not exceed that of leave-one-out procedure. The proposed set of predictor variables could be used to assess the compatibility between secretion pathways and secretion substrates of proteobacteria by means of discriminant analysis.