Babesiosis.

Babesiosis is the disease caused by infection of the erythrocytes of mammals by Babesia species, which are Apicomplexa protozoa belonging to the suborder Piroplasmidea and the family Babesiidae. They are different from the Theileriidae, which can also infect white blood cells and endothelial cells. Babesiosis is one of the most important tick-borne infectious diseases of domestic and wild mammals and still poses significant diagnostic and therapeutic challenges for veterinary practitioners around the world. It is an increasing problem worldwide because of the expansion of tick habitats and the increased mobility of animals, which promote the spread of parasites into new geographical areas. Babesia species can, exceptionally, infect humans, especially splenectomised or immunocompromised individuals. The majority of human cases involve B. microti, a parasite of rodents, but human infections may also be caused by B. divergens, which infects cattle, or by Babesia related to B. odocoilei, which infect cervids. The majority of new developments, in regard to taxonomy, epidemiology, pathogenesis and control, concern canine babesiosis, whereas piroplasmosis in horses or cattle retains the classical description, therefore the focus of this article will be on infection in dogs.

Art meets science: The Cosmopolitan Chicken Research Project.

The Cosmopolitan Chicken Project is an artistic undertaking of renowned artist Koen Vanmechelen. In this project, the artist interbreeds domestic chickens from different countries aiming at the creation of a true Cosmopolitan Chicken as a symbol for global diversity. The unifying theme is the chicken and the egg, symbols that link scientific, political, philosophical and ethical issues. The Cosmopolitan Chicken Research Project is the scientific component of this artwork. Based on state of the art genomic techniques, the project studies the effect of the crossing of chickens on the genetic diversity. Also, this research is potentially applicable to the human population. The setup of the CC®P is quite different from traditional breeding experiments: starting from the crossbreed of two purebred chickens (Mechelse Koekoek x Poule de Bresse), every generation is crossed with a few animals from another breed. For 26 of these purebred and crossbred populations, genetic diversity was measured (1) under the assumption that populations were sufficiently large to maintain all informative SNP within a generation and (2) under the circumstances of the CCP breeding experiment. Under the first assumption, a steady increase in genetic diversity was witnessed over the consecutive generations, thus indeed indicating the creation of a "Cosmopolitan Chicken Genome". However, under the conditions of the CCP, which reflects the reality within the human population, diversity is seen to fluctuate within given boundaries instead of steadily increasing. A reflection on this might be that this is because, in humans, an evolutionary optimum in genetic diversity is reached. Key words.

Microarray analysis reveals abnormal chromosomal complements in over 70% of 14 normally developing human embryos.

STUDY QUESTION: What are the aneuploidy rates and incidence of mosaicism in good-quality human preimplantation embryos. SUMMARY ANSWER: High-level mosaicism and structural aberrations are not restricted to arrested or poorly developing embryos but are also common in good-quality IVF embryos. WHAT IS KNOWN ALREADY: Humans, compared with other mammals, have a poor fertility rate, and even IVF treatments have a relatively low success rate. It is known that human gametes and early preimplantation embryos carry chromosomal abnormalities that are thought to lower their developmental potential. STUDY DESIGN, SIZE AND DURATION: The embryos studied came from nine young (age <35 years old) IVF patients and were part of a cohort of embryos that all resulted in healthy births. These 14 embryos inseminated by ICSI and cryopreserved on Day 2 of development were thawed, cultured overnight and allowed to succumb by being left at room temperature for 24 h. Following removal of the zona pellucida, blastomeres were disaggregated and collected. PARTICIPANTS/MATERIALS, SETTING AND METHODS: There were 91 single blastomeres collected and amplified by multiple displacement amplification. Array-comparative genomic hybridization was performed on the amplified DNA. Array-data were normalized and aneuploidy was detected by the circular binary segmentation method. MAIN RESULTS AND THE ROLE OF CHANCE: The good-quality embryos exhibited high rates of aneuploidy, 10 of 14 (71.4%) of the embryos being mosaic. While none of the embryos had the same aneuploidy pattern in all cells, 4 of 14 (28.6%) were uniformly diploid. Of the 70 analysed blastomeres, 55.7% were diploid and 44.3% had chromosomal abnormalities, while 29% of the abnormal cells carried structural aberrations. WIDER IMPLICATIONS OF THE FINDINGS: Finding such a high rate of aneuploidy and mosaicism in excellent quality embryos from cycles with a high implantation rate warrants further research on the origin and significance of chromosomal abnormalities in human preimplantation embryos. STUDY FUNDING/COMPETING INTEREST(S): This research was supported by the Instituut voor de aanmoediging van innovatie door Wetenschap en Technologie in Vlaanderen (IWT-Vlaanderen). A.M. is a PhD student at the IWT-Vlaanderen. C.S. is a postdoctoral fellow at the FWO Vlaanderen. There are no competing interests.

Combined mRNA microarray and proteomic analysis of eutopic endometrium of women with and without endometriosis.

BACKGROUND: An early semi-invasive diagnosis of endometriosis has the potential to allow early treatment and minimize disease progression but no such test is available at present. Our aim was to perform a combined mRNA microarray and proteomic analysis on the same eutopic endometrium sample obtained from patients with and without endometriosis. METHODS: mRNA and protein fractions were extracted from 49 endometrial biopsies obtained from women with laparoscopically proven presence (n= 31) or absence (n= 18) of endometriosis during the early luteal (n= 27) or menstrual phase (n= 22) and analyzed using microarray and proteomic surface enhanced laser desorption ionization-time of flight mass spectrometry, respectively. Proteomic data were analyzed using a least squares-support vector machines (LS-SVM) model built on 70% (training set) and 30% of the samples (test set). RESULTS: mRNA analysis of eutopic endometrium did not show any differentially expressed genes in women with endometriosis when compared with controls, regardless of endometriosis stage or cycle phase. mRNA was differentially expressed (P< 0.05) in women with (925 genes) and without endometriosis (1087 genes) during the menstrual phase when compared with the early luteal phase. Proteomic analysis based on five peptide peaks [2072 mass/charge (m/z); 2973 m/z; 3623 m/z; 3680 m/z and 21133 m/z] using an LS-SVM model applied on the luteal phase endometrium training set allowed the diagnosis of endometriosis (sensitivity, 91; 95% confidence interval (CI): 74-98; specificity, 80; 95% CI: 66-97 and positive predictive value, 87.9%; negative predictive value, 84.8%) in the test set. CONCLUSION: mRNA expression of eutopic endometrium was comparable in women with and without endometriosis but different in menstrual endometrium when compared with luteal endometrium in women with endometriosis. Proteomic analysis of luteal phase endometrium allowed the diagnosis of endometriosis with high sensitivity and specificity in training and test sets. A potential limitation of our study is the fact that our control group included women with a normal pelvis as well as women with concurrent pelvic disease (e.g. fibroids, benign ovarian cysts, hydrosalpinges), which may have contributed to the comparable mRNA expression profile in the eutopic endometrium of women with endometriosis and controls.

Challenges of interpreting copy number variation in syndromic and non-syndromic congenital heart defects.

Array comparative genomic hybridization (aCGH) has led to an increased detection of causal chromosomal imbalances in individuals with congenital heart defects (CHD). The introduction of aCGH as a diagnostic tool in a clinical cardiogenetic setting entails numerous challenges. Based on our own experience as well as those of others described in the literature, we outline the state of the art and attempt to answer a number of outstanding questions such as the detection frequency of causal imbalances in different patient populations, the added value of higher-resolution arrays, and the existence of predictive factors in syndromic cases. We introduce a step-by-step approach for clinical interpretation of copy number variants (CNV) detected in CHD, which is primarily based on gene content and overlap with known chromosomal syndromes, rather than on CNV inheritance and size. Based on this algorithm, we have reclassified the detected aberrations in aCGH studies for their causality for syndromic and non-syndromic CHD. From this literature overview, supplemented with own investigations in a cohort of 46 sporadic patients with severe non-syndromic CHD, it seems clear that the frequency of causal CNVs in non-syndromic CHD populations is lower than that in syndromic CNV populations (3.6 vs. 19%). Moreover, causal CNVs in non-syndromic CHD mostly involve imbalances with a moderate effect size and reduced penetrance, whereas the majority of causal imbalances in syndromic CHD consistently affects human development and significantly reduces reproductive fitness.

Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment.

MOTIVATION: HIV-1 antiviral resistance is a major cause of antiviral treatment failure. The in vivo fitness landscape experienced by the virus in presence of treatment could in principle be used to determine both the susceptibility of the virus to the treatment and the genetic barrier to resistance. We propose a method to estimate this fitness landscape from cross-sectional clinical genetic sequence data of different subtypes, by reverse engineering the required selective pressure for HIV-1 sequences obtained from treatment naive patients, to evolve towards sequences obtained from treated patients. The method was evaluated for recovering 10 random fictive selective pressures in simulation experiments, and for modeling the selective pressure under treatment with the protease inhibitor nelfinavir. RESULTS: The estimated fitness function under nelfinavir treatment considered fitness contributions of 114 mutations at 48 sites. Estimated fitness correlated significantly with the in vitro resistance phenotype in 519 matched genotype-phenotype pairs (R(2) = 0.47 (0.41 - 0.54)) and variation in predicted evolution under nelfinavir selective pressure correlated significantly with observed in vivo evolution during nelfinavir treatment for 39 mutations (with FDR = 0.05). AVAILABILITY: The software is available on request from the authors, and data sets are available from http://jose.med.kuleuven.be/~kdforc0/nfv-fitness-data/.

Bayesian network analysis of resistance pathways against HIV-1 protease inhibitors.

Interpretation of Human Immunodeficiency Virus 1 (HIV-1) genotypic drug resistance is still a major challenge in the follow-up of antiviral therapy in infected patients. Because of the high degree of HIV-1 natural variation, complex interactions and stochastic behaviour of evolution, the role of resistance mutations is in many cases not well understood. Using Bayesian network learning of HIV-1 sequence data from diverse subtypes (A, B, C, F and G), we could determine the specific role of many resistance mutations against the protease inhibitors (PIs) nelfinavir (NFV), indinavir (IDV), and saquinavir (SQV). Such networks visualize relationships between treatment, selection of resistance mutations and presence of polymorphisms in a graphical way. The analysis identified 30N, 88S, and 90M for nelfinavir, 90M for saquinavir, and 82A/T and 46I/L for indinavir as most probable major resistance mutations. Moreover we found striking similarities for the role of many mutations against all of these drugs. For example, for all three inhibitors, we found that the novel mutation 89I was minor and associated with mutations at positions 90 and 71. Bayesian network learning provides an autonomous method to gain insight in the role of resistance mutations and the influence of HIV-1 natural variation. We successfully applied the method to three protease inhibitors. The analysis shows differences with current knowledge especially concerning resistance development in several non-B subtypes.

The t(4;8) is mediated by homologous recombination between olfactory receptor gene clusters, but other 4p16 translocations occur at random.

The t(4;8)(p16;p23) is the second most common constitutional chromosomal translocation and is caused by an ectopic meiotic recombination between the olfactory receptor gene clusters (ORGC), located on chromosome 4p and 8p. Given that ORGCs are scattered across the genome and make-up about 0.1% of the human genome we reasoned that translocations between 4p16 and other chromosomes might be mediated by ectopic recombination between different ORGC. In 13 patients, we mapped the breakpoints of either a balanced or unbalanced translocation between chromosome 4p16 and different chromosomes. For all four t(4;8) cases, the breakpoints fall within the 4p and 8pter ORGC, confirming that non-allelic homologous recombination (NAHR) between the ORGC is the main mechanism of the t(4;8) formation. For the nine other translocations, the breakpoints on chromosome 4 mapped to different loci, one of them within the ORGC and in two flanking the ORGC. In these three cases, the translocation breakpoint at the reciprocal chromosome did not contain ORGC sequences. We conclude that only the t(4;8) is mediated by NAHR between ORGC.

Analysis of HIV-1 pol sequences using Bayesian Networks: implications for drug resistance.

Human Immunodeficiency Virus-1 (HIV-1) antiviral resistance is a major cause of antiviral therapy failure and compromises future treatment options. As a consequence, resistance testing is the standard of care. Because of the high degree of HIV-1 natural variation and complex interactions, the role of resistance mutations is in many cases insufficiently understood. We applied a probabilistic model, Bayesian networks, to analyze direct influences between protein residues and exposure to treatment in clinical HIV-1 protease sequences from diverse subtypes. We can determine the specific role of many resistance mutations against the protease inhibitor nelfinavir, and determine relationships between resistance mutations and polymorphisms. We can show for example that in addition to the well-known major mutations 90M and 30N for nelfinavir resistance, 88S should not be treated as 88D but instead considered as a major mutation and explain the subtype-dependent prevalence of the 30N resistance pathway.

Predicting the outcome of pregnancies of unknown location: Bayesian networks with expert prior information compared to logistic regression.

BACKGROUND: As women present at earlier gestations to early pregnancy units (EPUs), the number of women diagnosed with a pregnancy of unknown location (PUL) increases. Some of these women will have an ectopic pregnancy (EP), and it is this group in the PUL population that poses the greatest concern. The aim of this study was to develop Bayesian networks to predict EPs in the PUL population. METHODS: Data were gathered in a single EPU from all women with a PUL. This data set was divided into a model-building (599 women with 44 EPs) and a validation (257 women with 22 EPs) data set and consisted of the following variables: vaginal bleeding, fluid in the pouch of Douglas, midline echo, lower abdominal pain, age, endometrial thickness, gestation days, the ratio of HCG at 48 and 0 h, progesterone levels (0 and 48 h) and the clinical outcome of the PUL. We developed Bayesian networks with expert information using this data set to predict EPs. RESULTS: The best Bayesian network used the gestational age, HCG ratio and the progesterone level at 48 h and had an area under the receiver operator characteristic curve (AUC) of 0.88 for predicting EPs when tested prospectively. CONCLUSIONS: Discrete-valued Bayesian networks are more complex to build than, for example, logistic regression. Nevertheless, we have demonstrated that such models can be used to predict EPs in a PUL population. Prospective interventional multicentre studies are needed to validate the use of such models in clinical practice.

Emerging patterns of cryptic chromosomal imbalance in patients with idiopathic mental retardation and multiple congenital anomalies: a new series of 140 patients and review of published reports.

BACKGROUND: Chromosomal abnormalities are a major cause of mental retardation and multiple congenital anomalies (MCA/MR). Screening for these chromosomal imbalances has mainly been done by standard karyotyping. Previous array CGH studies on selected patients with chromosomal phenotypes and normal karyotypes suggested an incidence of 10-15% of previously unnoticed de novo chromosomal imbalances. OBJECTIVE: To report array CGH screening of a series of 140 patients (the largest published so far) with idiopathic MCA/MR but normal karyotype. RESULTS: Submicroscopic chromosomal imbalances were detected in 28 of the 140 patients (20%) and included 18 deletions, seven duplications, and three unbalanced translocations. Seventeen of 24 imbalances were confirmed de novo and 19 were assumed to be causal. Excluding subtelomeric imbalances, our study identified 11 clinically relevant interstitial submicroscopic imbalances (8%). Taking this and previously reported studies into consideration, array CGH screening with a resolution of at least 1 Mb has been undertaken on 432 patients with MCA/MR. Most imbalances are non-recurrent and spread across the genome. In at least 8.8% of these patients (38 of 432) de novo intrachromosomal alterations have been identified. CONCLUSIONS: Array CGH should be considered an essential aspect of the genetic analysis of patients with MCA/MR. In addition, in the present study three patients were mosaic for a structural chromosome rearrangement. One of these patients had monosomy 7 in as few as 8% of the cells, showing that array CGH allows detection of low grade mosaicisims.

Balancing false positives and false negatives for the detection of differential expression in malignancies.

A basic problem of microarray data analysis is to identify genes whose expression is affected by the distinction between malignancies with different properties. These genes are said to be differentially expressed. Differential expression can be detected by selecting the genes with P-values (derived using an appropriate hypothesis test) below a certain rejection level. This selection, however, is not possible without accepting some false positives and negatives since the two sets of P-values, associated with the genes whose expression is and is not affected by the distinction between the different malignancies, overlap. We describe a procedure for the study of differential expression in microarray data based on receiver-operating characteristic curves. This approach can be useful to select a rejection level that balances the number of false positives and negatives and to assess the degree of overlap between the two sets of P-values. Since this degree of overlap characterises the balance that can be reached between the number of false positives and negatives, this quantity can be seen as a quality measure of microarray data with respect to the detection of differential expression. As an example, we apply our method to data sets studying acute leukaemia.

Probabilistic graphical models for computational biomedicine.

BACKGROUND: As genomics becomes increasingly relevant to medicine, medical informatics and bioinformatics are gradually converging into a larger field that we call computational biomedicine. OBJECTIVES: Developing a computational framework that is common to the different disciplines that compose computational biomedicine will be a major enabler of the further development and integration of this research domain. METHODS: Probabilistic graphical models such as Hidden Markov Models, belief networks, and missing-data models together with computational methods such as dynamic programming, Expectation-Maximization, data-augmentation Gibbs sampling, and the Metropolis-Hastings algorithm provide the tools for an integrated probabilistic approach to computational biomedicine. RESULTS AND CONCLUSIONS: We show how graphical models have already found a broad application in different fields composing computational biomedicine. We also indicate several challenges that lie at the interface between medical informatics, statistical genomics, and bioinformatics. We also argue that graphical models offer a unified framework making it possible to integrate in a statistically meaningful way multiple models ranging from the molecular level to cellular and to clinical levels. Because of their versatility and firm statistical underpinning, we assert that probabilistic graphical models can serve as the lingua franca for many computationally intensive approaches to biology and medicine. As such, graphical models should be a foundation of the curriculum of students in these fields. From such a foundation, students could then build towards specific computational methods in medical informatics, medical image analysis, statistical genetics, or bioinformatics while keeping the communication open between these areas.

Evaluation of the vector space representation in text-based gene clustering.

Thanks to its increasing availability, electronic literature can now be a major source of information when developing complex statistical models where data is scarce or contains much noise. This raises the question of how to deeply integrate information from domain literature with experimental data. Evaluating what kind of statistical text representations can integrate literature knowledge in clustering still remains an unsufficiently explored topic. In this work we discuss how the bag-of-words representation can be used successfully to represent genetic annotation and free-text information coming from different databases. We demonstrate the effect of various weighting schemes and information sources in a functional clustering setup. As a quantitative evaluation, we contrast for different parameter settings the functional groupings obtained from text with those obtained from expert assessments and link each of the results to a biological discussion.

Isolation, characterization and inhibition by acarbose of the alpha-amylase from Lactobacillus fermentum: comparison with Lb. manihotivorans and Lb. plantarum amylases.

Extracellular alpha-amylase from Lactobacillus fermentum (FERMENTA) was purified by glycogen precipitation and ion exchange chromatography. The purification was approximately 28-fold with a 27% yield. The FERMENTA molecular mass (106,000 Da) is in the same range as the ones determined for L. amylovorus (AMYLOA), L. plantarum (PLANTAA) and L. manihotivorans (MANIHOA) alpha-amylases. The amino acid composition of FERMENTA differs from the other lactobacilli considered here, but however, indicates that the peptidic sequence contains two equal parts: the N-terminal catalytic part; and the C-terminal repeats. The isoelectric point of FERMENTA, PLANTAA, MANIHOA are approximately the same (3.6). The FERMENTA optimum pH (5.0) is slightly more acidic and the optimum temperature is lower (40 degrees C). Raw starch hydrolysis catalyzed by all three amylases liberates maltotriose and maltotretaose. Maltose is also produced by FERMENTA and MANIHOA. Maltohexaose FERMENTA catalyzed hydrolysis produces maltose and maltotriose. Finally, kinetics of FERMENTA, PLANTAA and MANIHOA using amylose as a substrate and acarbose as an inhibitor, were carried out. Statistical analysis of kinetic data, expressed using a general velocity equation and assuming rapid equilibrium, showed that: (1) in the absence of inhibitor k(cat)/Km are, respectively, 1x10(9), 12.6x10(9) and 3.2x10(9) s(-1) M(-1); and (2) the inhibition of FERMENTA is of the mixed non-competitive type (K(1i)=5.27 microM; L(1i)=1.73 microM) while the inhibition of PLANTAA and MANIHOA is of the uncompetitive type (L(1i)=1.93 microM and 1.52 microM, respectively). Whatever the inhibition type, acarbose is a strong inhibitor of these Lactobacillus amylases. These results indicate that, as found in porcine and barley amylases, Lactobacillus amylases contain in addition to the active site, a soluble carbohydrate (substrate or product) binding site.

Efficacy and tolerance of calcium alginate versus vaseline gauze dressings in the treatment of diabetic foot lesions.

BACKGROUND: The study aimed at comparing the efficacy and tolerance of an alginate wound dressing with a vaseline gauze dressing in the treatment of diabetic foot lesions. METHODS: This open-label randomized multicenter controlled study was designed to assess the effect of an up to 6-week treatment with either calcium alginate or vaseline gauze dressings. Lesions were either acute or chronic, under cleansing, and with a surface area of 1-50 cm(2); osteomyelitis and severe hypovascularization were non-inclusion criteria. Dressings were changed every day then, once granulation had occurred, every 2 to 3 days. Primary outcome was the proportion of patients with granulation tissue over 75% of the wound area and having a 40% decrease in wound surface area; secondary outcomes were pain on dressing changes, the number of dressing changes, and adverse events. RESULTS: Seventy-seven patients were enrolled. Due to the premature cessation of treatment in 13 patients, it was decided to reduce the period of the efficacy analysis to 4 weeks (without revising the criteria of efficacy). The success rate was of 42.8% in the calcium alginate group and of 28.5% in the vaseline gauze group (not significant difference). A subsequent analysis of granulation tissue surfaces covering the wounds at week 4 (all surfaces taken together) showed a superiority of calcium alginate (p=0.04). Pain on dressing change was lower in the calcium alginate group (p=0.047) and the total number of dressing changes tended also to be lower (p=0.07). Adverse events, which occurred 4 times in the calcium alginate group and 6 times in the other, were judged independent of the treatments. CONCLUSIONS: As compared with vaseline gauze, calcium alginate appears to be more appropriate for topical treatment of diabetic foot lesions in terms of both healing and tolerance.

A higher-order background model improves the detection of promoter regulatory elements by Gibbs sampling.

MOTIVATION: Transcriptome analysis allows detection and clustering of genes that are coexpressed under various biological circumstances. Under the assumption that coregulated genes share cis-acting regulatory elements, it is important to investigate the upstream sequences controlling the transcription of these genes. To improve the robustness of the Gibbs sampling algorithm to noisy data sets we propose an extension of this algorithm for motif finding with a higher-order background model. RESULTS: Simulated data and real biological data sets with well-described regulatory elements are used to test the influence of the different background models on the performance of the motif detection algorithm. We show that the use of a higher-order model considerably enhances the performance of our motif finding algorithm in the presence of noisy data. For Arabidopsis thaliana, a reliable background model based on a set of carefully selected intergenic sequences was constructed. AVAILABILITY: Our implementation of the Gibbs sampler called the Motif Sampler can be used through a web interface: http://www.esat.kuleuven.ac.be/~thijs/Work/MotifSampler.html. CONTACT: gert.thijs@esat.kuleuven.ac.be; yves.moreau@esat.kuleuven.ac.be

Starch digestion in tropical fishes: isolation, structural studies and inhibition kinetics of alpha-amylases from two tilapias Oreochromis niloticus and Sarotherodon melanotheron.

alpha-Amylases from the intestinal cavity of two tilapia species, Oreochromis niloticus (ONI-AMY) and Sarotherodon melanotheron (SME-AMY), were purified using ammonium sulfate precipitation, affinity chromatography and chromatofocusing procedures. The purification was approximately 100-fold. The amylolytic activity, specific activity, product distribution, pH and temperature profile of ONI-AMY and SME-AMY are quite similar. The molecular mass differs slightly: 56600 (ONI-AMY) vs. 55500 (SME-AMY). As shown by isoelectric focusing analysis, both amylases contain two isoforms A and B with distinct pI: 7.2 (A) and 7.8 (B), vs. 8.3 (A) and 8.8 (B), respectively. It was not possible to isolate B, since B converts into A with time. The kinetics of the inhibition of ONI-AMY and SME-AMY activity by alpha-, beta- and gamma-cyclodextrin (alpha-, beta- and gamma-CD) were investigated using amylose as the substrate. Statistical analysis of the kinetic data expressed using a general velocity equation and assuming rapid equilibrium showed that the inhibition is of the mixed noncompetitive type. Similar results were obtained with ONI-AMY and SME-AMY. beta- and gamma-CD are stronger inhibitors than alpha-CD. ONI-AMY and SME-AMY are then closely related and show the general features common to the members of the alpha-amylase class (family 13). They enable ONI and SME tilapias to digest starch in food.

Mechanism of porcine pancreatic alpha-amylase. Inhibition of amylose and maltopentaose hydrolysis by alpha-, beta- and gamma-cyclodextrins.

The effects of alpha-, beta- and gamma-cyclodextrins on the amylose and maltopentaose hydrolysis catalysed by porcine pancreatic alpha-amylase (PPA) were investigated. The results of the statistical analysis performed on the kinetic data using the general initial velocity equation of a one-substrate reaction in the presence of one inhibitor indicate that the type of inhibition involved depends on the substrate used: the inhibition of amylose hydrolysis by alpha-, beta- and gamma-cyclodextrin is of the competitive type, while the inhibition of maltopentaose hydrolysis is of the mixed noncompetitive type. Consistently, the Lineweaver-Burk plots intersect on the vertical axis when amylose is used as the substrate, while in the case of maltopentaose, the intersection occurs at a point located in the second quadrant. The inhibition of the hydrolysis therefore involves only one abortive complex, PPA-cyclodextrin, when amylose is used as the substrate, while two abortive complexes, PPA-cyclodextrin and PPA-maltopentaose-cyclodextrin, are involved with maltopentaose. The mixed noncompetitive inhibition thus shows the existence of one accessory binding site. In any case, only one molecule of inhibitor binds to PPA. In line with these findings, the difference spectra of PPA produced by alpha-, beta- and gamma-cyclodextrin indicate that binding occurs at a tryptophan and a tyrosine residue. The corresponding dissociation constants and the inhibition constants obtained using the kinetic approach are in the same range (1.2-7 mM). The results obtained here on the inhibition of maltopentaose hydrolysis by cyclodextrin are similar to those previously obtained with acarbose as the inhibitor [Alkazaz, M., Desseaux, V., Marchis-Mouren, G., Prodanov, E. & Santimone, M. (1998) Eur. J. Biochem. 252, 100-107], but differ from those obtained with amylose as the substrate and acarbose as inhibitor [Alkazaz, M., Desseaux, V., Marchis-Mouren, G., Payan, F., Forest, E. & Santimone, M. (1996) Eur. J. Biochem. 241, 787-796]. It is concluded that the hydrolysis of both long and short chain substrates requires at least one secondary binding site, including a tryptophan residue.