Characterization of the superoxide dismutase SOD1 gene of Kluyveromyces marxianus L3 and improved production of SOD activity

Superoxide dismutase (SOD) activity is one major defense line against oxidative stress for all of the aerobic organisms, and industrial production of this enzyme is highly demanded. The Cu/Zn superoxide dismutase gene (KmSOD1) of Kluyveromyces marxianus L3 was cloned and characterized. The deduced KmSod1p protein shares 86% and 71% of identity with Kluyveromyces lactis and Saccharomyces cerevisiae Sod1p, respectively. The characteristic motifs and the amino acid residues involved in coordinating copper and zinc and in enzymatic function were conserved. To the aim of developing a microbial production of Cu/Zn superoxide dismutase, we engineered the K. marxianus L3 strain with the multicopy plasmid YG-KmSOD1 harboring the KmSOD1 gene. The production of KmSOD1p in K. marxianus L3 and K. marxianus L3 (pYG-KmSOD1) in response to different compositions of the culture medium was evaluated. The highest specific activity (472 U(SOD) mg(prot) (-1)) and the highest volumetric yield (8.8 x 10(5) U(SOD) l(-1)) were obtained by the recombinant strain overexpressing KmSOD1 in the presence of Cu(2+) and Zn(2+) supplements to the culture media. The best performing culture conditions were positively applied to a laboratory scale fed-batch process reaching a volumetric yield of 1.4 x 10(6) U(SOD) l(-1)

Kinetics and metabolism of Bifidobacterium adolescentis MB 239 growing on glucose, galactose, lactose, and galactooligosaccharides

The kinetics and the metabolism of Bifidobacterium adolescentis MB 239 growing on galactooligosaccharides (GOS), lactose, galactose, and glucose were investigated. An unstructured unsegregated model for growth in batch cultures was developed, and kinetic parameters were calculated with a recursive algorithm. The growth rate and cellular yield were highest on galactose, followed by lactose and GOS, and were lowest on glucose. Lactate, acetate, and ethanol yields allowed the calculation of carbon fluxes toward fermentation products. Distributions between two- and three-carbon products were similar on all the carbohydrates (55 and 45%, respectively), but ethanol yields were different on glucose, GOS, lactose, and galactose, in decreasing order of production. Based on the stoichiometry of the fructose-6-phosphate shunt and on the carbon distribution among the products, the ATP yield was calculated. The highest yield was obtained on galactose, while the yields were 5, 8, and 25% lower on lactose, GOS, and glucose, respectively. Therefore, a correspondence among ethanol production, low ATP yields, and low biomass production was established, demonstrating that carbohydrate preferences may result from different distributions of carbon fluxes through the fermentative pathway. During the fermentation of a GOS mixture, substrate selectivity based on the degree of polymerization was exhibited, since lactose and the trisaccharide were the first to be consumed, while a delay was observed until longer oligosaccharides were utilized. Throughout the growth on both lactose and GOS, galactose accumulated in the cultural broth, suggesting that beta(1-4) galactosides can be hydrolyzed before they are taken up

The running of the electromagnetic coupling alpha in small-angle Bhabha scattering

A method to determine the running of alpha from a measurement of small-angle Bhabha scattering is proposed and worked out. The method is suited to high statistics experiments at e+e- colliders, which are equipped with luminometers in the appropriate angular region. A new simulation code predicting small-angle Bhabha scattering is also presentedComment: 15 pages, 3 Postscript figure

Identification of recurrent genetic patterns from targeted sequencing panels with advanced data science: a case-study on sporadic and genetic neurodegenerative diseases

open8noThis work is funded by the University of Bologna, the IRCCS Institute of Neurological sciences of Bologna, and by the European Grants H2020 GenoMed4All [AM1] (Grant N. 101017549) and H2020 MSCA-ITN IMforFUTURE (Grant N. 721815).Background Targeted Next Generation Sequencing is a common and powerful approach used in both clinical and research settings. However, at present, a large fraction of the acquired genetic information is not used since pathogenicity cannot be assessed for most variants. Further complicating this scenario is the increasingly frequent description of a poli/oligogenic pattern of inheritance showing the contribution of multiple variants in increasing disease risk. We present an approach in which the entire genetic information provided by target sequencing is transformed into binary data on which we performed statistical, machine learning, and network analyses to extract all valuable information from the entire genetic profile. To test this approach and unbiasedly explore the presence of recurrent genetic patterns, we studied a cohort of 112 patients affected either by genetic Creutzfeldt–Jakob (CJD) disease caused by two mutations in the PRNP gene (p.E200K and p.V210I) with different penetrance or by sporadic Alzheimer disease (sAD). Results Unsupervised methods can identify functionally relevant sources of variation in the data, like haplogroups and polymorphisms that do not follow Hardy–Weinberg equilibrium, such as the NOTCH3 rs11670823 (c.3837 + 21 T > A). Supervised classifiers can recognize clinical phenotypes with high accuracy based on the mutational profile of patients. In addition, we found a similar alteration of allele frequencies compared the European population in sporadic patients and in V210I-CJD, a poorly penetrant PRNP mutation, and sAD, suggesting shared oligogenic patterns in different types of dementia. Pathway enrichment and protein–protein interaction network revealed different altered pathways between the two PRNP mutations. Conclusions We propose this workflow as a possible approach to gain deeper insights into the genetic information derived from target sequencing, to identify recurrent genetic patterns and improve the understanding of complex diseases. This work could also represent a possible starting point of a predictive tool for personalized medicine and advanced diagnostic applications.openTarozzi, M.; Bartoletti-Stella, A.; Dall’Olio, D.; Matteuzzi, T.; Baiardi, S.; Parchi, P.; Castellani, G.; Capellari, S.Tarozzi, M.; Bartoletti-Stella, A.; Dall’Olio, D.; Matteuzzi, T.; Baiardi, S.; Parchi, P.; Castellani, G.; Capellari, S

Refractive index inhomogeneity within an aerogel block

Evaluating local inhomogeneities of the refractive index inside aerogel blocks to be used as Cherenkov radiator is important for a high energy physics experiment where angular resolution is crucial. Two approaches are described and compared. The first one is based on the bending of a laser beam induced by refractive index gradients along directions normal to the unperturbed optical path. The second method exploits the Cherenkov effect itself by shooting an ultra-relativistic collimated electron beam through different points of the aerogel surface. Local refractive index variations result in sizable differences in the Cherenkov photons distribution. © 2005 Elsevier B.V. All rights reserved

Gastrointestinal neuroendocrine neoplasms (GI-NENs): hot topics in morphological, functional, and prognostic imaging

Neuroendocrine neoplasms (NENs) are heterogeneous tumours with a common phenotype descended from the diffuse endocrine system. NENs are found nearly anywhere in the body but the most frequent location is the gastrointestinal tract. Gastrointestinal neuroendocrine neoplasms (GI-NENs) are rather uncommon, representing around 2% of all gastrointestinal tumours and 20–30% of all primary neoplasms of the small bowel. GI-NENs have various clinical manifestations due to the different substances they can produce; some of these tumours appear to be associated with familial syndromes, such as multiple endocrine neoplasm and neurofibromatosis type 1. The current WHO classification (2019) divides NENs into three major categories: well-differentiated NENs, poorly differentiated NENs, and mixed neuroendocrine-non-neuroendocrine neoplasms. The diagnosis, localization, and staging of GI-NENs include morphology and functional imaging, above all contrast-enhanced computed tomography (CECT), and in the field of nuclear medicine imaging, a key role is played by (68)Ga-labelled-somatostatin analogues ((68)Ga-DOTA-peptides) positron emission tomography/computed tomography (PET/TC). In this review of recent literature, we described the objectives of morphological/functional imaging and potential future possibilities of prognostic imaging in the assessment of GI-NENs