Evolving a lipase for hydrolysis of natural triglycerides along with enhanced tolerance towards a protease and surfactants

In the accompanying paper, we described evolving a lipase to the point where variants were soluble, stable and capable of degrading C8 TAG and C8 esters. These variants were tested for their ability to survive in an environment that might be encountered in a washing machine. Unfortunately, they were inactivated both by treatment with a protease used in laundry detergents and by very low concentrations of sodium dodecyl sulfate (SDS). In addition, all the variants had very low levels of activity with triglycerides with long aliphatic chains and with naturally occurring oils, like olive oil. Directed evolution was used to select variants with enhanced properties. In the first 10 rounds of evolution, the primary screen was selected for variants capable of hydrolyzing olive oil whereas the secondary screen was selected for enhanced tolerance towards a protease and SDS. In the final six rounds of evolution, the primary and secondary screens identified variants that retained activity after treatment with SDS. Sixteen cycles of evolution gave variants with greatly enhanced lipolytic activity on substrates that had both long (C16 and C18) as well as short (C3 and C8) chains. We found variants that were stable for more than 3 hours in protease concentrations that rapidly degrade the wild-type enzyme. Enhanced tolerance towards SDS was found in variants that could break down naturally occurring lipid and resist protease attack. The amino acid changes that gave enhanced properties were concentrated in the cap domain responsible for substrate binding

Improving on nature's shortcomings: evolving a lipase for increased lipolytic activity, expression and thermostability.

An enzyme must be soluble, stable, active and easy to produce to be useful in industrial applications. Not all enzymes possess these attributes. We set out to determine how many changes are required to convert an enzyme with poor properties into one that has useful properties. Lipase Lip3 from Drosophila melanogaster had been previously optimised for expression in Escherichia coli. The expression levels were good, but Lip3 was mainly insoluble with poor activity. Directed evolution was used to identify variants with enhanced activity along with improved solubility. Five variants and the wild-type (wt) enzyme were purified and characterised. The yield of the wt enzyme was just 2.2 mg/L of culture, while a variant, produced under the same conditions, gave 351 mg. The improvement of activity of the best variant was 200 times higher than that of the wt when the crude lysates were analysed using pNP-C8, but with purified protein, the improvement observed was 1.5 times higher. This means that most of the increase of activity is due to increase in solubility and stability. All the purified variants showed increased thermal stability compared with the wt enzyme that had a T1/2 of 37°C, while the mutant with P291L of 42.2°C and the mutant R7_47D with five mutations had a value of 52.9°C, corresponding to an improvement of 16°C. The improved variants had between five and nine changes compared with the wt enzyme. There were four changes that were found in all 30 final round variants for which sequences were obtained; three of these changes were found in the substrate-binding domain

Classification tools for carotenoid content estimation in Manihot esculenta via metabolomics and machine learning

Cassava genotypes (Manihot esculenta Crantz) with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The color variability of cassava roots, which can vary from white to red, is related to the presence of several carotenoid pigments. The present study has shown how CIELAB color measurement on cassava roots tissue can be used as a non-destructive and very fast technique to quantify the levels of carotenoids in cassava root samples, avoiding the use of more expensive analytical techniques for compound quantification, such as UV-visible spectrophotometry and the HPLC. For this, we used machine learning techniques, associating the colorimetric data (CIELAB) with the data obtained by UV-vis and HPLC, to obtain models of prediction of carotenoids for this type of biomass. Best values of R2 (above 90%) were observed for the predictive variable TCC determined by UV-vis spectrophotometry. When we tested the machine learning models using the CIELAB values as inputs, for the total carotenoids contents quantified by HPLC, the Partial Least Squares (PLS), Support Vector Machines, and Elastic Net models presented the best values of R2 (above 40%) and Root-Mean-Square Error (RMSE). For the carotenoid quantification by UV-vis spectrophotometry, R2 (around 60%) and RMSE values (around 6.5) are more satisfactory. Ridge regression and Elastic Network showed the best results. It can be concluded that the use colorimetric technique (CIELAB) associated with UV-vis/HPLC and statistical techniques of prognostic analysis through machine learning can predict the content of total carotenoids in these samples, with good precision and accuracy.CAPES -Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(407323/2013-9)info:eu-repo/semantics/publishedVersio

El orden Carnivora (Mammalia) en el Perú: Estado del conocimiento y prioridades de investigación para su conservación

The high diversity of Peruvian carnivore species may pose problems when deciding to which taxa and topics new research efforts should be directed. In this publication, we evaluated the research effort made on each taxa -by assessing the number of publications per species-, point out the knowledge gaps that are important to the conservation of each species and present the first evaluation of research priorities for this group of animals to the country. We registered 145 publications about Peruvian carnivores made since 1943. The number of publications is significantly different between taxa, between subjects and between ecoregions where the research was conducted. According to the proposed priority scale, the species to be studied with greater priority is Nasua olivacea and the lowest priority is for Leopardus pardalis. The results of our study highlight the urgent need to conduct research on certain species of carnivores about which there are few published data, locally and globally, and which occupy a low number of ecoregions in the country. Both the scale of research priorities and the list of knowledge gaps presented here will be useful to guide logistical and financial efforts, for individual researchers as well as for private or governmental institutions.La alta diversidad de especies de carnívoros del Perú puede generar problemas al momento de decidir los taxa y temas sobre los que deben dirigirse los esfuerzos de investigación. En este trabajo se evalúa el esfuerzo de investigación en base al número de publicaciones realizadas para cada familia y especie de carnívoro en el Perú. Asimismo, se señalan los vacíos de información relevantes para la conservación de cada especie y se presenta la primera evaluación de las prioridades de investigación sobre este grupo animal en el Perú. Se registró 145 publicaciones sobre carnívoros peruanos realizadas desde el año 1943. El número de publicaciones presentó grandes diferencias entre taxa, entre temas estudiados y entre las ecorregiones en las que se realizaron las investigaciones. Según la escala de prioridades propuesta, la especie que debe ser estudiada con mayor prioridad es el coatí andino Nasua olivacea y la de menor prioridad es el ocelote Leopardus pardalis. Los resultados de nuestro trabajo resaltan la urgencia de realizar investigaciones sobre ciertas especies de carnívoros de las que existen pocos datos publicados, tanto a nivel local como global, y que se distribuyen en pocas ecorregiones del Perú. Tanto la escala de prioridades de investigación como la lista de vacíos de información serán de utilidad para guiar esfuerzos logísticos y financieros de investigadores particulares, instituciones privadas y gubernamentales.

Estimating the herd immunity threshold by accounting for the hidden asymptomatics using a COVID-19 specific model

A quantitative COVID-19 model that incorporates hidden asymptomatic patients is developed, and an analytic solution in parametric form is given. The model incorporates the impact of lock-down and resulting spatial migration of population due to announcement of lock-down. A method is presented for estimating the model parameters from real-world data, and it is shown that the various phases in the observed epidemiological data are captured well. It is shown that increase of infections slows down and herd immunity is achieved when active symptomatic patients are 10-25% of the population for the four countries we studied. Finally, a method for estimating the number of asymptomatic patients, who have been the key hidden link in the spread of the infections, is presented. © 2020 Kaushal et al

Cigarette smoking alters sialylation in the Fallopian tube of women, with implications for the pathogenesis of ectopic pregnancy

Sialylation creates a negative charge on the cell surface that can interfere with blastocyst implantation. For example, α2,6-sialylation on terminal galactose, catalyzed by the sialyltransferase ST6GAL1, inhibits the binding of galectin-1, a β-galactoside-binding lectin. We recently reported the potential involvement of galectin-1 and -3 in the pathogenesis of tubal ectopic pregnancy; however, the precise role of galectins and their ligand glycoconjugates remain unclear. Here, we investigated the expression of the genes encoding α2,3- and α2,6-galactoside sialyltransferases (ST3GAL1−6 and ST6GAL1−2) and the localization of sialic acids in the Fallopian tube of women with or without ectopic implantation. ST6GAL1 expression was higher in the mid-secretory phase than the proliferative phase of non-pregnant women (P < 0.0001), whereas ST6GAL1 (P < 0.0001), ST3GAL3 (P = 0.0029), ST3GAL5 (P = 0.0089), and ST3GAL6 (P = 0.0018) were all lower in Fallopian tubes with ectopic implantations. α2,3- and α2,6-sialic acids, however, both remained enriched on the surface of Fallopian tube epithelium. Cigarette smoking, a major risk factor for tubal ectopic pregnancy, was associated with reduced mid-secretory-phase expression of ST6GAL1 (P = 0.0298), but elevated expression of ST3GAL5 (P = 0.0006), an enzyme known to be involved in ciliogenesis. Indeed, sialic acid-containing ciliated inclusion cysts, which are associated with abnormal ciliogenesis, were observed within the epithelium at a higher frequency in women who smoked (P = 0.0177), suggesting that abnormal ciliogenesis is associated with smoking. Thus, cigarette smoking alters sialylation in the Fallopian tube epithelium, and is potentially a source of decreased tubal transport and increased receptivity for blastocyst in the human Fallopian tube

A preliminary study of genetic factors that influence susceptibility to bovine tuberculosis in the British cattle herd

Associations between specific host genes and susceptibility to Mycobacterial infections such as tuberculosis have been reported in several species. Bovine tuberculosis (bTB) impacts greatly the UK cattle industry, yet genetic predispositions have yet to be identified. We therefore used a candidate gene approach to study 384 cattle of which 160 had reacted positively to an antigenic skin test (‘reactors’). Our approach was unusual in that it used microsatellite markers, embraced high breed diversity and focused particularly on detecting genes showing heterozygote advantage, a mode of action often overlooked in SNP-based studies. A panel of neutral markers was used to control for population substructure and using a general linear model-based approach we were also able to control for age. We found that substructure was surprisingly weak and identified two genomic regions that were strongly associated with reactor status, identified by markers INRA111 and BMS2753. In general the strength of association detected tended to vary depending on whether age was included in the model. At INRA111 a single genotype appears strongly protective with an overall odds ratio of 2.2, the effect being consistent across nine diverse breeds. Our results suggest that breeding strategies could be devised that would appreciably increase genetic resistance of cattle to bTB (strictly, reduce the frequency of incidence of reactors) with implications for the current debate concerning badger-culling

Constraining the dark energy equation of state with H ii galaxies

This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/mnras/stw1813We use the H II galaxies L–σ relation and the resulting Hubble expansion cosmological probe of a sample of just 25 high-z (up to z ∼ 2.33) H II galaxies, in a joint likelihood analysis with other well tested cosmological probes (cosmic microwave background, CMB, Baryon Acoustic Oscillations, BAOs) in an attempt to constrain the dark energy equation of state (EoS). The constraints, although still weak, are in excellent agreement with those of a similar joint analysis using the well established SNIa Hubble expansion probe. Interestingly, even with the current small number of available high redshift H II galaxies, the H II/BAO/CMB joint analysis gives a 13 per cent improvement of the quintessence dark energy cosmological constraints compared to the BAO/CMB joint analysis. We have further performed extensive Monte Carlo simulations, with a realistic redshift sampling, to explore the extent to which the use of the L–σ relation, observed in H II galaxies, can constrain effectively the parameter space of the dark energy EoS. The simulations predict substantial improvement in the constraints when increasing the sample of high-z H II galaxies to 500, a goal that can be achieved in reasonable observing times with existing large telescopes and state-of-the-art instrumentation.RC, RT, ET and MP are grateful to the Mexican research council (CONACYT) for supporting this research under studentship 224117 and grants 263561, CB-2005-01-49847, CB-2007-01-84746 and CB-2008-103365-F. SB acknowledges support by the Research Center for Astronomy of the Academy of Athens in the context of the programme ‘Tracing the Cosmic Acceleration’. MP acknowledges the hospitality of the KAVLI Institute for Cosmology in Cambridge, where this work was completed

Optimizing the mix design of cold bitumen emulsion mixtures using response surface methodology

Cold mix asphalt (CMA) has been increasingly recognized as an important alternative worldwide. One of the common types of CMA is cold bitumen emulsion mixture (CBEM). In the present study, the optimization of CBEM has been investigated, to determine optimum proportions to gain suitable levels of both mechanical and volumetric properties. A central composite design (CCD) with response surface methodology (RSM) was applied to optimize the mix design parameters, namely bitumen emulsion content (BEC), pre-wetting water content (PWC) and curing temperature (CT). This work aimed to investigate the interaction effect between these parameters on the mechanical and volumetric properties of CBEMs. The indirect tensile stiffness modulus (ITSM) and indirect tensile strength (ITS) tests were performed to obtain the mechanical response while air voids and dry density were measured to obtain volumetric responses. The results indicate that the interaction of BEC, PWC and CT influences the mechanical properties of CBEM. However, the PWC tended to influence the volumetric properties more significantly than BEC. The individual effects of BEC and PWC are important, rather than simply total fluid content which is used in conventional mix design method. Also, the results show only limited variation in optimum mix design proportions (BEC and PWC) over a range of CT from 10oC to 30oC. The variation range for optimum BEC was 0.42% and 0.20% for PWC. Furthermore, the experimental results for the optimum mix design were corresponded well with model predictions. It was concluded that optimization using RSM is an effective approach for mix design of CBEMs

Phenethyisoquinoline alkaloids from the leaves of Androcymbium palaestinum

Thirteen compounds were isolated from the methanolic extract of the leaves of Androcymbium palaestinum Baker (Colchicaceae). Of these, three were new, two were new natural products, and eight were known. The new isolated compounds were (+)-1-demethylandrocine (5), (−)-andropalaestine (8), and (+)-2-demethyl-β-lumicolchicone (10), while the new natural products were (+)-O-methylkreysigine-N-oxide (3) and (+)-O,O-dimethylautumnaline (9). Moreover, two known compounds are reported for the first time from this species, specifically (−)-colchicine (11) and (−)-3-demethyldemecolcine (13). The structures of the isolated compounds were elucidated using a series of spectroscopic and spectrometric techniques, principally HRESIMS, 1D-NMR (1H and 13C NMR) and 2D-NMR (COSY, edited-HSQC, and HMBC). ECD spectroscopy was used for assigning the absolute configurations of compounds 3, 5, and 10. The cytotoxic activities of the isolated compounds were evaluated using the MDA-MB-435 (melanoma), MDA-MB-231 (breast), and OVCAR3 (ovary) cancer cell lines. Compound 11 was the most potent against all tested cell lines, with IC50 values of 12, 95 and 23 nM, respectively.This research was supported, in part, by the Deanship of Research, Jordan University of Science and Technology, Irbid, Jordan (Grant No. 258/2017) and the National Cancer Institute/National Institutes of Health, Bethesda, MD, USA via P01 CA125066. We thank Dr. L. Flores Bocanegra, J. M. Gallagher, Z. Y. Al Subeh, and Dr. N. D. Paguigan from UNCG for technical help and valuable suggestions. This work was performed in part at the Joint School of Nanoscience and Nanoengineering, a member of the Southeastern Nanotechnology Infrastructure Corridor (SENIC) and National Nanotechnology Coordinated Infrastructure (NNCI), which is supported by the National Science Foundation (Grant ECCS-1542174)