Computational design of catalytically active TIM barrel xylanases

TIM barrel enzymes perform five out of six Enzyme Commission (EC) reaction classes, and are therefore one of the most promising class of enzymes for computational design. Up until now, chimeric TIM barrels were made out of half barrels and catalytic activity was installed using laborious rounds of random mutagenesis, selection and rational design, whereas a recently described de novo designed TIM barrel lacked the elaborate loop conformations necessary to install catalytic activity, and indeed did not show activity. In order to design catalytically active TIM barrel glycoside-hydrolase 10 family xylanases, we sampled diverse protein backbone conformations, in some cases generating completely new combinations of backbones at all eight beta-alpha blades, and optimized the sequence for both protein stability and catalytic activity. We then selected structurally diverse, low energy subset of the designs for further characterization. Designs had \u3c60% sequence identity to natural xylanases, incorporating many insertions and deletions in loop regions. All designs expressed well and 30% showed catalytic activity, the most active one having Kcat/Km = 106. The design process samples extensively the sequence-structure space and the designs can serve as a library for altered enzyme selectivity. Moreover, our algorithm is general and robust, and can be applied to other TIM barrel enzyme families having a few dozen solved structures and to other modular protein folds

Quantifying Long-Term Urban Grassland Dynamics: Biotic Homogenization and Extinction Debts

Sustainable urban nature conservation calls for a rethinking of conventional approaches. Traditionally, conservationists have not incorporated the history of the landscape in management strategies. This study shows that extant vegetation patterns are correlated to past landscapes indicating potential extinction debts. We calculated urban landscape measures for seven time periods (1938–2019) and correlated it to three vegetation sampling events (1995, 2012, 2019) using GLM models. We also tested whether urban vegetation was homogenizing. Our results indicated that urban vegetation in our study area is not currently homogenizing but that indigenous forb species richness is declining significantly. Furthermore, long-term studies are essential as the time lags identified for different vegetation sampling periods changed as well as the drivers best predicting these changes. Understanding these dynamics are critical to ensuring sustainable conservation of urban vegetation for future citizens

A combined computational-experimental approach to define the structural origin of antibody recognition of sialyl-Tn, a tumor-associated carbohydrate antigen.

Anti-carbohydrate monoclonal antibodies (mAbs) hold great promise as cancer therapeutics and diagnostics. However, their specificity can be mixed, and detailed characterization is problematic, because antibody-glycan complexes are challenging to crystallize. Here, we developed a generalizable approach employing high-throughput techniques for characterizing the structure and specificity of such mAbs, and applied it to the mAb TKH2 developed against the tumor-associated carbohydrate antigen sialyl-Tn (STn). The mAb specificity was defined by apparent KD values determined by quantitative glycan microarray screening. Key residues in the antibody combining site were identified by site-directed mutagenesis, and the glycan-antigen contact surface was defined using saturation transfer difference NMR (STD-NMR). These features were then employed as metrics for selecting the optimal 3D-model of the antibody-glycan complex, out of thousands plausible options generated by automated docking and molecular dynamics simulation. STn-specificity was further validated by computationally screening of the selected antibody 3D-model against the human sialyl-Tn-glycome. This computational-experimental approach would allow rational design of potent antibodies targeting carbohydrates

On the convergence of gaussian belief propagation with nodes of arbitrary size

CITATION: Kamper, F., Steel, S. J. & Du Preez, J. A. 2019. On the convergence of Gaussian belief propagation with nodes of arbitrary size. Journal of Machine Learning Research, 20(165):1-37.The original publication is available at http://jmlr.orgThis paper is concerned with a multivariate extension of Gaussian message passing applied to pairwise Markov graphs (MGs). Gaussian message passing applied to pairwise MGs is often labeled Gaussian belief propagation (GaBP) and can be used to approximate the marginal of each variable contained in the pairwise MG. We propose a multivariate extension of GaBP (we label this GaBP-m) that can be used to estimate higher-dimensional marginals. Beyond the ability to estimate higher-dimensional marginals, GaBP-m exhibits better convergence behavior than GaBP, and can also provide more accurate univariate marginals. The theoretical results of this paper are based on an extension of the computation tree analysis conducted on univariate nodes to the multivariate case. The main contribution of this paper is the development of a convergence condition for GaBP-m that moves beyond the walk-summability of the precision matrix. Based on this convergence condition, we derived an upper bound for the number of iterations required for convergence of the GaBP-m algorithm. An upper bound on the dissimilarity between the approximate and exact marginal covariance matrices was established. We argue that GaBP-m is robust towards a certain change in variables, a property not shared by iterative solvers of linear systems, such as the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods. The advantages of using GaBP-m over GaBP are also illustrated empirically.https://www.jmlr.org/papers/v20/18-040.htmlPublisher's versio

Metagenomics Reveals Bacterial and Archaeal Adaptation to Urban Land-Use : N Catabolism, Methanogenesis, and Nutrient Acquisition

Urbanization results in the systemic conversion of land-use, driving habitat and biodiversity loss. The "urban convergence hypothesis" posits that urbanization represents a merging of habitat characteristics, in turn driving physiological and functional responses within the biotic community. To test this hypothesis, we sampled five cities (Baltimore, MD, United States; Helsinki and Lahti, Finland; Budapest, Hungary; Potchefstroom, South Africa) across four different biomes. Within each city, we sampled four land-use categories that represented a gradient of increasing disturbance and management (from least intervention to highest disturbance: reference, remnant, turf/lawn, and ruderal). Previously, we used amplicon sequencing that targeted bacteria/archaea (16S rRNA) and fungi (ITS) and reported convergence in the archaeal community. Here, we applied shotgun metagenomic sequencing and QPCR of functional genes to the same soil DNA extracts to test convergence in microbial function. Our results suggest that urban land-use drives changes in gene abundance related to both the soil N and C metabolism. Our updated analysis found taxonomic convergence in both the archaeal and bacterial community (16S amplicon data). Convergence of the archaea was driven by increased abundance of ammonia oxidizing archaea and genes for ammonia oxidation (QPCR and shotgun metagenomics). The proliferation of ammonia-oxidizers under turf and ruderal land-use likely also contributes to the previously documented convergence of soil mineral N pools. We also found a higher relative abundance of methanogens (amplicon sequencing), a higher relative abundance of gene sequences putatively identified as Ni-Fe hydrogenase and nickel uptake (shotgun metagenomics) under urban land-use; and a convergence of gene sequences putatively identified as contributing to the nickel transport function under urban turf sites. High levels of disturbance lead to a higher relative abundance of gene sequences putatively identified as multiple antibiotic resistance protein marA and multidrug efflux pump mexD, but did not lead to an overall convergence in antibiotic resistance gene sequences.Peer reviewe

Earthworm assemblages in urban habitats across biogeographical regions

In urban landscapes, humans are the most significant factor determining belowground diversity, including earthworms. Within the framework of the Global Urban Soil Ecology and Education Network (GLUSEEN), a multi-city comparison was carried out to assess the effects of soil disturbance on earthworms. In each of five cities (Baltimore, USA; Budapest, Hungary; Helsinki and Lahti, Finland; Potchefstroom, South Africa), covering four climatic and biogeographical regions, four habitat types (ruderal, turf/lawn, remnant and reference) were sampled. The survey resulted in 19 species belonging to 9 genera and 4 families. The highest total species richness was recorded in Baltimore (16), while Budapest and the Finnish cities had relatively low (5–6) species numbers. Remnant forests and lawns supported the highest earthworm biomass. Soil properties (i.e. pH and organic matter content) explained neither earthworm community composition nor abundance. Evaluating all cities together, earthworm communities were significantly structured by habitat type. Communities in the two adjacent cities, Helsinki and Lahti were very similar, but Budapest clearly separated from the Finnish cities. Earthworm community structure in Baltimore overlapped with that of the other cities. Despite differences in climate, soils and biogeography among the cities, earthworm communities were highly similar within the urban habitat types. This indicates that human-mediated dispersal is an important factor shaping the urban fauna, both at local and regional scales.Peer reviewe

Adrenocorticotrophic hormone-stimulated cortisol release by the head kidney inter-renal tissue from sea bream (Sparus aurata) fed with linseed oil and soyabean oil

The mode of action of highly unsaturated fatty acids (HUFA) in regulating gilthead sea bream (Sparus aurata) head kidney (HK) cortisol production was studied through in vitro trials using a dynamic superfusion system. Fish were previously fed with different diets containing several inclusion levels of linseed oil (LO) or soyabean oil (SO) for 26 weeks. Five diets were tested; anchovy oil was the only lipid source for the control diet (fish oil, FO) and two different substitution levels (70 and 100 %) were tested using either LO or SO (70LO, 70SO, 100LO and 100SO). Fatty acid compositions of the HK reflected the dietary input, thus EPA, DHA, arachidonic acid and n-3 HUFA were significantly (P,0·05) reduced in fish fed vegetable oils compared with fish fed the FO diet. Feeding 70 or 100% LO increased significantly (P,0·05) cortisol release in HK after stimulation with adrenocorticotrophic hormone (ACTH), while feeding SO had no effect on this response. Cortisol stimulation factor (SF) was increased in fish fed the 70LO and 100LO diets compared with fish fed the control diet. Moreover, eicosanoid inhibition by incubating the HK tissue with indomethacin (INDO) as a cyclo-oxygenase (COX) inhibitor, or nordihydroguaiaretic acid (NDGA) as a lipoxygenase (LOX) inhibitor, significantly reduced (P,0·05) the cortisol release after ACTH stimulation in the 70LO and 100LO diets. Cortisol SF was reduced in the FO, 70LO and 100LO diets when incubating the HK with INDO or NDGA, while it was increased in the 70SO diet. The present results indicate that changing the fatty acid profile of gilthead sea bream HK by including LO and/or SO in the fish diet affected the in vitro cortisol release, and this effect is partly mediated by COX and/or LOX metabolites

3D-QSAR and docking studies of pentacycloundecylamines at the sigma-1 (σ1) receptor

Pentacycloundecylamine (PCU) derived compounds have been shown to be promising lead structures for the development of novel drug candidates aimed at a variety of neurodegenerative and psychiatric diseases. Here we show for the first time a 3D quantitative structure–activity relationship (3D-QSAR) for a series of aza-PCU-derived compounds with activity at the sigma-1 (r1) receptor. A comparative molecular field analysis (CoMFA) model was developed with a partial least squares cross validated (q2) regression value of 0.6, and a non-cross validatedr2 of 0.9. The CoMFA model was effective at predicting the sigma-1 activities of atest set with an r2 >0.7. We also describe here the docking of the PCU-derivedcompounds into a homology model of the sigma-1 (r1) receptor, which was developed to gain insight into binding of these cage compounds to the receptor. Based on docking studies we evaluated in a [3H]pentazocine binding assay anoxa-PCU, NGP1-01 (IC50 = 1.78 lM) and its phenethyl derivative (IC50 = 1.54 lM). Results from these studies can be used to develop new compounds with specific affinity for the sigma-1(r1)Web of Scienc