a Extracellular processes in wastewater treatment

PhD ThesisOne of the limitations of low-temperature anaerobic treatment of domestic wastewater is poor lipid degradation. Even when psychrophiles are used as an inoculum, the lipids degrade relatively less than carbohydrates and proteins. The first step towards the rational engineering of lipolysis in any system is to identify the lipolytic bacteria. In this study the combination of metagenomics and metaproteomics is used to screen for potential and actual lipolytic bacteria and their extracellular lipases in anaerobic membrane bioreactors treating domestic wastewater at 4℃ and 15℃. The reactors were inoculated by psychrophilic biomass collected from the sediment and soils of Lake Geneva, Switzerland (annual temperature range -11 – 21 °C) and Svalbard, Norway (annual temperature range - 16 – 6 °C), respectively. The feed of the reactors was primary influent collected from an activated sludge plant. The bacterial psychrophilic community and their lipases at 4℃ and 15℃ were compared. Of the 40 recovered putative lipolytic metagenome-assembled genomes (MAGs), only three (Chlorobium, Desulfobacter, and Mycolicibacterium) were common and abundant (relative abundance ≥ 1%) in all reactors. Notably, some MAGs that represented aerobic autotrophs (Nitrosomonas) contained lipases. Therefore, the lipases found may not always be associated with exogenous lipid degradation and may have other roles such as polyhydroxyalkanoates accumulation/degradation and interference with the outer membranes of other bacteria. Different protein classification tools were used for the putative lipase sequences identified by metagenomics to verify if they have potential lipolytic activity. None of the current tools, including InterProScan, could precisely assign lipolytic activity to these sequences. Enrichment of public databases by lipase sequences that have been experimentally tested can alleviate this problem. Metaproteomics did not provide sufficient proteome coverage for relatively lower abundant proteins such as lipases. The expression of fadL genes (long-chain fatty acid transporters) was confirmed for four genera (Dechloromonas, Azoarcus, Aeromonas and Sulfurimonas), but none of them was recovered as putative lipolytic MAGs. Metaproteomics also confirmed the presence of 15 relatively abundant (≥1%) genera in all reactors, of which at least 6 can potentially accumulate lipid/polyhydroxyalkanoates. For most putative lipolytic MAGs, there was no statistically significant correlation between the read abundance and ii reactor conditions such as temperature, phase (biofilm and bulk liquid), and feed type (treated by ultraviolet light or not). Reactor temperature had no statistical correlation with the length of the lipases either. Results obtained by metagenomics and metaproteomics did not confirm each other and further work is required to identify the true lipid degraders in these systems

Effect of anions interaction on the removal efficiency of nanofilters for the potable water treatment

The interaction between the ions and the charge of membranes can affect the efficiency of pollutant removal. The present study investigated the removal efficiency of hexavalent chromium and nitrate ions from both actual and synthetic contaminated water via two different commercial spiral wound polyamide nanofilters. In addition, the interaction of ions under different experimental conditions was investigated by using a Box-Behnken design (BBD). The Box–Behnken design optimized the contributing factors which included pH (5-9), the initial concentration of Cr (VI) (0.05-5 mg/L) and the initial concentration of nitrate (40-160 mg/L). The maximum removal efficiency of both Cr (VI) and nitrate was achieved at a pH of 9.0, as 99 % and 90 % for the Iranian nanofilter (NF-I) and 98 % and 82 % for the Korean nanofilter (NF-K), respectively. The results also indicated that as the initial concentration of Cr (VI) increased, the removal efficiency was enhanced while the removal efficiency of nitrate decreased according to the pH. However, by increasing the initial concentration of nitrate, the removal efficiency of both the Cr (VI) and nitrate increased. For actual water samples at an optimum pressure of 0.6 Mpa (NF-K) and 0.8 Mpa (NF-I), the removal efficiency of Cr(VI) and nitrate obtained was 95% and 76 % for the NF-K and 97 % and 86 % for the NF-I, respectively

An Application of Manifold Learning in Global Shape Descriptors

With the rapid expansion of applied 3D computational vision, shape descriptors have become increasingly important for a wide variety of applications and objects from molecules to planets. Appropriate shape descriptors are critical for accurate (and efficient) shape retrieval and 3D model classification. Several spectral-based shape descriptors have been introduced by solving various physical equations over a 3D surface model. In this paper, for the first time, we incorporate a specific manifold learning technique, introduced in statistics and machine learning, to develop a global, spectral-based shape descriptor in the computer graphics domain. The proposed descriptor utilizes the Laplacian Eigenmap technique in which the Laplacian eigenvalue problem is discretized using an exponential weighting scheme. As a result, our descriptor eliminates the limitations tied to the existing spectral descriptors, namely dependency on triangular mesh representation and high intra-class quality of 3D models. We also present a straightforward normalization method to obtain a scale-invariant and noise-resistant descriptor. The extensive experiments performed in this study using two standard 3D shape benchmarks—high-resolution TOSCA and McGill datasets—demonstrate that the present contribution provides a highly discriminative and robust shape descriptor under the presence of a high level of noise, random scale variations, and low sampling rate, in addition to the known isometric-invariance property of the Laplace–Beltrami operator. The proposed method significantly outperforms state-of-the-art spectral descriptors in shape retrieval and classification. The proposed descriptor is limited to closed manifolds due to its inherited inability to accurately handle manifolds with boundaries

Multi-Modal Medical Image Registration with Full or Partial Data: A Manifold Learning Approach

Multi-modal image registration is the primary step in integrating information stored in two or more images, which are captured using multiple imaging modalities. In addition to intensity variations and structural differences between images, they may have partial or full overlap, which adds an extra hurdle to the success of registration process. In this contribution, we propose a multi-modal to mono-modal transformation method that facilitates direct application of well-founded mono-modal registration methods in order to obtain accurate alignment of multi-modal images in both cases, with complete (full) and incomplete (partial) overlap. The proposed transformation facilitates recovering strong scales, rotations, and translations. We explain the method thoroughly and discuss the choice of parameters. For evaluation purposes, the effectiveness of the proposed method is examined and compared with widely used information theory-based techniques using simulated and clinical human brain images with full data. Using RIRE dataset, mean absolute error of 1.37, 1.00, and 1.41 mm are obtained for registering CT images with PD-, T1-, and T2-MRIs, respectively. In the end, we empirically investigate the efficacy of the proposed transformation in registering multi-modal partially overlapped images

Looking for lipases and lipolytic organisms in low-temperature anaerobic reactors treating domestic wastewater

Poor lipid degradation limits low-temperature anaerobic treatment of domestic wastewater even when psychrophiles are used. We combined metagenomics and metaproteomics to find lipolytic bacteria and their potential, and actual, cold-adapted extracellular lipases in anaerobic membrane bioreactors treating domestic wastewater at 4 and 15 °C. Of the 40 recovered putative lipolytic metagenome-assembled genomes (MAGs), only three (Chlorobium, Desulfobacter, and Mycolicibacterium) were common and abundant (relative abundance ≥ 1%) in all reactors. Notably, some MAGs that represented aerobic autotrophs contained lipases. Therefore, we hypothesised that the lipases we found are not always associated with exogenous lipid degradation and can have other roles such as polyhydroxyalkanoates (PHA) accumulation/degradation and interference with the outer membranes of other bacteria. Metaproteomics did not provide sufficient proteome coverage for relatively lower abundant proteins such as lipases though the expression of fadL genes, long-chain fatty acid transporters, was confirmed for four genera (Dechloromonas, Azoarcus, Aeromonas and Sulfurimonas), none of which were recovered as putative lipolytic MAGs. Metaproteomics also confirmed the presence of 15 relatively abundant (≥ 1%) genera in all reactors, of which at least 6 can potentially accumulate lipid/polyhydroxyalkanoates. For most putative lipolytic MAGs, there was no statistically significant correlation between the read abundance and reactor conditions such as temperature, phase (biofilm and bulk liquid), and feed type (treated by ultraviolet light or not). Results obtained by metagenomics and metaproteomics did not confirm each other and extracellular lipases and lipolytic bacteria were not easily identifiable in the anaerobic membrane reactors used in this study. Further work is required to identify the true lipid degraders in these systems.BT/Environmental Biotechnolog