Evaluation and improvements of clustering algorithms for detecting remote homologous protein families.

BACKGROUND: An important problem in computational biology is the automatic detection of protein families (groups of homologous sequences). Clustering sequences into families is at the heart of most comparative studies dealing with protein evolution, structure, and function. Many methods have been developed for this task, and they perform reasonably well (over 0.88 of F-measure) when grouping proteins with high sequence identity. However, for highly diverged proteins the performance of these methods can be much lower, mainly because a common evolutionary origin is not deduced directly from sequence similarity. To the best of our knowledge, a systematic evaluation of clustering methods over distant homologous proteins is still lacking. RESULTS: We performed a comparative assessment of four clustering algorithms: Markov Clustering (MCL), Transitive Clustering (TransClust), Spectral Clustering of Protein Sequences (SCPS), and High-Fidelity clustering of protein sequences (HiFix), considering several datasets with different levels of sequence similarity. Two types of similarity measures, required by the clustering sequence methods, were used to evaluate the performance of the algorithms: the standard measure obtained from sequence-sequence comparisons, and a novel measure based on profile-profile comparisons, used here for the first time. CONCLUSIONS: The results reveal low clustering performance for the highly divergent datasets when the standard measure was used. However, the novel measure based on profile-profile comparisons substantially improved the performance of the four methods, especially when very low sequence identity datasets were evaluated. We also performed a parameter optimization step to determine the best configuration for each clustering method. We found that TransClust clearly outperformed the other methods for most datasets. This work also provides guidelines for the practical application of clustering sequence methods aimed at detecting accurately groups of related protein sequences.

Combining and concentrating nanocelluloses for cryogels with remarkable strength and wet resilience.

Cellulose cryogels are promising eco-friendly materials that exhibit low density, high porosity, and renewability. However, the applications of these materials are limited by their lower mechanical and water resistance compared to petrochemical-based lightweight materials. In this work, nanocelluloses were functionalized with cationic and anionic groups, and these nanomaterials were combined to obtain strong and water-resilient cryogels. To prepare the cryogels, anionic and cationic micro- and nanofibrils (CNFs) were produced at three different sizes and combined in various weight ratios, forming electrostatic complexes. The complex phase was concentrated by centrifugation and freeze-dried. Porous and open cellular structures were assembled in all compositions tested (porosity >90 %). Compressive testing revealed that the most resistant cryogels (1.7 MPa) were obtained with equivalent amounts of negatively and positively charged CNFs with lengths between 100 and 1200 nm. The strength at this condition was achieved as CNF electrostatic complexes assembled in thick cells, as observed by synchrotron X-ray tomography. In addition to mechanical strength, electrostatic complexation provided remarkable structural stability in water for the CNF cryogels, without compromising their biodegradability. This route by electrostatic complexation is a practical strategy to combine and concentrate nanocelluloses to tailor biodegradable lightweight materials with high strength and wet stability.

Corona-treated polyethylene films are macroscopic charge bilayers.

Top and bottom surfaces of polyethylene (PE) films exposed to corona discharge display large and opposite electrostatic potentials, forming an electric bilayer in agreement with recent and unexpected findings from Zhiqiang et al. Water wetting, chemical composition and roughness of the two surfaces are different. Surprisingly, the bottom surface, opposite to the corona electrode is charged but it is not oxidized, neither is it wetted with water. Moreover, its morphology is unaltered by charging, while the hydrophilic top surface is much rougher with protruding islands that are the result of oxidation followed by phase separation and polymer-polymer dewetting. Common liquids extract the oxidized, hydrophilic material formed at the upper surface, a result that explains the well-known sensitivity of adhesive joints made using corona-treated thermoplastics to liquids, especially water. These results show that poling the surface closer to the corona electrode triggers another but different charge build-up process at the opposite surface. The outcome is another poled PE surface showing high potential but with unchanged chemical composition, morphology and wetting behavior as the pristine surface, thus opening new possibilities for surface engineering.

Stabilizing both oil droplets and titanium dioxide nanoparticles in aqueous dispersion with nanofibrillated cellulose.

Nanocellulose is a well-known stabilizer for several colloidal dispersions, including emulsions and solid nanoparticles, replacing surfactants, polymers, and other additives, and therefore providing more minimalistic and eco-friendly formulations. However, could this ability be extended to stabilize oil droplets and inorganic nanoparticles simultaneously in the same colloidal system? This work aimed to answer this question. We evaluated both cationic and anionic nanofibrillated celluloses to stabilize both titanium dioxide nanoparticles and oil droplets. The resulting suspensions held their macroscopic stability for up to 2 months, regardless of pH or surface charge. Cryo-TEM images revealed a complex network formation involving nanofibers and TiO2 nanoparticles, which agrees with the high viscosity values and gel-like behavior found in rheology measurements. We propose that the formation of this network is responsible for the simultaneous stabilization of oil droplets and TiO2 nanoparticles, and that this may be used as a formulation tool for other complex systems.

Acid-base site detection and mapping on solid surfaces by Kelvin force microscopy (KFM).

Electrostatic potential at the surface of acidic or basic solids changes under higher relative humidity (RH), as determined by using Kelvin force microscopy (KFM). The potential on acid surfaces becomes more negative as the water vapor pressure increases, while it becomes more positive on basic solids. These results verify the following hypothesis: OH(-) or H(+) ions associated with atmospheric water ion clusters are selectively adsorbed on solid surfaces, depending on the respective Brønsted acid or base character. Therefore, Kelvin microscopy, under variable humidity, is a rigorous but convenient alternative to determine the acid-base character of solid surfaces, with a great advantage: it uses only one amphoteric and simple reagent to determine both the acid and base sites. Moreover, this technique provides information on the spatial distribution of acid-base sites, which is currently inaccessible to any other method.

How lignin sticks to cellulose-insights from atomic force microscopy enhanced by machine-learning analysis and molecular dynamics simulations.

Elucidating cellulose-lignin interactions at the molecular and nanometric scales is an important research topic with impacts on several pathways of biomass valorization. Here, the interaction forces between a cellulosic substrate and lignin are investigated. Atomic force microscopy with lignin-coated tips is employed to probe the site-specific adhesion to a cellulose film in liquid water. Over seven thousand force-curves are analyzed by a machine-learning approach to cluster the experimental data into types of cellulose-tip interactions. The molecular mechanisms for distinct types of cellulose-lignin interactions are revealed by molecular dynamics simulations of lignin globules interacting with different cellulose Iß crystal facets. This unique combination of experimental force-curves, data-driven analysis, and molecular simulations opens a new approach of investigation and updates the understanding of cellulose-lignin interactions at the nanoscale.

A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models.

BACKGROUND: Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). RESULTS: We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. CONCLUSIONS: The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions.

A comparative pan-genomic analysis of 53 C. pseudotuberculosis strains based on functional domains.

Corynebacterium pseudotuberculosis is a pathogenic bacterium with great veterinary and economic importance. It is classified into two biovars: ovis, nitrate-negative, that causes lymphadenitis in small ruminants and equi, nitrate-positive, causing ulcerative lymphangitis in equines. With the explosive growth of available genomes of several strains, pan-genome analysis has opened new opportunities for understanding the dynamics and evolution of C. pseudotuberculosis. However, few pan-genomic studies have compared biovars equi and ovis. Such studies have considered a reduced number of strains and compared entire genomes. Here we conducted an original pan-genome analysis based on protein sequences and their functional domains. We considered 53 C. pseudotuberculosis strains from both biovars isolated from different hosts and countries. We have analysed conserved domains, common domains more frequently found in each biovar and biovar-specific (unique) domains. Our results demonstrated that biovar equi is more variable; there is a significant difference in the number of proteins per strains, probably indicating the occurrence of more gene loss/gain events. Moreover, strains of biovar equi presented a higher number of biovar-specific domains, 77 against only eight in biovar ovis, most of them are associated with virulence mechanisms. With this domain analysis, we have identified functional differences among strains of biovars ovis and equi that could be related to niche-adaptation and probably help to better understanding mechanisms of virulence and pathogenesis. The distribution patterns of functional domains identified in this work might have impacts on bacterial physiology and lifestyle, encouraging the development of new diagnoses, vaccines, and treatments for C. pseudotuberculosis diseases.Communicated by Ramaswamy H. Sarma.

Disassembly of TEMPO-Oxidized Cellulose Fibers: Intersheet and Interchain Interactions in the Isolation of Nanofibers and Unitary Chains.

Cellulose disassembly is an important issue in designing nanostructures using cellulose-based materials. In this work, we present a combination of experimental and theoretical study addressing the disassembly of cellulose nanofibrils. Through 2,2,6,6-tetramethylpiperidine-1-oxyl-mediated oxidation processes, combined with atomic force microscopy results, we show the formation of nanofibers with diameters corresponding to that of a single-cellulose polymer chain. The formation of these polymer chains is controlled by repulsive electrostatic interactions between the oxidized chains. Further, first-principles calculations have been performed in order to provide an atomistic understanding of the cellulose disassembling processes, focusing on the balance between the interchain (IC) and intersheet (IS) interactions upon oxidation. First, we analyze these interactions in pristine systems, where we found the IS interaction to be stronger than the IC interaction. In the oxidized systems, we have considered the formation of (charged) carboxylate groups along the inner sites of elementary fibrils. We show a net charge concentration on the carboxylate groups, supporting the emergence of repulsive electrostatic interactions between the cellulose nanofibers. Indeed, our total energy results show that the weakening of the binding strength between the fibrils is proportional to the concentration and net charge density of the carboxylate group. Moreover, by comparing the IC and IS binding energies, we found that most of the disassembly processes should take place by breaking the IC O-H···O hydrogen bond interactions and thus supporting the experimental observation of single- and double-cellulose polymer chains.

Tailoring strength of nanocellulose foams by electrostatic complexation.

Supramolecular assembly of biobased components in water is a promising strategy to construct advanced materials. Herein, electrostatic complexation was used to prepare wet-resilient foams with improved mechanical property. Small-angle X-ray scattering and cryo-transmission electron microscopy experiments showed that suspensions with oppositely charged cellulose nanofibers are a mixture of clusters and networks of entangled fibers. The balance between these structures governs the colloidal stability and the rheological behavior of CNFs in water. Foams prepared from suspensions exhibited maximum compressive modulus at the mass composition of 1:1 (ca 0.12 MPa), suggesting that meaningful attractive interactions happen at this point and act as stiffening structure in the material. Besides the electrostatic attraction, hydrogen bonds and hydrophobic contacts may also occur within the clustering, improving the water stability of cationic foams. These results may provide a basis for the development of robust all- cellulose materials prepared in water, with nontoxic chemicals.

Enhanced Hydrophobicity in Nanocellulose-Based Materials: Toward Green Wearable Devices.

Nanocellulose is a promising material for fabricating green, biocompatible, flexible, and foldable devices. One of the main issues of using nanocellulose as a fundamental component for wearable electronics is the influence of environmental conditions on it. The water adsorption promotes the swelling of nanopaper substrates, which directly affects the devices' electrical properties prepared on/with it. Here, plant-based nanocellulose substrates, and ink composites deposited on them, are chemically modified using hexamethyldisilazane to enhance the system's hydrophobicity. After the treatment, the electrical properties of the devices exhibit stable operation under humidity levels around 95%. Such stability demonstrates that the hexamethyldisilazane modification substantially suppresses the water adsorption on fundamental device structures, namely, substrate plus conducting ink. These results attest to the robustness necessary to use nanocellulose as a key material in wearable devices such as electronic skins and tattoos and contribute to the worldwide efforts to create biodegradable devices engineered in a more deterministic fashion.

Morphology and self-arraying of SDS and DTAB dried on mica surface.

Dewetting phenomena produce interesting patterns that may impart new properties to solid surfaces. Sodium dodecyl sulfate (SDS) and dodecyltrimethylammonium bromide (DTAB) aqueous solutions, dried on mica surfaces under different drying conditions, undergo dewetting events forming structured deposits that were imaged by scanning electron microscopy (SEM), atomic force (AFM) and Kelvin force microscopy (KFM). Dry SDS, in most situations, displays long branched stripes formed due to fingering instability, while DTAB undergoes stick-slip motion forming patterns of parallel continuous or split stripes. In both systems, independently of drying conditions, surfactants pack forming lamellar structures, but with different orientations: SDS lamellae are aligned parallel to the substrate whereas DTAB lamellae are normal to the mica plane. Electric potential maps of SDS obtained by KFM show well-defined electrostatic patterns: surfactant layers deposited on mica are overall negative with a larger excess of negative charge in the interlamellar space than in the lamellar faces.

Double stabilization mechanism of O/W Pickering emulsions using cationic nanofibrillated cellulose.

HYPOTHESIS: Hydrophobic oleic acid/water interfaces are negatively charged. Hence, the use of cationic nanocelluloses as stabilizers of Pickering emulsions could improve the colloidal stability due to the electrostatic complexation at the oil-water interface. EXPERIMENTS: Two cationic nanofibrillated cellulose (cNFCs) with two degrees of substitution were prepared and used as stabilizers of Pickering emulsions. The adsorption of cNFCs at the oil: water interface was evaluated by interfacial tension, atomic force microscopy, and centrifugation measurements. LUMiSizer and optical microscopy techniques were used to analyze the colloidal stability and oil droplets morphology, respectively. Besides, the rheological behavior of the continuous aqueous phase was determined through flow and stress sweep curves. Finally, the dispersion of cNFCs in a diluted emulsion was visualized by cryogenic transmission electron microscopy (cryo-TEM). FINDINGS: Cationic NFCs were more efficient in partitioning to the oil:water interface compared to their anionic analogous, oCNF. The electrostatic attraction between the positively charged trimethylammonium groups and the negatively charged deprotonated oleic acid reduced the interfacial tension and improved the colloidal stability of O/W Pickering emulsions. cNFCs dispersed in the aqueous phase were found to increase the viscosity, decelerating the oil drops coalescence. Therefore, the stabilization of cNFCs Pickering emulsions had a synergistic effect from the electrostatic complexation at the liquid-liquid interface and network formation in the aqueous phase, as visualized by cryo-TEM.

Low-energy preparation of cellulose nanofibers from sugarcane bagasse by modulating the surface charge density.

In this work, cellulose nanofibers (CNF) were obtained from sugarcane bagasse (SC) without high-energy mechanical treatments, using TEMPO-mediated oxidation. Variable NaClO concentrations were used to impart electrostatic repulsion between surface charged groups thus facilitating fibril separation. CNFs with diameters in the 3-5 nm range were obtained by oxidation of SC pulp with NaClO at 25 and 50 mmol/g. After a 30 min -sonication step, these CNFs were broken down into cellulose nanocrystals (CNC) by mechanical action. Both CNF and CNC preparation by this method are possible in SC due to its particular cell wall morphology and were not achieved in eucalyptus biomass, which is more recalcitrant. This work provided thus a new pathway to modulate the final morphology of cellulose particles by combining a low recalcitrant raw material with different surface charge densities.

Tailoring the Antimicrobial Response of Cationic Nanocellulose-Based Foams through Cryo-Templating.

To shed light on novel sustainable materials with antimicrobial functionality, in this contribution, we describe the use of cationic nanocellulose to produce foams featuring antibacterial activity against the powerful human pathogen Escherichia coli. Dialdehyde cellulose was cationized with Girard's reagent T (GRT), mechanically disintegrated into nanofibrillated cellulose (NFC), and shaped into foams through different protocols. All steps were carried out in aqueous media and in the absence of hazardous chemicals. While evaporative drying led to compact films (density of 1.3 g cm-3), freeze-casting (i.e., freezing and freeze-drying) produced monolithic cryogels with low densities (<50 mg cm-3) and porosities of ca. 98%. Although highly porous, the cryogels obtained through rapid freezing remarkably presented smaller pores than those that were previously frozen in a slow fashion. The quaternary ammonium groups of GRT-cationized NFC removed E. coli to different extents depending upon sample morphology. We demonstrated in an innovative manner that porosity, which is directly associated with surface area, and pore size play an essential role on the antimicrobial performance. This outcome arises from the inaccessibility of bacterial cells to cationic surfaces inside monoliths composed of small pores. We herein present an uncomplicated, environmentally friendly protocol for fine-tuning the porosity and pore size of all-cellulose materials through cryo-templating. Controlling these morphometric parameters allowed us to achieve a ca. 85% higher anti-E. coli activity when comparing samples made up of the very same material (i.e., the same NFC concentration and degree of substitution) but presented as dense films. These findings bear clear implications for the pursuit of sustainable materials presenting multifunctionality.

Structural descriptor database: a new tool for sequence-based functional site prediction.

BACKGROUND: The Structural Descriptor Database (SDDB) is a web-based tool that predicts the function of proteins and functional site positions based on the structural properties of related protein families. Structural alignments and functional residues of a known protein set (defined as the training set) are used to build special Hidden Markov Models (HMM) called HMM descriptors. SDDB uses previously calculated and stored HMM descriptors for predicting active sites, binding residues, and protein function. The database integrates biologically relevant data filtered from several databases such as PDB, PDBSUM, CSA and SCOP. It accepts queries in fasta format and predicts functional residue positions, protein-ligand interactions, and protein function, based on the SCOP database. RESULTS: To assess the SDDB performance, we used different data sets. The Trypsion-like Serine protease data set assessed how well SDDB predicts functional sites when curated data is available. The SCOP family data set was used to analyze SDDB performance by using training data extracted from PDBSUM (binding sites) and from CSA (active sites). The ATP-binding experiment was used to compare our approach with the most current method. For all evaluations, significant improvements were obtained with SDDB. CONCLUSION: SDDB performed better when trusty training data was available. SDDB worked better in predicting active sites rather than binding sites because the former are more conserved than the latter. Nevertheless, by using our prediction method we obtained results with precision above 70%.

Phase Behavior Controlled by the Addition of Long-Chain n-Alcohols in Systems of Cationic Surfactant/Anionic Polyion Complex Salts and Water.

Phase behavior of surfactants in water may be affected by the addition of a third component, and the present study discusses how long-chain n-alcohols affect phase transitions of systems formed by the surfactant hexadecyltrimethylammonium bromide, C16TAB, or its complex salts formed with polyacrylate, C16TAPA30, as well as other previously reported complex salts/water/alcohol systems. Structural characterization by X-ray diffraction patterns at small and wide angles and different temperatures was performed for samples containing n-decanol, n-dodecanol, or n-tetradecanol. Differential scanning calorimetry (DSC) was also used to study the phase transition. The results allowed us to observe and understand the coexistence of lamellar gel (Lß) and lamellar liquid-crystal (Lα) phases, elucidating the structure of a previously reported mesophase, proposing an alternative assignment. Whereas the chain-melting transition is well-known to be sharp for lipids, we have found that it is broader for C16TAB and C16TAPA in the presence of these n-alcohols. We have investigated the effects of their composition and chain length on the temperature and enthalpy of transition. This elucidates why the addition of n-alcohols with chains slightly shorter than that of the surfactants leads to the formation of an ordered gel-like lamellar phase (Lß). n-Alcohols act as neutral cosurfactants, leading to more packing, and all of the factors converge to a limit situation, associated with a common critical area occupied by each alkyl chain. We compared our results with other mesophase systems from the literature, demonstrating that the same trends of phase behavior occur for complex salts of other polyelectrolytes with alkyltrimethylammonium surfactants.

Homology Inference Based on a Reconciliation Approach for the Comparative Genomics of Protozoa.

Protozoa parasites are responsible for several diseases in tropical countries, such as malaria, sleeping sickness, Chagas disease, leishmaniasis, amebiasis, and giardiasis, which together threaten millions of people around the world. In addition, most of the classic parasitic diseases due to protozoa are zoonotic. Understanding the biology of these organisms plays a relevant role in combating these diseases. Using homology inference and comparative genomics, this study targeted 3 protozoan species from different Phyla: Cryptosporidium muris (Apicomplexa), Entamoeba invadens (Amoebozoa), and Trypanosoma grayi (Euglenozoa). In this study, we propose a new approach for the identification of homologs, based on the reconciliation of the results of 2 different homology inference software programs. Our results showed that 46.1% (59/128) of the groups inferred by our reconciliation approach could be validated using this methodology. These validated groups are here called homologous Supergroups and were compared with SUPERFAMILY and Pfam Clans.

Cellulose nanocrystals as carriers in medicine and their toxicities: A review.

Cellulose nanocrystals (CNCs) are crystalline nanoparticles that present myriad applications. CNCs are produced from a variety of renewable sources, and they can be chemically modified. Although there are promising perspectives for introducing CNCs into pharmaceutical formulations, prior to achieving commercial products the influence of many parameters such as extraction and toxicity of the resulting products must be revealed. Since there is great physicochemical flexibility in the steps of obtaining and conjugating CNCs, there are uncountable and complex outcomes from the interactions of those parameters. We present a discussion that helps to unveil the whole panorama on the use of CNCs as drug delivery systems. The methods of producing CNCs are correlated to the resulting nanotoxicity from the cellular to organism level. This review points to relevant concerns that must be overcome to attain safe use of these nanostructures. We also discuss the patents and commercially available products based on CNCs.

Fast and reliable BIA/amperometric quantification of acetylcysteine using a nanostructured double hydroxide sensor.

This study reports the preparation and characterization of nickel/lead hydroxide nanoparticles used to construct electrochemical sensors, which were investigated for amperometric quantification of N-acetylcysteine (NAC). The newly synthesised material presents good uniformity, with the lead (II) ions homogenously incorporated into the alpha nickel hydroxide crystal structure, confirmed by X-ray diffraction, transmission electron microscopy and X-ray photoelectron spectroscopy analyses. Films of nanoparticles (3 nm in size) were prepared on conductive fluorine-doped tin oxide-coated glass slides and used connected to a specially built batch injection analysis (BIA) cell with a capacity of only 4 mL and the electrode positioned in the bottom. To attain optimal analytical performance, the main parameters for BIA measurements (volume injected, different velocities of injection and best distance of the pipette from the electrode) were evaluated, as was the working potential, to determine the optimal conditions. Linear responses were obtained for the concentration range from 20 to 220 µmol L-1, and the limits of detection (3σ/slope) and quantification (10σ/slope) were calculated as 0.23 µmol L-1 and 0.70 µmol L-1, respectively. The new NAC sensor does not exhibit a memory effect and has enormous potential utility in the quantitative determination of N-acetylcysteine in drugs. The results of the analysis of NAC obtained using BIA presented good concordance with those obtained by chromatography. The analytical frequency attained using BIA (120 analysis h-1) compares very favourably with the one obtained using chromatography (6 analysis h-1).