Removal performance and mechanism of typical amino acids in water by the peroxymonosulfate/Fe3O4 nanoparticles

Dissolved organic nitrogen (DON) as precursors of nitrogenous disinfection byproducts (N-DBPs) has become a serious issue for drinking water treatment. Here, Fe3O4/peroxymonosulfate (PMS) system was used to examine the amino acid removal and formation of N-DBPs in the system and the corresponding mechanisms. Results showed a remarked variation in removal efficiency of three typical amino acids, i.e., glutamate (78%), histidine (53%) and phenylalanine (27%) in Fe3O4/PMS system at optimum conditions (0.1 g/L Fe3O4, 1.5 mM PMS, 1 h). Notably, Fe3O4/PMS treatment led to dichloroacetonitrile (DCAN) formation caused by the chlorination of glutamate, phenylalanine and histidine being reduced by 53.3%, 9.7% and 41.9%, respectively. The degradation and subsequent N-DBPs formation in the Fe3O4/PMS system mainly depended on the types and properties of the amino acids. The formation of dichloroacetamide (DCAcAm) exhibited different trends, which may be due to the different R group structure of the three amino acids and the special aromaticity of imidazole ring in the histidine side chain that facilitates its quick electrophilic substitution and ring-opening reaction. This study highlights that the Fe3O4/PMS system is a promising strategy to remove DON and efficiently eliminate N-DBPs formation in the drinking water treatment process depending on the amino acid type.

SegmA: Residue Segmentation of cryo-EM density maps

The cryo-EM resolution revolution enables the development of algorithms for direct de-novo modelling of protein structures from given cryo-EM density maps. Deep Learning tools have been applied to locate structure patterns, such as rotamers, secondary structures and Cα atoms. We present a deep neural network (nicknamed SegmA) for the residue type segmentation of a cryo-EM density map. The network labels voxels in a cryo-EM map by the residue type (amino acid type or nucleic acid) of the sampled macromolecular structure. It also provides a visual representation of the density map by coloring the different types of voxels by their assgned colors. SegmA's algorithm combines a rotation equivariant group convolutional network with a traditional U-net network in a cascade. In addition SegmA estimates the labeling accuracy and reports only labels assigned with high confidence. At resolution of 3 Å SegmAs accuracy is 80% for nucleotides. Amino acids which can be seen by eye, such as LEU, ARG and PHE, are detected by Segma with about 70% accuracy. A web server of the application is under development at https://dev.dcsh7cbr3o89e.amplifyapp.com. The SegmA open code is available at https://github.com/Mark-Rozanov/SegmA_3A/ tree/master .

Homopeptide and homocodon levels across fungi are coupled to GC/AT-bias and intrinsic disorder, with unique behaviours for some amino acids

Homopeptides (runs of one amino-acid type) are evolutionarily important since they are prone to expand/contract during DNA replication, recombination and repair. To gain insight into the genomic/proteomic traits driving their variation, we analyzed how homopeptides and homocodons (which are pure codon repeats) vary across 405 Dikarya, and probed their linkage to genome GC/AT bias and other factors. We find that amino-acid homopeptide frequencies vary diversely between clades, with the AT-rich Saccharomycotina trending distinctly. As organisms evolve, homocodon and homopeptide numbers are majorly coupled to GC/AT-bias, exhibiting a bi-furcated correlation with degree of AT- or GC-bias. Mid-GC/AT genomes tend to have markedly fewer simply because they are mid-GC/AT. Despite these trends, homopeptides tend to be GC-biased relative to other parts of coding sequences, even in AT-rich organisms, indicating they absorb AT bias less or are inherently more GC-rich. The most frequent and most variable homopeptide amino acids favour intrinsic disorder, and there are an opposing correlation and anti-correlation versus homopeptide levels for intrinsic disorder and structured-domain content respectively. Specific homopeptides show unique behaviours that we suggest are linked to inherent slippage probabilities during DNA replication and recombination, such as poly-glutamine, which is an evolutionarily very variable homopeptide with a codon repertoire unbiased for GC/AT, and poly-lysine whose homocodons are overwhelmingly made from the codon AAG.

Homopeptide and Homocodon Levels are Coupled to GC/AT Bias Levels, Intrinsic Disorder Propensity and other Factors Across Diverse Fungi

Homopeptides (consecutive runs of one amino-acid type) are suggested to play important roles in proteome evolution, since they are prone to expand/contract during DNA replication, recombination and repair. It is currently not clear how homopeptide frequencies vary as organisms evolve, and which genomic/proteomic traits drive variation. Thus, to gain insight, we analyzed how homopeptides and homocodons (which are pure codon repeats) vary across 405 Dikarya, and probed how this variation is linked to GC/AT bias amongst other factors. We observe that amino-acid homopeptide frequencies vary diversely between clades (even close relatives), with the AT-rich Saccharomycotina trending distinctly. As organisms evolve, homocodon and homopeptide numbers are majorly coupled to GC/AT-bias, with medium GC/AT genomes having markedly fewer. Despite this, homopeptides tend to be more GC-rich than other proteome areas, even in AT-rich organisms, indicating they absorb AT bias less or are inherently more GC-rich. Furthermore, the purity of homopeptides (i.e., the degree one codon type predominates in them) varies least for amino acids with GC/AT-balanced codon repertoires, with most variation for arginine since it has only one AT-rich codon (out of six). The most frequent and most variable homopeptide amino acids have greater intrinsic disorder propensity, and annotated intrinsic disorder fractions are strongly correlated with homopeptide levels (unlike structured domain fractions, which are anti-correlated). Poly-glutamine uniquely behaves as an evolutionarily very variable homopeptide with a codon repertoire unbiased for GC/AT. In summary, homopeptide/homocodon levels are coupled to or influenced by several factors, including GC/AT bias and amino-acid intrinsic disorder propensity.

Nearest-neighbor NMR spectroscopy: categorizing spectral peaks by their adjacent nuclei

Methyl-NMR enables atomic-resolution studies of structure and dynamics of large proteins in solution. However, resonance assignment remains challenging. The problem is to combine existing structural informational with sparse distance restraints and search for the most compatible assignment among the permutations. Prior classification of peaks as either from isoleucine, leucine, or valine reduces the search space by many orders of magnitude. However, this is hindered by overlapped leucine and valine frequencies. In contrast, the nearest-neighbor nuclei, coupled to the methyl carbons, resonate in distinct frequency bands. Here, we develop a framework to imprint additional information about passively coupled resonances onto the observed peaks. This depends on simultaneously orchestrating closely spaced bands of resonances along different magnetization trajectories, using principles from control theory. For methyl-NMR, the method is implemented as a modification to the standard fingerprint spectrum (the 2D-HMQC). The amino acid type is immediately apparent in the fingerprint spectrum. There is no additional relaxation loss or an increase in experimental time. The method is validated on biologically relevant proteins. The idea of generating new spectral information using passive, adjacent resonances is applicable to other contexts in NMR spectroscopy.

Structural Determinants within the Adenovirus Early Region 1A Protein Spacer Region Necessary for Tumorigenesis

ABSTRACT It has long been established that group A human adenoviruses (HAdV-A12, -A18, and -A31) can cause tumors in newborn rodents, with tumorigenicity related to the presence of a unique spacer region located between conserved regions 2 and 3 within the HAdV-A12 early region 1A (E1A) protein. Group B adenoviruses are weakly oncogenic, whereas most of the remaining human adenoviruses are nononcogenic. In an attempt to understand better the relationship between the structure of the AdE1A spacer region and oncogenicity of HAdVs, the structures of synthetic peptides identical or very similar to the adenovirus 12 E1A spacer region were determined and found to be α-helical using nuclear magnetic resonance (NMR) spectroscopy. This contrasts significantly with some previous suggestions that this region is unstructured. Using available predictive algorithms, the structures of spacer regions from other E1As were also examined, and the extent of the predicted α-helix was found to correlate reasonably well with the tumorigenicity of the respective virus. We suggest that this may represent an as-yet-unknown binding site for a partner protein required for tumorigenesis. IMPORTANCE This research analyzed small peptides equivalent to a region within the human adenovirus early region 1A protein that confers, in part, tumor-inducing properties to various degrees on several viral strains in rats and mice. The oncogenic spacer region is α-helical, which contrasts with previous suggestions that this region is unstructured. The helix is characterized by a stretch of amino acids rich in alanine residues that are organized into a hydrophobic, or “water-hating,” surface that is considered to form a major site of interaction with cellular protein targets that mediate tumor formation. The extent of α-helix in E1A from other adenovirus species can be correlated to a limited degree to the tumorigenicity of that virus. Some serotypes show significant differences in predicted structural propensity, suggesting that the amino acid type and physicochemical properties are also of importance.

Structural determinants within the adenovirus early region 1A protein spacer region necessary for tumourigenesis

It has long been established that group-A adenoviruses (HAdV-A12, -A18 and -A31) can cause tumours in new-born rodents with tumourigenicity related to the presence of a unique spacer region located between conserved regions 2 and 3 within the Ad12E1A protein. Group B adenoviruses are weakly oncogenic whereas most of the remaining human adenoviruses are non-oncogenic. In order to understand better the relationship between the structure of the AdE1A spacer region and oncogenicity of HAdVs the structure of synthetic peptides identical or very similar to the adenovirus12 E1A spacer region have been determined to be α-helical using NMR spectroscopy. This contrasts significantly with some previous suggestions that this region is unstructured. Using available predictive algorithms, the structures of spacer regions from other E1As were also examined and the extent of predicted α-helix was found to correlate reasonably well with the tumorigenicity of the respective viruses.ImportanceThis research analysed small peptides equivalent to a region within the human adenovirus early region 1A protein that confers, in part, tumour inducing properties to varying degrees on several viral strains in rats and mice. The oncogenic spacer region is alpha-helical, which contrasts with previous suggestions that this region is unstructured. The helix is characterised by a stretch of amino acids rich in alanine residues that are organised into a hydrophobic or ‘water-hating’ surface that is considered to form a major site of interaction with cellular protein targets that mediate tumour formation. The extent of alpha-helix in E1A from other adenovirus species can be correlated to a limited degree to the tumourigenicity of that virus. Some serotypes show significant differences in predicted structural propensity suggesting the amino acid type and physicochemical properties are also of importance.