Dynamic, but Not Necessarily Disordered, Human-Virus Interactions Mediated through SLiMs in Viral Proteins

Most viruses have small genomes that encode proteins needed to perform essential enzymatic functions. Across virus families, primary enzyme functions are under functional constraint; however, secondary functions mediated by exposed protein surfaces that promote interactions with the host proteins may be less constrained. Viruses often form transient interactions with host proteins through conformationally flexible interfaces. Exposed flexible amino acid residues are known to evolve rapidly suggesting that secondary functions may generate diverse interaction potentials between viruses within the same viral family. One mechanism of interaction is viral mimicry through short linear motifs (SLiMs) that act as functional signatures in host proteins. Viral SLiMs display specific patterns of adjacent amino acids that resemble their host SLiMs and may occur by chance numerous times in viral proteins due to mutational and selective processes. Through mimicry of SLiMs in the host cell proteome, viruses can interfere with the protein interaction network of the host and utilize the host-cell machinery to their benefit. The overlap between rapidly evolving protein regions and the location of functionally critical SLiMs suggest that these motifs and their functional potential may be rapidly rewired causing variation in pathogenicity, infectivity, and virulence of related viruses. The following review provides an overview of known viral SLiMs with select examples of their role in the life cycle of a virus, and a discussion of the structural properties of experimentally validated SLiMs highlighting that a large portion of known viral SLiMs are devoid of predicted intrinsic disorder based on the viral SLiMs from the ELM database.

A gap-filling algorithm for prediction of metabolic interactions in microbial communities

The study of microbial communities and their interactions has attracted the interest of the scientific community, because of their potential for applications in biotechnology, ecology and medicine. The complexity of interspecies interactions, which are key for the macroscopic behavior of microbial communities, cannot be studied easily experimentally. For this reason, the modeling of microbial communities has begun to leverage the knowledge of established constraint-based methods, which have long been used for studying and analyzing the microbial metabolism of individual species based on genome-scale metabolic reconstructions of microorganisms. A main problem of genome-scale metabolic reconstructions is that they usually contain metabolic gaps due to genome misannotations and unknown enzyme functions. This problem is traditionally solved by using gap-filling algorithms that add biochemical reactions from external databases to the metabolic reconstruction, in order to restore model growth. However, gap-filling algorithms could evolve by taking into account metabolic interactions among species that coexist in microbial communities. In this work, a gap-filling method that resolves metabolic gaps at the community level was developed. The efficacy of the algorithm was tested by analyzing its ability to resolve metabolic gaps on a synthetic community of auxotrophic Escherichia coli strains. Subsequently, the algorithm was applied to resolve metabolic gaps and predict metabolic interactions in a community of Bifidobacterium adolescentis and Faecalibacterium prausnitzii, two species present in the human gut microbiota, and in an experimentally studied community of Dehalobacter and Bacteroidales species of the ACT-3 community. The community gap-filling method can facilitate the improvement of metabolic models and the identification of metabolic interactions that are difficult to identify experimentally in microbial communities.

Genetic screen for suppressors of increased silencing in rpd3 mutants in Saccharomyces cerevisiae identifies a potential role for H3K4 methylation

Several studies have identified the paradoxical phenotype of increased heterochromatic gene silencing at specific loci that results from deletion or mutation of the histone deacetylase (HDAC) gene RPD3. To further understand this phenomenon, we conducted a genetic screen for suppressors of this extended silencing phenotype at the HMR locus in Saccharomyces cerevisiae. Most of the mutations that suppressed extended HMR-silencing in rpd3 mutants without completely abolishing silencing were identified in the histone H3 lysine 4 methylation (H3K4me) pathway, specifically in SET1, BRE1 and BRE2. These second site mutations retained normal HMR silencing, therefore appear to be specific for the rpd3Δ extended silencing phenotype. As an initial assessment of the role of H3K4 methylation in extended silencing, we rule out some of the known mechanisms of Set1p/H3K4me mediated gene repression by HST1, HOS2 and HST3 encoded HDACs. Interestingly, we demonstrate that the RNA Polymerase III complex remains bound and active at the HMR-tDNA in rpd3 mutants despite silencing extending beyond the normal barrier. We discuss these results as they relate to the interplay among different chromatin modifying enzyme functions and the importance of further study of this enigmatic phenomenon.

Comparative Metagenomics Reveals Microbial Communities and Their Associated Functions in Two Types of Fuzhuan Brick Tea

Fuzhuan brick tea (FBT) is a unique post-fermented tea product, naturally co-fermented by microorganisms, and has gained global popularity due to its potential health benefits for humans. Considerable efforts have been made toward elucidating the microbial diversity within FBT, but an understanding of the underlying FBT community interactions and functions remains poorly studied. Consequently, the microbial communities of two types of FBT, originating from Hunan and Shaanxi provinces, were investigated using comparative shotgun metagenomic sequencing and functional annotations. Metagenomic analysis indicated that two communities shared similar taxonomic and functional attributes. Two samples shared 486 genera, in which Pseudomonas contributed most to the abundant functions within the two samples. The carbohydrate active enzyme functions of the communities primarily comprised GH (32.92%), GT (26.8%), CEs (20.43%), and AAs (18.04%). Furthermore, the overall metabolic pathways encoded by the metagenomes were largely associated with carbohydrate and amino acid metabolism, with nine metabolic pathways that were differential between two groups including penicillin and cephalosporin biosynthesis. Significantly, a total of 35 potential probiotics were inferred, with Pseudomonas putida being the most abundant inferred probiotic (80%) within the FBT communities. This study provides new insights into FBT microbial communities on their potential functions and roles in FBT characteristics.

DNA repair glycosylase hNEIL1 triages damaged bases via competing interaction modes

DNA glycosylases must distinguish the sparse damaged sites from the vast expanse of normal DNA bases. However, our understanding of the nature of nucleobase interrogation is still limited. Here, we show that hNEIL1 (human endonuclease VIII-like 1) captures base lesions via two competing states of interaction: an activated state that commits catalysis and base excision repair, and a quarantine state that temporarily separates and protects the flipped base via auto-inhibition. The relative dominance of the two states depends on key residues of hNEIL1 and chemical properties (e.g. aromaticity and hydrophilicity) of flipped bases. Such a DNA repair mechanism allows hNEIL1 to recognize a broad spectrum of DNA damage while keeps potential gratuitous repair in check. We further reveal the molecular basis of hNEIL1 activity regulation mediated by post-transcriptional modifications and provide an example of how exquisite structural dynamics serves for orchestrated enzyme functions.

Targeted chromosomal Escherichia coli:dnaB exterior surface residues regulate DNA helicase behavior to maintain genomic stability and organismal fitness

Helicase regulation is vital for replisome progression, where the helicase enzyme functions to unwind duplex DNA and aids in the coordination of replication fork activities. Currently, mechanisms for helicase regulation that involve interactions with both DNA strands through a steric exclusion and wrapping (SEW) model and conformational shifts between dilated and constricted states have been examined in vitro. To better understand the mechanism and cellular impact of helicase regulation, we used CRISPR-Cas9 genome editing to study four previously identified SEW-deficient mutants of the bacterial replicative helicase DnaB. We discovered that these four SEW mutations stabilize constricted states, with more fully constricted mutants having a generally greater impact on genomic stress, suggesting a dynamic model for helicase regulation that involves both excluded strand interactions and conformational states. These dnaB mutations result in increased DNA damage and chromosome complexity, less stable genomes, and ultimately less viable and fit strains. Notably, while two mutations stabilized fully constricted states, they have distinct effects on genomic stability, suggesting a complex relationship between helicase regulation mechanisms and faithful, efficient DNA replication. This work explores the genomic impacts of helicase dysregulation in vivo, supporting a combined dynamic regulatory mechanism involving SEW and conformational changes and relates current mechanistic understanding to functional helicase behavior.

A gap-filling algorithm for prediction of metabolic interactions in microbial communities

The study of microbial communities and their interactions has attracted the interest of the scientific community, because of their potential for applications in biotechnology, ecology and medicine. The complexity of interspecies interactions, which are key for the macroscopic behavior of microbial communities, cannot be studied easily experimentally. For this reason, the modeling of microbial communities has begun to leverage the knowledge of established constraint-based methods, which have long been used for studying and analyzing the microbial metabolism of individual species based on genome-scale metabolic reconstructions of microorganisms. A main problem of genome-scale metabolic reconstructions is that they usually contain metabolic gaps due to genome misannotations and unknown enzyme functions. This problem is traditionally solved by using gap-filling algorithms that add biochemical reactions from external databases to the metabolic reconstruction, in order to restore model growth. However, gap-filling algorithms could evolve by taking into account metabolic interactions among species that coexist in microbial communities. In this work, a gap-filling method that resolves metabolic gaps at the community level was developed. The efficacy of the algorithm was tested by analyzing its ability to resolve metabolic gaps on a synthetic community of auxotrophic Escherichia coli strains. Subsequently, the algorithm was applied to resolve metabolic gaps and predict metabolic interactions in a community of Bifidobacterium adolescentis and Faecalibacterium prausnitzii, two species present in the human gut microbiota, and in an experimentally studied community of Dehalobacter and Bacteroidales species of the ACT-3 community. The community gap-filling method can facilitate the improvement of metabolic models and the identification of metabolic interactions that are difficult to identify experimentally in microbial communities.

An Arabidopsis Oxalyl-CoA Decarboxylase, AtOXC, Is Important for Oxalate Catabolism in Plants

Considering the widespread occurrence of oxalate in nature and its broad impact on a host of organisms, it is surprising that so little is known about the turnover of this important acid. In plants, oxalate oxidase is the most well-studied enzyme capable of degrading oxalate, but not all plants possess this activity. Recently, acyl-activating enzyme 3 (AAE3), encoding an oxalyl-CoA synthetase, was identified in Arabidopsis. This enzyme has been proposed to catalyze the first step in an alternative pathway of oxalate degradation. Since this initial discovery, this enzyme and proposed pathway have been found to be important to other plants and yeast as well. In this study, we identify, in Arabidopsis, an oxalyl-CoA decarboxylase (AtOXC) that is capable of catalyzing the second step in this proposed pathway of oxalate catabolism. This enzyme breaks down oxalyl-CoA, the product of AtAAE3, into formyl-CoA and CO2. AtOXC:GFP localization suggested that this enzyme functions within the cytosol of the cell. An Atoxc knock-down mutant showed a reduction in the ability to degrade oxalate into CO2. This reduction in AtOXC activity resulted in an increase in the accumulation of oxalate and the enzyme substrate, oxalyl-CoA. Size exclusion studies suggest that the enzyme functions as a dimer. Computer modeling of the AtOXC enzyme structure identified amino acids of predicted importance in co-factor binding and catalysis. Overall, these results suggest that AtOXC catalyzes the second step in this alternative pathway of oxalate catabolism.

The study of Enzyme-Water Mutualism Theory

A variety of experiments have shown that water can occur as a liquid of high and low density, with various physical characteristics, as the product of two kinds of hydrogen association between H20 molecules. This is essential intracellular, since solutes may favor a water type or other, creates local gradients of different waters behaviors which, due to volume restrictions, cannot be balanced by the flux but can be balanced by a shift between water shapes. It is quite probable that the developmental powers have manipulated this extraordinary water capacity, contributing to mutualism among adjacent H2O molecules and macromolecules. A consequence is a spectrum of substrate unique enzyme with macromolecular hydration, which enhances the catalysis, and hydrated by the more favorable ones of the two water configurations. Moreover, owing to selective isolation of enzyme reaction components, the variations in the water structure of low /high density purvey the pathway for protein folding; a basic requirement for enzyme functions without neglecting thermodynamics.