MODELING PROTEIN INTERACTIONS THROUGH STRUCTURE ALIGNMENT

Rapid accumulation of the experimental data on protein-protein complexes drives the paradigm shift in protein docking from "traditional" template free approaches to template based techniques. Homology docking algorithms based on sequence similarity between target and template complexes can account for ~ 20% of known protein-protein interactions. When homologous templates for the target complex are not available, but the structure of the target monomers is known, docking through structural alignment may provide an adequate solution. Such an algorithm was developed based on the structural comparison of monomers to co-crystallized interfaces. A library of the interfaces was generated from the biological units. The success of the structure alignment of the interfaces depends on the way the interface is defined in terms of its structural content. We performed a systematic large-scale study to find the optimal definition/size of the interface for the structure alignment-based docking applications. The performance was the best when the interface was defined with a distance cutoff of 12 Å. The structure alignment protocol was validated, for both full and partial alignment, on the DOCKGROUND benchmark sets. Both protocols performed equally for higher-accuracy models (i-RMSD &le 5 Å). Overall, the partial structure alignment yielded more acceptable models than the full structure alignment (86 acceptable models were provided by partial structure alignment only, compared to 31 by full structure alignment only). Most templates identified by the partial structure alignment had very low sequence identity to targets and such templates were hard to detect by sequence-based methods. Detailed analysis of the models obtained for 372 test cases concluded that templates for higher-accuracy models often shared not only local but also global structural similarity with the targets. However, interface similarity even in these cases was more prominent, reflected in more accurate models yielded by partial structure alignment. Conservation of protein-protein interfaces was observed in very diverse proteins. For example, target complexes shared interface structural similarity not only with hetero- and homo-complexes but also, in few cases, with crystal packing interfaces. The results indicate that the structure alignment techniques provide a much needed addition to the docking arsenal, with the combined structure alignment and template free docking success rate significantly surpassing that of the free docking alone

Metabolic Syndrome, Gut Microbiome and Dietary Bioactive Peptides, an Unexplored Triad

The gut microbiome is a complex, biochemically rich and essential component of the human metabolic system. It has been our understanding for very long that the gut microbes are primarily there to digest the undigested food (mainly fibers), get nourishment, and in return release metabolites helping host cells — short-chain fatty acids produced by gut microbes are a great source of energy for the colonocytes. It is only in the last decade, with advancements of DNA sequencing platforms, that we are lettered about the association between the gut microbial composition and metabolic disorders such as obesity, dysglycemia, dyslipidemia, and cardiovascular diseases. This creates a momentum to understand the factors shaping the composition of the gut-microbiome, nature of dysbiosis (perturbation of gut microbial composition) associated with human health and ways to modulate the gut microbiome to achieve the desired health benefit

Docking by structural similarity at protein-protein interfaces

Rapid accumulation of experimental data on protein-protein complexes drives the paradigm shift in protein docking from ‘traditional,’ template free approaches to template based techniques. Homology docking algorithms based on sequence similarity between target and template complexes can account for up to 20% of known protein-protein interactions. When highly homologous templates for the target complex are not available, but the structure of the target monomers is known, docking by local structural alignment may provide an adequate solution. Such an algorithm was developed based on the structural comparison of monomers to co-crystallized interfaces. A library of the interfaces was generated from co-crystallized protein-protein complexes in PDB. The partial structure alignment algorithm was validated on the Dockground benchmark sets. The optimal performance of the partial (interface) structure alignment was achieved with the interface residues defined by 12Å distance across the interface. Overall, the partial structural alignment yielded more accurate models than the full structure alignment. Most templates identified by the partial structural alignment had low sequence identity to the target, which makes them hard to detect by sequence-based methods. The results indicate that the structure alignment techniques provide a much needed addition to the docking arsenal, with the combined structural alignment and template free docking success rate significantly surpassing that of the free docking alone

Protein Docking by the Interface Structure Similarity: How Much Structure Is Needed?

The increasing availability of co-crystallized protein-protein complexes provides an opportunity to use template-based modeling for protein-protein docking. Structure alignment techniques are useful in detection of remote target-template similarities. The size of the structure involved in the alignment is important for the success in modeling. This paper describes a systematic large-scale study to find the optimal definition/size of the interfaces for the structure alignment-based docking applications. The results showed that structural areas corresponding to the cutoff values <12 Å across the interface inadequately represent structural details of the interfaces. With the increase of the cutoff beyond 12 Å, the success rate for the benchmark set of 99 protein complexes, did not increase significantly for higher accuracy models, and decreased for lower-accuracy models. The 12 Å cutoff was optimal in our interface alignment-based docking, and a likely best choice for the large-scale (e.g., on the scale of the entire genome) applications to protein interaction networks. The results provide guidelines for the docking approaches, including high-throughput applications to modeled structures.This work was supported by National Institutes of Health grant R01 GM074255

Docking by structural similarity at protein-protein interfaces

Rapid accumulation of experimental data on protein-protein complexes drives the paradigm shift in protein docking from ‘traditional,’ template free approaches to template based techniques. Homology docking algorithms based on sequence similarity between target and template complexes can account for up to 20% of known protein-protein interactions. When highly homologous templates for the target complex are not available, but the structure of the target monomers is known, docking by local structural alignment may provide an adequate solution. Such an algorithm was developed based on the structural comparison of monomers to co-crystallized interfaces. A library of the interfaces was generated from co-crystallized protein-protein complexes in PDB. The partial structure alignment algorithm was validated on the Dockground benchmark sets. The optimal performance of the partial (interface) structure alignment was achieved with the interface residues defined by 12Å distance across the interface. Overall, the partial structural alignment yielded more accurate models than the full structure alignment. Most templates identified by the partial structural alignment had low sequence identity to the target, which makes them hard to detect by sequence-based methods. The results indicate that the structure alignment techniques provide a much needed addition to the docking arsenal, with the combined structural alignment and template free docking success rate significantly surpassing that of the free docking alone

Metabolic Syndrome, Gut Microbiome and Dietary Bioactive Peptides, an Unexplored Triad

The gut microbiome is a complex, biochemically rich and essential component of the human metabolic system. It has been our understanding for very long that the gut microbes are primarily there to digest the undigested food (mainly fibers), get nourishment, and in return release metabolites helping host cells -- short-chain fatty acids produced by gut microbes are a great source of energy for the colonocytes. It is only in the last decade, with advancements of DNA sequencing platforms, that we are lettered about the association between the gut microbial composition and metabolic disorders such as obesity, dysglycemia, dyslipidemia, and cardiovascular diseases . This creates a momentum to understand the factors shaping the composition of the gut-microbiome, nature of dysbiosis (perturbation of gut microbial composition) associated with human health and ways to modulate the gut microbiome to achieve the desired health benefit

The MSDIN family in amanitin-producing mushrooms and evolution of the prolyl oligopeptidase genes

The biosynthetic pathway for amanitins and related cyclic peptides in deadly Amanita (Amanitace ae) mushrooms represents the first known ribosomal cyclic peptide pathway in the Fungi. Amanitins are found outside of the genus in distantly related agarics Galerina (Strophariaceae) and Lepiota (Agaricaceae). A long-standing question in the field persists: why is this pathway present in these phylogenetically disjunct agarics? Two deadly mushrooms, A. pallidorosea and A. subjunquillea, were deep sequenced, and sequences of biosynthetic genes encoding MSDINs (cyclic peptide presursor) and prolyl oligopeptidases (POPA and POPB) were obtained. The two Amanita species yielded 20 and 18 MSDINs, respectively. In addition, two MSDIN sequences were cloned from L. brunneoincarnata basidiomes. The toxin MSDIN genes encoding amatoxins or phallotoxins from the three genera were compared, and a phylogenetic tree constructed. Prolyl oligopeptidase B (POPB), a key enzyme in the biosynthetic pathway, was used in phylogenetic reconstruction to infer the evolutionary history of the genes. Phylogenenies of POPB and POPA based on both coding and amino acid sequences showed very different results: while POPA genes clearly reflected the phylogeny of the host species, POPB did not; strikingly, it formed a well supported monophyletic clade, despite that the species belong to different genera in disjunct families. POPA, a known house-keeping gene, was shown to be restricted in a branch containing on Amanita species and the phylogeny resembled that of those Amanita species. Phylogenetic analyses of MSDIN and POPB genes showed tight coordination and disjunct disdistribution. A POPB gene tree was compared with a corresponding species tree, and distances and substitution rates were compared. The results suggested POPB genes have significant smaller distances and substitution rates were compared. The result suggested POPB genes have significant smaller distances and rates than the house-keeping rpb2, discounting massive gene loss. Under this assumption, the consistently cluster Galerina and Amantia POPB genes, while Lepiota POPB is distant. Our result suggests that horizontal gene transfer (HGT), at least between Amanita and Galerian, was invovled in the acquisition of POPB genes, which may shed light on the evolution of the a-amanitin biosynthetic pathway

Clinical and Genomic Characterization of Recurrent Enterococcal Bloodstream Infection in Patients With Acute Leukemia

Background. Rates and risk factors for recurrent enterococcal bloodstream infection (R-EBSI) and whether the same genetic lineage causes index EBSI and R-EBSI are unknown in patients with acute leukemia (AL) receiving chemotherapy. Methods. Ninety-two AL patients with EBSI from 2010 to 2015 were included. Enterococcal bloodstream infection was defined by 31 positive blood cultures for Enterococcus faecium or Enterococcus faecalis and fever, hypotension, or chills. Clearance was defined by 31 negative cultures 324 hours after last positive culture and defervescence. Recurrent enterococcal bloodstream infection was defined by a positive blood culture for Enterococcus 324 hours after clearance. Categorical variables were reported as proportions and compared by the χ2 test. Continuous variables were summarized by median and interquartile range (IQR) and compared by the Wilcoxon-Mann-Whitney Test. P values \u3c.05 were considered significant. Whole-genome sequencing was performed on available paired BSI isolates from 7 patients. Results. Twenty-four patients (26%) had 31 episodes of R-EBSI. Median time to R-EBSI (IQR) was 26 (13–50) days. Patients with R-EBSI had significantly longer durations of fever and metronidazole exposure during their index EBSI. Thirty-nine percent of E. faecium R-EBSI isolates became daptomycin-nonsusceptible Enterococcus (DNSE) following daptomycin therapy for index EBSI. Whole-genome sequencing analysis confirmed high probability of genetic relatedness of index EBSI and R-EBSI isolates for 4/7 patients. Conclusions. Recurrent enterococcal bloodstream infection and DNSE are common in patients with AL and tend to occur within the first 30 days of index EBSI. Duration of fever and metronidazole exposure may be useful in determining risk for R-EBSI. Whole-genome sequencing analysis demonstrates that the same strain causes both EBSI and R-EBSI in some patients

A real-time PCR assay for accurate quantification of the individual members of the Altered Schaedler Flora microbiota in gnotobiotic mice

Changes in the gastrointestinal microbial community are frequently associated with chronic diseases such as Inflammatory Bowel Diseases. However, understanding the relationship of any individual taxon within the community to host physiology is made complex due to the diversity and individuality of the gut microbiota. Defined microbial communities such as the Altered Schaedler Flora (ASF) help alleviate the challenges of a diverse microbiota by allowing one to interrogate the relationship between individual bacterial species and host responses. An important aspect of studying these relationships with defined microbial communities is the ability to measure the population abundance and dynamics of each member. Herein, we describe the development of an improved ASF species-specific and sensitive real-time quantitative polymerase chain reaction (qPCR) for use with SYBR Green chemistry to accurately assess individual ASF member abundance. This approach targets hypervariable regions V1 through V3 of the 16S rRNA gene of each ASF taxon to enhance assay specificity. We demonstrate the reproducibility, sensitivity and application of this new method by quantifying each ASF bacterium in two inbred mouse lines. We also used it to assess changes in ASF member abundance before and after acute antibiotic perturbation of the community as well as in mice fed two different diets. Additionally, we describe a nested PCR assay for the detection of lowly abundant ASF members. Altogether, this improved qPCR method will facilitate gnotobiotic research involving the ASF community by allowing for reproducible quantification of its members under various physiological conditions