7 The Molecular Biology of Tryptophan Synthase: A Model for Protein–Protein Interaction

Abstract

The use of plastic produced from non-renewable resources constitutes a major environmental problem of the modern society. Polylactide polymers (PLA) have recently gained enormous attention as one possible substitution of petroleum derived polymers. A prerequisite for high quality PLA production is the provision of optically pure lactic acid, which cannot be obtained by chemical synthesis in an economical way. Microbial fermentation is therefore the commercial option to obtain lactic acid as monomer for PLA production. However, one major economic hurdle for commercial lactic acid production as basis for PLA is the costly separation procedure, which is needed to recover and purify the product from the fermentation broth. Yeasts, such as Saccharomyces cerevisiae (bakers yeast) offer themselves as production organisms because they can tolerate low pH and grow on mineral media what eases the purification of the acid. However, naturally yeasts do not produce lactic acid. By metabolic engineering, ethanol was exchanged with lactic acid as end product of fermentation. A vast amount of effort has been invested into the development of yeasts for lactic acid production since the first paper on this topic by Dequin and process insight. If pH stress is used as basis for DNA microarray analyses, in order to improve the host, what exactly is addressed? Growth? Or productivity? They might be connected, but can be negatively correlated. A better growing strain might not be a better producer. So if the question was growth, the answer might not be what was initially intended (productivity).

A major task for the future is to learn to ask the right questions – a lot of studies intended to lead to better productivity, did lead to interesting results, but NOT to better production strains.

Taking together what we learned from lactic acid production with yeasts, we see a bright future for bulk and fine chemical production with these versatile hosts.     

Protein Glycosylation in Helicobacter pylori: Beyond the Flagellins?

Glycosylation of flagellins by pseudaminic acid is required for virulence in Helicobacter pylori. We demonstrate that, in H. pylori, glycosylation extends to proteins other than flagellins and to sugars other than pseudaminic acid. Several candidate glycoproteins distinct from the flagellins were detected via ProQ-emerald staining and DIG- or biotin- hydrazide labeling of the soluble and outer membrane fractions of wild-type H. pylori, suggesting that protein glycosylation is not limited to the flagellins. DIG-hydrazide labeling of proteins from pseudaminic acid biosynthesis pathway mutants showed that the glycosylation of some glycoproteins is not dependent on the pseudaminic acid glycosylation pathway, indicating the existence of a novel glycosylation pathway. Fractions enriched in glycoprotein candidates by ion exchange chromatography were used to extract the sugars by acid hydrolysis. High performance anion exchange chromatography with pulsed amperometric detection revealed characteristic monosaccharide peaks in these extracts. The monosaccharides were then identified by LC-ESI-MS/MS. The spectra are consistent with sugars such as 5,7-diacetamido-3,5,7,9-tetradeoxy-L-glycero-L-manno-nonulosonic acid (Pse5Ac7Ac) previously described on flagellins, 5-acetamidino-7-acetamido-3,5,7,9-tetradeoxy-L-glycero-L-manno-nonulosonic acid (Pse5Am7Ac), bacillosamine derivatives and a potential legionaminic acid derivative (Leg5AmNMe7Ac) which were not previously identified in H. pylori. These data open the way to the study of the mechanism and role of protein glycosylation on protein function and virulence in H. pylori.     

Computational Prediction of Protein–Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.     

The rOmp22–HpaA Fusion Protein Confers Protective Immunity Against Helicobacter pylori in Mice

Helicobacter pylori (H. pylori) plays an essential role in the development of various gastroduodenal diseases; however, no vaccines preventing H. pylori infection have been available now. This study was to evaluate the protective effect of rOmp22–HpaA fusion protein against H. pylori infection in mouse model and to screen the candidate to be used in the development of an oral vaccine against H. pylori. rOmp22, rHpaA, rOmp22+rHpaA, and rOmp22–HpaA groups were used to immunize mice with mLT63 as adjuvant by intragastric route, respectively, four times at 1-week intervals. Two weeks after last immunization, all of the animals were orally challenged with H. pylori NCTC11637 and then were killed after another 2 weeks. The mice gastric tissue of all groups was separated to detect the presence of infection by urease tests, to culture H. pylori, and to observe the histological characteristics. The protective effect against H. pylori challenge in mice immunized with rOmp22–HpaA fusion protein and mLT63 adjuvant was significantly higher than PBS and mLT63 control groups (P < 0.05), but no significant difference was detected among rOmp22, rHpaA, rOmp22+rHpaA, and rOmp22–HpaA groups (P > 0.05). rOmp22–HpaA fusion protein retained immunogenicity and could be used as an antigen candidate in the development of an oral vaccine against H. pylori infection.     

Dynamic Circadian Protein–Protein Interaction Networks Predict Temporal Organization of Cellular Functions

Essentially all biological processes depend on protein–protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (∼24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner.     

A Critical Assessment of Information-guided Protein–Protein Docking Predictions

The structures of protein complexes are increasingly predicted via protein–protein docking (PPD) using ambiguous interaction data to help guide the docking. These data often are incomplete and contain errors and therefore could lead to incorrect docking predictions. In this study, we performed a series of PPD simulations to examine the effects of incompletely and incorrectly assigned interface residues on the success rate of PPD predictions. The results for a widely used PPD benchmark dataset obtained using a new interface information-driven PPD (IPPD) method developed in this work showed that the success rate for an acceptable top-ranked model varied, depending on the information content used, from as high as 95% when contact relationships (though not contact distances) were known for all residues to 78% when only the interface/non-interface state of the residues was known. However, the success rates decreased rapidly to ∼40% when the interface/non-interface state of 20% of the residues was assigned incorrectly, and to less than 5% for a 40% incorrect assignment. Comparisons with results obtained by re-ranking a global search and with those reported for other data-guided PPD methods showed that, in general, IPPD performed better than re-ranking when the information used was more complete and more accurate, but worse when it was not, and that when using bioinformatics-predicted information on interface residues, IPPD and other data-guided PPD methods performed poorly, at a level similar to simulations with a 40% incorrect assignment. These results provide guidelines for using information about interface residues to improve PPD predictions and reveal a bottleneck for such improvement imposed by the low accuracy of current bioinformatic interface residue predictions.Proteins work in close association with other proteins to mediate the intricate functions of a cell. The atomic resolution of the structure of a protein complex can therefore help one understand a protein''s function in detail. Protein–protein docking (PPD),¹ a computational approach that complements experimental structure determinations, has attracted increasing research interest (1, 2), in part because it remains challenging to determine most structures of protein complexes via experimental techniques (3).To improve the performance of PPD predictions, experimentally derived data (e.g. distances) and information (e.g. the identity of interface residues) have been used either as a filter allowing less plausible docking solutions to be disregarded (4–9) or as a constraint to guide the docking process (10, 11). Various types of data and information have been used to aid PPD (12); these range from distances between, or the relative orientation of, the two interacting proteins to simple identification of the amino acid residues directly involved in the binding of the two proteins (13). Despite considerable success, the caveat for all these data-guided PPD predictions is that the data or information used must be correct in order to avoid spurious results caused by misguiding (12). It is therefore pertinent and important to evaluate the effects of errors in the incorporated data or information on the quality of PPD solutions.We have recently shown that the use of just a few distance constraints can improve the success rates of PPD such that they rival, or are even better than, those of a global search ranked using a sophisticated energy function, and that errors in the distance data significantly decrease the success rates of prediction (11). However, because distance data for interacting proteins are usually hard to obtain, other types of data or information, even if “ambiguous” (10), are increasingly used in PPD predictions (12, 14). In this study, we investigated the effects of incompletely and incorrectly assigned interface/non-interface residues, a major source of the so-called ambiguous data, on information-guided PPD predictions.As illustrated in Fig. 1, the information content of interface/non-interface residues can be rich enough to reveal the identity of every pair of residues in contact, but not their contact distances, or so poor as to reveal the interface/non-interface state of these residues but not their pairing relationship, for one or both of the two interacting proteins. To determine how these different levels of residue information content can help PPD predictions and the extent to which the use of incorrectly assigned residues degrades prediction success rates, we have developed a new interface information-driven PPD method (IPPD) and carried out a series of PPD simulations on a well-tested benchmark dataset. The results showed that when the information content was rich, excellent predictions (success rates for producing an acceptable top-ranked model > 70%) could be made via IPPD or by re-ranking a global search''s solutions using the same interface information, and that, encouragingly, the success of predictions remained respectable (top-ranked success rates > 15%) when the content was poor. However, when enough of the interface residues were incorrectly assigned, as would be the case when using interface residues predicted by a state-of-the-art bioinformatics method such as CPORT (15), few models ranked first by IPPD or other PPD methods, including HADDOCK (10), a popular ambiguous data-driven PPD method, came close to being acceptable. These results suggest that we can greatly increase the power of PPD predictions for practical applications only if the accuracy of current bioinformatics methods for predicting the interface residues of protein complexes can be significantly improved.Open in a separate windowFig. 1.Contact matrix of two interacting proteins, A and B, and the contact vectors of their residues. In the contact matrix, M_ij = 1 or 0, respectively, denotes contact or a lack of contact between residue i in protein A and residue j in protein B. In the contact vectors, V_Ai = 1 or 0, respectively, when residue Ai has, or does not have, at least one contact with any residue of protein B.     

Cholesterol glucosylation–based survival strategy in Helicobacter pylori

Helicobacter pylori is a major chronic health problem, infecting more than half of the population worldwide. H. pylori infection is linked with various clinical complications ranging from gastritis to gastric cancer. The resolution of gastritis and peptic ulcer appears to be linked with the eradication of H. pylori. However, resistance to antibiotics and eradication failure rates are reaching alarmingly high levels. This calls for urgent action in finding alternate methods for H. pylori eradication. Here, we discuss the recently identified mechanism of H. pylori known as cholesterol glucosylation, mediated by the enzyme cholesterol-α-glucosyltransferase, encoded by the gene cgt. Cholesterol glucosylation serves several functions that include promoting immune evasion, enhancing antibiotic resistance, maintaining the native helical morphology, and supporting functions of prominent virulence factors such as CagA and VacA. Consequently, strategies aiming at inhibition of the cholesterol glucosylation process have the potential to attenuate the potency of H. pylori infection and abrogate H. pylori immune evasion capabilities. Knockout of H. pylori cgt results in unsuccessful colonization and elimination by the host immune responses. Moreover, blocking cholesterol glucosylation can reverse antibiotic susceptibility in H. pylori. In this work, we review the main roles of cholesterol glucosylation in H. pylori and evaluate whether this mechanism can be targeted for the development of alternate methods for eradication of H. pylori infection.     

Is Helicobacter pylori the cause of dyspepsia?

OBJECTIVE--To determine the association between infection with Helicobacter pylori and dyspepsia. DESIGN--Cross sectional study of dyspeptic subjects and age and sex matched controls identified by a questionnaire survey of all inhabitants aged 20-69. (Endoscopy, histological examination, and microbiological examinations of biopsies from the gastric mucosa were performed blind.) SETTING--Population based survey in Sørreisa, Norway. SUBJECTS--All 782 dyspeptic subjects (excluding those with a previous history of peptic ulcer, gall stones or kidney stones, and coronary heart disease) and controls were offered an endoscopy, of whom 309 dyspeptic subjects and 310 controls attended. MAIN OUTCOME MEASURES--Prevalences of endoscopic and histological diagnoses and of cultures positive for H pylori. RESULTS--A high prevalence of positive cultures, increasing with age, was found in both dyspeptic subjects (48%) and non-dyspeptic controls (36%) (p = 0.004). Positive cultures in both dyspeptic subjects and controls were strongly associated with histological gastritis (70%, 95% confidence interval 65.5 to 85.3; 60%, 52.7 to 67.7, respectively) and peptic ulcer (92%, 61.5 to 99.8; 64.1, 9.4 to 99.2, respectively). Only 3% of subjects with a histologically non-inflamed gastric mucosa had this infection (dyspeptic subjects 2%, 0.2 to 7.0; controls 4%; 1.2 to 8.8). CONCLUSIONS--The relation between dyspeptic symptoms and H pylori is dubious; H pylori seems to have a pathogenetic role in gastritis and may be a contributing factor but not a cause of peptic ulcer.     

Assessing Coverage of Protein Interaction Data Using Capture–Recapture Models

Protein interaction networks comprise thousands of individual binary links between distinct proteins. Whilst these data have attracted considerable attention and been the focus of many different studies, the networks, their structure, function, and how they change over time are still not fully known. More importantly, there is still considerable uncertainty regarding their size, and the quality of the available data continues to be questioned. Here, we employ statistical models of the experimental sampling process, in particular capture–recapture methods, in order to assess the false discovery rate and size of protein interaction networks. We uses these methods to gauge the ability of different experimental systems to find the true binary interactome. Our model allows us to obtain estimates for the size and false-discovery rate from simple considerations regarding the number of repeatedly interactions, and provides suggestions as to how we can exploit this information in order to reduce the effects of noise in such data. In particular our approach does not require a reference dataset. We estimate that approximately more than half of the true physical interactome has now been sampled in yeast.     

Global estimate of gastric cancer in Helicobacter pylori–infected population: A systematic review and meta-analysis

There is information regarding the rates of gastric cancer (GC) in different populations and the important role of Helicobacter pylori in GC development; however, no comprehensive study has yet been performed to investigate the prevalence of GC in H. pylori–infected patients. PubMed, Embase, and Cochrane Library through January 1, 2000 were searched without language restrictions. Quality of included studies was assessed with a critical appraisal checklist recommended by the Joanna Briggs Institute. All of the analyses were conducted using Comprehensive Meta-Analysis Software Version 2.0 and Stata 14.0. Forty-four studies from 17 countries were included. The pooled frequency of GC was 17.4% (95% confidence interval: 16.4–18.5) in H. pylori–infected population. The frequency of GC among H. pylori–infected population varied markedly across countries. The highest rate of GC was observed in H. pylori–infected individuals from Asian countries. The frequency of GC was relatively high in H. pylori–infected population in the world. However, the eradication of H. pylori might be a promising strategy for GC prevention, especially in high-risk populations such as Asian countries.     

Helicobacter pylori: an invading microorganism? A review

In this review we evaluate the pros and cons of Helicobacter pylori invasion of epithelial cells as part of the natural history of H. pylori infection. H. pylori is generally considered an extracellular microorganism. However, a growing body of evidence supports the controversial hypothesis that at least a subset of H. pylori microorganisms has an intracellular (intraepithelial) location. Most significant is the fact that H. pylori invades cultured epithelial cells with invasion frequencies similar to Yersinia enterocolitica and better than Shigella flexneri; furthermore, studies of invasion mechanisms suggest that H. pylori invasion of and survival within epithelial cells is not merely a passive event, but requires active participation of the microorganism. Although many studies of human gastric biopsy specimens have failed to demonstrate any intracellular H. pylori, some studies have revealed a minor fraction of H. pylori inside gastric epithelial cells, with possible linkage to peptic ulceration and epithelial cell damage. In conclusion, these data encourage further research to establish whether intracellular H. pylori does play a role in H. pylori colonization of the human stomach and in peptic ulcer pathogenesis.