Acceptor specificity of the human leukocyte alpha3 fucosyltransferase: role of FucT-VII in the generation of selectin ligands

The alpha3 fucosyltransferase, FucT-VII, is one of the key glycosyltransferases involved in the biosynthesis of the sialyl Lewis X (sLex) antigen on human leukocytes. The sialyl Lewis X antigen (NeuAcalpha(2-3)Galbeta(1-4)[Fucalpha(1-3)]GlcNAc-R) is an essential component of the recruitment of leukocytes to sites of inflammation, mediating the primary interaction between circulating leukocytes and activated endothelium. In order to characterize the enzymatic properties of the leukocyte alpha3 fucosyltransferase FucT-VII, the enzyme has been expressed in Trichoplusia ni insect cells. The enzyme is capable of synthesizing both sLexand sialyl-dimeric-Lexstructures in vitro , from 3'-sialyl-lacNAc and VIM-2 structures, respectively, with only low levels of fucose transfer observed to neutral or 3'-sulfated acceptors. Studies using fucosylated NeuAcalpha(2-3)-(Galbeta(1- 4)GlcNAc)3-Me acceptors demonstrate that FucT-VII is able to synthesize both di-fucosylated and tri-fucosylated structures from mono- fucosylated precursors, but preferentially fucosylates the distal GlcNAc within a polylactosamine chain. Furthermore, the rate of fucosylation of the internal GlcNAc residues is reduced once fucose has been added to the distal GlcNAc. These results indicate that FucT-VII is capable of generating complex selectin ligands, in vitro , however the order of fucose addition to the lactosamine chain affects the rate of selectin ligand synthesis.      

A Highlights from MBoC Selection: A troponin T variant linked with pediatric dilated cardiomyopathy reduces the coupling of thin filament activation to myosin and calcium binding

Dilated cardiomyopathy (DCM) is a significant cause of pediatric heart failure. Mutations in proteins that regulate cardiac muscle contraction can cause DCM; however, the mechanisms by which molecular-level mutations contribute to cellular dysfunction are not well understood. Better understanding of these mechanisms might enable the development of targeted therapeutics that benefit patient subpopulations with mutations that cause common biophysical defects. We examined the molecular- and cellular-level impacts of a troponin T variant associated with pediatric-onset DCM, R134G. The R134G variant decreased calcium sensitivity in an in vitro motility assay. Using stopped-flow and steady-state fluorescence measurements, we determined the molecular mechanism of the altered calcium sensitivity: R134G decouples calcium binding by troponin from the closed-to-open transition of the thin filament and decreases the cooperativity of myosin binding to regulated thin filaments. Consistent with the prediction that these effects would cause reduced force per sarcomere, cardiomyocytes carrying the R134G mutation are hypocontractile. They also show hallmarks of DCM that lie downstream of the initial insult, including disorganized sarcomeres and cellular hypertrophy. These results reinforce the importance of multiscale studies to fully understand mechanisms underlying human disease and highlight the value of mechanism-based precision medicine approaches for DCM.     

ERRATUM: New Body Mass Estimates for Omomys carteri,a Middle Eocene Primate From North America. Am J Phys Anthropol 109:41–52.

Payseur BA, Covert HA, Vinyard CJ, Dagosto M. 1999. New Body Mass Estimates for Omomys carteri, a Middle Eocene Primate From North America. Am J Phys Anthropol 109:41–52. This article included an incomplete Table 2. The final two columns, showing “Intercept” and “SEE” data were omitted. The complete Table 2, with these two columns included, is provided below.     

Trans-substitution of the proximal hydrogen bond in myoglobin: I. Structural consequences of hydrogen bond deletion

The structural role of a side-chain to side-chain protein hydrogen bond is examined using trans-substitution of the proximal histidine of myoglobin with methylimidazoles (Barrick, Biochemistry 1994;33:6546-6554). Modification of the chemical structure of exogenous ligands allows this hydrogen bond to be disrupted. Comparison of the crystal structures of H93G myoglobin complexed 4-methylimidazole (4meimd; methylation at carbon 4) and 1-methylimidazole (1meimd; methylation at the adjacent nitrogen, preventing hydrogen bonding between the imidazole ligand and the protein) shows that the polypeptide, heme, and methylimidazole orientations are the same within error. For 4meimd there appear to be major and minor conformations corresponding to different tautomeric states of the ligand. Conformational heterogeneity is also seen in the hyperfine-shifted region of the NMR spectrum of 4meimd complexed with high-spin H93G deoxyMb. The major conformation of the 4meimd ligand and the 1meimd ligand, as seen in the respective crystal structures, are quite similar except that the proximal ligand NH-to-Ser92-OH hydrogen bond is eliminated in the 1meimd complex, and instead the proximal ligand CH is adjacent to the Ser92-OH. Thus, this system provides a means to eliminate the Mb proximal hydrogen bond in a chemically and structurally conservative way.     

Effect of multiple prolyl isomerization reactions on the stability and folding kinetics of the notch ankyrin domain: experiment and theory

Studies on the folding kinetics of the Notch ankyrin domain have demonstrated that the major refolding phase is slow, the minor refolding phase is limited by the isomerization of prolyl peptide bonds, and that unfolding is multiexponential. Here, we explore the relationship between prolyl isomerization and folding heterogeneity using a combination of experiment and simulation. Proline residues were replaced with alanine, both singly and in various combinations. These destabilizing substitutions combine to eliminate the minor refolding phase, although unfolding heterogeneity persists even when all seven proline residues are replaced. To test whether prolyl isomerization influences the major refolding phase, we modeled folding and prolyl isomerization as a system of sequential reactions. Simulations that use rate constants of the major folding phase of the Notch ankyrin domain to represent intrinsic folding indicate that even with seven prolyl isomerization reactions, only two significant phases should be observed, and that the fast observed phase provides a good approximation of the intrinsic folding in the absence of prolyl isomerization. These results indicate that the major refolding phase of the Notch ankyrin domain reflects an intrinsically slow folding transition, rather than coupling of fast folding events with slow prolyl isomerization steps. This is consistent with the observation that the single observed refolding phase of a construct in which all proline residues are replaced remains slow. Finally, the simulation fails to produce a second unfolding phase at high urea concentrations, indicating that prolyl isomerization does not play a role in the three-state mechanism that leads to this heterogeneity.     

Experimental characterization of the folding kinetics of the notch ankyrin domain

Proteins constructed from linear arrays of tandem repeats provide a simplified architecture for understanding protein folding. Here, we examine the folding kinetics of the ankyrin repeat domain from the Drosophila Notch receptor, which consists of six folded ankyrin modules and a seventh partly disordered N-terminal ankyrin repeat sequence. Both the refolding and unfolding kinetics are best described as a sum of two exponential phases. The slow, minor refolding phase is limited by prolyl isomerization in the denatured state (D). The minor unfolding phase, which appears as a lag during fluorescence-detected unfolding, is consistent with an on-pathway intermediate (I). This intermediate, although not directly detected during refolding, is shown to be populated by interrupted refolding experiments. When plotted against urea, the rate constants for the major unfolding and refolding phases define a single non-linear v-shaped chevron, as does the minor unfolding phase. These two chevrons, along with unfolding amplitudes, are well-fitted by a sequential three-state model, which yields rate constants for the individual steps in folding and unfolding. Based on these fitted parameters, the D to I step is rate-limiting, and closely matches the major observed refolding phase at low denaturant concentrations. I appears to be midway between N and D in folding free energy and denaturant sensitivity, but has Trp fluorescence properties close to N. Although the Notch ankyrin domain has a simple architecture, folding is slow, with the limiting refolding rate constant as much as seven orders of magnitude smaller than expected from topological predictions.     

Structure and Notch receptor binding of the tandem WWE domain of Deltex

Deltex is a cytosolic effector of Notch signaling thought to bind through its N-terminal domain to the Notch receptor. Here we report the structure of the Drosophila Deltex N-terminal domain, which contains two tandem WWE sequence repeats. The WWE repeats, which adopt a novel fold, are related by an approximate two-fold axis of rotation. Although the WWE repeats are structurally distinct, they interact extensively and form a deep cleft at their junction that appears well suited for ligand binding. The two repeats are thermodynamically coupled; this coupling is mediated in part by a conserved segment that is immediately C-terminal to the second WWE domain. We demonstrate that although the Deltex WWE tandem is monomeric in solution, it forms a heterodimer with the ankyrin domain of the Notch receptor. These results provide structural and functional insight into how Deltex modulates Notch signaling, and how WWE modules recognize targets for ubiquitination.     

High definition bronchoscopy: a randomized exploratory study of diagnostic value compared to standard white light bronchoscopy and autofluorescence bronchoscopy

Background

Videobronchoscopy is an essential diagnostic procedure for evaluation of the central airways and pivotal for the diagnosis and staging of lung cancer. Technological improvements have resulted in high definition (HD) images with advanced real time image enhancement techniques (i-scan).

Objectives

In this study we aimed to explore the sensitivity of HD+ i-scan bronchoscopy for detection of epithelial changes like vascular abnormalities and suspicious preinvasive lesions, and tumors.

Methods

In patients scheduled for a therapeutic or diagnostic procedure under general anesthesia videos of the bronchial tree were made using 5 videobronchoscopy modes in random order: normal white light videobronchoscopy (WLB), HD-bronchoscopy (HD), HD bronchoscopy with surface enhancement technique (i-scan1), HD with surface- and tone enhancement technique (i-scan2) and dual mode autofluorescence videobronchoscopy (AFB). The videos were scored in random order by two independent and blinded expert bronchoscopists.

Results

In 29 patients all videos were available for analysis. Vascular abnormalities were scored most frequently in HD + i-scan2 bronchoscopy (1.33 ± 0.29 abnormal or suspicious sites per patient) as compared to 0.12 ± 0.05 site for AFB (P = 0.003). Sites suspicious for preinvasive lesions were most frequently reported using AFB (0.74 ± 0.12 sites per patient) as compared to 0.17 ± 0.06 for both WLB and HD bronchoscopy (P = 0.003). Tumors were detected equally by all modalities. The preferred modality was HD bronchoscopy with i-scan (tone- plus surface and surface enhancement in respectively 38% and 35% of cases P = 0.006).

Conclusions

This study shows that high definition bronchoscopy with image enhancement technique may result in better detection of subtle vascular abnormalities in the airways. Since these abnormalities may be related to preneoplastic lesions and tumors this is of clinical relevance. Further investigations using this technique relating imaging to histology are warranted.     

The BioLexicon: a large-scale terminological resource for biomedical text mining

Background

Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events.

Results

This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard.

Conclusions

The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.     

Application of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor Aggressiveness

To assess the usefulness and applications of machine vision (MV) and machine learning (ML) techniques that have been used to develop a single cell-based phenotypic (live and fixed biomarkers) platform that correlates with tumor biological aggressiveness and risk stratification, 100 fresh prostate samples were acquired, and areas of prostate cancer were determined by post-surgery pathology reports logged by an independent pathologist. The prostate samples were dissociated into single-cell suspensions in the presence of an extracellular matrix formulation. These samples were analyzed via live-cell microscopy. Dynamic and fixed phenotypic biomarkers per cell were quantified using objective MV software and ML algorithms. The predictive nature of the ML algorithms was developed in two stages. First, random forest (RF) algorithms were developed using 70% of the samples. The developed algorithms were then tested for their predictive performance using the blinded test dataset that contained 30% of the samples in the second stage. Based on the ROC (receiver operating characteristic) curve analysis, thresholds were set to maximize both sensitivity and specificity. We determined the sensitivity and specificity of the assay by comparing the algorithm-generated predictions with adverse pathologic features in the radical prostatectomy (RP) specimens. Using MV and ML algorithms, the biomarkers predictive of adverse pathology at RP were ranked and a prostate cancer patient risk stratification test was developed that distinguishes patients based on surgical adverse pathology features. The ability to identify and track large numbers of individual cells over the length of the microscopy experimental monitoring cycles, in an automated way, created a large biomarker dataset of primary biomarkers. This biomarker dataset was then interrogated with ML algorithms used to correlate with post-surgical adverse pathology findings. Algorithms were generated that predicted adverse pathology with >0.85 sensitivity and specificity and an AUC (area under the curve) of >0.85. Phenotypic biomarkers provide cellular and molecular details that are informative for predicting post-surgical adverse pathologies when considering tumor biopsy samples. Artificial intelligence ML-based approaches for cancer risk stratification are emerging as important and powerful tools to compliment current measures of risk stratification. These techniques have capabilities to address tumor heterogeneity and the molecular complexity of prostate cancer. Specifically, the phenotypic test is a novel example of leveraging biomarkers and advances in MV and ML for developing a powerful prognostic and risk-stratification tool for prostate cancer patients.