Multiple duplications of yeast hexose transport genes in response to selection in a glucose-limited environment

When microbes evolve in a continuous, nutrient-limited environment, natural selection can be predicted to favor genetic changes that give cells greater access to limiting substrate. We analyzed a population of baker's yeast that underwent 450 generations of glucose-limited growth. Relative to the strain used as the inoculum, the predominant cell type at the end of this experiment sustains growth at significantly lower steady-state glucose concentrations and demonstrates markedly enhanced cell yield per mole glucose, significantly enhanced high-affinity glucose transport, and greater relative fitness in pairwise competition. These changes are correlated with increased levels of mRNA hybridizing to probe generated from the hexose transport locus HXT6. Further analysis of the evolved strain reveals the existence of multiple tandem duplications involving two highly similar, high- affinity hexose transport loci, HXT6 and HXT7. Selection appears to have favored changes that result in the formation of more than three chimeric genes derived from the upstream promoter of the HXT7 gene and the coding sequence of HXT6. We propose a genetic mechanism to account for these changes and speculate as to their adaptive significance in the context of gene duplication as a common response of microorganisms to nutrient limitation.      

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.      

Protection from fluorescein isothiocyanate-induced fibrosis in IL-13-deficient, but not IL-4-deficient, mice results from impaired collagen synthesis by fibroblasts

Intratracheal injection of FITC results in acute lung injury and progresses to fibrosis by day 21 postchallenge. In response to FITC, BALB/c mice produce IL-4 and IL-13 in the lung. To investigate whether IL-4 and/or IL-13 were important profibrotic mediators in this model, we examined the fibrotic response to FITC in mice that were genetically deficient in IL-4 (IL-4(-/-)), IL-13 (IL-13(-/-)), or IL-4 and IL-13 combined (IL-4/13(-/-)). Baseline levels of collagen were similar in all mice. In response to FITC, both BALB/c and IL-4(-/-) mice developed fibrosis, whereas the IL-13(-/-) and IL-4/13(-/-) mice were significantly protected, as measured by total lung collagen levels and histology. Total leukocyte recruitment to the lung was similar in all four strains of mice when measured on days 7, 14, and 21 post-FITC. BALB/c mice showed prominent eosinophilia on day 7 that was absent in IL-4(-/-), IL-13(-/-), and IL-4/13(-/-) mice, suggesting that eosinophilia is not necessary for development of a fibrotic response. There were no significant differences in the percentages of any other leukocytes analyzed between the genotypes. Similarly, protection in IL-13(-/-) mice was not associated with alterations in cytokine or eicosanoid profiles. Interestingly, TGF-beta1 production was not reduced in IL-13(-/-) mice. Analyses of fibroblasts isolated from the four genotypes demonstrated that although there were similar numbers of fibroblasts present in cultures of lung minces, fibroblasts from IL-13-deficient strains have reduced basal and stimulated levels of collagen production. IL-13Ralpha1 expression increases on fibroblasts during fibrotic responses in vivo, and IL-13 increases collagen synthesis in fibroblasts. Thus, IL-13 mediates its profibrotic actions through direct effects on fibroblast production of extracellular matrix.     

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.     

Temporal aggregation bias and inference of causal regulatory networks.

Time course experiments with microarrays have begun to provide a glimpse into the dynamic behavior of gene expression. In a typical experiment, scientists use microarrays to measure the abundance of mRNA at discrete time points after the onset of a stimulus. Recently, there has been much work on using these data to infer causal regulatory networks that model how genes influence each other. However, microarray studies typically have slow sampling rates that can lead to temporal aggregation of the signal. That is, each successive sampling point represents the sum of all signal changes since the previous sample. In this paper, we show that temporal aggregation can bias algorithms for causal inference and lead them to discover spurious relations that would not be found if the signal were sampled at a much faster rate. We discuss the implications of temporal aggregation on inference, the problems it creates, and potential directions for solutions.     

Quirks of dye nomenclature. 3. Trypan blue

Trypan blue is colorant from the 19^th century that has an association with Africa as a chemotherapeutic agent against protozoan (Trypanosomal) infections, which cause sleeping sickness. The dye still is used for staining biopsies, living cells and organisms, and it also has been used as a colorant for textiles.     

Prediction and course of symptoms and lung function around an exacerbation in chronic obstructive pulmonary disease

Background

Frequent exacerbations induce a high burden to Chronic Obstructive Pulmonary Disease (COPD). We investigated the course of exacerbations in the published COSMIC study that investigated the effects of 1-year withdrawal of fluticasone after a 3-month run-in treatment period with salmeterol/fluticasone in patients with COPD.

Methods

In 373 patients, we evaluated diary cards for symptoms, Peak Expiratory Flow (PEF), and salbutamol use and assessed their course during exacerbations.

Results

There were 492 exacerbations in 224 patients. The level of symptoms of cough, sputum, dyspnea and nocturnal awakening steadily increased from 2 weeks prior to exacerbation, with a sharp rise during the last week. Symptoms of cough, sputum, and dyspnea reverted to baseline values at different rates (after 4, 4, and 7 weeks respectively), whereas symptoms of nocturnal awakening were still increased after eight weeks. The course of symptoms was similar around a first and second exacerbation. Increases in symptoms and salbutamol use and decreases in PEF were associated with a higher risk to develop an exacerbation, but with moderate predictive values, the areas under the receiver operating curves ranging from 0.63 to 0.70.

Conclusions

Exacerbations of COPD are associated with increased symptoms that persist for weeks and the course is very similar between a first and second exacerbation. COPD exacerbations are preceded by increased symptoms and salbutamol use and lower PEF, yet predictive values are too low to warrant daily use in clinical practice.