Modeling <Emphasis Type="Italic">Neisseria meningitidis</Emphasis> metabolism: from genome to metabolic fluxes

Background  

Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years.     

Simulation of human atherosclerotic femoral plaque tissue: the influence of plaque material model on numerical results

Background

Due to the limited number of experimental studies that mechanically characterise human atherosclerotic plaque tissue from the femoral arteries, a recent trend has emerged in current literature whereby one set of material data based on aortic plaque tissue is employed to numerically represent diseased femoral artery tissue. This study aims to generate novel vessel-appropriate material models for femoral plaque tissue and assess the influence of using material models based on experimental data generated from aortic plaque testing to represent diseased femoral arterial tissue.

Methods

Novel material models based on experimental data generated from testing of atherosclerotic femoral artery tissue are developed and a computational analysis of the revascularisation of a quarter model idealised diseased femoral artery from a 90% diameter stenosis to a 10% diameter stenosis is performed using these novel material models. The simulation is also performed using material models based on experimental data obtained from aortic plaque testing in order to examine the effect of employing vessel appropriate material models versus those currently employed in literature to represent femoral plaque tissue.

Results

Simulations that employ material models based on atherosclerotic aortic tissue exhibit much higher maximum principal stresses within the plaque than simulations that employ material models based on atherosclerotic femoral tissue. Specifically, employing a material model based on calcified aortic tissue, instead of one based on heavily calcified femoral tissue, to represent diseased femoral arterial vessels results in a 487 fold increase in maximum principal stress within the plaque at a depth of 0.8 mm from the lumen.

Conclusions

Large differences are induced on numerical results as a consequence of employing material models based on aortic plaque, in place of material models based on femoral plaque, to represent a diseased femoral vessel. Due to these large discrepancies, future studies should seek to employ vessel-appropriate material models to simulate the response of diseased femoral tissue in order to obtain the most accurate numerical results.

     

Review and classification of variability analysis techniques with clinical applications

Background

Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction.

Method

A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE.

Results

The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%.

Conclusions

The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study.     

Impact on disease development, genomic location and biological function of copy number alterations in non-small cell lung cancer

Lung cancer, of which more than 80% is non-small cell, is the leading cause of cancer-related death in the United States. Copy number alterations (CNAs) in lung cancer have been shown to be positionally clustered in certain genomic regions. However, it remains unclear whether genes with copy number changes are functionally clustered. Using a dense single nucleotide polymorphism array, we performed genome-wide copy number analyses of a large collection of non-small cell lung tumors (n = 301). We proposed a formal statistical test for CNAs between different groups (e.g., non-involved lung vs. tumors, early vs. late stage tumors). We also customized the gene set enrichment analysis (GSEA) algorithm to investigate the overrepresentation of genes with CNAs in predefined biological pathways and gene sets (i.e., functional clustering). We found that CNAs events increase substantially from germline, early stage to late stage tumor. In addition to genomic position, CNAs tend to occur away from the gene locations, especially in germline, non-involved tissue and early stage tumors. Such tendency decreases from germline to early stage and then to late stage tumors, suggesting a relaxation of selection during tumor progression. Furthermore, genes with CNAs in non-small cell lung tumors were enriched in certain gene sets and biological pathways that play crucial roles in oncogenesis and cancer progression, demonstrating the functional aspect of CNAs in the context of biological pathways that were overlooked previously. We conclude that CNAs increase with disease progression and CNAs are both positionally and functionally clustered. The potential functional capabilities acquired via CNAs may be sufficient for normal cells to transform into malignant cells.     

The natural history of group I introns

There are four major classes of introns: self-splicing group I and group II introns, tRNA and/or archaeal introns and spliceosomal introns in nuclear pre-mRNA. Group I introns are widely distributed in protists, bacteria and bacteriophages. Group II introns are found in fungal and land plant mitochondria, algal plastids, bacteria and Archaea. Group II and spliceosomal introns share a common splicing pathway and might be related to each other. The tRNA and/or archaeal introns are found in the nuclear tRNA of eukaryotes and in archaeal tRNA, rRNA and mRNA. The mechanisms underlying the self-splicing and mobility of a few model group I introns are well understood. By contrast, the role of these highly distinct processes in the evolution of the 1500 group I introns found thus far in nature (e.g. in algae and fungi) has only recently been clarified. The explosion of new sequence data has facilitated the use of comparative methods to understand group I intron evolution in a broader context and to generate hypotheses about intron insertion, splicing and spread that can be tested experimentally.     

Homogeneity of the 16S rDNA sequence among geographically disparate isolates of Taylorella equigenitalis

Background

At present, six accessible sequences of 16S rDNA from Taylorella equigenitalis (T. equigenitalis) are available, whose sequence differences occur at a few nucleotide positions. Thus it is important to determine these sequences from additional strains in other countries, if possible, in order to clarify any anomalies regarding 16S rDNA sequence heterogeneity. Here, we clone and sequence the approximate full-length 16S rDNA from additional strains of T. equigenitalis isolated in Japan, Australia and France and compare these sequences to the existing published sequences.

Results

Clarification of any anomalies regarding 16S rDNA sequence heterogeneity of T. equigenitalis was carried out. When cloning, sequencing and comparison of the approximate full-length 16S rDNA from 17 strains of T. equigenitalis isolated in Japan, Australia and France, nucleotide sequence differences were demonstrated at the six loci in the 1,469 nucleotide sequence. Moreover, 12 polymorphic sites occurred among 23 sequences of the 16S rDNA, including the six reference sequences.

Conclusion

High sequence similarity (99.5% or more) was observed throughout, except from nucleotide positions 138 to 501 where substitutions and deletions were noted.