Stability of telomeric G-quadruplexes

In most eukaryotes, telomeric DNA consists of repeats of a short motif that includes consecutive guanines and may hence fold into G-quadruplexes. Budding yeasts have telomeres composed of longer repeats and show variation in the degree of repeat homogeneity. Although telomeric sequences from several organisms have been shown to fold into G-quadruplexes in vitro, surprisingly, no study has been dedicated to the comparison of G-quadruplex folding and stability of known telomeric sequences. Furthermore, to our knowledge, folding of yeast telomeric sequences into intramolecular G-quadruplexes has never been investigated. Using biophysical and biochemical methods, we studied sequences mimicking about four repetitions of telomeric motifs from a variety of organisms, including yeasts, with the aim of comparing the G-quadruplex folding potential of telomeric sequences among eukaryotes. G-quadruplex folding did not appear to be a conserved feature among yeast telomeric sequences. By contrast, all known telomeric sequences from eukaryotes other than yeasts folded into G-quadruplexes. Nevertheless, while G(3)T(1-4)A repeats (found in a variety of organisms) and G(4)T(2,4) repeats (found in ciliates) folded into stable G-quadruplexes, G-quadruplexes formed by repetitions of G(2)T(2)A and G(2)CT(2)A motifs (found in many insects and in nematodes, respectively) appeared to be in equilibrium with non-G-quadruplex structures (likely hairpin-duplexes).     

N-cadherin expression is involved in malignant behavior of head and neck cancer in relation to epithelial-mesenchymal transition

The loss of E-cadherin and the gain of N-cadherin expression are known as "cadherin switching". Cadherin switching is a major hallmark of epithelial-mesenchymal transition (EMT). EMT is a crucial process in cancer progression, providing cancer cells with the ability to escape from the primary focus, to invade stromal tissues and to migrate to distant regions. Although down-regulation of E-cadherin is well known in various cancers, there are a few studies on N-cadherin expression in cancer. Here, therefore, we investigated whether N-cadherin expression was associated with the progression of head and neck squamous cell carcinoma (HNSCC). First, we examined the expression of N-cadherin by immunohistochemistry and its correlation with clinico-pathological findings. High expression of N-cadherin was observed in 52 of 80 HNSCC cases and was significantly correlated with malignant behaviors. Next, we examined the correlation between N-cadherin and E-cadherin. Cadherin switching (high expression of N-cadherin and low expression of E-cadherin) was found in 30 of 80 HNSCC cases and was well correlated with histological differentiation, pattern of invasion and lymph node metastasis in HNSCC cases. Moreover, we examined the expression of N-cadherin and E-cadherin by RT-PCR in 16 HNSCC cell lines to confirm the immunohistochemical findings. N-cadherin expression was observed in 7 of 16 HNSCC cells, and cadherin switching was observed in 2 HNSCC cells. Interestingly, HNSCC cells with cadherin switching have EMT features. In conclusion, we suggest that i) N-cadherin may play an important role in malignant behaviors of HNSCC, and ii) cadherin switching might be considered as a discrete critical event in EMT and metastatic potential of HNSCC.     

A Thermolabile Aldolase A Mutant Causes Fever-Induced Recurrent Rhabdomyolysis without Hemolytic Anemia

Aldolase A deficiency has been reported as a rare cause of hemolytic anemia occasionally associated with myopathy. We identified a deleterious homozygous mutation in the ALDOA gene in 3 siblings with episodic rhabdomyolysis without hemolytic anemia. Myoglobinuria was always triggered by febrile illnesses. We show that the underlying mechanism involves an exacerbation of aldolase A deficiency at high temperatures that affected myoblasts but not erythrocytes. The aldolase A deficiency was rescued by arginine supplementation in vitro but not by glycerol, betaine or benzylhydantoin, three other known chaperones, suggesting that arginine-mediated rescue operated by a mechanism other than protein chaperoning. Lipid droplets accumulated in patient myoblasts relative to control and this was increased by cytokines, and reduced by dexamethasone. Our results expand the clinical spectrum of aldolase A deficiency to isolated temperature-dependent rhabdomyolysis, and suggest that thermolability may be tissue specific. We also propose a treatment for this severe disease.

Abstract Summary

Using recent technical advances involving exome analysis, we identified a new missense mutation in the ALDOA gene, encoding a key enzyme in the glycolytic pathway. The patients presented with severe recurrent rhabdomyolysis without hemolytic anemia. The decrease of aldolase A activity in myoblasts was enhanced at high temperature and could explain the fever-induced rhabdomyolysis. By contrast, enzyme thermolability was not found in erythrocytes, possibly accounting for the unusual clinical phenotype of the patients. Enzyme thermolability was rescued by arginine supplementation in vitro but not by other chaperone compounds.     

SPF: A spatial and functional data analytic approach to cell imaging data

The tumor microenvironment (TME), which characterizes the tumor and its surroundings, plays a critical role in understanding cancer development and progression. Recent advances in imaging techniques enable researchers to study spatial structure of the TME at a single-cell level. Investigating spatial patterns and interactions of cell subtypes within the TME provides useful insights into how cells with different biological purposes behave, which may consequentially impact a subject’s clinical outcomes. We utilize a class of well-known spatial summary statistics, the K-function and its variants, to explore inter-cell dependence as a function of distances between cells. Using techniques from functional data analysis, we introduce an approach to model the association between these summary spatial functions and subject-level outcomes, while controlling for other clinical scalar predictors such as age and disease stage. In particular, we leverage the additive functional Cox regression model (AFCM) to study the nonlinear impact of spatial interaction between tumor and stromal cells on overall survival in patients with non-small cell lung cancer, using multiplex immunohistochemistry (mIHC) data. The applicability of our approach is further validated using a publicly available multiplexed ion beam imaging (MIBI) triple-negative breast cancer dataset.     

Evolutionary Relationships of Primary Prokaryotic Endosymbionts of Whiteflies and Their Hosts

Whiteflies (Hemiptera: Sternorrhyncha: Aleyrodidae) are plant sap-sucking insects that harbor prokaryotic primary endosymbionts (P-endosymbionts) within specialized cells located in their body cavity. Four-kilobase DNA fragments containing 16S-23S ribosomal DNA (rDNA) were amplified from the P-endosymbiont of 24 whiteflies from 22 different species of 2 whitefly subfamilies. In addition, 3-kb DNA fragments containing mitochondrial cytB, nd1, and large-subunit rDNA (LrDNA) were amplified from 17 whitefly species. Comparisons of the P-endosymbiont (16S-23S rDNA) and host (cytB-nd1-LrDNA) phylogenetic trees indicated overall congruence consistent with a single infection of a whitefly ancestor with a bacterium and subsequent cospeciation (cocladogenesis) of the host and the P-endosymbiont. On the basis of both the P-endosymbiont and host trees, the whiteflies could be subdivided into at least five clusters. The major subdivision was between the subfamilies Aleyrodinae and Aleurodicinae. Unlike the P-endosymbionts of may other insects, the P-endosymbionts of whiteflies were related to Pseudomonas and possibly to the P-endosymbionts of psyllids. The lineage consisting of the P-endosymbionts of whiteflies is given the designation “Candidatus Portiera” gen. nov., with a single species, “Candidatus Portiera aleyrodidarum” sp. nov.     

Causes and consequences of increase in child survival rates: ethnoepidemiology among the Hmong of Thailand.

The Hmong "hill tribe" minority in Thailand has much higher exposure to factors usually associated with risk of child mortality (high fertility, low status of women, low education, less use of modern medical care for births, exposure to warfare, economic and physical disruption, and poor hygienic conditions) than the rural ethnic Thai population. Nonetheless, infant mortality has declined from over 120 per 1000 to under 50 per 1000 live births among both these populations in the past 30 years. The reason for the rapid increase in child survival among the Hmong appears to be better access to and more use of modern curative and preventive medical care associated with road construction rather than major changes in social or hygienic conditions. Conventional wisdom suggests that high fertility is both a cause and a consequence of high infant and child mortality and that parents will not reduce fertility until they see that mortality has declined. Most Hmong parents recognize the decline in child mortality and attribute it to better access to modern medical care. Most Hmong parents also say that, if they were starting to have children now, they would want to have fewer children. Fear of child death is infrequently mentioned as a motive for having more children, and the perceived decline in child mortality is rarely mentioned as a reason for reduced fertility. Most Hmong parents explain their desired family size in terms of economic conditions rather than perceived risk of child mortality. Results of this study suggest that fertility and child mortality can vary independently of one another and that major reductions in child mortality can be accomplished without waiting for major social changes (e.g., improved education or status of women) or major reductions in fertility.     

Comparing normalization methods and the impact of noise

Introduction

Failure to properly account for normal systematic variations in OMICS datasets may result in misleading biological conclusions. Accordingly, normalization is a necessary step in the proper preprocessing of OMICS datasets. In this regards, an optimal normalization method will effectively reduce unwanted biases and increase the accuracy of downstream quantitative analyses. But, it is currently unclear which normalization method is best since each algorithm addresses systematic noise in different ways.

Objective

Determine an optimal choice of a normalization method for the preprocessing of metabolomics datasets.

Methods

Nine MVAPACK normalization algorithms were compared with simulated and experimental NMR spectra modified with added Gaussian noise and random dilution factors. Methods were evaluated based on an ability to recover the intensities of the true spectral peaks and the reproducibility of true classifying features from orthogonal projections to latent structures—discriminant analysis model (OPLS-DA).

Results

Most normalization methods (except histogram matching) performed equally well at modest levels of signal variance. Only probabilistic quotient (PQ) and constant sum (CS) maintained the highest level of peak recovery (>?67%) and correlation with true loadings (>?0.6) at maximal noise.

Conclusion

PQ and CS performed the best at recovering peak intensities and reproducing the true classifying features for an OPLS-DA model regardless of spectral noise level. Our findings suggest that performance is largely determined by the level of noise in the dataset, while the effect of dilution factors was negligible. A minimal allowable noise level of 20% was also identified for a valid NMR metabolomics dataset.