Next-generation sequencing of HIV-1 RNA genomes: determination of error rates and minimizing artificial recombination.

Next-generation sequencing (NGS) is a valuable tool for the detection and quantification of HIV-1 variants in vivo. However, these technologies require detailed characterization and control of artificially induced errors to be applicable for accurate haplotype reconstruction. To investigate the occurrence of substitutions, insertions, and deletions at the individual steps of RT-PCR and NGS, 454 pyrosequencing was performed on amplified and non-amplified HIV-1 genomes. Artificial recombination was explored by mixing five different HIV-1 clonal strains (5-virus-mix) and applying different RT-PCR conditions followed by 454 pyrosequencing. Error rates ranged from 0.04-0.66% and were similar in amplified and non-amplified samples. Discrepancies were observed between forward and reverse reads, indicating that most errors were introduced during the pyrosequencing step. Using the 5-virus-mix, non-optimized, standard RT-PCR conditions introduced artificial recombinants in a fraction of at least 30% of the reads that subsequently led to an underestimation of true haplotype frequencies. We minimized the fraction of recombinants down to 0.9-2.6% by optimized, artifact-reducing RT-PCR conditions. This approach enabled correct haplotype reconstruction and frequency estimations consistent with reference data obtained by single genome amplification. RT-PCR conditions are crucial for correct frequency estimation and analysis of haplotypes in heterogeneous virus populations. We developed an RT-PCR procedure to generate NGS data useful for reliable haplotype reconstruction and quantification.

Proton flux across artificial vesicle bilayers

The study of proton conductance across artificial membranes has revealed a surprisingly high permeability for H+, (Pnet H+). A high Pnet H+ is difficult to reconcile with the biological requirement for the maintenance of pH gradients across the plasma membranes of cells, organellar study was undertaken to examine the role played by cholesterol and phospholipid fatty acid side chain composition in determining how well a membrane will function as a barrier to acid. The effects of counter-ion movement on acidification rates were examined in order to interpret the data obtained from variations in membrane composition. In phosphate buffered saline solutions, vesicle membranes composed of unsaturated fatty acid phosphatidylcholines proved to be poorer barriers to acid than membranes composed of saturated fatty acids. The barrier properties of these membranes could be ranked in the following order: DPL, (palmitic) $>$ Egg PC, (mixed chains) $>$ DLL, (linoleic), with DPL being the most effective in maintaining a one pH unit gradient near neutrality. Cholesterol decreased acidification rates of membranes made from the unsaturated phosphatidylcholines Egg PC and DLL, but enhanced acidification rates in vesicle membranes composed of the saturated phospholipid DPL. The cholesterol and fatty acid side chain effects were mediated by changes in membrane fluidity, with more rigid bilayers forming better barriers to acid. Experimental evidence was obtained which confirmed the Pnet H+ is very high relative to the permeabilities of other ions. Counter-ion controlled acidification rates depended on the size and charge of the ion which was moving in order to maintain electroneutrality. The biological relevance of a high intrinsic Pnet H+ and the possible role of counter-ion controlled acidification were discussed. ^

Peptide nucleic acids: Mechanism of tight binding and application in artificial nuclease

Peptide nucleic acids (PNA) are mimics of nucleic acids with a peptidic backbone. Duplexes and triplexes formed between PNA and DNA or RNA possess remarkable thermal stability, they are resistant to nuclease cleavage and can better discriminate mismatches. Understanding the mechanism for the tight binding between PNA and oligonucleotides is important for the design and development of better PNA-based drugs.^ We have performed molecular dynamics (MD) simulations of 8-mer PNA/DNA duplex and two analogous duplexes with chiral modification of PNA strand (D- or L-Alanine modification). MD simulations were performed with explicit water and Na$\sp{+}$ counter ions. The 1.5-ns simulations were carried out with AMBER using periodic boundary and particle mesh Ewald summation. The point charges for PNA monomers were derived from fitting electrostatic potentials, obtained from ab initio calculation, to atomic centers using RESP. Derived charges reveal significantly altered charge distribution on the PNA bases and predict the Watson-Crick H-bonds involving PNA to be stronger. Results from NMR studies investigating H-bond interactions between DNA-DNA and DNA-PNA base pairs in non-polar environment are consistent with this prediction. MD simulations demonstrated that the PNA strand is more flexible than the DNA strand in the same duplex. That this flexibility might be important for the duplex stability is tested by introducing modification into the PNA backbones. Results from MD simulation revealed dramatically altered structures for the modified PNA-DNA duplexes. Consistent with previous NMR results, we also found no intrachain hydrogen bonds between O7$\sp\prime$ and N1$\sp\prime$ of the neighboring residues in our MD study. Our study reveals that in addition to the lack of charge repulsion, stronger Watson-Crick hydrogen bonds together with flexible backbone are important factors for the enhanced stability of the PNA-DNA duplex.^ In a related study, we have developed an application of Gly-Gly-His-(Gly)$\sb3$-PNA conjugate as an artificial nuclease. We were able to demonstrate cleavage of single stranded DNA at a single site upon Ni(II) binding to Gly-Gly-His tripeptide and activation of nuclease with monoperoxyphthalic acid. ^

Home artificial nutrition in Switzerland: an epidemiological survey from 2005 to 2009.

BACKGROUND AND AIMS Home artificial nutrition (HAN), including oral nutritional supplements (ONS) and enteral (HEN) and parenteral (HPN) nutrition, is an established, important treatment for malnourished patients. The aim of this study was to analyze the epidemiological data of patients on HAN in Switzerland. METHODS This retrospective study recorded all new cases of HAN in Switzerland from January 2005 to December 2009. RESULTS A total of 12,917 cases were recorded: 6,731 (52%) males and 6,186 (48%) females, with a mean age of 65.0 ± 17.6 years. The number of patients on ONS was 7,827 (57.4%), on HEN 3,966 (39.4%) and on HPN 433 (3.2%). The most common underlying disease category was neoplasms (6,519, 50.7%). The number of patients on ONS increased from 57.0% (n = 1,252) to 60.8% (n = 2,039), and on HPN from 2.1% (n = 45) to 4.0% (n = 134) between 2005 and 2009. CONCLUSIONS This first analysis of the large-scale Swiss registry of HAN shows that approximately half of the patients received ONS, whereas HPN was rarely delivered. The frequency of ONS and HPN increased from the year 2005 to 2009. In accordance with previous European studies, malignant tumors were by far the most frequent indication for HAN.

SNARE-fusion mediated insertion of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE protein-based method for incorporation of multiple membrane proteins into artificial membrane vesicles of well-defined composition, and for delivery of large water-soluble substrates into these vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0 ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

SNARE-fusion mediated inserton of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE-protein based method for incorporation of multiple membrane proteins into membranes, and for delivery of large water-soluble substrates into closed membrane vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0-ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

GoCARB in the Context of an Artificial Pancreas

Background: In an artificial pancreas (AP), the meals are either manually announced or detected and their size estimated from the blood glucose level. Both methods have limitations, which result in suboptimal postprandial glucose control. The GoCARB system is designed to provide the carbohydrate content of meals and is presented within the AP framework. Method: The combined use of GoCARB with a control algorithm is assessed in a series of 12 computer simulations. The simulations are defined according to the type of the control (open or closed loop), the use or not-use of GoCARB and the diabetics’ skills in carbohydrate estimation. Results: For bad estimators without GoCARB, the percentage of the time spent in target range (70-180 mg/dl) during the postprandial period is 22.5% and 66.2% for open and closed loop, respectively. When the GoCARB is used, the corresponding percentages are 99.7% and 99.8%. In case of open loop, the time spent in severe hypoglycemic events (<50 mg/dl) is 33.6% without the GoCARB and is reduced to 0.0% when the GoCARB is used. In case of closed loop, the corresponding percentage is 1.4% without the GoCARB and is reduced to 0.0% with the GoCARB. Conclusion: The use of GoCARB improves the control of postprandial response and glucose profiles especially in the case of open loop. However, the most efficient regulation is achieved by the combined use of the control algorithm and the GoCARB.

Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension

BACKGROUND The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established. AIMS To assess diagnostic accuracy of six serum scores, artificial neural networks and liver stiffness measured by transient elastography, for diagnosing cirrhosis, clinically significant portal hypertension and oesophageal varices. METHODS 202 consecutive compensated patients requiring liver biopsy and hepatic venous pressure gradient measurement were included. Several serum tests (alone and combined into scores) and liver stiffness were measured. Artificial neural networks containing or not liver stiffness as input variable were also created. RESULTS The best non-invasive method for diagnosing cirrhosis, portal hypertension and oesophageal varices was liver stiffness (C-statistics=0.93, 0.94, and 0.90, respectively). Among serum tests/scores the best for diagnosing cirrhosis and portal hypertension and oesophageal varices were, respectively, Fibrosis-4, and Lok score. Artificial neural networks including liver stiffness had high diagnostic performance for cirrhosis, portal hypertension and oesophageal varices (accuracy>80%), but were not statistically superior to liver stiffness alone. CONCLUSIONS Liver stiffness was the best non-invasive method to assess the presence of cirrhosis, portal hypertension and oesophageal varices. The use of artificial neural networks integrating different non-invasive tests did not increase the diagnostic accuracy of liver stiffness alone.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^