Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.     

Antimicrobial activity of selected synbiotics targeted for the elderly against pathogenic Escherichia coli strains

The aim of the present study was to evaluate the antimicrobial activity of two synbiotic combinations, Lactobacillus fermentum with short-chain fructooligosaccharides (FOS-LF) and Bifidobacterium longum with isomaltooligosaccharides (IMO-BL), against enterohaemorrhagic Escherichia coli O157:H7 and enteropathogenic E. coli O86. Antimicrobial activity was determined (1) by co-culturing the synbiotics and pathogens in batch cultures, and (2) with the three-stage continuous culture system (gut model), inoculated with faecal slurry from an elderly donor. In the co-culture experiments, IMO-BL was significantly inhibitory to both E. coli strains, while FOS-LF was slightly inhibitory or not inhibitory. Factors other than acid production appeared to play a role in the inhibition. In the gut models, both synbiotics effectively inhibited E. coli O157 in the first vessel, but not in vessels 2 and 3. E. coli O86 was not significantly inhibited.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Assessment of the reporting of quality and outcome measures in hepatic resections: a call for 90-day reporting in all hepatectomy series

BackgroundThe aim of this paper is to assess the current state of quality and outcomes measures being reported for hepatic resections in the recent literature.MethodsMedline and PubMed databases were searched for English language articles published between 1 January 2002 and 30 April 2013. Two examiners reviewed each article and relevant citations for appropriateness of inclusion, which excluded papers of liver donor hepatic resections, repeat hepatectomies or meta-analyses. Data were extracted and summarized by two examiners for analysis.ResultsFifty-five studies were identified with suitable reporting to assess peri-operative mortality in hepatic resections. In only 35% (19/55) of the studies was the follow-up time explicitly stated, and in 47% (26/55) of studies peri-operative mortality was limited to in-hospital or 30 days. The time period in which complications were captured was not explicitly stated in 19 out of 28 studies. The remaining studies only captured complications within 30 days of the index operation (8/28). There was a paucity of quality literature addressing truly patient-centred outcomes.ConclusionQuality outcomes after a hepatic resection are inconsistently reported in the literature. Quality outcome studies for a hepatectomy should report mortality and morbidity at a minimum of 90 days after surgery.