Tethering of human Ago proteins to mRNA mimics the miRNA-mediated repression of protein synthesis

MicroRNAs (miRNAs) are approximately 21-nt-long RNAs involved in regulating development, differentiation, and other processes in eukaryotes. In metazoa, nearly all miRNAs control gene expression by imperfectly base-pairing with the 3'-untranslated region (3'-UTR) of target mRNAs and repressing protein synthesis by an unknown mechanism. It is also unknown whether miRNA-mRNA duplexes containing mismatches and bulges provide specific features that are recognized by factors mediating the repression. miRNAs form part of ribonucleoprotein complexes, miRNPs, that contain Argonaute (Ago) and other proteins. Here we demonstrate that effects of miRNAs on translation can be mimicked in human HeLa cells by the miRNA-independent tethering of Ago proteins to the 3'-UTR of a reporter mRNA. Inhibition of protein synthesis occurred without a change in the reporter mRNA level and was dependent on the number, but not the position, of the hairpins tethering hAgo2 to the 3'-UTR. These findings indicate that a primary function of miRNAs is to guide their associated proteins to the mRNA.     

Modulation of gut microbiota from obese individuals by in vitro fermentation of citrus pectin in combination with Bifidobacterium longum BB-46

This study aimed to evaluate the effects of three treatments, i.e., Bifidobacterium longum BB-46 (T1), B. longum BB-46 combined with the pectin (T2), and harsh extracted pectin from lemon (T3) on obesity-related microbiota using the Simulator of the Human Intestinal Microbial Ecosystem (SHIME®). The effects of the treatments were assessed by the analysis of the intestinal microbial composition (using 16S rRNA gene amplicon sequencing) and the levels of short-chain fatty acids (SCFAs) and ammonium ions (NH₄⁺). Treatments T2 and T3 stimulated members of the Ruminococcaceae and Succinivibrionaceae families, which were positively correlated with an increase in butyric and acetic acids. Proteolytic bacteria were reduced by the two treatments, concurrently with a decrease in NH₄⁺. Treatment T1 stimulated the production of butyric acid in the simulated transverse and descending colon, reduction of NH₄⁺ as well as the growth of genera Lactobacillus, Megamonas, and members of Lachnospiracea. The results indicate that both B. longum BB-46 and pectin can modulate the obesity-related microbiota; however, when the pectin is combined with B. longum BB-46, the predominant effect of the pectin can be observed. This study showed that the citric pectin is able to stimulate butyrate-producing bacteria as well as genera related with anti-inflammatory effects. However, prospective clinical studies are necessary to evaluate the anti/pro-obesogenic and inflammatory effects of this pectin for future prevention of obesity.

     

Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival

Background

Modern experimental techniques deliver data sets containing profiles of tens of thousands of potential molecular and genetic markers that can be used to improve medical diagnostics. Previous studies performed with three different experimental methods for the same set of neuroblastoma patients create opportunity to examine whether augmenting gene expression profiles with information on copy number variation can lead to improved predictions of patients survival. We propose methodology based on comprehensive cross-validation protocol, that includes feature selection within cross-validation loop and classification using machine learning. We also test dependence of results on the feature selection process using four different feature selection methods.

Results

The models utilising features selected based on information entropy are slightly, but significantly, better than those using features obtained with t-test. The synergy between data on genetic variation and gene expression is possible, but not confirmed. A slight, but statistically significant, increase of the predictive power of machine learning models has been observed for models built on combined data sets. It was found while using both out of bag estimate and in cross-validation performed on a single set of variables. However, the improvement was smaller and non-significant when models were built within full cross-validation procedure that included feature selection within cross-validation loop. Good correlation between performance of the models in the internal and external cross-validation was observed, confirming the robustness of the proposed protocol and results.

Conclusions

We have developed a protocol for building predictive machine learning models. The protocol can provide robust estimates of the model performance on unseen data. It is particularly well-suited for small data sets. We have applied this protocol to develop prognostic models for neuroblastoma, using data on copy number variation and gene expression. We have shown that combining these two sources of information may increase the quality of the models. Nevertheless, the increase is small and larger samples are required to reduce noise and bias arising due to overfitting.

Reviewers

This article was reviewed by Lan Hu, Tim Beissbarth and Dimitar Vassilev.

     

Linked Lists and the Method of Lights in Molecular Dynamics Simulation - Search for the Best Method of Forces Evaluation in Sequential MD Codes

Abstract

In this paper two methods of forces evaluation used in the MD codes are presented and compared against the classical linked lists algorithm [3,4] and its modified version [5]. The first algorithm, so called the method of lights is a sequential version of the CYBER 205 vector oriented code [6]. A new algorithm of forces evaluation is also proposed, which incorporates advantages of the method of lights and the linked lists technique.     

A novel microarray approach reveals new tissue-specific signatures of known and predicted mammalian microRNAs

Microarrays to examine the global expression levels of microRNAs (miRNAs) in a systematic in-parallel manner have become important tools to help unravel the functions of miRNAs and to understand their roles in RNA-based regulation and their implications in human diseases. We have established a novel miRNA-specific microarray platform that enables the simultaneous expression analysis of both known and predicted miRNAs obtained from human or mouse origin. Chemically modified 2′-O-(2-methoxyethyl)-(MOE) oligoribonucleotide probes were arrayed onto Evanescent Resonance (ER) microchips by robotic spotting. Supplementing the complementary probes against miRNAs with carefully designed mismatch controls allowed for accurate sequence-specific determination of miRNA expression profiles obtained from a panel of mouse tissues. This revealed new expression signatures of known miRNAs as well as of novel miRNAs previously predicted using bioinformatic methods. Systematic confirmation of the array data with northern blotting and, in particular, real-time PCR suggests that the described microarray platform is a powerful tool to analyze miRNA expression patterns with rapid throughput and high fidelity.     

Effect of soil and water environment on typeability of PowerPlex Y (Promega) in selected tissue samples

In cases of decomposed bodies Y chromosomal STR markers may be useful in identification of a male relative. The authors assessed typeability PowerPlex Y (Promega) loci in tissue material stored in water and soil environment. Tissue material was collected during autopsies of five persons aged 20-30 years with time of death determined within the limit of 14 hours. Heart muscle, liver and lung specimens were stored in pond water, sea water, sand and peat soil. DNA was extracted by organic method from tissue samples collected in 7-day intervals. Liver specimens were typeable in all PowerPlex Y loci within 100 days of storage in pond water with gradual decline at DYS392 in sea water. Heart muscle specimens stored in pond water exhibited allelic loss at DYS19, DYS385, DYS389II and DYS392, while all loci were typeable in sea water stored samples. For lung specimens allelic loss was noted throughout the profile. Storage of liver specimens in peat soil for more than 14 days resulted in allelic drop-out, and after 21 days no profiles were typeable. Heart muscle specimens were typeable in all PowerPlex Y systems after 35-day storage in sand, while allelic drop-out and subsequent lack of profiles were noted after 14 and 35 days respectively. Lung specimens stored in garden soil exhibited allelic drop-out and subsequent lack of profiles after 7 and 21 days, respectively. All PowerPlex Y loci were typeable in the latter material in sand up to day 35 with gradual decline of longer amplicons (DYS19, DYS385, DYS389II and DYS392).     

Differences between TNM classification and 2-[18F]FDG PET parameters of primary tumor in NSCLC patients

BackgroundThe aim of the study was to compare the TNM classification with 2-[¹⁸F]FDG PE T biological parameters of primary tumor in patients with NSCLC.Materials and methodsRetrospective analysis was performed on a group of 79 newly diagnosed NSCLC patients. PET scans were acquired on Gemini TF PET/CT scanner 60–70 min after injection of 2-[¹⁸F]FDG with the mean activity of 364 ± 75 MBq, with the area being examined from the vertex to mid-thigh. The reconstructed PET images were evaluated using MIM 7.0 Software for SUV_max, MTV and TLG values.ResultsThe analysis of the cancer stage according to TNM 8^th edition showed stage IA2 in 8 patients, stage IA3 — 6 patients, stage IB — 4 patients, IIA — 3 patients, 15 patients with stage IIB, stage IIIA — 17 patients, IIIB — 5, IIIC — 5, IVA in 7 patients and stage IVB in 9 patients. The lowest TLG values of primary tumor were observed in stage IA2 (11.31 ± 15.27) and the highest in stage IIIC (1003.20 ± 953.59). The lowest value of primary tumor in SUV_max and MTV were found in stage IA2 (6.8 ± 3.8 and 1.37 ± 0.42, respectively), while the highest SUV_max of primary tumor was found in stage IIA (13.4 ± 11.4) and MTV in stage IIIC (108.15 ± 127.24).ConclusionTNM stages are characterized by different primary tumor 2-[¹⁸F]FDG PET parameters, which might complement patient outcome.     

Plasma Membranes Are Subcompartmentalized into a Plethora of Coexisting and Diverse Microdomains in Arabidopsis and Nicotiana benthamiana

Eukaryotic plasma membranes are highly compartmentalized structures. So far, only a few individual proteins that function in a wide range of cellular processes have been shown to segregate into microdomains. However, the biological roles of most microdomain-associated proteins are unknown. Here, we investigated the heterogeneity of distinct microdomains and the complexity of their coexistence. This diversity was determined in living cells of intact multicellular tissues using 20 different marker proteins from Arabidopsis thaliana, mostly belonging to the Remorin protein family. These proteins associate with microdomains at the cytosolic leaflet of the plasma membrane. We characterized these membrane domains and determined their lateral dynamics by extensive quantitative image analysis. Systematic colocalization experiments with an extended subset of marker proteins tested in 45 different combinations revealed the coexistence of highly distinct membrane domains on individual cell surfaces. These data provide valuable tools to study the lateral segregation of membrane proteins and their biological functions in living plant cells. They also demonstrate that widely used biochemical approaches such as detergent-resistant membranes cannot resolve this biological complexity of membrane compartmentalization in vivo.