MMS2plot: An R Package for Visualizing Multiple MS/MS Spectra for Groups of Modified and Non‐Modified Peptides

A large number of post‐translational modifications (PTMs) in proteins are buried in the unassigned mass spectrometric (MS) spectra in shot‐gun proteomics datasets. Because the modified peptide fragments are low in abundance relative to the corresponding non‐modified versions, it is critical to develop tools that allow facile evaluation of assignment of PTMs based on the MS/MS spectra. Such tools will preferably have the ability to allow comparison of fragment ion spectra and retention time between the modified and unmodified peptide pairs or group. Herein, MMS2plot, an R package for visualizing peptide‐spectrum matches (PSMs) for multiple peptides, is described. MMS2plot features a batch mode and generates the output images in vector graphics file format that facilitate evaluation and publication of the PSM assignment. MMS2plot is expected to play an important role in PTM discovery from large‐scale proteomics datasets generated by liquid chromatography‐MS/MS. The MMS2plot package is freely available at https://github.com/lileir/MMS2plot under the GPL‐3 license.     

Positive selection and convergent evolution shape molecular phenotypic traits of innate immunity receptors in tits (Paridae)

Despite widespread variability and redundancy abounding animal immunity, little is currently known about the rate of evolutionary convergence (functionally analogous traits not inherited from a common ancestor) in host molecular adaptations to parasite selective pressures. Toll‐like receptors (TLRs) provide the molecular interface allowing hosts to recognize pathogenic structures and trigger early danger signals initiating an immune response. Using a novel combination of bioinformatic approaches, here we explore genetic variation in ligand‐binding regions of bacteria‐sensing TLR4 and TLR5 in 29 species belonging to the tit family of passerine birds (Aves: Paridae). Three out of the four consensual positively selected sites in TLR4 and six out of 14 positively selected positions in TLR5 were located on the receptor surface near the functionally important sites, and based on the phylogenetic pattern evolved in a convergent (parallel) manner. This type of evolution was also seen at one N‐glycosylation site and two positively selected phosphorylation sites, providing the first evidence of convergence in post‐translational modifications in evolutionary immunology. Finally, the overall mismatch between phylogeny and the clustering of surface charge distribution demonstrates that convergence is common in overall TLR4 and TLR5 molecular phenotypes involved in ligand binding. Our analysis did not reveal any broad ecological traits explaining the convergence observed in electrostatic potentials, suggesting that information on microbial symbionts may be needed to explain TLR evolution. Adopting state‐of‐the‐art predictive structural bionformatics, we have outlined a new broadly applicable methodological approach to estimate the functional significance of positively selected variation and test for the adaptive molecular convergence in protein‐coding polymorphisms.     

Evaluating the effectiveness of retention forestry to enhance biodiversity in production forests of Central Europe using an interdisciplinary,multi‐scale approach

Retention forestry, which retains a portion of the original stand at the time of harvesting to maintain continuity of structural and compositional diversity, has been originally developed to mitigate the impacts of clear‐cutting. Retention of habitat trees and deadwood has since become common practice also in continuous‐cover forests of Central Europe. While the use of retention in these forests is plausible, the evidence base for its application is lacking, trade‐offs have not been quantified, it is not clear what support it receives from forest owners and other stakeholders and how it is best integrated into forest management practices. The Research Training Group ConFoBi (Conservation of Forest Biodiversity in Multiple‐use Landscapes of Central Europe) focusses on the effectiveness of retention forestry, combining ecological studies on forest biodiversity with social and economic studies of biodiversity conservation across multiple spatial scales. The aim of ConFoBi is to assess whether and how structural retention measures are appropriate for the conservation of forest biodiversity in uneven‐aged and selectively harvested continuous‐cover forests of temperate Europe. The study design is based on a pool of 135 plots (1 ha) distributed along gradients of forest connectivity and structure. The main objectives are (a) to investigate the effects of structural elements and landscape context on multiple taxa, including different trophic and functional groups, to evaluate the effectiveness of retention practices for biodiversity conservation; (b) to analyze how forest biodiversity conservation is perceived and practiced, and what costs and benefits it creates; and (c) to identify how biodiversity conservation can be effectively integrated in multi‐functional forest management. ConFoBi will quantify retention levels required across the landscape, as well as the socio‐economic prerequisites for their implementation by forest owners and managers. ConFoBi's research results will provide an evidence base for integrating biodiversity conservation into forest management in temperate forests.     

Autophagy in plants: Physiological roles and post‐translational regulation

In eukaryotes, autophagy helps maintain cellular homeostasis by degrading and recycling cytoplasmic materials via a tightly regulated pathway.Over the past few decades, significant progress has been made towards understanding the physiological functions and molecular regulation of autophagy in plant cells. Increasing evidence indicates that autophagy is essential for plant responses to several developmental and environmental cues, functioning in diverse processes such as senescence, male fertility, root meristem maintenance, responses to nutrient starvation,and biotic and abiotic stress. Recent studies have demonstrated that, similar to nonplant systems,the modulation of core proteins in the plant autophagy machinery by posttranslational modifications such as phosphorylation, ubiquitination,lipidation, S-sulfhydration, S-nitrosylation, and acetylation is widely involved in the initiation and progression of autophagy. Here, we provide an overview of the physiological roles and posttranslational regulation of autophagy in plants.     

Polyglutamylase activity of tubulin tyrosine ligase-like 4 is negatively regulated by the never in mitosis gene A family kinase never in mitosis gene A -related kinase 5

BACKGROUNDTubulins, building blocks of microtubules, are modified substrates of diverse post-translational modifications including phosphorylation, polyglycylation and polyglutamylation. Polyglutamylation of microtubules, catalyzed by enzymes from the tubulin tyrosine ligase-like (TTLL) family, can regulate interactions with molecular motors and other proteins. Due to the diversity and functional importance of microtubule modifications, strict control of the TTLL enzymes has been suggested.AIMTo characterize the interaction between never in mitosis gene A-related kinase 5 (NEK5) and TTLL4 proteins and the effects of TTLL4 phosphorylation.METHODSThe interaction between NEK5 and TTLL4 was identified by yeast two-hybrid screening using the C-terminus of NEK5 (a.a. 260–708) as bait and confirmed by immunoprecipitation. The phosphorylation sites of TTLL4 were identified by mass spectrometry and point mutations were introduced.RESULTSHere, we show that NEK5 interacts with TTLL4 and regulates its polyglutamylation activity. We further show that NEK5 can also interact with TTLL5 and TTLL7. The silencing of NEK5 increases the levels of polyglutamylation of proteins by increasing the activity of TTLL4. The same effects were observed after the expression of the catalytically inactive form of NEK5. This regulation of TTLL4 activity involves its phosphorylation at Y815 and S1136 amino acid residues.CONCLUSIONOur results demonstrate, for the first time, the regulation of TTLL activity through phosphorylation, pointing to NEK5 as a potential effector kinase. We also suggest a general control of tubulin polyglutamylation through NEK family members in human cells.     

Deep Learning Using Havrda-Charvat Entropy for Classification of Pulmonary Optical Endomicroscopy

1) ObjectivePulmonary optical endomicroscopy (POE) is an imaging technology in real time. It allows to examine pulmonary alveoli at a microscopic level. Acquired in clinical settings, a POE image sequence can have as much as 25% of the sequence being uninformative frames (i.e. pure-noise and motion artifacts). For future data analysis, these uninformative frames must be first removed from the sequence. Therefore, the objective of our work is to develop an automatic detection method of uninformative images in endomicroscopy images.2) Material and methodsWe propose to take the detection problem as a classification one. Considering advantages of deep learning methods, a classifier based on CNN (Convolutional Neural Network) is designed with a new loss function based on Havrda-Charvat entropy which is a parametrical generalization of the Shannon entropy. We propose to use this formula to get a better hold on all sorts of data since it provides a model more stable than the Shannon entropy.3) ResultsOur method is tested on one POE dataset including 3895 distinct images and is showing better results than using Shannon entropy and behaves better with regard to the problem of overfitting. We obtain 70% of accuracy with Shannon entropy versus 77 to 79% with Havrda-Charvat.4) ConclusionWe can conclude that Havrda-Charvat entropy is better suited for restricted and or noisy datasets due to its generalized nature. It is also more suitable for classification in endomicroscopy datasets.