Cryptides: latent peptides everywhere

Proteomic surveys with top-down platforms are today revealing thousands of naturally occurring fragments of bigger proteins. Some of them have not functional meaning because they derive from pathways responsible for protein degradation, but many have specific functions, often completely different from that one of the parent proteins. These peptides encrypted in the protein sequence are nowadays called cryptides. They are frequent in the animal and plant kingdoms and represent a new interesting –omic field of investigation. To point out how much widespread is their presence, we describe here the most studied cryptides from very common sources such as serum albumin, immunoglobulins, hemoglobin, and from saliva and milk proteins. Given its vastness, it is unfeasible to cover the topic exhaustively, therefore only several selected examples of cryptides from other sources are thereafter reported. Demanding is the development of new –omic platforms for the functional screening of new cryptides, which could provide suggestion for peptides and peptido-mimetics with variegate fields of application.     

A change of course:JIPB to focus on fundamental questions in plant sciences

Benefited from the speedy development of omic tools and the use of model plants, such as rice, Arabidopsis and Medicargo, plant biologists have recently made tremendous breakthroughs in understanding plant growth,development, and response to environmental changes.     

Joint analysis of genetic and epigenetic data using a conditional autoregressive model

Background

Rapidly evolving high-throughput technology has made it cost-effective to collect multilevel omic data in clinical and biological studies. Different types of omic data collected from these studies provide both shared and complementary information, and can be integrated into association analysis to enhance the power of identifying novel disease-associated biomarkers. To model the joint effect of genetic markers and DNA methylation on the phenotype of interest, we propose a joint conditional autoregressive (JCAR) model. A linear score test is used for hypothesis testing and the corresponding p value can be obtained using the Davies method.

Results

The JCAR model was applied to the GAW20 data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study. In our application of the JCAR model, we consider a baseline model and a full model. In the baseline model, we consider 3 different scenarios: a model with only genetic information, a model with only DNA methylation information at visit 2, and a model using both genetic and DNA methylation information at visit 2. For the full model, we consider both genetic and DNA methylation information at visit 2 and visit 4. The top 10 significant genes are reported for each model. Based on the results, we found that the gene MYO3B was significant as long as the methylation information was considered in the analysis.

Conclusions

JCAR is a useful tool for joint association analysis of genetic and epigenetic data. It is easy to implement and is computationally efficient. It can also be extended to analyze other types of omic data.

     

Wing colors based on arrangement of the multilayer structure of wing scales in lycaenid butterflies (Insecta: Lepidoptera)

Male wing colors and wing scale morphology were examined for three species of lycaenid butterflies: Chrysozephyrus ataxus, Favonius cognatus and F. jezoensis. Measurement of spectral reflectance on the wing surface with a spectrophotometer revealed species‐specific reflection spectra, with one or two peaks in the ultraviolet and/or green ranges. Observations of wing scales using an optical microscope revealed that light was reflected from the inter‐ridge regions, where transmission electron microscopy revealed a multilayer structure. Based on the multilayer dimensions obtained, three models were devised and compared to explain the measured reflectance spectrum. The results showed that the best fit is a model in which thicknesses of thin films of the multilayer system are not constant and air spaces between cuticle layers are more or less packed with cuticle spacers. This suggests that the specific wing colors of the species examined are produced by the species‐specific arrangement of the multilayer structure of wing scales.     

Allometry and Shade Tolerance in Pole‐Sized Trees of Two Contrasting Dipterocarp Species in Sabah,Malaysia1

We compared the allometry of two contrasting late‐successional dipterocarp species to test whether a monolayer (shade‐tolerant)–multilayer (shade‐intolerant) model applies to pole‐sized trees. Crown traits of the more shade‐tolerant species (Vatica micrantha) did not conform to either of the familiar monolayer or multilayer models for pole‐sized trees, but instead were consistent with a “persistent multilayer” model. Species differences in crown traits may be influenced more by future rather than present light environments.     

From observational to actionable: rethinking omics in biologics production

As the era of omics continues to expand with increasing ubiquity and success in both academia and industry, omics-based experiments are becoming commonplace in industrial biotechnology, including efforts to develop novel solutions in bioprocess optimization and cell line development. Omic technologies provide particularly valuable ‘observational’ insights for discovery science, especially in academic research and industrial R&D; however, biomanufacturing requires a different paradigm to unlock ‘actionable’ insights from omics. Here, we argue the value of omic experiments in biotechnology can be maximized with deliberate selection of omic approaches and forethought about analysis techniques. We describe important considerations when designing and implementing omic-based experiments and discuss how systems biology analysis strategies can enhance efforts to obtain actionable insights in mammalian-based biologics production.     

Multi–omic analysis of signalling factors in inflammatory comorbidities

Background

Inflammation is a core element of many different, systemic and chronic diseases that usually involve an important autoimmune component. The clinical phase of inflammatory diseases is often the culmination of a long series of pathologic events that started years before. The systemic characteristics and related mechanisms could be investigated through the multi–omic comparative analysis of many inflammatory diseases. Therefore, it is important to use molecular data to study the genesis of the diseases. Here we propose a new methodology to study the relationships between inflammatory diseases and signalling molecules whose dysregulation at molecular levels could lead to systemic pathological events observed in inflammatory diseases.

Results

We first perform an exploratory analysis of gene expression data of a number of diseases that involve a strong inflammatory component. The comparison of gene expression between disease and healthy samples reveals the importance of members of gene families coding for signalling factors. Next, we focus on interested signalling gene families and a subset of inflammation related diseases with multi–omic features including both gene expression and DNA methylation. We introduce a phylogenetic–based multi–omic method to study the relationships between multi–omic features of inflammation related diseases by integrating gene expression, DNA methylation through sequence based phylogeny of the signalling gene families. The models of adaptations between gene expression and DNA methylation can be inferred from pre–estimated evolutionary relationship of a gene family. Members of the gene family whose expression or methylation levels significantly deviate from the model are considered as the potential disease associated genes.

Conclusions

Applying the methodology to four gene families (the chemokine receptor family, the TNF receptor family, the TGF– β gene family, the IL–17 gene family) in nine inflammation related diseases, we identify disease associated genes which exhibit significant dysregulation in gene expression or DNA methylation in the inflammation related diseases, which provides clues for functional associations between the diseases.

     

Role of hydrophilic and hydrophobic contacts in folding of the second beta-hairpin fragment of protein G: molecular dynamics simulation studies of an all-atom model

Predicting the folding mechanism of the second beta-hairpin fragment of the Ig-binding domain B of streptococcal protein G is unexpectedly challenging for simplified reduced models because the models developed so far indicated a different folding mechanism from what was suggested from high-temperature unfolding and equilibrium free-energy surface analysis based on established all-atom empirical force fields in explicit or implicit solvent. This happened despite the use of empirical residue-based interactions, multibody hydrophobic interactions, and inclusions of hydrogen bonding effects in the simplified models. This article employs a recently developed all-atom (except nonpolar hydrogens) model interacting with simple square-well potentials to fold the peptide fragment by molecular dynamics simulation methods. In this study, 193 out of 200 trajectories are folded at two reduced temperatures (3.5 and 3.7) close to the transition temperature T* approximately 4.0. Each simulation takes <7 h of CPU time on a Pentium 800-MHz PC. Folding of the new all-atom model is found to be initiated by collapse before the formation of main-chain hydrogen bonds. This verifies the mechanism proposed from previous all-atom unfolding and equilibrium simulations. The new model further predicts that the collapse is initiated by two nucleation contacts (a hydrophilic contact between D46 and T49 and a hydrophobic contact between Y45 and F52), in agreement with recent NMR measurements. The results suggest that atomic packing and native contact interactions play a dominant role in folding mechanism.     

Biomarkers intersect with the exposome

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.     

Kinetic and structural study of the interaction of myelin basic protein with dipalmitoylphosphatidylglycerol layers

The interaction of myelin basic protein (MBP) with dipalmitoylphosphatidylglycerol films has been investigated by means of a microgravimetric gauge sensitive to the changes in load and structural modifications of the layer deposited onto its surface. Fourier transform infrared spectroscopy, circular dichroism, and x-ray diffraction have confirmed protein uptake by the lipid phase along with a global disordering effect onto the lipid alkyl chains and have shown a temporal evolution of the structure of water penetrating the lipid phase together with the protein. These effects are clearly related to the temporal variation of the microgravimetric gauge signal. Finally, measurements carried out on pre-annealed samples point out the role of mesoscopic morphology in determining the pathways through which MBP penetrates the lipid multilayer. The results obtained in our model system could be useful in clarifying the mechanisms of the myelinating and demyelinating processes that take place in the natural membrane.     

Low Energy Intraband Plasmons and Electron Energy Loss Spectra of Single and Multilayered Graphene

We present a theory for the calculation of the low energy intraband plasmon frequencies and the electron energy loss (EEL) spectra of single layer and multilayer graphene sheets. Our calculation shows that the number of plasmons that can be excited is equal to the number of graphene layers in the sample. One of these is the dominant in-phase plasmon having a square root dependence on the wave number at low wave vectors, whereas the others are out-of-phase plasmons having near linear dependences on the wave number. The EEL spectra of a single layer graphene shows a single peak at the plasmon frequency, which has been observed experimentally. The EEL spectra of all multilayer graphenes have two peaks, one corresponding to the dominant in-phase plasmon and the other due to the out of phase plasmons. We predict that careful measurement of the EEL of multilayer graphene will show both peaks due to the low energy intraband plasmons.

     

Biomarkers intersect with the exposome

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.     

New perspectives for synergy research with the “omic”-technologies

Synergistic effects, understood as true overadditive effects, are often observed in experimental and clinical studies using phytopharmaceuticals. The introduction of the “omic”-technologies is now opening new perspectives in rationalizing these effects and making use of them in the development of a new generation of phytopharmaceuticals. This review describes possible mechanism of synergistic actions of herbal drugs by mono- and multitargeting and by the activation of signal cascades. It examins the possibilities of the standardization of single and multi component plant extracts and the prediction and assessment of the toxicity and safety of plant extracts with the support of the “omic”-technologies. It further discusses the use of phytopharmaceuticals in the context of an “individualized medicine”. It makes proposals how to use the “omic”-technologies to rationalize and develop combination therapies of phytopharmaceuticals and synthetic drugs to minimize adverse reactions (ARs) or improve the therapeutic efficacy. Examples of clinical studies are given which explore already the potential of such co-medications. Modern medical therapy has acknowledged for quite some time the usefulness of combination therapies in the treatment of multifactorial diseases like cancer, cardiovascular or rheumatic diseases. The term “synergy” is rarely used in this context, the combinatory mechanisms of actions seldom completely understood and the potentially occurring adverse reactions feared. A systematic exploitation of synergy effects of phytomedical interventions alone or in combination with synthetic drugs should lead in a long term perspective to the discovery and development of more rational evidence-based interventions in the prevention and therapy of multifactorial diseases and should thereby enrich modern pharmacotherapy.     

Formidable females redux:male social integration into female networks and the value of dynamic multilayer networks

The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,we investigate how integration between male and female grooming and aggression interaction networks influences male power trajectories in vervet monkeys Chlorocebus pygerythrus.Our previous analyses of this phenomenon used a monolayer approach,and our aim here is to extend these analyses using a dynamic multilayer approach.To do so,we constructed a temporal series of male and female interaction layers.We then used a multivariate multilevel autoregression model to compare cross-lagged associations between a male's centrality in the female grooming layer and changes in male Elo ratings.Our results confirmed our original findings:changes in male centrality within the female grooming network were weakly but positively tied to changes in their Elo ratings.However,the multilayer network approach offered additional insights into this social process,identifying how changes in a male's centrality cascade through the other network layers.This dynamic view indicates that the changes in Elo ratings are likely to be short-lived,but that male centrality within the female network had a much stronger impact throughout the multilayer network as a whole,especially on reducing intermale aggression(i.e.,aggression directed by males toward other males).We suggest that multilayer social network approaches can take advantage of increased amounts of social data that are more commonly collected these days,using a variety of methods.Such data are inherently multilevel and multilayered,and thus offer the ability to quantify more precisely the dynamics of animal social behaviors.     

Effects of dielectric permittivities on skin heating due to millimeter wave exposure

Background  

Because the possibility of millimeter wave (MMW) exposure has increased, public concern about the health issues due to electromagnetic radiation has also increased. While many studies have been conducted for MMW exposure, the effect of dielectric permittivities on skin heating in multilayer/heterogeneous human-body models have not been adequately investigated. This is partly due to the fact that a detailed investigation of skin heating in a multilayer model by computational methods is difficult since many parameters are involved. In the present study, therefore, theoretical analyses were conducted to investigate the relationship between dielectric permittivities and MMW-induced skin heating in a one-dimensional three-layer model (skin, fat, and muscle).