scholarly journals Scenes From Tick Physiology: Proteins of Sialome Talk About Their Biological Processes

Author(s):  
Natalia Fernández-Ruiz ◽  
Agustín Estrada-Peña

Ticks are blood-sucking parasites with different strategies of feeding depending on the tick family. The major families are Ixodidae or Argasidae, being slow or fast feeders, respectively. In the recent years, the advances in molecular sequencing techniques have enabled to gain knowledge about the proteome of the tick’s salivary glands. But an holistic view of the biological processes underlying the expression of the sialome has been neglected. In this study we propose the use of standard biological processes as a tool to draw the physiology of the tick’s salivary glands. We used published data on the sialome of Rhipicephalus sanguineus s.l. (Ixodidae) and Ornithodoros rostratus (Argasidae). A partial set of proteins obtained by these studies were used to define the biological process(es) in which proteins are involved. We used a directed network construction in which the nodes are proteins (source) and biological processes (target), separately for the low-level processes (“children”) and the top-level ones (“parents”). We applied the method to feeding R. sanguineus at different time slices, and to different organs of O. rostratus. The network connects the proteins and the processes with a strength directly proportional to the transcript per millions of each protein. We used PageRank as a measure of the importance of each biological process. As suggested in previous studies, the sialome of unfed R. sanguineus express about 30% less biological processes than feeding ticks. Another decrease (25%) is noticed at the middle of the feeding and before detachment. However, top-level processes are deeply affected only at the onset of feeding, demonstrating a redundancy in the feeding. When ixodid-argasid are compared, large differences were observed: they do not share 91% of proteins, but share 90% of the biological processes. However, caution must be observed when examining these results. The hypothesis of different proteins linked to similar biological process(es) in both ticks is an extreme not confirmed in this study. Considering the limitations of this study, carried out with a selected set of proteins, we propose the networks of proteins of sialome linked to their biological processes as a tool aimed to explain the biological processes behind families of proteins.

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Erica Ponzi ◽  
Magne Thoresen ◽  
Therese Haugdahl Nøst ◽  
Kajsa Møllersen

Abstract Background Cancer genomic studies often include data collected from several omics platforms. Each omics data source contributes to the understanding of the underlying biological process via source specific (“individual”) patterns of variability. At the same time, statistical associations and potential interactions among the different data sources can reveal signals from common biological processes that might not be identified by single source analyses. These common patterns of variability are referred to as “shared” or “joint”. In this work, we show how the use of joint and individual components can lead to better predictive models, and to a deeper understanding of the biological process at hand. We identify joint and individual contributions of DNA methylation, miRNA and mRNA expression collected from blood samples in a lung cancer case–control study nested within the Norwegian Women and Cancer (NOWAC) cohort study, and we use such components to build prediction models for case–control and metastatic status. To assess the quality of predictions, we compare models based on simultaneous, integrative analysis of multi-source omics data to a standard non-integrative analysis of each single omics dataset, and to penalized regression models. Additionally, we apply the proposed approach to a breast cancer dataset from The Cancer Genome Atlas. Results Our results show how an integrative analysis that preserves both components of variation is more appropriate than standard multi-omics analyses that are not based on such a distinction. Both joint and individual components are shown to contribute to a better quality of model predictions, and facilitate the interpretation of the underlying biological processes in lung cancer development. Conclusions In the presence of multiple omics data sources, we recommend the use of data integration techniques that preserve the joint and individual components across the omics sources. We show how the inclusion of such components increases the quality of model predictions of clinical outcomes.


1995 ◽  
Vol 308 (1) ◽  
pp. 243-249 ◽  
Author(s):  
J M C Ribeiro ◽  
M Schneider ◽  
J A Guimarães

The salivary anticoagulant of the blood-sucking bug Rhodnius prolixus was purified to homogeneity using a protocol consisting of weak cation-exchange, DEAE, hydrophobic-interaction and octadecyl reverse-phase chromatography, yielding a protein with the same N-terminal sequence as nitrophorin 2, one of the four NO haem protein carriers present in the salivary glands of Rhodnius with a molecular mass of 19689 Da [D. Champagne, R.H. Nussenzveig and J.M.C. Ribeiro, (1995) J. Biol. Chem. 270, in the press]. To exclude the possibility of the nitrophorin being a contaminant, another chromatographic protocol was performed, consisting of chromatofocusing followed by strong-cation-exchange chromatography. Again the anticoagulant was eluted with nitrophorin 2. Nitrophorin 2 inhibits coagulation Factor VIII-mediated activation of Factor X and accounts for all the anti-clotting activity observed in Rhodnius salivary glands.


2008 ◽  
Vol 105 (46) ◽  
pp. 17700-17705 ◽  
Author(s):  
Richard Llewellyn ◽  
David S. Eisenberg

As genome sequencing outstrips the rate of high-quality, low-throughput biochemical and genetic experimentation, accurate annotation of protein function becomes a bottleneck in the progress of the biomolecular sciences. Most gene products are now annotated by homology, in which an experimentally determined function is applied to a similar sequence. This procedure becomes error-prone between more divergent sequences and can contaminate biomolecular databases. Here, we propose a computational method of assignment of function, termed Generalized Functional Linkages (GFL), that combines nonhomology-based methods with other types of data. Functional linkages describe pairwise relationships between proteins that work together to perform a biological task. GFL provides a Bayesian framework that improves annotation by arbitrating a competition among biological process annotations to best describe the target protein. GFL addresses the unequal strengths of functional linkages among proteins, the quality of existing annotations, and the similarity among them while incorporating available knowledge about the cellular location or individual molecular function of the target protein. We demonstrate GFL with functional linkages defined by an algorithm known as zorch that quantifies connectivity in protein–protein interaction networks. Even when using proteins linked only by indirect or high-throughput interactions, GFL predicts the biological processes of many proteins in Saccharomyces cerevisiae, improving the accuracy of annotation by 20% over majority voting.


2018 ◽  
Author(s):  
Valerie Wood ◽  
Antonia Lock ◽  
Midori A. Harris ◽  
Kim Rutherford ◽  
Jürg Bähler ◽  
...  

AbstractThe first decade of genome sequencing stimulated an explosion in the characterization of unknown proteins. More recently, the pace of functional discovery has slowed, leaving around 20% of the proteins even in well-studied model organisms without informative descriptions of their biological roles. Remarkably, many uncharacterized proteins are conserved from yeasts to human, suggesting that they contribute to fundamental biological processes. To fully understand biological systems in health and disease, we need to account for every part of the system. Unstudied proteins thus represent a collective blind spot that limits the progress of both basic and applied biosciences.We use a simple yet powerful metric based on Gene Ontology (GO) biological process terms to define characterized and uncharacterized proteins for human, budding yeast, and fission yeast. We then identify a set of conserved but unstudied proteins in S. pombe, and classify them based on a combination of orthogonal attributes determined by large-scale experimental and comparative methods. Finally, we explore possible reasons why these proteins remain neglected, and propose courses of action to raise their profile and thereby reap the benefits of completing the catalog of proteins’ biological roles.


Biomolecules ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 190 ◽  
Author(s):  
Fanindra Kumar Deshmukh ◽  
Dana Yaffe ◽  
Maya Olshina ◽  
Gili Ben-Nissan ◽  
Michal Sharon

The last decade has seen accumulating evidence of various proteins being degraded by the core 20S proteasome, without its regulatory particle(s). Here, we will describe recent advances in our knowledge of the functional aspects of the 20S proteasome, exploring several different systems and processes. These include neuronal communication, post-translational processing, oxidative stress, intrinsically disordered protein regulation, and extracellular proteasomes. Taken together, these findings suggest that the 20S proteasome, like the well-studied 26S proteasome, is involved in multiple biological processes. Clarifying our understanding of its workings calls for a transformation in our perception of 20S proteasome-mediated degradation—no longer as a passive and marginal path, but rather as an independent, coordinated biological process. Nevertheless, in spite of impressive progress made thus far, the field still lags far behind the front lines of 26S proteasome research. Therefore, we also touch on the gaps in our knowledge of the 20S proteasome that remain to be bridged in the future.


Resources ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 94 ◽  
Author(s):  
Serena Conserva ◽  
Fabio Tatti ◽  
Vincenzo Torretta ◽  
Navarro Ferronato ◽  
Paolo Viotti

Secondary clarifiers are demanded to separate solids created in activated sludge biological processes to achieve both a clarified effluent and to manage the biological processes itself. Indeed, the biological process may influence the sludge characteristics, and conversely, the settling efficiency of the sedimentation basin plays an important role on the biological process in the activated sludge system. The proposed model represents a tool for better addressing the design and management of activated sludge system in wastewater treatment plants. The aim is to develop a numerical model which takes into account both the conditions in the biological reactor and the sludge characteristics coupled to the hydrodynamic behavior of a clarifier tank. The obtained results show that the different conditions in the reactor exert a great influence on the sedimentation efficiency.


2019 ◽  
Vol 276 ◽  
pp. 06030 ◽  
Author(s):  
Iva Yenis Septiariva ◽  
Tri Padmi ◽  
Enri Damanhuri ◽  
Qomarudin Helmy

Landfill is the most commonly method of municipal solid waste disposal in many countries. This practice has great potential to produce highly polluted leachate in massive quantities, which can cause environmental contamination. Biological processes are known as a common method to treat municipal leachate however this process alone in is less effective, especially in reducing the concentration of organic pollutants (BOD5/COD ratio). Leachate properties are site-specific and greatly influenced by landfill age. This study focuses on the investigation of treatment methods that can increase the extent of leachate biodegradability by applying an ozone concentration of 2.5 mg/L with up to 360 minutes of contact time. In this study, batch reactors were used and operated in anaerobic and aerobic conditions. The leachate used here represents both young and old leachate. Several treatment combinations were compared: Variation I (a combination of biologically aerobic and anaerobic process), Variation II (ozonation included as a pre-treatment process), and Variation III (ozonation was included as a post-treatment process). The results suggest that the BOD5/COD ratios of young and old leachates were 0.58 and 0.21, respectively. The COD removal for a young and old leachate treatment by biological process alone was 96.8% and 50.8%, respectively. Meanwhile, a combination of anaerobic-ozonation-aerobic processes gave better COD removal. Ozonation had a significant effect on the old leachate treatment, where the COD removal rose from 50.8% to 75%. Ozonation is a type of technology that can be applied to a subsequence treatment of biological processes in order to elevate the COD removal efficiency.


Author(s):  
Andres M Cifuentes-Bernal ◽  
Vu Vh Pham ◽  
Xiaomei Li ◽  
Lin Liu ◽  
Jiuyong Li ◽  
...  

Abstract Motivation microRNAs (miRNAs) are important gene regulators and they are involved in many biological processes, including cancer progression. Therefore, correctly identifying miRNA–mRNA interactions is a crucial task. To this end, a huge number of computational methods has been developed, but they mainly use the data at one snapshot and ignore the dynamics of a biological process. The recent development of single cell data and the booming of the exploration of cell trajectories using ‘pseudotime’ concept have inspired us to develop a pseudotime-based method to infer the miRNA–mRNA relationships characterizing a biological process by taking into account the temporal aspect of the process. Results We have developed a novel approach, called pseudotime causality, to find the causal relationships between miRNAs and mRNAs during a biological process. We have applied the proposed method to both single cell and bulk sequencing datasets for Epithelia to Mesenchymal Transition, a key process in cancer metastasis. The evaluation results show that our method significantly outperforms existing methods in finding miRNA–mRNA interactions in both single cell and bulk data. The results suggest that utilizing the pseudotemporal information from the data helps reveal the gene regulation in a biological process much better than using the static information. Availability and implementation R scripts and datasets can be found at https://github.com/AndresMCB/PTC. Supplementary information Supplementary data are available at Bioinformatics online.


2018 ◽  
Vol 250 ◽  
pp. 01017 ◽  
Author(s):  
Abubakar Sadiq Muhammed ◽  
Khairul Anuar Kassim ◽  
Muttaqa Uba Zango

Recently, the concept of using biological process in soil improvement otherwise called bio-mediated soil improvement technique has shown greater prospects in the mitigation of liquefiable soils. It is an environmental friendly technique that has generated great interest to geotechnical engineers. This paper presents a review on the microorganism responsible for the biological processes in soil improvement system, factors that affect biological process, identifying the mechanism of liquefaction and commonly adopted method to mitigate liquefaction. Next, the effect of microbial induced calcite precipitation (MICP) on the strength and cyclic response were also analyzed, where it was identified that higher cementation level leads to formation of larger sized calcite crystals which in turn leads to the improved shear strength, stiffness and cyclic resistance ratio of the soil. However, the effects of various bacteria, cementation reagent concentrations amongst other factors were not fully explored in most of the studies. Finally, some of the challenges that lay ahead for the emerging technology are optimizing treatment factors (bacteria and cementation reagent concentration), upscaling process, training of researchers/technologist and long – time durability of the improved soils.


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