Human cytomegalovirus infection perturbs neural progenitor cell fate via the expression of viral microRNAs.

Human cytomegalovirus (HCMV) preferentially targets neural progenitor cells (NPCs) in congenitally infected fetal brains, inducing neurodevelopmental disorders. While HCMV expresses several microRNAs (miRNAs) during infection, their roles in NPC infection are unclear. Here, we characterized expression of cellular and viral miRNAs in HCMV-infected NPCs during early infection by microarray and identified seven differentially expressed cellular miRNAs and six significantly upregulated HCMV miRNAs. Deep learning approaches were used to identify potential targets of significantly upregulated HCMV miRNAs against differentially expressed cellular messenger RNA (mRNAs), and the associations with miRNA-mRNA expression changes were observed. Gene ontology enrichment analysis indicated cellular gene targets were significantly enriched in pathways involved in neurodevelopment and cell-cycle processes. Viral modulation of selected miRNAs and cellular gene targets involved in neurodevelopmental processes were further validated by real-time quantitative reverse transcription polymerase chain reaction. Finally, a predicted 3' untranslated region target site of hcmv-miR-US25-1 in Jag1, a factor important for neurogenesis, was confirmed by mutagenesis. Reduction of Jag1 RNA and protein levels in NPCs was observed in response to transient expression of hcmv-miR-US25-1. A hcmv-miR-US25-1 mutant virus (ΔmiR-US25) displayed limited ability to downregulate Jag1 mRNA levels and protein levels during the early infection stage compared with the wild type virus. Our collective experimental and computational investigation of miRNAs and cellular mRNAs expression in HCMV-infected NPCs yields new insights into the roles of viral miRNAs in regulating NPC fate and their contributions to HCMV neuropathogenesis.

Globally Accessible Distributed Data Sharing (GADDS): a decentralized FAIR platform to facilitate data sharing in the life sciences.

MOTIVATION: Technical advances have revolutionized the life sciences and researchers commonly face challenges associated with handling large amounts of heterogeneous digital data. The Findable, Accessible, Interoperable and Reusable (FAIR) principles provide a framework to support effective data management. However, implementing this framework is beyond the means of most researchers in terms of resources and expertise, requiring awareness of metadata, policies, community agreements and other factors such as vocabularies and ontologies. RESULTS: We have developed the Globally Accessible Distributed Data Sharing (GADDS) platform to facilitate FAIR-like data-sharing in cross-disciplinary research collaborations. The platform consists of (i) a blockchain-based metadata quality control system, (ii) a private cloud-like storage system and (iii) a version control system. GADDS is built with containerized technologies, providing minimal hardware standards and easing scalability, and offers decentralized trust via transparency of metadata, facilitating data exchange and collaboration. As a use case, we provide an example implementation in engineered living material technology within the Hybrid Technology Hub at the University of Oslo. AVAILABILITY AND IMPLEMENTATION: Demo version available at https://github.com/pavelvazquez/GADDS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Network characterization of the Entangled Model for sustainability indicators. Analysis of the network properties for scenarios.

Policy-makers require strategies to select a set of sustainability indicators that are useful for monitoring sustainability. For this reason, we have developed a model where sustainability indicators compete for the attention of society. This model has shown to have steady situations where a set of sustainability indicators are stable. To understand the role of the network configuration, in this paper we analyze the network properties of the Entangled Sustainability model. We have used the degree distribution, the clustering coefficient, and the interaction strength distribution as main measures. We also analyze the network properties for scenarios compared against randomly generated scenarios. We found that the stable situations show different characteristics from the unstable transitions present in the model. We also found that the complex emergent feature of sustainability shown in the model is an attribute of the scenarios, however, the randomly generated scenarios do not present the same network properties.

Skeletal muscle: from birth to old age, routes to mechanical and metabolic failure. / Músculo esquelético: del nacimiento a la vejez, rutas hacia la falla mecánica y metabólica.

Skeletal muscle (SM) is the most abundant tissue and the largest reservoir of protein in the body. It transports glucose in an insulin dependent manner by the glucose transporter type 4 (GLUT4) and contributes in the maintenance of serum amino acids concentration. By its mass and energetic requirements, it is fundamental for the systemic metabolic balance. In the present work, we present the effect of gestational undernourishment (GU) on the mechanical and metabolic properties of SM at birth and in old age in an animal model. Mechanical studies were performed on isolated muscles, while the GLUT4, amino acid transporters LAT2, SNAT2 and insulin receptors (IR) determination were performed on isolated transverse-tubule membranes (TT). The GU in offspring at birth, results in low muscle mass with increased contraction force and resistance to fatigue. However, in two-years old rats, there was muscle hypotrophy and sarcopenia, the force decreased between 50 and 70% in control rats and rats with GU respectively, accompanied by a lower expression of LAT2, SNAT2 and IR in TT. In conclusion, GU irreversibly affects the SM, an effect that could be similar in humans, which help us to understand the events that associate the GU with the metabolic debacle of SM and the metabolic diseases of human adulthood.

Reversible oxidation of vicinal-thiols motif in sarcoplasmic reticulum calcium regulatory proteins is involved in muscle fatigue mechanism.

The mechanism underlying fatigue in skeletal muscle (SM) related to the redox-potential hypothesis, ranges from a direct effect of oxygen reactive species, to a number of other free radical intermediates targeting specific amino acids in the Ca(2+)-regulatory proteins of the sarcoplasmic reticulum (SR). In the present study, we investigate the selective oxidation/reduction of the protein motif Cys-(Xn=2-6)-Cys, known as a vicinal thiol group (VTG), present in the SR Ca(2+)-ATPase (SERCA) and in the Ca(2+)-channel ryanodine receptor (RyR) which are modified during muscle fatigue in SM. Selective oxidation of VTG with phenyl arsine oxide (PAO) increases fatigue in rat isolated SM and fatigue is prevented when muscle is previously incubated with a VTG selective reducing agent, 2,3-dimercaptopropanol (British anti-Lewisite (BAL)). In isolated SR membranes, PAO [<0.1mM] modifies SERCA conformation and inhibits ATPase activity but does not affect Ca(2+)-release. However, PAO at [>0.1mM] inhibits SERCA and RyR activities in a reversible manner by selectively reducing them. Interestingly, as observed by differential scanning calorimetry, the conformation of SERCA from fatigued muscle changed in a similar manner as when SERCA VTG where oxidized. The addition of BAL to fatigued muscle restored the structural conformation and activity of SERCA with full recovery of muscle force production after fatigue. We conclude that VTG reversible oxidation of SR Ca(2+) regulatory proteins are involved in muscle contraction/relaxation and are a molecular mechanism to be considered for muscle fatigue.

An Entangled Model for Sustainability Indicators.

Nowadays the challenge for humanity is to find pathways towards sustainable development. Decision makers require a set of sustainability indicators to know if the sustainability strategies are following those pathways. There are more than one hundred sustainability indicators but they differ on their relative importance according to the size of the locality and change on time. The resources needed to follow these sustainability indicators are scarce and in some instances finite, especially in smaller regions. Therefore strategies to select set of these indicators are useful for decision makers responsible for monitoring sustainability. In this paper we propose a model for the identification and selection of a set of sustainability indicators that adequately represents human systems. In developing this model, we applied evolutionary dynamics in a space where sustainability indicators are fundamental entities interconnected by an interaction matrix. we used a fixed interaction that simulates the current context for the city of Cuernavaca, México as an example. We were able to identify and define relevant sets indicators for the system by using the Pareto principle. In this case we identified a set of sixteen sustainability indicators with more than 80% of the total strength. This set presents resilience to perturbations. For the Tangled Nature framework we provided a manner of treating different contexts (i.e., cities, counties, states, regions, countries, continents or the whole planet), dealing with small dimensions. This model provides decision makers with a valuable tool to select sustainability indicators set for towns, cities, regions, countries, continents or the entire planet according to a coevolutionary framework. The social legitimacy can arise from the fact that each individual indicator must be selected from those that are most important for the subject community.

Regulation of fast skeletal muscle activity by SERCA1 vicinal-cysteines.

During prolonged skeletal muscle contractions free radicals are produced that may lead to fatigue. Vicinal cysteines, known as a Vicinal-thiol groups react preferentially among them depending on redox potential. Therefore, we examined the role of VT groups on the activity and conformational changes of sarcoplasmic reticulum (SR) Ca(2+)-ATPase (SERCA1) from rabbit skeletal muscle isolated SR, by selective oxidation-reduction of VT-groups. After Ca(2+) is released from the SR to start contraction, SERCA1 pumps this cytosolic Ca(2+) back to the SR leading to muscle relaxation. Phenylarsine oxide (PAO) reacts selectively with VT-proteins forming dithioarsines, which are stable but exchanges rapidly with 2,3-dimercaptopropanol (BAL). When 0.1 mM PAO is added to isolated SR, 60 and 67% inhibition of SERCA1 hydrolytic and Ca(2+) uptake activities, respectively is observed. ATPase activity was fully reversible with 1 mM BAL. The SERCA1 thermal inactivation determined from isolated SR from muscle at rest showed a single transition for inactivation (T(i)) at 49 +/- 1.12 degrees C. In the presence of 0.1 mM PAO, SERCA1 shows two transitions at T(i) 34 +/-0.9 degrees C and at 27 +/-1.2 degrees C. The thermal denaturation profile of SERCA1 from muscle at rest, showed two transitions at T(m) = 51.5 +/-1.3 degrees C and 63 +/-1.02 degrees C related to nucleotide and Ca(2+) binding domains, respectively. Whereas isolated SR obtained after a protocol of tetanic stimulation to produce muscle fatigue, showed three transitions in the SERCA1 denaturation profile similar to the effect of PAO, addition of 1 mM BAL reverted the effect of fatigue on SERCA1 denaturation profile. These results indicate a mechanism relating VT group's oxidation to muscle fatigue.