The epitranscriptome landscape of small noncoding RNAs in stem cells.

Stem cells (SCs) are unique cells that have an inherent ability to self-renew or differentiate. Both fate decisions are strongly regulated at the molecular level via intricate signaling pathways. The regulation of signaling networks promoting self-renewal or differentiation was thought to be largely governed by the action of transcription factors. However, small noncoding RNAs (ncRNAs), such as vault RNAs, and their post-transcriptional modifications (the epitranscriptome) have emerged as additional regulatory layers with essential roles in SC fate decisions. RNA post-transcriptional modifications often modulate RNA stability, splicing, processing, recognition, and translation. Furthermore, modifications on small ncRNAs allow for dual regulation of RNA activity, at both the level of biogenesis and RNA-mediated actions. RNA post-transcriptional modifications act through structural alterations and specialized RNA-binding proteins (RBPs) called writers, readers, and erasers. It is through SC-context RBPs that the epitranscriptome coordinates specific functional roles. Small ncRNA post-transcriptional modifications are today exploited by different mechanisms to facilitate SC translational studies. One mechanism readily being studied is identifying how SC-specific RBPs of small ncRNAs regulate fate decisions. Another common practice of using the epitranscriptome for regenerative applications is using naturally occurring post-transcriptional modifications on synthetic RNA to generate induced pluripotent SCs. Here, we review exciting insights into how small ncRNA post-transcriptional modifications control SC fate decisions in development and disease. We hope, by illustrating how essential the epitranscriptome and their associated proteome are in SCs, they would be considered as novel tools to propagate SCs for regenerative medicine.

Electrostatically coupled SiO2 nanoparticles/poly (L-DOPA) antifouling coating on a nanofiltration membrane.

In this work, the fouling resistance of TFC (thin film composite) nanofiltration membranes have been enhanced using an electrostatically coupled SiO2 (silica dioxide) nanoparticles/poly(L-DOPA) (3-(3,4-dihydroxyphenyl)-l-alanine) antifouling coating. SiO2 nanoparticles were synthesized in different size ranges and combined with L-DOPA; and then coated as an anti-fouling layer on the membrane surface by recirculated deposition. Membranes were coated with S-NP (silica nanoparticles) in small (19.8 nm), medium (31.6 nm) and large (110.1 nm) sizes. The zwitterionic compound L-DOPA in the form of self-polymerized poly(L-DOPA) (PDOPA) helped with the attachment of the S-NP to the membrane surface. It was confirmed by AFM (atomic force microscopy) measurement that coating of membranes led to an increase in hydrophilicity and reduction in surface roughness, which in turn led to a 60% reduction in the adhesion force of the foulant on the membrane as compared to the neat membrane. The modified membranes experienced almost no flux decline during the filtration experimental period, whereas the unmodified membrane showed a sharp flux decline. The best coating conditions of silica nanoparticles resulting in enhanced anti-fouling properties were identified. The biofouling film formation on the membranes was evaluated quantitatively using the flow cytometry method. The results indicated that the modified membranes had 50% lower microbial population growth in terms of total event count compared to the neat membrane. Overall, the experimental results have confirmed that the coating of electrostatically coupled SiO2 nanoparticles and PDOPA (S-NP/PDOPA) on TFC-NF (nanofiltration) membrane surfaces is effective in improving the fouling resistance of the membranes. This result has positive implications for reducing membrane fouling in desalination and industrial wastewater treatment applications.

Receptor Activity-modifying Proteins 2 and 3 Generate Adrenomedullin Receptor Subtypes with Distinct Molecular Properties.

Adrenomedullin (AM) is a peptide hormone with numerous effects in the vascular systems. AM signals through the AM1 and AM2 receptors formed by the obligate heterodimerization of a G protein-coupled receptor, the calcitonin receptor-like receptor (CLR), and receptor activity-modifying proteins 2 and 3 (RAMP2 and RAMP3), respectively. These different CLR-RAMP interactions yield discrete receptor pharmacology and physiological effects. The effective design of therapeutics that target the individual AM receptors is dependent on understanding the molecular details of the effects of RAMPs on CLR. To understand the role of RAMP2 and -3 on the activation and conformation of the CLR subunit of AM receptors, we mutated 68 individual amino acids in the juxtamembrane region of CLR, a key region for activation of AM receptors, and determined the effects on cAMP signaling. Sixteen CLR mutations had differential effects between the AM1 and AM2 receptors. Accompanying this, independent molecular modeling of the full-length AM-bound AM1 and AM2 receptors predicted differences in the binding pocket and differences in the electrostatic potential of the two AM receptors. Druggability analysis indicated unique features that could be used to develop selective small molecule ligands for each receptor. The interaction of RAMP2 or RAMP3 with CLR induces conformational variation in the juxtamembrane region, yielding distinct binding pockets, probably via an allosteric mechanism. These subtype-specific differences have implications for the design of therapeutics aimed at specific AM receptors and for understanding the mechanisms by which accessory proteins affect G protein-coupled receptor function.

Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges.

Microbial communities are ubiquitous and carry an exceptionally broad metabolic capability. Upon environmental perturbation, microbes are also amongst the first natural responsive elements with perturbation-specific cues and markers. These communities are thereby uniquely positioned to inform on the status of environmental conditions. The advent of microbial omics has led to an unprecedented volume of complex microbiological data sets. Importantly, these data sets are rich in biological information with potential for predictive environmental classification and forecasting. However, the patterns in this information are often hidden amongst the inherent complexity of the data. There has been a continued rise in the development and adoption of machine learning (ML) and deep learning architectures for solving research challenges of this sort. Indeed, the interface between molecular microbial ecology and artificial intelligence (AI) appears to show considerable potential for significantly advancing environmental monitoring and management practices through their application. Here, we provide a primer for ML, highlight the notion of retaining biological sample information for supervised ML, discuss workflow considerations, and review the state of the art of the exciting, yet nascent, interdisciplinary field of ML-driven microbial ecology. Current limitations in this sphere of research are also addressed to frame a forward-looking perspective toward the realization of what we anticipate will become a pivotal toolkit for addressing environmental monitoring and management challenges in the years ahead.

PreImplantation factor (PIF*) regulates systemic immunity and targets protective regulatory and cytoskeleton proteins.

Secreted by viable embryos, PIF is expressed by the placenta and found in maternal circulation. It promotes implantation and trophoblast invasion, achieving systemic immune homeostasis. Synthetic PIF successfully transposes endogenous PIF features to non-pregnant immune and transplant models. PIF affects innate and activated PBMC cytokines and genes expression. We report that PIF targets similar proteins in CD14+, CD4+ and CD8+ cells instigating integrated immune regulation. PIF-affinity chromatography followed by mass-spectrometry, pathway and heatmap analysis reveals that SET-apoptosis inhibitor, vimentin, myosin-9 and calmodulin are pivotal for immune regulation. PIF acts on macrophages down-stream of LPS (lipopolysaccharide-bacterial antigen) CD14/TLR4/MD2 complex, targeting myosin-9, thymosin-α1 and 14-3-3eta. PIF mainly targets platelet aggregation in CD4+, and skeletal proteins in CD8+ cells. Pathway analysis demonstrates that PIF targets and regulates SET, tubulin, actin-b, and S100 genes expression. PIF targets systemic immunity and has a short circulating half-life. Collectively, PIF targets identified; protective, immune regulatory and cytoskeleton proteins reveal mechanisms involved in the observed efficacy against immune disorders.

PIF direct immune regulation: Blocks mitogen-activated PBMCs proliferation, promotes TH2/TH1 bias, independent of Ca(2+).

PreImplantation Factor (PIF(9&15)) secreted by viable embryos exerts an essential transplant acceptance and immune regulatory role in pregnancy. Synthetic PIF replicates endogenous PIF's effect in pregnant and non-pregnant immune disorder models. PIF binds macrophages to regulate CD3/CD28-induced T-cell response. We present evidence that PIF regulates the co-stimulatory T-cell receptor, CD2, which binds to and is activated by phytohemagglutinin (PHA), a potent mitogen, confirming PIF's ability to systemically respond to diverse immune stimulants. PIF's effect on PHA-activated PBMC (male and non-pregnant females) proliferation and cytokine secretion was tested, showing that both PIF(9&15) block PHA-induced PBMC proliferation and promote anti-inflammatory IL10 secretion, while reducing pro-inflammatory IFNγ secretion. Thus favoring a T(H)2 cytokine bias. Surface plasmon resonance spectroscopy, immunocytochemistry and Flex station experiments reveal that PIF effect is direct. PIF targets intracellular targets but does not affect early Ca(2+) mobilization. By promoting the CD2 receptor in activated T-cells and through inhibition of co-ligand CD58 expression, PIF regulates antigen-presenting cell (APC)-T-cell interactions required for PHA action. Structure-based design demonstrated that PIF15 offers improved target specificity as compared to PIF9. Collectively, PIF directly regulates mitogen-induced PBMC activation. Results support PIF translation for therapy of immune disorders.

Key cellular components and interactive histocompatibility molecules regulating tolerance to the fetal allograft.

Implantation is a major landmark in life. It involves the correct apposition of the embryo in the maternal endometrium. The cellular environment influences placenta development, and direct contact of the fetus with maternal tissues is achieved through decidual cells. At the decidua, and at systemic level, the correct balance of cells potentially acting as antigen-presenting cells and histocompatibility products play a pivotal role in achieving feto-maternal tolerance. Here, we review some of the current issues associated with the interplay between cells and molecules needed for pregnancy development.