Regulatory Phenomena Research Articles

Epigenetic control of T-DNA during transgenesis and pathogenesis.

Mobile elements known as T-DNAs are transferred from pathogenic Agrobacterium to plants and reprogram the host cell to form hairy roots or tumors. Disarmed non-oncogenic T-DNAs are extensively used to deliver transgenes in plant genetic engineering. Such T-DNAs were the first known targets of RNA silencing mechanisms, which detect foreign RNA in plant cells and produce small RNAs that induce transcript degradation. These T-DNAs can also be transcriptionally silenced by the deposition of epigenetic marks such as DNA methylation and the dimethylation of lysine 9 (H3K9me2) in plants. Here, we review the targeting and the roles of RNA silencing and DNA methylation on T-DNAs in transgenic plants as well as during pathogenesis. In addition, we discuss the crosstalk between T-DNAs and genome-wide changes in DNA methylation during pathogenesis. We also cover recently discovered regulatory phenomena, such as T-DNA suppression and RNA silencing-independent and epigenetic-independent mechanisms that can silence T-DNAs. Finally, we discuss the implications of findings on T-DNA silencing for the improvement of plant genetic engineering.

A REVIEW OF THE DEVELOPMENT OF AN UNDERSTANDING OF ANTIBIOTIC INTERACTIONS, FROM MECHANISMS OF ACTION TO NOVEL RESISTANCE AND THE SEARCH FOR NATURAL ALTERNATIVES

Recent research has also highlighted the importance of interspecies signalling in terms of ecology, immunology, and evolution. Despite being frequently linked to the direct inhibition of microbial growth, signalling molecules can transmit data about complex, coordinated regulatory phenomena such as virulence island expression, periodic biosynthetic activity, stress responses, cell density, motility, and biofilm formation. Genetically encoded quorum sensing signals, at low concentrations, increase the spread of horizontally acquired antibiotic resistance genes, modify host immune response profiles, and control the expression of virulence determinants. Antibiotics suppress infectious diseases, facilitate health interventions such as surgery, and improve the treatment outcomes of human and animal diseases (e.g., by minimising morbidity, mortality, and hospital length of stay). However, the emergence of drug-resistant biofilms continues to undermine many therapeutic modalities. These intricate settings that provide antibiotics include the presence of individually resistant cells, non-linear nutrient transport and blockage effects, and limited yet subpopulation-biased genetic plasticity. For the longest time, the mainstay of contemporary medicine has been the use of antibiotics to treat bacterial infections 5. However, the creation and spread of antibiotic resistance, a serious worldwide health concern brought on by the abuse and misuse of antibiotics, constantly jeopardises their function. 2. The decrease in the number of novel, efficacious antibiotics being introduced to the market exacerbates these problems. Optimising the usage of already available antibiotics by learning more about how they behave in the intricate microbial and host ecosystems connected to bacterial illnesses is one way to address this. This involves, but is not limited to, looking into how combinations of antibiotics affect treatment outcomes and how these interactions alter in certain settings to either help or hinder the evolution of antibiotic resistance.

Why do we need to go beyond overall biological variability assessment in metabolomics?

Unlike other systems such as plants, microorganisms or fungi, human cells are not proficient in eliciting the production of defense compounds in response to external stresses and threats. Human metabolism is essentially based on a set of primary metabolites that participate in the various regulatory events of cells and tissues. The challenge is therefore to maintain homeostasis and allow the survival of the individual through the modulation of existing endogenous metabolic pathways with a relatively stable set of ubiquitous compounds. Since these complex regulatory phenomena are potentially subject to multiple influences, assessing their overall variability, as achieved by most conventional approaches, is not sufficiently informative. The experimental evaluation of several factors acting simultaneously on the metabolome is paramount. Because metabolomics involves the characterization of multivariate metabolic phenotypes, such a methodology requires specific data analysis tools to fully exploit the relevant information considering the different factors, as well as their respective impact on metabolite levels. The investigation of high-dimensional multifactorial data in metabolomics opens new challenges and requires the development of innovative experimental strategies involving structured designs of experiments to assess cause-effect associations and offer deeper insight into relevant biological information. In the future, key outputs should not only consider lists of metabolites, but also include their specific variation related to each effect that can be identified and/or quantified, thus allowing accurate biochemical and functional relationships to be highlighted.

Differential haplotype expression in class I MHC genes during SARS-CoV-2 infection of human lung cell lines.

Cell entry of SARS-CoV-2 causes genome-wide disruption of the transcriptional profiles of genes and biological pathways involved in the pathogenesis of COVID-19. Expression allelic imbalance is characterized by a deviation from the Mendelian expected 1:1 expression ratio and is an important source of allele-specific heterogeneity. Expression allelic imbalance can be measured by allele-specific expression analysis (ASE) across heterozygous informative expressed single nucleotide variants (eSNVs). ASE reflects many regulatory biological phenomena that can be assessed by combining genome and transcriptome information. ASE contributes to the interindividual variability associated with the disease. We aim to estimate the transcriptome-wide impact of SARS-CoV-2 infection by analyzing eSNVs. We compared ASE profiles in the human lung cell lines Calu-3, A459, and H522 before and after infection with SARS-CoV-2 using RNA-Seq experiments. We identified 34 differential ASE (DASE) sites in 13 genes (HLA-A, HLA-B, HLA-C, BRD2, EHD2, GFM2, GSPT1, HAVCR1, MAT2A, NQO2, SUPT6H, TNFRSF11A, UMPS), all of which are enriched in protein binding functions and play a role in COVID-19. Most DASE sites were assigned to the MHC class I locus and were predominantly upregulated upon infection. DASE sites in the MHC class I locus also occur in iPSC-derived airway epithelium basal cells infected with SARS-CoV-2. Using an RNA-Seq haplotype reconstruction approach, we found DASE sites and adjacent eSNVs in phase (i.e., predicted on the same DNA strand), demonstrating differential haplotype expression upon infection. We found a bias towards the expression of the HLA alleles with a higher binding affinity to SARS-CoV-2 epitopes. Independent of gene expression compensation, SARS-CoV-2 infection of human lung cell lines induces transcriptional allelic switching at the MHC loci. This suggests a response mechanism to SARS-CoV-2 infection that swaps HLA alleles with poor epitope binding affinity, an expectation supported by publicly available proteome data.

Early B cells repopulation in multiple sclerosis patients treated with rituximab is not predictive of a risk of relapse or clinical progression.

BackgroundIt is currently unknown whether early B cell reconstitution (EBR) in MS patients under rituximab is associated with a risk of relapse or progression.ObjectivesAnalyzing EBR in rituximab-treated patients and its putative association with clinical findings.MethodsProspective lymphocytes immunophenotyping was performed in a monocentric cohort of MS patients treated by rituximab for 2 years. EBR was defined when B cells concentration was > 5 cells/mm3. B cell subsets were retrospectively associated with clinical data. Clinical and radiological monitoring included relapses, EDSS (Expanded Disability Status Scale), SDMT (Symbol Digit Modalities Test), and MRI.Results182 patients were analyzed (61 remitting-relapsing and 121 progressive-active). 38.5% experienced EBR at least once, but very few (7/182) showed systematic reconstitution. Most patients remained stable upon treatment, regardless of the occurrence of EBR. Dynamics of B cell reconstitution featured increased naïve/transitional B cells, and decreased memory subsets. Homeostasis of the B cell compartment differed at baseline between patients experiencing or not EBR upon treatment. In patients with EBR, reciprocal dynamics of transitional and pro-inflammatory double-negative B cell subsets was associated with better response to rituximab treatment.ConclusionEBR is common in rituximab-treated MS patients and is not associated with clinical disease activity. EBR in the peripheral blood may reflect regulatory immunological phenomena in subgroup of patients.

Connecting nutritional deprivation and pubertal inhibition via GRK2-mediated repression of kisspeptin actions in GnRH neurons

BackgroundPerturbations in the timing of puberty, with potential adverse consequences in later health, are increasingly common. The underlying neurohormonal mechanisms are unfolded, but nutritional alterations are key contributors. Efforts to unveil the basis of normal puberty and its metabolic control have focused on mechanisms controlling expression of Kiss1, the gene encoding the puberty-activating neuropeptide, kisspeptin. However, other regulatory phenomena remain ill-defined. Here, we address the putative role of the G protein-coupled-receptor kinase-2, GRK2, in GnRH neurons, as modulator of pubertal timing via repression of the actions of kisspeptin, in normal maturation and conditions of nutritional deficiency. MethodsHypothalamic RNA and protein expression analyses were conducted in maturing female rats. Pharmacological studies involved central administration of GRK2 inhibitor, βARK1-I, and assessment of gonadotropin responses to kisspeptin or phenotypic and hormonal markers of puberty, under normal nutrition or early subnutrition in female rats. In addition, a mouse line with selective ablation of GRK2 in GnRH neurons, aka G-GRKO, was generated, in which hormonal responses to kisspeptin and puberty onset were monitored, in normal conditions and after nutritional deprivation. ResultsHypothalamic GRK2 expression increased along postnatal maturation in female rats, especially in the preoptic area, where most GnRH neurons reside, but decreased during the juvenile-to-pubertal transition. Blockade of GRK2 activity enhanced Ca+2 responses to kisspeptin in vitro, while central inhibition of GRK2 in vivo augmented gonadotropin responses to kisspeptin and advanced puberty onset. Postnatal undernutrition increased hypothalamic GRK2 expression and delayed puberty onset, the latter being partially reversed by central GRK2 inhibition. Conditional ablation of GRK2 in GnRH neurons enhanced gonadotropin responses to kisspeptin, accelerated puberty onset, and increased LH pulse frequency, while partially prevented the negative impact of subnutrition on pubertal timing and LH pulsatility in mice. ConclusionsOur data disclose a novel pathway whereby GRK2 negatively regulates kisspeptin actions in GnRH neurons, as major regulatory mechanism for tuning pubertal timing in nutritionally-compromised conditions.

Gene Co-Expression in Breast Cancer: A Matter of Distance.

Gene regulatory and signaling phenomena are known to be relevant players underlying the establishment of cellular phenotypes. It is also known that such regulatory programs are disrupted in cancer, leading to the onset and development of malignant phenotypes. Gene co-expression matrices have allowed us to compare and analyze complex phenotypes such as breast cancer (BrCa) and their control counterparts. Global co-expression patterns have revealed, for instance, that the highest gene-gene co-expression interactions often occur between genes from the same chromosome (cis-), meanwhile inter-chromosome (trans-) interactions are scarce and have lower correlation values. Furthermore, strength of cis- correlations have been shown to decay with the chromosome distance of gene couples. Despite this loss of long-distance co-expression has been clearly identified, it has been observed only in a small fraction of the whole co-expression landscape, namely the most significant interactions. For that reason, an approach that takes into account the whole interaction set results appealing. In this work, we developed a hybrid method to analyze whole-chromosome Pearson correlation matrices for the four BrCa subtypes (Luminal A, Luminal B, HER2+ and Basal), as well as adjacent normal breast tissue derived matrices. We implemented a systematic method for clustering gene couples, by using eigenvalue spectral decomposition and the k–medoids algorithm, allowing us to determine a number of clusters without removing any interaction. With this method we compared, for each chromosome in the five phenotypes: a) Whether or not the gene-gene co-expression decays with the distance in the breast cancer subtypes b) the chromosome location of cis- clusters of gene couples, and c) whether or not the loss of long-distance co-expression is observed in the whole range of interactions. We found that in the correlation matrix for the control phenotype, positive and negative Pearson correlations deviate from a random null model independently of the distance between couples. Conversely, for all BrCa subtypes, in all chromosomes, positive correlations decay with distance, and negative correlations do not differ from the null model. We also found that BrCa clusters are distance-dependent, meanwhile for the control phenotype, chromosome location does not determine the clustering. To our knowledge, this is the first time that a dependence on distance is reported for gene clusters in breast cancer. Since this method uses the whole cis- interaction geneset, combination with other -omics approaches may provide further evidence to understand in a more integrative fashion, the mechanisms that disrupt gene regulation in cancer.

Picking the right metaphors for addressing microbial systems: economic theory helps understanding biological complexity.

Any descriptive language is necessarily metaphoric and interpretative. Two somewhat overlapping-but not identical-languages have been thoroughly employed in the last decade to address the issue of regulatory complexity in biological systems: the terminology of network theory and the jargon of electric circuitry. These approaches have found many formal equivalences between the layout of extant genetic circuits and the architecture of man-made counterparts. However, these languages still fail to describe accurately key features of biological objects, in particular the diversity of signal-transfer molecules and the diffusion that is inherent to any biochemical system. Furthermore, current formalisms associated with networks and circuits can hardly face the problem of multi-scale regulatory complexity-from single molecules to entire ecosystems. We argue that the language of economic theory might be instrumental not only to portray accurately many features of regulatory networks, but also to unveil aspects of the biological complexity problem that remain opaque to other types of analyses. The main perspective opened by the economic metaphor when applied to control of microbiological activities is a focus on metabolism, not gene selfishness, as the necessary background to make sense of regulatory phenomena. As an example, we analyse and reinterpret the widespread phenomenon of catabolite repression with the formal frame of the consumer's choice theory.

An Information Theoretical Multilayer Network Approach to Breast Cancer Transcriptional Regulation.

Breast cancer is a complex, highly heterogeneous disease at multiple levels ranging from its genetic origins and molecular processes to clinical manifestations. This heterogeneity has given rise to the so-called intrinsic or molecular breast cancer subtypes. Aside from classification, these subtypes have set a basis for differential prognosis and treatment. Multiple regulatory mechanisms—involving a variety of biomolecular entities—suffer from alterations leading to the diseased phenotypes. Information theoretical approaches have been found to be useful in the description of these complex regulatory programs. In this work, we identified the interactions occurring between three main mechanisms of regulation of the gene expression program: transcription factor regulation, regulation via noncoding RNA, and epigenetic regulation through DNA methylation. Using data from The Cancer Genome Atlas, we inferred probabilistic multilayer networks, identifying key regulatory circuits able to (partially) explain the alterations that lead from a healthy phenotype to different manifestations of breast cancer, as captured by its molecular subtype classification. We also found some general trends in the topology of the multi-omic regulatory networks: Tumor subtype networks present longer shortest paths than their normal tissue counterpart; epigenomic regulation has frequently focused on genes enriched for certain biological processes; CpG methylation and miRNA interactions are often part of a regulatory core of conserved interactions. The use of probabilistic measures to infer information regarding theoretical-derived multilayer networks based on multi-omic high-throughput data is hence presented as a useful methodological approach to capture some of the molecular heterogeneity behind regulatory phenomena in breast cancer, and potentially other diseases.

Zooming in on protein-RNA interactions: a multi-level workflow to identify interaction partners.

Interactions between proteins and RNA are at the base of numerous cellular regulatory and functional phenomena. The investigation of the biological relevance of non-coding RNAs has led to the identification of numerous novel RNA-binding proteins (RBPs). However, defining the RNA sequences and structures that are selectively recognised by an RBP remains challenging, since these interactions can be transient and highly dynamic, and may be mediated by unstructured regions in the protein, as in the case of many non-canonical RBPs. Numerous experimental and computational methodologies have been developed to predict, identify and verify the binding between a given RBP and potential RNA partners, but navigating across the vast ocean of data can be frustrating and misleading. In this mini-review, we propose a workflow for the identification of the RNA binding partners of putative, newly identified RBPs. The large pool of potential binders selected by in-cell experiments can be enriched by in silico tools such as catRAPID, which is able to predict the RNA sequences more likely to interact with specific RBP regions with high accuracy. The RNA candidates with the highest potential can then be analysed in vitro to determine the binding strength and to precisely identify the binding sites. The results thus obtained can furthermore validate the computational predictions, offering an all-round solution to the issue of finding the most likely RNA binding partners for a newly identified potential RBP.

Gene Co-expression Is Distance-Dependent in Breast Cancer.

Breast carcinomas are characterized by anomalous gene regulatory programs. As is well-known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis- (intra-chromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Co-expression Networks by using TCGA-derived RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans- co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the ratio of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans- co-expression in all molecular subtypes. We also observed that gene cis- co-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

Regulatory Phenomena in the Glutathione Peroxidase Superfamily.

Significance: The selenium-containing Glutathione peroxidases (GPxs)1-4 protect against oxidative challenge, inhibit inflammation and oxidant-induced regulated cell death. Recent Advances: GPx1 and GPx4 dampen phosphorylation cascades predominantly via prevention of inactivation of phosphatases by H2O2 or lipid hydroperoxides. GPx2 regulates the balance between regeneration and apoptotic cell shedding in the intestine. It inhibits inflammation-induced carcinogenesis in the gut but promotes growth of established cancers. GPx3 deficiency facilitates platelet aggregation likely via disinhibition of thromboxane biosynthesis. It is also considered a tumor suppressor. GPx4 is expressed in three different forms. The cytosolic form proved to inhibit interleukin-1-driven nuclear factor κB activation and leukotriene biosynthesis. Moreover, it is a key regulator of ferroptosis, because it reduces hydroperoxy groups of complex lipids and silences lipoxygenases. By alternate substrate use, the nuclear form contributes to chromatin compaction. Mitochondrial GPx4 forms the mitochondrial sheath of spermatozoa and, thus, guarantees male fertility. Out of the less characterized GPxs, the cysteine-containing GPx7 and GPx8 are unique in contributing to oxidative protein folding in the endoplasmic reticulum by reacting with protein isomerase as an alternate substrate. A yeast 2-Cysteine glutathione peroxidase equipped with CP and CR was reported to sense H2O2 for inducing an adaptive response. Critical Issues: Most of the findings compiled are derived from tissue culture and/or animal studies only. Their impact on human physiology is sometimes questionable. Future Directions: The expression of individual GPxs and GPx-dependent regulatory phenomena are to be further investigated, in particular in respect to human health.

An in Vivo Binding Assay for RNA-Binding Proteins Based on Repression of a Reporter Gene

We study translation repression in bacteria by engineering a regulatory circuit that functions as a binding assay for RNA binding proteins (RBP) in vivo. We do so by inducing expression of a fluorescent protein-RBP chimera, together with encoding its binding site at various positions within the ribosomal initiation region (+11-13 nt from the AUG) of a reporter module. We show that when bound by their cognate RBPs, the phage coat proteins for PP7 (PCP) and Qβ (QCP), strong repression is observed for all hairpin positions within the initiation region. Yet, a sharp transition to no-effect is observed when positioned in the elongation region, at a single-nucleotide resolution. Employing in vivo Selective 2'-hydroxyl acylation analyzed by primer extension followed by sequencing (SHAPE-seq) for a representative construct, established that in the translationally active state the mRNA molecule is nonstructured, while in the repressed state a structured signature was detected. We then utilize this regulatory phenomena to quantify the binding affinity of the coat proteins of phages MS2, PP7, GA, and Qβ to 14 cognate and noncognate binding sites in vivo. Using our circuit, we demonstrate qualitative differences between in vitro to in vivo binding characteristics for various variants when comparing to past studies. Furthermore, by introducing a simple mutation to the loop region for the Qβ-wt site, MCP binding is abolished, creating the first high-affinity QCP site that is completely orthogonal to MCP. Consequently, we demonstrate that our hybrid transcriptional-post-transcriptional circuit can be utilized as a binding assay to quantify RNA-RBP interactions in vivo.

Translating Alzheimer's disease-associated polymorphisms into functional candidates: a survey of IGAP genes and SNPs.

The International Genomics of Alzheimer's Project (IGAP) is a consortium for characterizing the genetic landscape of Alzheimer's disease (AD). The identified and/or confirmed 19 single-nucleotide polymorphisms (SNPs) associated with AD are located on non-coding DNA regions, and their functional impacts on AD are as yet poorly understood. We evaluated the roles of the IGAP SNPs by integrating data from many resources, based on whether the IGAP SNP was (1) a proxy for a coding SNP or (2) associated with altered mRNA transcript levels. For (1), we confirmed that 12 AD-associated coding common SNPs and five nonsynonymous rare variants are in linkage disequilibrium with the IGAP SNPs. For (2), the IGAP SNPs in CELF1 and MS4A6A were associated with expression of their neighboring genes, MYBPC3 and MS4A6A, respectively, in blood. The IGAP SNP in DSG2 was an expression quantitative trait loci (eQTL) for DLGAP1 and NETO1 in the human frontal cortex. The IGAP SNPs in ABCA7, CD2AP, and CD33 each acted as eQTL for AD-associated genes in brain. Our approach for identifying proxies and examining eQTL highlighted potentially impactful, novel gene regulatory phenomena pertinent to the AD phenotype.

The Misuse of Tobin's Q

We examine the common and growing misuse of Tobin’s q as a proxy for firm value within the law and finance literatures. We trace the history of Tobin’s q, beginning with its original role as a mean-reverting construct that macroeconomists used to model investment policy. We document how the original version of q morphed into the simplified market-to-book ratio version that law and finance scholars regularly use today to examine regulatory policy, corporate governance, and other economic phenomena. Whereas macroeconomists rejected this simplistic version of q because of measurement error problems, law and finance scholars embraced it as a proxy for firm value. In addition, we demonstrate empirically why the simplistic version of q is so problematic. Many of the problems arise because regressions that have as their dependent variable a ratio with book value in the denominator are likely to produce biased estimates, due to both omitted assets and time-varying, firm-specific characteristics that can systematically alter a firm’s book value. As a result, the simplistic version of q produces non-classical measurement error in regression specifications that seek to estimate the relationship between firm value and various corporate and regulatory phenomena. We also confirm, consistent with macroeconomists’ view of the original Tobin’s q, that the market-to-book estimate of q is mean-reverting in terms of stockholder returns. Finally, we suggest a new approach. We replicate the details of one leading study that was based on the simplistic version of q and then show how its results differ when we employ several alternative approaches. We propose that scholars should use these alternative approaches, including direct estimates of firm value instead of the simplistic market-to-book ratio, and, when possible, should supplement the popular fixed effects estimator with the first difference estimator. Overall, our message is straightforward: scholars should view with suspicion any assertions about corporate governance and regulation that are based on the use of market-to-book ratios as the dependent variable in regressions.

High-resolution spatiotemporal transcriptome mapping of tomato fruit development and ripening

Tomato (Solanum lycopersicum) is an established model for studying fruit biology; however, most studies of tomato fruit growth and ripening are based on homogenized pericarp, and do not consider the internal tissues, or the expression signatures of individual cell and tissue types. We present a spatiotemporally resolved transcriptome analysis of tomato fruit ontogeny, using laser microdissection (LM) or hand dissection coupled with RNA-Seq analysis. Regulatory and structural gene networks, including families of transcription factors and hormone synthesis and signaling pathways, are defined across tissue and developmental spectra. The ripening program is revealed as comprising gradients of gene expression, initiating in internal tissues then radiating outward, and basipetally along a latitudinal axis. We also identify spatial variations in the patterns of epigenetic control superimposed on ripening gradients. Functional studies elucidate previously masked regulatory phenomena and relationships, including those associated with fruit quality traits, such as texture, color, aroma, and metabolite profiles.

Synapse-Specific Regulation Revealed at Single Synapses Is Concealed When Recording Multiple Synapses.

Synaptic transmission and its activity-dependent modulation, known as synaptic plasticity, are fundamental processes in nervous system function. Neurons may receive thousands of synaptic contacts, but synaptic regulation may occur only at individual or discrete subsets of synapses, which may have important consequences on the spatial extension of the modulation of synaptic information. Moreover, while several electrophysiological methods are used to assess synaptic transmission at different levels of observation, i.e., through local field potential and individual whole-cell recordings, their experimental limitations to detect synapse-specific modulation is poorly defined. We have investigated how well-known synapse-specific short-term plasticity, where some synapses are regulated and others left unregulated, mediated by astrocytes and endocannabinoid (eCB) signaling can be assessed at different observational levels. Using hippocampal slices, we have combined local field potential and whole-cell recordings of CA3-CA1 synaptic activity evoked by Schaffer collateral stimulation of either multiple or single synapses through bulk or minimal stimulation, respectively, to test the ability to detect short-term synaptic changes induced by eCB signaling. We also developed a mathematical model assuming a bimodal distribution of regulated and unregulated synapses based on realistic experimental data to simulate physiological results and to predict the experimental requirements of the different recording methods to detect discrete changes in subsets of synapses. We show that eCB-induced depolarization-induced suppression of excitation (DSE) and astrocyte-mediated synaptic potentiation can be observed when monitoring single or few synapses, but are statistically concealed when recording the activity of a large number of synapses. These results indicate that the electrophysiological methodology is critical to properly assess synaptic changes occurring in subsets of synapses, and they suggest that relevant synapse-specific regulatory phenomena may be experimentally undetected but may have important implications in the spatial extension of synaptic plasticity phenomena.

Global/Transnational Laww Challenges to Theorizing about Law

Global/transnational “law” discourse seems to be premised on two important assumptions: first, that the empirical reality of the present day globalized world requires moving beyond the traditional concept of international law, because it no longer successfully depicts the nature of “raw data” of various regulatory and adjudicative phenomena taking place at the transnational level; and second, that the analytical rigor of the long dominant positivist strand of jurisprudence, which insists on the criterial approach to law and its autonomous status, nowadays contributes more to the obfuscation than to the clarification of its subject matter. Both of these assumptions lead to the claims that significantly challenge our traditional theorizing about law. According to the first – substantive – challenge, global/transnational phenomena give rise to the birth of a novel, non-statist and post-modern concept of law. According to the second – epistemological – challenge, the nature of the inquired phenomena requires adopting new research strategies which goes beyond the traditional method of the dominant analytical jurisprudence. I will scrutinize both of these challenges. As regards the first of them, I will show that while the strong claim that we are in the possession of some entirely novel concept of (global/transnational) law is not warranted, more modest claims regarding functional sphere of validity and genuinely new (global/transnational) sources of law merit significant weight. When it comes to the second claim, I will argue that the obsession with “law” as the “default descriptor” (Somek) for various global instruments of regulation and standardization stems largely from the erroneous assumption about the special, i.e. “exclusionary” nature of legal rules. Once the direct link between legal “normativity”, “validity”, and “bindingness” is exposed as unsubstantiated, the path is cleared for a more nuanced investigation about the nature of different phenomena that do not pass the threshold of “legality”. This, finally, implies that calls to substitute analyticity and criterialism with some sort of legal pluralist approach, which self-consciously blurs the lines between law and non-law, should be abandoned in favor of a refined analytical approach, which relies on a different sort of socio-legal investigation, the one that treats law as a normative order that is a product of specific historical development and that is as such in interaction with other social normative orders.

RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking

BackgroundCigarette smoking is the leading modifiable risk factor for disease and death worldwide. Previous studies quantifying gene-level expression have documented the effect of smoking on mRNA levels. Using RNA sequencing, it is possible to analyze the impact of smoking on complex regulatory phenomena (e.g. alternative splicing, differential isoform usage) leading to a more detailed understanding of the biology underlying smoking-related disease.MethodsWe used whole-blood RNA sequencing to describe gene and exon-level expression differences between 229 current and 286 former smokers in the COPDGene study. We performed differential gene expression and differential exon usage analyses using the voom/limma and DEXseq R packages. Samples from current and former smokers were compared while controlling for age, gender, race, lifetime smoke exposure, cell counts, and technical covariates.ResultsAt an adjusted p-value <0.05, 171 genes were differentially expressed between current and former smokers. Differentially expressed genes included 7 long non-coding RNAs that have not been previously associated with smoking: LINC00599, LINC01362, LINC00824, LINC01624, RP11-563D10.1, RP11-98G13.1, AC004791.2. Secondary analysis of acute smoking (having smoked within 2-h) revealed 5 of the 171 smoking genes demonstrated an acute response above the baseline effect of chronic smoking. Exon-level analyses identified 9 exons from 8 genes with significant differential usage by smoking status, suggesting smoking-induced changes in isoform expression.ConclusionsTranscriptomic changes at the gene and exon levels from whole blood can refine our understanding of the molecular mechanisms underlying the response to smoking.

The pharmacological regulation of cellular mitophagy.

Small molecules are pharmacological tools of considerable value for dissecting complex biological processes and identifying potential therapeutic interventions. Recently, the cellular quality-control process of mitophagy has attracted considerable research interest; however, the limited availability of suitable chemical probes has restricted our understanding of the molecular mechanisms involved. Current approaches to initiate mitophagy include acute dissipation of the mitochondrial membrane potential (ΔΨm) by mitochondrial uncouplers (for example, FCCP/CCCP) and the use of antimycin A and oligomycin to impair respiration. Both approaches impair mitochondrial homeostasis and therefore limit the scope for dissection of subtle, bioenergy-related regulatory phenomena. Recently, novel mitophagy activators acting independently of the respiration collapse have been reported, offering new opportunities to understand the process and potential for therapeutic exploitation. We have summarized the current status of mitophagy modulators and analyzed the available chemical tools, commenting on their advantages, limitations and current applications.