The transcription factor EGR2 is the molecular linchpin connecting STAT6 activation to the late, stable epigenomic program of alternative macrophage polarization.

Macrophages polarize into functionally distinct subtypes while responding to microenvironmental cues. The identity of proximal transcription factors (TFs) downstream from the polarization signals are known, but their activity is typically transient, failing to explain the long-term, stable epigenomic programs developed. Here, we mapped the early and late epigenomic changes of interleukin-4 (IL-4)-induced alternative macrophage polarization. We identified the TF, early growth response 2 (EGR2), bridging the early transient and late stable gene expression program of polarization. EGR2 is a direct target of IL-4-activated STAT6, having broad action indispensable for 77% of the induced gene signature of alternative polarization, including its autoregulation and a robust, downstream TF cascade involving PPARG. Mechanistically, EGR2 binding results in chromatin opening and the recruitment of chromatin remodelers and RNA polymerase II. Egr2 induction is evolutionarily conserved during alternative polarization of mouse and human macrophages. In the context of tissue resident macrophages, Egr2 expression is most prominent in the lung of a variety of species. Thus, EGR2 is an example of an essential and evolutionarily conserved broad acting factor, linking transient polarization signals to stable epigenomic and transcriptional changes in macrophages.

The Nuclear Receptor PPARγ Controls Progressive Macrophage Polarization as a Ligand-Insensitive Epigenomic Ratchet of Transcriptional Memory.

Macrophages polarize into distinct phenotypes in response to complex environmental cues. We found that the nuclear receptor PPARγ drove robust phenotypic changes in macrophages upon repeated stimulation with interleukin (IL)-4. The functions of PPARγ on macrophage polarization in this setting were independent of ligand binding. Ligand-insensitive PPARγ bound DNA and recruited the coactivator P300 and the architectural protein RAD21. This established a permissive chromatin environment that conferred transcriptional memory by facilitating the binding of the transcriptional regulator STAT6 and RNA polymerase II, leading to robust production of enhancer and mRNAs upon IL-4 re-stimulation. Ligand-insensitive PPARγ binding controlled the expression of an extracellular matrix remodeling-related gene network in macrophages. Expression of these genes increased during muscle regeneration in a mouse model of injury, and this increase coincided with the detection of IL-4 and PPARγ in the affected tissue. Thus, a predominantly ligand-insensitive PPARγ:RXR cistrome regulates progressive and/or reinforcing macrophage polarization.

The Transcription Factor STAT6 Mediates Direct Repression of Inflammatory Enhancers and Limits Activation of Alternatively Polarized Macrophages.

The molecular basis of signal-dependent transcriptional activation has been extensively studied in macrophage polarization, but our understanding remains limited regarding the molecular determinants of repression. Here we show that IL-4-activated STAT6 transcription factor is required for the direct transcriptional repression of a large number of genes during in vitro and in vivo alternative macrophage polarization. Repression results in decreased lineage-determining transcription factor, p300, and RNA polymerase II binding followed by reduced enhancer RNA expression, H3K27 acetylation, and chromatin accessibility. The repressor function of STAT6 is HDAC3 dependent on a subset of IL-4-repressed genes. In addition, STAT6-repressed enhancers show extensive overlap with the NF-κB p65 cistrome and exhibit decreased responsiveness to lipopolysaccharide after IL-4 stimulus on a subset of genes. As a consequence, macrophages exhibit diminished inflammasome activation, decreased IL-1ß production, and pyroptosis. Thus, the IL-4-STAT6 signaling pathway establishes an alternative polarization-specific epigenenomic signature resulting in dampened macrophage responsiveness to inflammatory stimuli.

The fission yeast ortholog of Coilin, Mug174, forms Cajal body-like nuclear condensates and is essential for cellular quiescence.

The Cajal body, a nuclear condensate, is crucial for ribonucleoprotein assembly, including small nuclear RNPs (snRNPs). While Coilin has been identified as an integral component of Cajal bodies, its exact function remains unclear. Moreover, no Coilin ortholog has been found in unicellular organisms to date. This study unveils Mug174 (Meiosis-upregulated gene 174) as the Coilin ortholog in the fission yeast Schizosaccharomyces pombe. Mug174 forms phase-separated condensates in vitro and is often associated with the nucleolus and the cleavage body in vivo. The generation of Mug174 foci relies on the trimethylguanosine (TMG) synthase Tgs1. Moreover, Mug174 interacts with Tgs1 and U snRNAs. Deletion of the mug174+ gene in S. pombe causes diverse pleiotropic phenotypes, encompassing defects in vegetative growth, meiosis, pre-mRNA splicing, TMG capping of U snRNAs, and chromosome segregation. In addition, we identified weak homology between Mug174 and human Coilin. Notably, human Coilin expressed in fission yeast colocalizes with Mug174. Critically, Mug174 is indispensable for the maintenance of and transition from cellular quiescence. These findings highlight the Coilin ortholog in fission yeast and suggest that the Cajal body is implicated in cellular quiescence, thereby preventing human diseases.

Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress.

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

Macrophage PPARγ, a Lipid Activated Transcription Factor Controls the Growth Factor GDF3 and Skeletal Muscle Regeneration.

Tissue regeneration requires inflammatory and reparatory activity of macrophages. Macrophages detect and eliminate the damaged tissue and subsequently promote regeneration. This dichotomy requires the switch of effector functions of macrophages coordinated with other cell types inside the injured tissue. The gene regulatory events supporting the sensory and effector functions of macrophages involved in tissue repair are not well understood. Here we show that the lipid activated transcription factor, PPARγ, is required for proper skeletal muscle regeneration, acting in repair macrophages. PPARγ controls the expression of the transforming growth factor-ß (TGF-ß) family member, GDF3, which in turn regulates the restoration of skeletal muscle integrity by promoting muscle progenitor cell fusion. This work establishes PPARγ as a required metabolic sensor and transcriptional regulator of repair macrophages. Moreover, this work also establishes GDF3 as a secreted extrinsic effector protein acting on myoblasts and serving as an exclusively macrophage-derived regeneration factor in tissue repair.

FuzPred: a web server for the sequence-based prediction of the context-dependent binding modes of proteins.

Proteins form complex interactions in the cellular environment to carry out their functions. They exhibit a wide range of binding modes depending on the cellular conditions, which result in a variety of ordered or disordered assemblies. To help rationalise the binding behavior of proteins, the FuzPred server predicts their sequence-based binding modes without specifying their binding partners. The binding mode defines whether the bound state is formed through a disorder-to-order transition resulting in a well-defined conformation, or through a disorder-to-disorder transition where the binding partners remain conformationally heterogeneous. To account for the context-dependent nature of the binding modes, the FuzPred method also estimates the multiplicity of binding modes, the likelihood of sampling multiple binding modes. Protein regions with a high multiplicity of binding modes may serve as regulatory sites or hot-spots for structural transitions in the assembly. To facilitate the interpretation of the predictions, protein regions with different interaction behaviors can be visualised on protein structures generated by AlphaFold. The FuzPred web server (https://fuzpred.bio.unipd.it) thus offers insights into the structural and dynamical changes of proteins upon interactions and contributes to development of structure-function relationships under a variety of cellular conditions.

Bromide Ion Impurity-Induced Reaction between Selenium(IV) and Acidic Bromate: Prototype of a Cycle with Autocatalytic Behavior.

The selenium(IV)-bromate reaction in an acidic medium using phosphoric acid/phosphate buffer was investigated by UV-vis spectroscopy monitoring the formation of bromine. In an excess of bromate, the absorbance-time curves measured at 450 nm display a characteristic sigmoidal shape having a fairly long induction period, while in the opposite case, when selenium(IV) species is used in excess, the measured data follow the rise and fall behavior. Depending on the excess of Se(IV) the final bromine-containing product is either an elementary bromine or bromide ion. Simultaneous evaluation of the measured kinetic traces clearly indicated that, surprisingly, no direct reaction takes place between the reactants. Instead of that, a trace amount of bromide ion impurity in the stock bromate solution is sufficient to drive the system via the oxidation of the bromide ion by bromate producing elementary bromine followed by the subsequent selenite-bromine reaction reestablishing the bromide ion to open a new cycle. As a result, the concentration of bromide ions increases in a sigmoidal fashion during the course of the reaction unless enough selenium(IV) species is present; hence, the overall synergetic effect observed is the autocatalytic rise of bromide ions. Therefore, the cycle mentioned above may be considered as a prototype of autocatalytic cycles. This observation prompted us to clarify the explicit difference between an autocatalytic cycle and an autocatalytic reaction.

A Multi-Omics Approach Reveals Features That Permit Robust and Widespread Regulation of IFN-Inducible Antiviral Effectors.

The antiviral state, an initial line of defense against viral infection, is established by a set of IFN-stimulated genes (ISGs) encoding antiviral effector proteins. The effector ISGs are transcriptionally regulated by type I IFNs mainly via activation of IFN-stimulated gene factor 3 (ISGF3). In this study, the regulatory elements of effector ISGs were characterized to determine the (epi)genetic features that enable their robust induction by type I IFNs in multiple cell types. We determined the location of regulatory elements, the DNA motifs, the occupancy of ISGF3 subunits (IRF9, STAT1, and STAT2) and other transcription factors, and the chromatin accessibility of 37 effector ISGs in murine dendritic cells. The IFN-stimulated response element (ISRE) and its tripartite version occurred most frequently in the regulatory elements of effector ISGs than in any other tested ISG subsets. Chromatin accessibility at their promoter regions was similar to most other ISGs but higher than at the promoters of inflammation-related cytokines, which were used as a reference gene set. Most effector ISGs (81.1%) had at least one ISGF3 binding region proximal to the transcription start site (TSS), and only a subset of effector ISGs (24.3%) was associated with three or more ISGF3 binding regions. The IRF9 signals were typically higher, and ISRE motifs were "stronger" (more similar to the canonical sequence) in TSS-proximal versus TSS-distal regulatory regions. Moreover, most TSS-proximal regulatory regions were accessible before stimulation in multiple cell types. Our results indicate that "strong" ISRE motifs and universally accessible promoter regions that permit robust, widespread induction are characteristic features of effector ISGs.

OCT4 Acts as an Integrator of Pluripotency and Signal-Induced Differentiation.

Cell type specification relies on the capacity of undifferentiated cells to properly respond to specific differentiation-inducing signals. Using genomic approaches along with loss- and gain-of-function genetic models, we identified OCT4-dependent mechanisms that provide embryonic stem cells with the means to customize their response to external cues. OCT4 binds a large set of low-accessible genomic regions. At these sites, OCT4 is required for proper enhancer and gene activation by recruiting co-regulators and RAR:RXR or ß-catenin, suggesting an unexpected collaboration between the lineage-determining transcription factor and these differentiation-initiating, signal-dependent transcription factors. As a proof of concept, we demonstrate that overexpression of OCT4 in a kidney cell line is sufficient for signal-dependent activation of otherwise unresponsive genes in these cells. Our results uncover OCT4 as an integral and necessary component of signal-regulated transcriptional processes required for tissue-specific responses.

Storage Conditions Influence the Quality of Ginger - A Stability Study Inspired by Clinical Trials.

Ginger has traditionally been used to treat and prevent nausea and vomiting; however, the results of clinical trials are ambiguous. The efficacy of ginger is attributed to gingerols and their metabolites, shogaols. Since these compounds have different pharmacological profiles, the clinical efficacy of ginger products is largely dependent on their chemical composition. The goal of our study was to examine the stability of ginger, determining the 6-gingerol contents in order to assess the effects of different storage conditions. We have performed a 6-month stability test with dry ginger rhizome samples stored in a constant climate chamber in three different storage containers (uncovered glass container, glass container sealed with rubber stopper, and plastic container). The 6-gingerol contents were measured by HPLC method. The concentration of 6-gingerol decreased in all samples. In the sealed glass container, the decrease in 6-gingerol content was significantly lower than in the unsealed glass container and in the plastic container. These results demonstrate that storage conditions have a significant impact on the quality of ginger, which may also affect efficacy.

Compatible Kinetic Model for Quantitative Description of Dual-Clock Behavior of the Complex Thiourea-Iodate Reaction.

The thiourea-iodate reaction has been investigated simultaneously by ultraviolet-visible spectroscopy and high-performance liquid chromatography (HPLC). Absorbance-time traces measured at the isosbestic point of the iodine-triiodide system have revealed a special dual-clock behavior. During the first kinetic stage of the title reaction, iodine suddenly appears only after a well-defined time lag when thiourea is totally consumed due to the rapid thiourea-iodine system giving rise to a substrate-depletive clock reaction. After this delay, iodine in the system starts to build up suddenly to a certain level, where the system remains for quite a while. During this period, hydrolysis of formamidine disulfide as well as the formamidine disulfide-iodine system along with the Dushman reaction and subsequent reactions of the intermediates governs the parallel formation and disappearance of iodine, resulting in a fairly constant absorbance. The kinetic phase mentioned above is then followed by a more slowly increasing sigmoidally shaped profile that is characteristic of autocatalysis-driven clock reactions. HPLC studies have clearly shown that the thiourea dioxide-iodate system is responsible mainly for the latter characteristics. Of course, depending on the initial concentration ratio of the reactants, the absorbance-time curve may level off or reach a maximum followed by a declining phase. With an excess of thiourea, iodine may completely disappear from the solution as a result of the thiourea dioxide-iodine reaction. In the opposite case, with an excess of iodate, the final absorbance reaches a finite value, and at the same time, iodide ion will disappear completely from the solution due to the well-known Dushman (iodide-iodate) reaction. In addition, we have also shown that in the case of the formamidine disulfide-iodine reaction, unexpectedly the triiodide ion is more reactive toward formamidine disulfide than iodine. This feature can readily be interpreted by the enhancement of the rate of formation of the transition complex containing oppositely charged reactants. A 25-step kinetic model is proposed with just 10 fitted parameters to fit the 68 kinetic traces measured in the thiourea-iodate system and the second, but slower, kinetic phase of the thiourea-iodine reaction. The comprehensive kinetic model is constituted in such a way as to remain coherent in quantitatively describing all of the most important characteristics of the formamidine disulfide-iodine, thiourea dioxide-iodine, and thiourea dioxide-iodate systems.

Widespread occurrence of the droplet state of proteins in the human proteome.

A wide range of proteins have been reported to condensate into a dense liquid phase, forming a reversible droplet state. Failure in the control of the droplet state can lead to the formation of the more stable amyloid state, which is often disease-related. These observations prompt the question of how many proteins can undergo liquid-liquid phase separation. Here, in order to address this problem, we discuss the biophysical principles underlying the droplet state of proteins by analyzing current evidence for droplet-driver and droplet-client proteins. Based on the concept that the droplet state is stabilized by the large conformational entropy associated with nonspecific side-chain interactions, we develop the FuzDrop method to predict droplet-promoting regions and proteins, which can spontaneously phase separate. We use this approach to carry out a proteome-level study to rank proteins according to their propensity to form the droplet state, spontaneously or via partner interactions. Our results lead to the conclusion that the droplet state could be, at least transiently, accessible to most proteins under conditions found in the cellular environment.

Sequence-based Prediction of the Cellular Toxicity Associated with Amyloid Aggregation within Protein Condensates.

Various neurological dysfunctions are associated with cytotoxic amyloid-containing aggregates formed through the irreversible maturation of protein condensates generated by phase separation. Here, we investigate the amino acid code for this cytotoxicity using TDP-43 deep-sequencing data. Within the droplet landscape framework, we analyze the impact of mutations in the amyloid core, aggregation hot-spot, and droplet-promoting residues on TDP-43 cytotoxicity. Our analysis suggests that TDP-43 mutations associated with low cytotoxicity moderately decrease the probability of droplet formation while increasing the probability of multimodal binding. These mutations promote both ordered and disordered binding modes, thus facilitating the conversion between the droplet and amyloid states. Based on this understanding, we develop an extension of the FuzDrop method for the sequence-based prediction of the cytotoxicity of aging condensates and test it over 20,000 TDP-43 variants. Our analysis provides insight into the amino acid code that regulates the cytotoxicity associated with the maturation of liquid-like condensates into amyloid-containing aggregates, suggesting that, at least in the case of TDP-43, mutations that promote aggregation tend to decrease cytotoxicity, while those that promote droplet formation tend to increase cytotoxicity.

Specific enhancer selection by IRF3, IRF5 and IRF9 is determined by ISRE half-sites, 5' and 3' flanking bases, collaborating transcription factors and the chromatin environment in a combinatorial fashion.

IRF3, IRF5 and IRF9 are transcription factors, which play distinct roles in the regulation of antiviral and inflammatory responses. The determinants that mediate IRF-specific enhancer selection are not fully understood. To uncover regions occupied predominantly by IRF3, IRF5 or IRF9, we performed ChIP-seq experiments in activated murine dendritic cells. The identified regions were analysed with respect to the enrichment of DNA motifs, the interferon-stimulated response element (ISRE) and ISRE half-site variants, and chromatin accessibility. Using a machine learning method, we investigated the predictability of IRF-dominance. We found that IRF5-dominant regions differed fundamentally from the IRF3- and IRF9-dominant regions: ISREs were rare, while the NFKB motif and special ISRE half-sites, such as 5'-GAGA-3' and 5'-GACA-3', were enriched. IRF3- and IRF9-dominant regions were characterized by the enriched ISRE motif and lower frequency of accessible chromatin. Enrichment analysis and the machine learning method uncovered the features that favour IRF3 or IRF9 dominancy (e.g. a tripartite form of ISRE and motifs for NF-κB for IRF3, and the GAS motif and certain ISRE variants for IRF9). This study contributes to our understanding of how IRF members, which bind overlapping sets of DNA sequences, can initiate signal-dependent responses without activating superfluous or harmful programmes.

The active enhancer network operated by liganded RXR supports angiogenic activity in macrophages.

RXR signaling is predicted to have a major impact in macrophages, but neither the biological consequence nor the genomic basis of its ligand activation is known. Comprehensive genome-wide studies were carried out to map liganded RXR-mediated transcriptional changes, active binding sites, and cistromic interactions in the context of the macrophage genome architecture. The macrophage RXR cistrome has 5200 genomic binding sites, which are not impacted by ligand. Active enhancers are characterized by PU.1 binding, an increase of enhancer RNA, and P300 recruitment. Using these features, 387 liganded RXR-bound enhancers were linked to 226 genes, which predominantly reside in CTCF/cohesin-limited functional domains. These findings were molecularly validated using chromosome conformation capture (3C) and 3C combined with sequencing (3C-seq), and we show that selected long-range enhancers communicate with promoters via stable or RXR-induced loops and that some of the enhancers interact with each other, forming an interchromosomal network. A set of angiogenic genes, including Vegfa, has liganded RXR-controlled enhancers and provides the macrophage with a novel inducible program.

Sequence-based prediction of protein binding mode landscapes.

Interactions between disordered proteins involve a wide range of changes in the structure and dynamics of the partners involved. These changes can be classified in terms of binding modes, which include disorder-to-order (DO) transitions, when proteins fold upon binding, as well as disorder-to-disorder (DD) transitions, when the conformational heterogeneity is maintained in the bound states. Furthermore, systematic studies of these interactions are revealing that proteins may exhibit different binding modes with different partners. Proteins that exhibit this context-dependent binding can be referred to as fuzzy proteins. Here we investigate amino acid code for fuzzy binding in terms of the entropy of the probability distribution of transitions towards decreasing order. We implement these entropy calculations into the FuzPred (http://protdyn-fuzpred.org) algorithm to predict the range of context-dependent binding modes of proteins from their amino acid sequences. As we illustrate through a variety of examples, this method identifies those binding sites that are sensitive to the cellular context or post-translational modifications, and may serve as regulatory points of cellular pathways.

Correct classification and identification of autocatalysis.

It is generally accepted that autocatalysis is a kinetic phenomenon, where a product of a reacting system functions as a catalyst. Consequently, the reaction proceeds faster upon adding the corresponding product to the unreacted mixture of reactants providing an unequivocal possibility of how a system may be identified either experimentally or theoretically as an autocatalysis. Once this is approved, it often results in sigmoidal concentration-time profiles, though it is neither a necessary nor sufficient prerequisite because appropriate mechanistic and parametric conditions must be met to give rise to the appearance of this kinetic feature. Several mass action type kinetic models producing sigmoidal concentration-time profiles are systematically analyzed to clarify their correct characterization and classification. This procedure has led us to refine the definitions of autocatalysis and autocatalyst. A kinetic phenomenon where a product of the overall chemical event serves as a catalyst for at least one of its subsystems or for the whole system itself is called autocatalysis. This definition makes it clear that in the case of autocatalysis, the concentration of autocatalyst necessarily increases during the course of any real overall chemical or biochemical reaction. The way it is achieved thereby provides a suitable tool to classify autocatalytic processes by their elucidated and fine mechanistic details.

Labelled regulatory elements are pervasive features of the macrophage genome and are dynamically utilized by classical and alternative polarization signals.

The concept of tissue-specific gene expression posits that lineage-determining transcription factors (LDTFs) determine the open chromatin profile of a cell via collaborative binding, providing molecular beacons to signal-dependent transcription factors (SDTFs). However, the guiding principles of LDTF binding, chromatin accessibility and enhancer activity have not yet been systematically evaluated. We sought to study these features of the macrophage genome by the combination of experimental (ChIP-seq, ATAC-seq and GRO-seq) and computational approaches. We show that Random Forest and Support Vector Regression machine learning methods can accurately predict chromatin accessibility using the binding patterns of the LDTF PU.1 and four other key TFs of macrophages (IRF8, JUNB, CEBPA and RUNX1). Any of these TFs alone were not sufficient to predict open chromatin, indicating that TF binding is widespread at closed or weakly opened chromatin regions. Analysis of the PU.1 cistrome revealed that two-thirds of PU.1 binding occurs at low accessible chromatin. We termed these sites labelled regulatory elements (LREs), which may represent a dormant state of a future enhancer and contribute to macrophage cellular plasticity. Collectively, our work demonstrates the existence of LREs occupied by various key TFs, regulating specific gene expression programs triggered by divergent macrophage polarizing stimuli.

Multiple links between 5-methylcytosine content of mRNA and translation.

BACKGROUND: 5-Methylcytosine (m5C) is a prevalent base modification in tRNA and rRNA but it also occurs more broadly in the transcriptome, including in mRNA, where it serves incompletely understood molecular functions. In pursuit of potential links of m5C with mRNA translation, we performed polysome profiling of human HeLa cell lysates and subjected RNA from resultant fractions to efficient bisulfite conversion followed by RNA sequencing (bsRNA-seq). Bioinformatic filters for rigorous site calling were devised to reduce technical noise. RESULTS: We obtained ~ 1000 candidate m5C sites in the wider transcriptome, most of which were found in mRNA. Multiple novel sites were validated by amplicon-specific bsRNA-seq in independent samples of either human HeLa, LNCaP and PrEC cells. Furthermore, RNAi-mediated depletion of either the NSUN2 or TRDMT1 m5C:RNA methyltransferases showed a clear dependence on NSUN2 for the majority of tested sites in both mRNAs and noncoding RNAs. Candidate m5C sites in mRNAs are enriched in 5'UTRs and near start codons and are embedded in a local context reminiscent of the NSUN2-dependent m5C sites found in the variable loop of tRNA. Analysing mRNA sites across the polysome profile revealed that modification levels, at bulk and for many individual sites, were inversely correlated with ribosome association. CONCLUSIONS: Our findings emphasise the major role of NSUN2 in placing the m5C mark transcriptome-wide. We further present evidence that substantiates a functional interdependence of cytosine methylation level with mRNA translation. Additionally, we identify several compelling candidate sites for future mechanistic analysis.