Signal Sequence Research Articles

Streamlining heterologous expression of top carbonic anhydrases in Escherichia coli: bioinformatic and experimental approaches

BackgroundCarbonic anhydrase (CA) enzymes facilitate the reversible hydration of CO2 to bicarbonate ions and protons. Identifying efficient and robust CAs and expressing them in model host cells, such as Escherichia coli, enables more efficient engineering of these enzymes for industrial CO2 capture. However, expression of CAs in E. coli is challenging due to the possible formation of insoluble protein aggregates, or inclusion bodies. This makes the production of soluble and active CA protein a prerequisite for downstream applications.ResultsIn this study, we streamlined the process of CA expression by selecting seven top CA candidates and used two bioinformatic tools to predict their solubility for expression in E. coli. The prediction results place these enzymes in two categories: low and high solubility. Our expression of high solubility score CAs (namely CA5-SspCA, CA6-SazCAtrunc, CA7-PabCA and CA8-PhoCA) led to significantly higher protein yields (5 to 75 mg purified protein per liter) in flask cultures, indicating a strong correlation between the solubility prediction score and protein expression yields. Furthermore, phylogenetic tree analysis demonstrated CA class-specific clustering patterns for protein solubility and production yields. Unexpectedly, we also found that the unique N-terminal, 11-amino acid segment found after the signal sequence (not present in its homologs), was essential for CA6-SazCA activity.ConclusionsOverall, this work demonstrated that protein solubility prediction, phylogenetic tree analysis, and experimental validation are potent tools for identifying top CA candidates and then producing soluble, active forms of these enzymes in E. coli. The comprehensive approaches we report here should be extendable to the expression of other heterogeneous proteins in E. coli.

On The Determination of a Convex Sequence of Signals by Absolute Sum of Factors of Trigonometric Series

Five theorems on the identification of a convex sequence of signals via the absolute sum of elements of trigonometric series are established in this study. Several well-known results are specific cases of these theorems. When the function has bounded variation, it also addresses several special circumstances of fuzzy numbers.

Development and characterization of a multimeric recombinant protein using the spike protein receptor binding domain as an antigen to induce SARS-CoV-2 neutralization.

SARS-CoV2 virus, responsible for the COVID-19 pandemic, has four structural proteins and 16 nonstructural proteins. S-protein is one of the structural proteins exposed on the virus surface and is the main target for producing neutralizing antibodies and vaccines. The S-protein forms a trimer that can bind the angiotensin-converting enzyme 2 (ACE2) through its receptor binding domain (RBD) for cell entry. The goal of this study was to express in HEK293 cells a new RBD recombinant protein in a constitutive and stable manner in order to use it as an alternative immunogen and diagnostic tool for COVID-19. The protein was designed to contain an immunoglobulin signal sequence, an explanded C-terminal section of the RBD, a region responsible for the bacteriophage T4 trimerization inducer, and six histidines in the pCDNA-3.1 plasmid. Following transformation, the cells were selected with geneticin-G418 and purified from serum-fre culture supernatants using Ni2+-agarand size exclusion chromatography. The protein was structurally identified by cross-linking and circular dichroism experiments, and utilized to immunize mice in conjuction with AS03 or alum adjuvants. The mice sera were examined for antibody recognition, receptor-binding inhibition, and virus neutralization, while spleens were evaluated for γ-interferon production in the presence of RBD. The protein released in the culture supernatant of cells, and exhibited a molecular mass of 135 kDa with a secondary structure like the monomeric and trimeric RBD. After purification, it formed a multimeric structure comprising trimers and hexamers, which were able to bind the ACE2 receptor. It generated high antibody titers in mice when combined with AS03 adjuvant (up to 1:50,000). The sera were capable of inhibiting binding of biotin-labeled ACE2 to the virus S1 subunit and could neutralize the entry of the Wuhan virus strain into cells at dilutions up to 1:2000. It produced specific IFN-γ producing cells in immunized mouse splenocytes. Our data describe a new RBD containing protein, forming trimers and hexamers, which are able to induce a protective humoral and cellular response against SARS-CoV2. These results add a new arsenal to combat COVID-19, as an alternative immunogen or antigen for diagnosis.

Identification and Characterization of High-Molecular-Weight Proteins Secreted by Plasmodiophora brassicae That Suppress Plant Immunity.

Plasmodiophora brassicae is an obligate intracellular parasitic protist that causes clubroot disease on cruciferous plants. So far, some low-molecular-weight secreted proteins from P. brassicae have been reported to play an important role in plant immunity regulation, but there are few reports on its high-molecular-weight secreted proteins. In this study, 35 putative high-molecular-weight secreted proteins (>300 amino acids) of P. brassicae (PbHMWSP) genes that are highly expressed during the infection stage were identified using transcriptome analysis and bioinformatics prediction. Then, the secretory activity of 30 putative PbHMWSPs was confirmed using the yeast signal sequence trap system. Furthermore, the genes encoding 24 PbHMWSPs were successfully cloned and their functions in plant immunity were studied. The results showed that ten PbHMWSPs could inhibit flg22-induced reactive oxygen burst, and ten PbHMWSPs significantly inhibited the expression of the SA signaling pathway marker gene PR1a. In addition, nine PbHMWSPs could inhibit the expression of a marker gene of the JA signaling pathway. Therefore, a total of 19 of the 24 tested PbHMWSPs played roles in suppressing the immune response of plants. Of these, it is worth noting that PbHMWSP34 can inhibit the expression of JA, ET, and several SA signaling pathway marker genes. The present study is the first to report the function of the high-molecular-weight secreted proteins of P. brassicae in plant immunity, which will enrich the theory of interaction mechanisms between the pathogens and plants.

Parameter‐free predictive control with flexibility in power adjustment for grid‐connected converters under unbalanced grid conditions

AbstractThis paper introduces a novel finite control set predictive direct power control method for grid‐connected converters without cost function evaluations. Unlike conventional predictive direct power control, since the proposed method does not use the model parameters, their uncertainties do not cause prediction error and inappropriate voltage vector selection. The method employs a new form of voltage vector selection based on the slopes of active and reactive powers. The slopes are predicted in a manner with a low sensitivity to sampling noise, without updating a look‐up table, and recursive methods. Hence, there are no stagnation and convergence issues. Also, the proposed method avoids startup problems caused by data‐lacking due to directly regulating the active and reactive power by a switching logic. Flexible power oscillations control with balanced sinusoidal grid currents without any signal sequence extraction can also be achieved under this method in unbalanced grid conditions. The proposed method is assessed by both simulation and experimental studies, and its performance is compared with existing robust combined and model predictive control methods. The outcomes highlight the influence of the proposed approach and establish its superiority over the other considered methods.

Highly efficient and specific regulation of gene expression using enhanced CRISPR-Cas12f system.

The recently developed CRISPR activator (CRISPRa) system uses a CRISPR-Cas effector-based transcriptional activator to effectively control the expression of target genes without causing DNA damage. However, existing CRISPRa systems based on Cas9/Cas12a necessitate improvement in terms of efficacy and accuracy due to limitations associated with the CRISPR-Cas module itself. To overcome these limitations and effectively and accurately regulate gene expression, we developed an efficient CRISPRa system based on the small CRISPR-Cas effector Candidatus Woesearchaeota Cas12f (CWCas12f). By engineering the CRISPR-Cas module, linking activation domains, and using various combinations of linkers and nuclear localization signal sequences, the optimized eCWCas12f-VPR system enabled effective and target-specific regulation of gene expression compared with that using the existing CRISPRa system. The eCWCas12f-VPR system developed in this study has substantial potential for controlling the transcription of endogenous genes in living organisms and serves as a foundation for future gene therapy and biological research.

Adaptive Signal Modulation Evolved by the Inherent Nonlinearity of Phase-Change Quantum-Dot String.

To simulate a topological neural network handling weak signals via stochastic resonance (SR), it is necessary to introduce an inherent nonlinearity into nanoscale devices. We use the self-assembly method to successfully fabricate a phase-change quantum-dot string (PCQDS) crossing Pd/Nb:AlNO/AlNO/Nb:AlNO/Pd multilayer. The inherent nonlinearity of phase change couples with electron tunneling so that PCQDS responds to a long signal sequence in a modulated output style, in which the pulse pattern evolves to that enveloped by two sets of periodic wave characterized by neural action potential. We establish an SR mode consisting of several two-state systems in which dissipative tunneling is coupled to environment. Size oscillations owing to NbO QDs adaptively adjust barriers and wells, such that tunneling can be periodically modulated by either asymmetric energy or local temperature. When the external periodic signals are applied, the system first follows the forcing frequency. Subsequently, certain PCQDs oscillate independently and consecutively to produce complicated frequency and amplitude modulations.

A monoclonal antibody that recognizes a unique 13-residue epitope in the cytoplasmic tail of HLA-E

The Class I MHC molecule (MHC-I) HLA-E presents peptides that are derived from the signal sequences, either those of other MHC-I products, or of viral type I membrane glycoproteins. Monoclonal antibodies with proven specificity for HLA-E, and with no cross-reactions with other MHC-I products, have yet to be described. To obtain anti-HLA-E-specific antibodies suitable for a range of applications, we generated monoclonal antibodies against a unique feature of HLA-E: its cytoplasmic tail. We created an immunogen by performing an enzymatically catalyzed transpeptidation reaction to obtain a fusion of the cytoplasmic tail of HLA-E with a nanobody that recognizes murine Class II MHC (MHC-II) products. We obtained a mouse monoclonal antibody that recognizes a 13-residue stretch in the HLA-E cytoplasmic tail. We cloned the genes that encode this antibody in expression vectors to place an LPETG sortase recognition motif at the C-terminus of the heavy and light chains. This arrangement allows the site-specific installation of fluorophores or biotin at these C-termini. The resulting immunoglobulin preparations, labeled with 4 equivalents of a fluorescent or biotinylated payload of choice, can then be used for direct immunofluorescence or detection of the tag by fluorescence or by streptavidin-based methods. We also show that the 13-residue sequence can serve as an epitope tag, independent of the site of its placement within a protein’s sequence. The antibody can be used diagnostically to stain for HLA-E on patient tumor samples, it can be used as an antibody-epitope tag for extracellular proteins, and it enables research into the unique role of the cytoplasmic tail of HLA-E.

A temporal prediction model for ship maneuvering motion based on multi-head attention mechanism

In real-world maritime conditions, accurately predicting ship maneuvering motion over ultrashort periods can enhance the development of more precise vessel control algorithms. This study proposes a prediction model for ship maneuvering that utilizes a multi-head attention mechanism. To form a basis for this data-driven approach, we gathered training data from turning and zigzag tests of a ship conducted in natural sea environments. The model's predictive capability is assessed by comparing two strategies over a fixed 30-time-step forecast horizon: iterative multi-step forecasting (IMS) and direct multi-step forecasting (DMS). Notably, the model employs distinct attention layers to examine the temporal relationships among various motion variables across the three degrees of freedom in the output. Moreover, it uses separate attention layers to explore the distinct time response traits of the input motion states and control signals. The results demonstrate that different motion state variables display unique temporal correlations under different signal sequences, and the proposed network architecture effectively captures these temporal response traits.

Competitive Binding of Viral Nuclear Localization Signal Peptide and Inhibitor Ligands to Importin-α Nuclear Transport Protein.

Venezuelan equine encephalitis virus (VEEV) is a highly virulent pathogen whose nuclear localization signal (NLS) sequence from capsid protein binds to the host importin-α transport protein and blocks nuclear import. We studied the molecular mechanisms by which two small ligands, termed I1 and I2, interfere with the binding of VEEV's NLS peptide to importin-α protein. To this end, we performed all-atom replica exchange molecular dynamics simulations probing the competitive binding of the VEEV coreNLS peptide and I1 or I2 ligand to the importin-α major NLS binding site. As a reference, we used our previous simulations, which examined noncompetitive binding of the coreNLS peptide or the inhibitors to importin-α. We found that both inhibitors completely abrogate the native binding of the coreNLS peptide, forcing it to adopt a manifold of nonnative loosely bound poses within the importin-α major NLS binding site. Both inhibitors primarily destabilize the native coreNLS binding by masking its amino acids rather than competing with it for binding to importin-α. Because I2, in contrast to I1, binds off-site localizing on the edge of the major NLS binding site, it inhibits fewer coreNLS native binding interactions than I1. Structural analysis is supported by computations of the free energies of the coreNLS peptide binding to importin-α with or without competition from the inhibitors. Specifically, both inhibitors reduce the free energy gain from coreNLS binding, with I1 causing significantly larger loss than I2. To test our simulations, we performed AlphaScreen experiments measuring IC50 values for both inhibitors. Consistent with in silico results, the IC50 value for I1 was found to be lower than that for I2. We hypothesize that the inhibitory action of I1 and I2 ligands might be specific to the NLS from VEEV's capsid protein.

Detection of phase modulation disorder when processing a sequence of ultra-wideband quasi-radio signals against a background of white Gaussian noise

In conditions of a complex electromagnetic environment in communication and data transmission systems, a change in the type of modulation occurs when one or more signal parameters change abruptly, therefore the task of determining the type of signal modulation can be reduced to the task of detecting a disorder, that is, detecting the fact of a change in the type of modulation of the signal and estimation of the disorder time. The purpose of the work is to synthesize an algorithm for detecting phase modulation disorder when processing a sequence of ultra-wideband quasi-radio signals with unknown amplitude and initial phase against a background of white Gaussian noise and to analyze the effectiveness of the resulting algorithm based on the results of statistical modeling. The work synthesizes an algorithm for detecting a phase modulation disorder of a received sequence of ultra-wideband quasi-radio signals against a background of white Gaussian noise. To analyze the effectiveness of the resulting algorithm, statistical modeling of algorithm for detecting a phase modulation disorder is carried out. The dependences of the probability of detection of a disorder on the signal-to-noise ratio and the length of the sequence of received signals at a fixed moment of disorder are obtained. A comparison of the detection characteristics of phase modulation disorder of ultra-wideband quasi-radio signals and narrowband radio signals is made. It is shown that when a low-order phase modulation disorder is detected, the required values of the probability of detection are achieved at low signal-to-noise ratios, while with an increase in the modulation order and the use of its modifications, the efficiency indicators of the algorithm will deteriorate. The introduction of algorithms for detecting a disorder in radio engineering applications will allow optimizing synchronization algorithms and adaptation to interference conditions with a concomitant change in the type of modulation, as well as reducing the amount of transmitted service information in telecommunication systems.

A production platform for disulfide-bonded peptides in the periplasm of Escherichia coli

BackgroundRecombinant peptide production in Escherichia coli provides a sustainable alternative to environmentally harmful and size-limited chemical synthesis. However, in-vivo production of disulfide-bonded peptides at high yields remains challenging, due to degradation by host proteases/peptidases and the necessity of translocation into the periplasmic space for disulfide bond formation.ResultsIn this study, we established an expression system for efficient and soluble production of disulfide-bonded peptides in the periplasm of E. coli. We chose model peptides with varying complexity (size, structure, number of disulfide bonds), namely parathyroid hormone 1–84, somatostatin 1–28, plectasin, and bovine pancreatic trypsin inhibitor (aprotinin). All peptides were expressed without and with the N-terminal, low molecular weight CASPON™ tag (4.1 kDa), with the expression cassette being integrated into the host genome. During BioLector™ cultivations at microliter scale, we found that most of our model peptides can only be sufficiently expressed in combination with the CASPON™ tag, otherwise expression was only weak or undetectable on SDS-PAGE. Undesired degradation by host proteases/peptidases was evident even with the CASPON™ tag. Therefore, we investigated whether degradation happened before or after translocation by expressing the peptides in combination with either a co- or post-translational signal sequence. Our results suggest that degradation predominantly happened after the translocation, as degradation fragments appeared to be identical independent of the signal sequence, and expression was not enhanced with the co-translational signal sequence. Lastly, we expressed all CASPON™-tagged peptides in two industry-relevant host strains during C-limited fed-batch cultivations in bioreactors. We found that the process performance was highly dependent on the peptide-host-combination. The titers that were reached varied between 0.6–2.6 g L−1, and exceeded previously published data in E. coli. Moreover, all peptides were shown by mass spectrometry to be expressed to completion, including full formation of disulfide bonds.ConclusionIn this work, we demonstrated the potential of the CASPON™ technology as a highly efficient platform for the production of soluble peptides in the periplasm of E. coli. The titers we show here are unprecedented whenever parathyroid hormone, somatostatin, plectasin or bovine pancreatic trypsin inhibitor were produced in E. coli, thus making our proposed upstream platform favorable over previously published approaches and chemical synthesis.

Automatic Recognition of Auditory Brainstem Response Waveforms Using a Deep Learning-Based Framework.

Recognition of auditory brainstem response (ABR) waveforms may be challenging, particularly for older individuals or those with hearing loss. This study aimed to investigate deep learning frameworks to improve the automatic recognition of ABR waveforms in participants with varying ages and hearing levels. The research used a descriptive study design to collect and analyze pure tone audiometry and ABR data from 100 participants. The research was conducted at a tertiary academic medical center, specifically at the Clinical Audiology Center of Tsinghua Chang Gung Hospital (Beijing, China). Data from 100 participants were collected and categorized into four groups based on age and hearing level. Features from both time-domain and frequency-domain ABR signals were extracted and combined with demographic factors, such as age, sex, pure-tone thresholds, stimulus intensity, and original signal sequences to generate feature vectors. An enhanced Wide&Deep model was utilized, incorporating the Light-multi-layer perceptron (MLP) model to train the recognition of ABR waveforms. The recognition accuracy (ACC) of each model was calculated for the overall data set and each group. The ACC rates of the Light-MLP model were 97.8%, 97.2%, 93.8%, and 92.0% for Groups 1 to 4, respectively, with a weighted average ACC rate of 95.4%. For the Wide&Deep model, the ACC rates were 93.4%, 90.8%, 92.0%, and 88.3% for Groups 1 to 4, respectively, with a weighted average ACC rate of 91.0%. Both the Light-MLP model and the Wide&Deep model demonstrated excellent ACC in automatic recognition of ABR waveforms across participants with diverse ages and hearing levels. While the Wide&Deep model's performance was slightly poorer than that of the Light-MLP model, particularly due to the limited sample size, it is anticipated that with an expanded data set, the performance of Wide&Deep model may be further improved.

An Informer-Based Signal Sequence Detector for Mobile Molecular Communication

An Informer-Based Signal Sequence Detector for Mobile Molecular Communication

Serotype-Specific Regulation of Dengue Virus NS5 Protein Subcellular Localization.

Dengue virus (DENV) nonstructural protein 5 (NS5), consisting of methyltransferase and RNA-dependent RNA polymerase (RdRp) domains, is critical for viral RNA synthesis within endoplasmic reticulum-derived replication complexes in the cytoplasm. However, a significant proportion of NS5 is localized to the nucleus of infected cells for DENV2, 3, and 4, whereas DENV1 NS5 is localized diffusely in the cytoplasm. We still have an incomplete understanding of how the DENV NS5 subcellular localization is regulated. Within NS5, two putative nuclear localization signal (NLS) sequences have been identified: NLSCentral residing in the palm of the RdRp domain as well as the recently discovered NLSC-term residing in the flexible region at the C-terminal of the RdRp domain. We have previously shown that DENV2 NS5 nuclear localization can be significantly reduced by single-point mutations to the NLSC-term. Here, we present biochemical, virological, and structural data demonstrating that the relative importance of either NLS in NS5 nuclear localization is unique to each of the four DENV serotypes. DENV1 NS5's cytoplasmic localization appears to be due to a functionally weak interaction between its NLSCentral and importin-α (IMPα), while DENV2 NS5 is almost exclusively nuclear through its NLSC-term's strong interaction with IMPα. Both NLSs of DENV3 NS5 appear to contribute to directing its nuclear localization. Lastly, in the case of DENV4, the regulation of its NS5 nuclear localization remains an enigma but appears to be associated with its NLSC-term.

Molecular basis for differential Igk versus Igh V(D)J joining mechanisms

In developing B cells, V(D)J recombination assembles exons encoding IgH and Igκ variable regions from hundreds of gene segments clustered across Igh and Igk loci. V, D and J gene segments are flanked by conserved recombination signal sequences (RSSs) that target RAG endonuclease1. RAG orchestrates Igh V(D)J recombination upon capturing a JH-RSS within the JH-RSS-based recombination centre1–3 (RC). JH-RSS orientation programmes RAG to scan upstream D- and VH-containing chromatin that is presented in a linear manner by cohesin-mediated loop extrusion4–7. During Igh scanning, RAG robustly utilizes only D-RSSs or VH-RSSs in convergent (deletional) orientation with JH-RSSs4–7. However, for Vκ-to-Jκ joining, RAG utilizes Vκ-RSSs from deletional- and inversional-oriented clusters8, inconsistent with linear scanning2. Here we characterize the Vκ-to-Jκ joining mechanism. Igk undergoes robust primary and secondary rearrangements9,10, which confounds scanning assays. We therefore engineered cells to undergo only primary Vκ-to-Jκ rearrangements and found that RAG scanning from the primary Jκ-RC terminates just 8 kb upstream within the CTCF-site-based Sis element11. Whereas Sis and the Jκ-RC barely interacted with the Vκ locus, the CTCF-site-based Cer element12 4 kb upstream of Sis interacted with various loop extrusion impediments across the locus. Similar to VH locus inversion7, DJH inversion abrogated VH-to-DJH joining; yet Vκ locus or Jκ inversion allowed robust Vκ-to-Jκ joining. Together, these experiments implicated loop extrusion in bringing Vκ segments near Cer for short-range diffusion-mediated capture by RC-based RAG. To identify key mechanistic elements for diffusional V(D)J recombination in Igk versus Igh, we assayed Vκ-to-JH and D-to-Jκ rearrangements in hybrid Igh–Igk loci generated by targeted chromosomal translocations, and pinpointed remarkably strong Vκ and Jκ RSSs. Indeed, RSS replacements in hybrid or normal Igk and Igh loci confirmed the ability of Igk-RSSs to promote robust diffusional joining compared with Igh-RSSs. We propose that Igk evolved strong RSSs to mediate diffusional Vκ-to-Jκ joining, whereas Igh evolved weaker RSSs requisite for modulating VH joining by RAG-scanning impediments.

Efficient signal sequence of mRNA vaccines enhances the antigen expression to expand the immune protection against viral infection

The signal sequence played a crucial role in the efficacy of mRNA vaccines against virus pandemic by influencing antigen translation. However, limited research had been conducted to compare and analyze the specific mechanisms involved. In this study, a novel approach was introduced by substituting the signal sequence of the mRNA antigen to enhance its immune response. Computational simulations demonstrated that various signal peptides differed in their binding capacities with the signal recognition particle (SRP) 54 M subunit, which positively correlated with antigen translation efficiency. Our data revealed that the signal sequences of tPA and IL-6-modified receptor binding domain (RBD) mRNA vaccines sequentially led to higher antigen expression and elicited more robust humoral and cellular immune protection against the SARS-CoV-2 compared to the original signal sequence. By highlighting the importance of the signal sequence, this research provided a foundational and safe approach for ongoing modifications in signal sequence-antigen design, aiming to optimize the efficacy of mRNA vaccines.

SEMG biceps and triceps effort signals classification using 1D-CNN convolution

In this paper, we present a system for acquiring and classifying surface physiological muscles signals (sEMG) for the biceps and triceps muscles during movement or work, as normal or aggressive effort in order to control and command the aid prostheses to intervene only during aggressive efforts. Thus, the main objective of our work is to developing and improving the performance of the hand prostheses for daily life tasks for elderly persons or for persons who have hand muscle failure. Our contribution consists of detecting and classifying physiological signals of biceps and triceps muscles hand as normal and aggressive efforts, for that we proposed a technique based on a 1D Convolutional Neural Network (CNN-1D) using the Wavelet Scattering Transform as the sEMG feature extraction technique. Our methodology is carried out in two steps: the first step is crucial to build a database for deep learning network for sEMG signals classification based on fifty-five volunteers spanning various ages and genders. The second step achieves the sEMG signals effort classification as normal or aggressive efforts based on the classification network produced based on sEMG signal sequences treated by the WST. The obtained results for the training and validation sets indicate perfect performance of the proposed technique, with an accuracy, precision, sensitivity, and specificity of 100% for the training process, and 99.3%, 98.6%, 100% and 98.7% for the accuracy, precision, sensibility and specificity respectively. It is important to note that while perfect metrics on the training and the test set might suggest excellent model learning.

Conserved Cis-Acting Range Extender Element Mediates Extreme Long-Range Enhancer Activity in Mammals.

While most mammalian enhancers regulate their cognate promoters over moderate distances of tens of kilobases (kb), some enhancers act over distances in the megabase range. The sequence features enabling such extreme-distance enhancer-promoter interactions remain elusive. Here, we used in vivo enhancer replacement experiments in mice to show that short- and medium-range enhancers cannot initiate gene expression at extreme-distance range. We uncover a novel conserved cis-acting element, Range EXtender (REX), that confers extreme-distance regulatory activity and is located next to a long-range enhancer of Sall1. The REX element itself has no endogenous enhancer activity. However, addition of the REX to other short- and mid-range enhancers substantially increases their genomic interaction range. In the most extreme example observed, addition of the REX increased the range of an enhancer by an order of magnitude, from its native 71kb to 840kb. The REX element contains highly conserved [C/T]AATTA homeodomain motifs. These motifs are enriched around long-range limb enhancers genome-wide, including the ZRS, a benchmark long-range limb enhancer of Shh. Mutating the [C/T]AATTA motifs within the ZRS does not affect its limb-specific enhancer activity at short range, but selectively abolishes its long-range activity, resulting in severe limb reduction in knock-in mice. In summary, we identify a sequence signature globally associated with long-range enhancer-promoter interactions and describe a prototypical REX element that is necessary and sufficient to confer extreme-distance gene activation by remote enhancers.

Superoxide Dismutase Premodulates Oxidative Stress in Plastids for Protection of Tobacco Plants from Cold Damage Ultrastructure Damage

ROS-dependent induction of oxidative damage can be used as a trigger initiating genetically determined non-specific protection in plant cells and tissues. Plants are potentially able to withstand various specific (toxic, osmotic) factors of abiotic effects, but do not have sufficient or specific sensitivity to form an adequate effective response. In this work, we demonstrate one of the possible approaches for successful cold acclimation through the formation of effective protection of photosynthetic structures due to the insertion of the heterologous FeSOD gene into the tobacco genome under the control of the constitutive promoter and equipped with a signal sequence targeting the protein to plastid. The increased enzymatic activity of superoxide dismutase in the plastid compartment of transgenic tobacco plants enables them to tolerate the oxidative factor of environmental stresses scavenging ROS. On the other hand, the cost of such resistance is quite high and, when grown under normal conditions, disturbs the arrangement of the intrachloroplastic subdomains leading to the modification of stromal thylakoids, probably significantly affecting the photosynthesis processes that regulate the efficiency of photosystem II. This is partially compensated for by the fact that, at the same time, under normal conditions, the production of peroxide induces the activation of ROS detoxification enzymes. However, a violation of a number of processes, such as the metabolism of accumulation, and utilization and transportation of sugars and starch, is significantly altered, which leads to a shift in metabolic chains. The expected step for further improvement of the applied technology could be both the use of inducible promoters in the expression cassette, and the addition of other genes encoding for hydrogen peroxide-scavenging enzymes in the genetic construct that are downstream in the metabolic chain.