scholarly journals AbmR is a mycobacterial dual-function transcription factor and ribonucleoprotein with distinct DNA and RNA-binding determinants

2021 ◽  
Author(s):  
Roxie C. Girardin ◽  
Janice Pata ◽  
Xiaohong Qin ◽  
Haixin Sui ◽  
Kathleen A. McDonough
Keyword(s):  
Transcription Factor ◽  
Dna Binding ◽  
Rna Binding ◽  
Rna Stability ◽  
Dual Function ◽  
Dna And Rna ◽  
Binding Function ◽  
Rnase Digestion ◽  
Binding Determinants ◽  
Dna And Rna Binding

ABSTRACTThe bacterium Mycobacterium tuberculosis (Mtb) must adapt to myriad host-associated stressors. A recently identified transcription factor, AbmR (ATP-binding mcr11-regulator), regulates expression of an essential stress-responsive small RNA (Mcr11) and inhibits the growth of Mtb. Previously, AbmR was found to make 39S complexes of unknown function. Here we report that AbmR 39S complexes are comprised of AbmR and co-purifying RNAs and that RNA-binding inhibits AbmR’s DNA-binding function. While AbmR binds DNA and regulates gene expression in a sequence specific manner, RNA-binding is not sequence specific. Amino acid R146 is important for DNA-binding but completely dispensable for RNA-binding and 39S complex formation, establishing that the RNA- and DNA-binding functions of AbmR are distinct. RNA bound by AbmR was protected from RNase digestion, supporting an RNA modulatory function for the 39S complex. We also found that abmR is required for optimal survival during treatment with the ATP-depleting antibiotic bedaquiline, which is associated with extended RNA stability. These data establish a paradigm wherein a transcription factor assembles into large complexes to transition between mutually exclusive DNA-binding gene regulatory and RNA-binding RNA modulatory functions. Our findings indicate that AbmR is a dual-function protein that may have novel RNA regulatory roles in stress adapted Mtb.

scholarly journals Transcription factor-like 5 is a potential DNA/RNA-binding protein essential for maintaining male fertility in mice. Running title: Tcfl5 is haploinsufficient in vivo

2021 ◽  
Author(s):  
Weiya Xu ◽  
Yiyun Zhang ◽  
Dongdong Qin ◽  
Yiqian Gui ◽  
Shu Wang ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Fragile X ◽  
Specific Protein ◽  
Dual Function ◽  
Specific Cell ◽  
Chip Sequencing ◽  
Dna And Rna

Tissue-specific transcription factors often play key roles in the development of specific cell lineages. Transcription factor-like 5 (TCFL5) is a testis-specific protein that contains the basic helix-loop-helix domain, although the in vivo functions of TCFL5 remain unknown. Herein, we generated CRISPR/Cas9-mediated knockout mice to dissect the function of TCFL5 in mouse testes. Surprisingly, we found that it was difficult to generate homozygous mice with the Tcfl5 deletion since the heterozygous males (Tcfl5+/-) were infertile. We did, however, observe markedly abnormal phenotypes of spermatids and spermatozoa in the testes and epididymides of Tcfl5+/- mice. Mechanistically, we demonstrated that TCFL5 transcriptionally regulated a set of genes participating in male germ cell development, which we uncovered via RNA-sequencing and TCFL5 ChIP-sequencing. We also found that TCFL5 interacted with RNA-binding proteins (RBPs) that regulated RNA processing, and further identified the fragile X mental retardation gene 1, autosomal homolog (FXR1, a known RBP) as an interacting partner of TCFL5 that may coordinate the transition and localization of TCFL5 in the nucleus. Collectively, we herein report for the first time that Tcfl5 is haploinsufficient in vivo and hypothesize that TCFL5 may be a dual-function protein that mediates DNA and RNA to regulate spermatogenesis.

scholarly journals Transcription factor-like 5 is a potential DNA/RNA-binding protein essential for maintaining male fertility in mice

2021 ◽  
Author(s):  
Weiya Xu ◽  
Yiyun Zhang ◽  
Dongdong Qin ◽  
Yiqian Gui ◽  
Shu Wang ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Male Fertility ◽  
High Throughput Sequencing ◽  
Rna Binding ◽  
Specific Protein ◽  
Dual Function ◽  
Helix Loop Helix ◽  
Dna And Rna ◽  
First Time

Transcription factor-like 5 (TCFL5) is a testis-specific protein that contains the basic helix-loop-helix domain, but the in vivo functions of TCFL5 remain unknown. Herein, we generated CRISPR/Cas9-mediated knockout mice to dissect the function of TCFL5 in mouse testes. Surprisingly, we found that it was difficult to generate homozygous mice with the Tcfl5 deletion since the heterozygous males (Tcfl5+/-) were infertile. We did; however, observe markedly abnormal phenotypes of spermatids and spermatozoa in the testes and epididymides of Tcfl5+/- mice. Mechanistically, we demonstrated that TCFL5 transcriptionally and post-transcriptionally regulated a set of genes participating in male germ cell development via TCFL5 ChIP-DNA and eCLIP-RNA high-throughput sequencing. We also identified a known RBP, FXR1 as an interacting partner of TCFL5 that may coordinate the transition and localization of TCFL5 in the nucleus. Collectively, we herein report for the first time that Tcfl5 is haploinsufficient in vivo and acts as a dual-function protein that mediates DNA and RNA to regulate spermatogenesis.

Alteration of DNA and RNA Binding Activity of Human Telomere Binding Proteins Occurs during Cellular Senescence

1995 ◽  
Vol 218 (1) ◽  
pp. 241-247 ◽  
Author(s):  
Karen Hubbard ◽  
Sridevi N. Dhanaraj ◽  
Khalid A. Sethi ◽  
Janice Rhodes ◽  
Jeffrey Wilusz ◽  
...  
Keyword(s):  
Cellular Senescence ◽  
Binding Proteins ◽  
Rna Binding ◽  
Binding Activity ◽  
Dna And Rna ◽  
Human Telomere ◽  
Dna And Rna Binding

scholarly journals Borrelia burgdorferiSpoVG DNA- and RNA-Binding Protein Modulates the Physiology of the Lyme Disease Spirochete

2018 ◽  
Vol 200 (12) ◽  
Author(s):  
Christina R. Savage ◽  
Brandon L. Jutras ◽  
Aaron Bestor ◽  
Kit Tilly ◽  
Patricia A. Rosa ◽  
...  
Keyword(s):  
Lyme Disease ◽  
Rna Binding ◽  
Culture Conditions ◽  
Altered Expression ◽  
Content Type ◽  
Protein Levels ◽  
Dna And Rna ◽  
Physiological Alterations ◽  
Bacterial Replication ◽  
Dna And Rna Binding

ABSTRACTThe SpoVG protein ofBorrelia burgdorferi, the Lyme disease spirochete, binds to specific sites of DNA and RNA. The bacterium regulates transcription ofspoVGduring the natural tick-mammal infectious cycle and in response to some changes in culture conditions. Bacterial levels ofspoVGmRNA and SpoVG protein did not necessarily correlate, suggesting that posttranscriptional mechanisms also control protein levels. Consistent with this, SpoVG binds to its own mRNA, adjacent to the ribosome-binding site. SpoVG also binds to two DNA sites in theglpFKDoperon and to two RNA sites inglpFKDmRNA; that operon encodes genes necessary for glycerol catabolism and is important for colonization in ticks. In addition, spirochetes engineered to dysregulatespoVGexhibited physiological alterations.IMPORTANCEB. burgdorferipersists in nature by cycling between ticks and vertebrates. Little is known about how the bacterium senses and adapts to each niche of the cycle. The present studies indicate thatB. burgdorfericontrols production of SpoVG and that this protein binds to specific sites of DNA and RNA in the genome and transcriptome, respectively. Altered expression ofspoVGexerts effects on bacterial replication and other aspects of the spirochete's physiology.

scholarly journals Analyzing the Surface Structure of the Binding Domain on DNA and RNA Binding Proteins

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 30042-30049
Author(s):  
Wei Wang ◽  
Keliang Li ◽  
Hehe Lv ◽  
Hongjun Zhang ◽  
Shiguang Zhang ◽  
...  
Keyword(s):  
Surface Structure ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Binding Domain ◽  
Dna And Rna ◽  
Dna And Rna Binding

DNA and RNA binding studies on a novel bromo-bridged dimeric copper(II) complex stabilized from a Schiff base ligand

2019 ◽  
Vol 72 (22-24) ◽  
pp. 3625-3644 ◽  
Author(s):  
Naba Kr Mandal ◽  
Bhargab Guhathakurta ◽  
Pritha Basu ◽  
Ankur Bikash Pradhan ◽  
Chandra Shekhar Purohit ◽  
...  
Keyword(s):  
Schiff Base ◽  
Schiff Base Ligand ◽  
Rna Binding ◽  
Binding Studies ◽  
Dna And Rna ◽  
Dna And Rna Binding

scholarly journals Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities

2019 ◽  
Vol 35 (14) ◽  
pp. i269-i277 ◽  
Author(s):  
Ameni Trabelsi ◽  
Mohamed Chaabane ◽  
Asa Ben-Hur
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Rna Binding ◽  
Binding Specificity ◽  
Training Data ◽  
Supplementary Information ◽  
Recurrent Networks ◽  
Dna And Rna ◽  
Learning Architectures ◽  
Dna And Rna Binding

Abstract Motivation Deep learning architectures have recently demonstrated their power in predicting DNA- and RNA-binding specificity. Existing methods fall into three classes: Some are based on convolutional neural networks (CNNs), others use recurrent neural networks (RNNs) and others rely on hybrid architectures combining CNNs and RNNs. However, based on existing studies the relative merit of the various architectures remains unclear. Results In this study we present a systematic exploration of deep learning architectures for predicting DNA- and RNA-binding specificity. For this purpose, we present deepRAM, an end-to-end deep learning tool that provides an implementation of a wide selection of architectures; its fully automatic model selection procedure allows us to perform a fair and unbiased comparison of deep learning architectures. We find that deeper more complex architectures provide a clear advantage with sufficient training data, and that hybrid CNN/RNN architectures outperform other methods in terms of accuracy. Our work provides guidelines that can assist the practitioner in choosing an appropriate network architecture, and provides insight on the difference between the models learned by convolutional and recurrent networks. In particular, we find that although recurrent networks improve model accuracy, this comes at the expense of a loss in the interpretability of the features learned by the model. Availability and implementation The source code for deepRAM is available at https://github.com/MedChaabane/deepRAM. Supplementary information Supplementary data are available at Bioinformatics online.

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