Effects of nucleoid-associated proteins on bacterial chromosome structure and gene expression

2010 ◽  
Vol 13 (6) ◽  
pp. 773-780 ◽  
Author(s):  
Douglas F Browning ◽  
David C Grainger ◽  
Stephen JW Busby
2017 ◽  
Vol 114 (46) ◽  
pp. 12225-12230 ◽  
Author(s):  
Zhong Qian ◽  
Victor B. Zhurkin ◽  
Sankar Adhya

Bacterial chromosome (nucleoid) conformation dictates faithful regulation of gene transcription. The conformation is condition-dependent and is guided by several nucleoid-associated proteins (NAPs) and at least one nucleoid-associated noncoding RNA, naRNA4. Here we investigated the molecular mechanism of how naRNA4 and the major NAP, HU, acting together organize the chromosome structure by establishing multiple DNA–DNA contacts (DNA condensation). We demonstrate that naRNA4 uniquely acts by forming complexes that may not involve long stretches of DNA–RNA hybrid. Also, uncommonly, HU, a chromosome-associated protein that is essential in the DNA–RNA interactions, is not present in the final complex. Thus, HU plays a catalytic (chaperone) role in the naRNA4-mediated DNA condensation process.


2020 ◽  
Vol 27 (20) ◽  
pp. 3330-3345
Author(s):  
Ana G. Rodríguez-Hernández ◽  
Rafael Vazquez-Duhalt ◽  
Alejandro Huerta-Saquero

Nanomaterials have become part of our daily lives, particularly nanoparticles contained in food, water, cosmetics, additives and textiles. Nanoparticles interact with organisms at the cellular level. The cell membrane is the first protective barrier against the potential toxic effect of nanoparticles. This first contact, including the interaction between the cell membranes -and associated proteins- and the nanoparticles is critically reviewed here. Nanoparticles, depending on their toxicity, can cause cellular physiology alterations, such as a disruption in cell signaling or changes in gene expression and they can trigger immune responses and even apoptosis. Additionally, the fundamental thermodynamics behind the nanoparticle-membrane and nanoparticle-proteins-membrane interactions are discussed. The analysis is intended to increase our insight into the mechanisms involved in these interactions. Finally, consequences are reviewed and discussed.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanlei Yue ◽  
Ze Jiang ◽  
Enoch Sapey ◽  
Tingting Wu ◽  
Shi Sun ◽  
...  

Abstract Background In soybean, some circadian clock genes have been identified as loci for maturity traits. However, the effects of these genes on soybean circadian rhythmicity and their impacts on maturity are unclear. Results We used two geographically, phenotypically and genetically distinct cultivars, conventional juvenile Zhonghuang 24 (with functional J/GmELF3a, a homolog of the circadian clock indispensable component EARLY FLOWERING 3) and long juvenile Huaxia 3 (with dysfunctional j/Gmelf3a) to dissect the soybean circadian clock with time-series transcriptomal RNA-Seq analysis of unifoliate leaves on a day scale. The results showed that several known circadian clock components, including RVE1, GI, LUX and TOC1, phase differently in soybean than in Arabidopsis, demonstrating that the soybean circadian clock is obviously different from the canonical model in Arabidopsis. In contrast to the observation that ELF3 dysfunction results in clock arrhythmia in Arabidopsis, the circadian clock is conserved in soybean regardless of the functional status of J/GmELF3a. Soybean exhibits a circadian rhythmicity in both gene expression and alternative splicing. Genes can be grouped into six clusters, C1-C6, with different expression profiles. Many more genes are grouped into the night clusters (C4-C6) than in the day cluster (C2), showing that night is essential for gene expression and regulation. Moreover, soybean chromosomes are activated with a circadian rhythmicity, indicating that high-order chromosome structure might impact circadian rhythmicity. Interestingly, night time points were clustered in one group, while day time points were separated into two groups, morning and afternoon, demonstrating that morning and afternoon are representative of different environments for soybean growth and development. However, no genes were consistently differentially expressed over different time-points, indicating that it is necessary to perform a circadian rhythmicity analysis to more thoroughly dissect the function of a gene. Moreover, the analysis of the circadian rhythmicity of the GmFT family showed that GmELF3a might phase- and amplitude-modulate the GmFT family to regulate the juvenility and maturity traits of soybean. Conclusions These results and the resultant RNA-seq data should be helpful in understanding the soybean circadian clock and elucidating the connection between the circadian clock and soybean maturity.


2018 ◽  
Vol 29 (22) ◽  
pp. 2616-2621 ◽  
Author(s):  
Barbara J. Meyer

Determining sex is a binary developmental decision that most metazoans must make. Like many organisms, Caenorhabditis elegans specifies sex (XO male or XX hermaphrodite) by tallying X-chromosome number. We dissected this precise counting mechanism to determine how tiny differences in concentrations of signals are translated into dramatically different developmental fates. Determining sex by counting chromosomes solved one problem but created another—an imbalance in X gene products. We found that nematodes compensate for the difference in X-chromosome dose between sexes by reducing transcription from both hermaphrodite X chromosomes. In a surprising feat of evolution, X-chromosome regulation is functionally related to a structural problem of all mitotic and meiotic chromosomes: achieving ordered compaction of chromosomes before segregation. We showed the dosage compensation complex is a condensin complex that imposes a specific three-­dimensional architecture onto hermaphrodite X chromosomes. It also triggers enrichment of histone modification H4K20me1. We discovered the machinery and mechanism underlying H4K20me1 enrichment and demonstrated its pivotal role in regulating higher-order X-chromosome structure and gene expression.


2021 ◽  
Vol 12 ◽  
Author(s):  
Shuai Liu ◽  
Keji Zhao

The code of life is not only encrypted in the sequence of DNA but also in the way it is organized into chromosomes. Chromosome architecture is gradually being recognized as an important player in regulating cell activities (e.g., controlling spatiotemporal gene expression). In the past decade, the toolbox for elucidating genome structure has been expanding, providing an opportunity to explore this under charted territory. In this review, we will introduce the recent advancements in approaches for mapping spatial organization of the genome, emphasizing applications of these techniques to immune cells, and trying to bridge chromosome structure with immune cell activities.


2018 ◽  
Author(s):  
Kalyani B. Karunakaran ◽  
Srilakshmi Chaparala ◽  
Madhavi K. Ganapathiraju

AbstractFrom the schizophrenia drug-target interactome,1we studied the drugs that targeted multiple proteins in the interactome, or those that target proteins with many targets, or those that target novel (computationally predicted) interactors of schizophrenia associated proteins. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the selected drugs using the NextBio software suite, and shortlisted those that had a negative correlation with gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes which were differentially expressed on drug treatment, and had an anti-correlation with gene expression in schizophrenia, were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had pathophysiological overlap with schizophrenia. Drugs that are structurally similar to the shortlisted drugs, or targeted the same genes as these drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis may help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development, facing a high failure rate.


2021 ◽  
Author(s):  
Sara Artigas-Jerónimo ◽  
Margarita Villar ◽  
Agustín Estrada-Peña ◽  
Adrián Velázquez-Campoy ◽  
Pilar Alberdi ◽  
...  

The Akirin family of transcription cofactors are involved throughout the metazoan in the regulation of different biological processes such as immunity, interdigital regression, muscle and neural development. Akirin do not have catalytic or DNA-binding capability and exert its regulatory function primarily through interacting proteins such as transcription factors, chromatin remodelers, and RNA-associated proteins. In this study, we focused on the human Akirin2 regulome and interactome in neutrophil-like model human Caucasian promyelocytic leukemia HL60 cells. Our hypothesis is that metazoan evolved to have Akirin2 functional complements and different Akirin2-mediated mechanisms for the regulation of gene expression. To address this hypothesis, experiments were conducted using transcriptomics, proteomics and systems biology approaches in akirin2 knockdown and wildtype HL60 cells to characterize Akirin2 gene/protein targets, functional complements and to provide evidence of different mechanisms that may be involved in Akirin2-mediated regulation of gene expression. The results revealed Akirin2 gene/protein targets in multiple biological processes with higher representation of immunity and identified immune response genes as candidate Akirin2 functional complements. In addition to linking chromatin remodelers with transcriptional activation, Akirin2 also interacts with histone H3.1 for regulation of gene expression.


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