Nuclear prelamin a recognition factor and iron dysregulation in multiple sclerosis

Classification of subtypes and identification of dysregulated genes in sepsis

Background

Sepsis is a clinical syndrome with high mortality. Subtype identification in sepsis is meaningful for improving the diagnosis and treatment of patients. The purpose of this research was to identify subtypes of sepsis using RNA-seq datasets and further explore key genes that were deregulated during the development of sepsis.

Methods

The datasets GSE95233 and GSE13904 were obtained from the Gene Expression Omnibus database. Differential analysis of the gene expression matrix was performed between sepsis patients and healthy controls. Intersection analysis of differentially expressed genes was applied to identify common differentially expressed genes for enrichment analysis and gene set variation analysis. Obvious differential pathways between sepsis patients and healthy controls were identified, as were developmental stages during sepsis. Then, key dysregulated genes were revealed by short time-series analysis and the least absolute shrinkage and selection operator model. In addition, the MCPcounter package was used to assess infiltrating immunocytes. Finally, the dysregulated genes identified were verified using 69 clinical samples.

Results

A total of 898 common differentially expressed genes were obtained, which were chiefly related to increased metabolic responses and decreased immune responses. The two differential pathways (angiogenesis and myc targets v2) were screened on the basis of gene set variation analysis scores. Four subgroups were identified according to median expression of angiogenesis and myc target v2 genes: normal, myc target v2, mixed-quiescent, and angiogenesis. The genes CHPT1, CPEB4, DNAJC3, MAFG, NARF, SNX3, S100A9, S100A12, and METTL9 were recognized as being progressively dysregulated in sepsis. Furthermore, most types of immune cells showed low infiltration in sepsis patients and had a significant correlation with the key genes. Importantly, all nine key genes were highly expressed in sepsis patients.

Conclusion

This study revealed novel insight into sepsis subtypes and identified nine dysregulated genes associated with immune status in the development of sepsis. This study provides potential molecular targets for the diagnosis and treatment of sepsis.

NARF is a hypoxia-induced coactivator for OCT4-mediated breast cancer stem cell specification

Hypoxia is a key characteristic of the breast cancer microenvironment that promotes expression of the transcriptional activator hypoxia-inducible factor 1 (HIF-1) and is associated with poor patient outcome. HIF-1 increases the expression or activity of stem cell pluripotency factors, which control breast cancer stem cell (BCSC) specification and are required for cancer metastasis. Here, we identify nuclear prelamin A recognition factor (NARF) as a hypoxia-inducible, HIF-1 target gene in human breast cancer cells. NARF functions as an essential coactivator by recruiting the histone demethylase KDM6A to OCT4 bound to genes encoding the pluripotency factors NANOG, KLF4, and SOX2, leading to demethylation of histone H3 trimethylated at lysine-27 (H3K27me3), thereby increasing the expression of NANOG, KLF4, and SOX2, which, together with OCT4, mediate BCSC specification. Knockdown of NARF significantly decreased the BCSC population in vitro and markedly impaired tumor initiation capacity and lung metastasis in orthotopic mouse models.

Cerebral Iron Deposition in Neurodegeneration

Disruption of cerebral iron regulation appears to have a role in aging and in the pathogenesis of various neurodegenerative disorders. Possible unfavorable impacts of iron accumulation include reactive oxygen species generation, induction of ferroptosis, and acceleration of inflammatory changes. Whole-brain iron-sensitive magnetic resonance imaging (MRI) techniques allow the examination of macroscopic patterns of brain iron deposits in vivo, while modern analytical methods ex vivo enable the determination of metal-specific content inside individual cell-types, sometimes also within specific cellular compartments. The present review summarizes the whole brain, cellular, and subcellular patterns of iron accumulation in neurodegenerative diseases of genetic and sporadic origin. We also provide an update on mechanisms, biomarkers, and effects of brain iron accumulation in these disorders, focusing on recent publications. In Parkinson’s disease, Friedreich’s disease, and several disorders within the neurodegeneration with brain iron accumulation group, there is a focal siderosis, typically in regions with the most pronounced neuropathological changes. The second group of disorders including multiple sclerosis, Alzheimer’s disease, and amyotrophic lateral sclerosis shows iron accumulation in the globus pallidus, caudate, and putamen, and in specific cortical regions. Yet, other disorders such as aceruloplasminemia, neuroferritinopathy, or Wilson disease manifest with diffuse iron accumulation in the deep gray matter in a pattern comparable to or even more extensive than that observed during normal aging. On the microscopic level, brain iron deposits are present mostly in dystrophic microglia variably accompanied by iron-laden macrophages and in astrocytes, implicating a role of inflammatory changes and blood–brain barrier disturbance in iron accumulation. Options and potential benefits of iron reducing strategies in neurodegeneration are discussed. Future research investigating whether genetic predispositions play a role in brain Fe accumulation is necessary. If confirmed, the prevention of further brain Fe uptake in individuals at risk may be key for preventing neurodegenerative disorders.

Fantastic [FeFe]-Hydrogenases and Where to Find Them

[FeFe]-hydrogenases are complex metalloenzymes, key to microbial energy metabolism in numerous organisms. During anaerobic metabolism, they dissipate excess reducing equivalents by using protons from water as terminal electron acceptors, leading to hydrogen production. This reaction is coupled to reoxidation of specific redox partners [ferredoxins, NAD(P)H or cytochrome c3], that can be used either individually or simultaneously (via flavin-based electron bifurcation). [FeFe]-hydrogenases also serve additional physiological functions such as H2 uptake (oxidation), H2 sensing, and CO2 fixation. This broad functional spectrum is enabled by a modular architecture and vast genetic diversity, which is not fully explored and understood. This Mini Review summarises recent advancements in identifying and characterising novel [FeFe]-hydrogenases, which has led to expanding our understanding of their multiple roles in metabolism and functional mechanisms. For example, while numerous well-known [FeFe]-hydrogenases are irreversibly damaged by oxygen, some newly discovered enzymes display intrinsic tolerance. These findings demonstrate that oxygen sensitivity varies between different [FeFe]-hydrogenases: in some cases, protection requires the presence of exogenous compounds such as carbon monoxide or sulphide, while in other cases it is a spontaneous built-in mechanism that relies on a reversible conformational change. Overall, it emerges that additional research is needed to characterise new [FeFe]-hydrogenases as this will reveal further details on the physiology and mechanisms of these enzymes that will enable potential impactful applications.

Revealing potential diagnostic gene biomarkers of septic shock based on machine learning analysis

Background

Sepsis is an inflammatory response caused by infection with pathogenic microorganisms. The body shock caused by it is called septic shock. In view of this, we aimed to identify potential diagnostic gene biomarkers of the disease.

Material and methods

Firstly, mRNAs expression data sets of septic shock were retrieved and downloaded from the GEO (Gene Expression Omnibus) database for differential expression analysis. Functional enrichment analysis was then used to identify the biological function of DEmRNAs (differentially expressed mRNAs). Machine learning analysis was used to determine the diagnostic gene biomarkers for septic shock. Thirdly, RT-PCR (real-time polymerase chain reaction) verification was performed. Lastly, GSE65682 data set was utilized to further perform diagnostic and prognostic analysis of identified superlative diagnostic gene biomarkers.

Results

A total of 843 DEmRNAs, including 458 up-regulated and 385 down-regulated DEmRNAs were obtained in septic shock. 15 superlative diagnostic gene biomarkers (such as RAB13, KIF1B, CLEC5A, FCER1A, CACNA2D3, DUSP3, HMGN3, MGST1 and ARHGEF18) for septic shock were identified by machine learning analysis. RF (random forests), SVM (support vector machine) and DT (decision tree) models were used to construct classification models. The accuracy of the DT, SVM and RF models were very high. Interestingly, the RF model had the highest accuracy. It is worth mentioning that ARHGEF18 and FCER1A were related to survival. CACNA2D3 and DUSP3 participated in MAPK signaling pathway to regulate septic shock.

Conclusion

Identified diagnostic gene biomarkers may be helpful in the diagnosis and therapy of patients with septic shock.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07056-4.

A Novel LINS1 Truncating Mutation in Autosomal Recessive Nonsyndromic Intellectual Disability

The large majority of cases with intellectual disability are syndromic (i.e. occur with other well-defined clinical phenotypes) and have been studied extensively. Autosomal recessive nonsyndromic intellectual disability is a group of genetically heterogeneous disorders for which a number of potentially causative genes have been identified although the molecular basis of most of them remains unexplored. Here, we report the clinical characteristics and genetic findings of a family with two male siblings affected with autosomal recessive nonsyndromic intellectual disability. Whole exome sequencing was carried out on two affected male siblings and unaffected parents. A potentially pathogenic variant identified in this study was confirmed by Sanger sequencing to be inherited in an autosomal recessive fashion. We identified a novel nonsense mutation (p.Gln368Ter) in the LINS1 gene which leads to loss of 389 amino acids in the C-terminus of the encoded protein. The truncation mutation causes a complete loss of LINES_C domain along with loss of three known phosphorylation sites and a known ubiquitylation site in addition to other evolutionarily conserved regions of LINS1. LINS1 has been reported to cause MRT27 (mental retardation, autosomal recessive 27), a rare autosomal recessive nonsyndromic intellectual disability, with limited characterization of the phenotype. Identification of a potentially pathogenic truncating mutation in LINS1 in two profoundly intellectually impaired patients also confirms its role in cognition.