Integrated multi-omic data analysis and validation with yeast model show oxidative phosphorylation modulates protein aggregation in amyotrophic lateral sclerosis

Synthesis, computational docking and molecular dynamics studies of a new class of spiroquinoxalinopyrrolidine embedded chromanone hybrids as potent anti-cholinesterase agents

Novel structurally intriguing heterocycles embedded with spiropyrrolidine, quinoxaline and chromanone units were synthesized in good yields using a [Bmim]Br accelerated multicomponent reaction strategy. The key step of the reaction is 1,3-dipolar cycloaddition involving highly functionalized dipolarophile, viz. 3-benzylidenechroman-4-one, to afford spiroquinoxalinopyrrolidine embedded chromanone hybrid heterocycles. The formation of spiro products occurs via two C-C, two N-C and one C-N bonds possessing four adjoining stereogenic centers, two of which are spiro carbons. The newly synthesized spiro compounds showed potent acetylcholinesterase and butyrylcholinesterase inhibitory activities. Moreover, compounds with fluorine displayed the highest AChE (3.20 ± 0.16 μM) and BChE (18.14 ± 0.06 μM) inhibitory activities. Further, docking studies, followed by all-atom molecular dynamics, showed results that are consistent with in vitro experimental findings. Although docking scores for the synthesized derivatives were higher than those of the standard drug, MD MMPBSA results showed better binding of synthesized derivatives (-93.5 ± 11.9 kcal mol-1) compared to the standard drug galantamine (-66.2 ± 12.3 kcal mol-1) for AChE but exhibited similar values (-98.1 ± 11.2 and -97.9 ± 11.5 kcal mol-1) for BChE. These differences observed in drug binding with AChE/BChE are consistent with RMSD, RMSF, LIG plots, and FEL structural analysis. Taken together, these derivatives could be potential candidates as inhibitors of AChE and BChE.

Abnormal protein post-translational modifications induces aggregation and abnormal deposition of protein, mediating neurodegenerative diseases

Protein post-translational modifications (PPTMs) refer to a series of chemical modifications that occur after the synthesis of protein. Proteins undergo different modifications such as phosphorylation, acetylation, ubiquitination, and so on. These modifications can alter the protein's structure, function, and interaction, thereby regulating its biological activity. In neurodegenerative diseases, several proteins undergo abnormal post-translational modifications, which leads to aggregation and abnormal deposition of protein, thus resulting in neuronal death and related diseases. For example, the main pathological features of Alzheimer's disease are the aggregation of beta-amyloid protein and abnormal phosphorylation of tau protein. The abnormal ubiquitination and loss of α-synuclein are related to the onset of Parkinson's disease. Other neurodegenerative diseases such as Huntington's disease, amyotrophic lateral sclerosis, and so on are also connected with abnormal PPTMs. Therefore, studying the abnormal PPTMs in neurodegenerative diseases is critical for understanding the mechanism of these diseases and the development of significant therapeutic strategies. This work reviews the implications of PPTMs in neurodegenerative diseases and discusses the relevant therapeutic strategies.

Single-Cell RNA Sequencing Analysis of Microglia Dissected the Energy Metabolism and Revealed Potential Biomarkers in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a common neurodegenerative disease, accompanied by the gradual loss of motor neuron, even life-threatening. However, the pathogenesis, early diagnosis, and effective strategies of ALS are not yet completely understood. In this study, the function of differentially expressed genes (DEGs) in non-neuronal cells of the primary motor cortex of ALS patients (DATA1), the brainstem of SOD1 mutant ALS mice (DATA2), and the whole blood tissue of ALS patients (DATA3) were explored. The results showed that the functions of DEGs in non-neuronal cells were mainly related to energy metabolism (such as oxidative phosphorylation) and protein synthesis. In non-neuronal cells, six upregulated DEGs (HSPA8, SOD1, CALM1, CALM2, NEFL, COX6C) and three downregulated DEGs (SNRNP70, HSPA1A, HSPA1B) might be key factors in regulating ALS. Microglia played a key role in the development of ALS. The expression of SOD1 and TUBA4A in microglia in DATA1 was significantly increased. The integration analysis of DEGs in DATA1 and DATA2 showed that SOD1 and CALM1 might be potential biomarkers. The integration analysis of DEGs in DATA1 and DATA3 showed that CALM2 and HSPA1A might be potential biomarkers. Cell interaction showed that the interaction between microglia and other cells was reduced in high oxidative phosphorylation states, which might be a risk factor in ALS. Our research provided evidence for the pathogenesis, early diagnosis, and potential targeted therapy for ALS.

Saccharomyces cerevisiae as a Model for Studying Human Neurodegenerative Disorders: Viral Capsid Protein Expression

In this article, we briefly describe human neurodegenerative diseases (NDs) and the experimental models used to study them. The main focus is the yeast Saccharomyces cerevisiae as an experimental model used to study neurodegenerative processes. We review recent experimental data on the aggregation of human neurodegenerative disease-related proteins in yeast cells. In addition, we describe the results of studies that were designed to investigate the molecular mechanisms that underlie the aggregation of reporter proteins. The advantages and disadvantages of the experimental approaches that are currently used to study the formation of protein aggregates are described. Special attention is given to the similarity between aggregates that form as a result of protein misfolding and viral factories-special structural formations in which viral particles are formed inside virus-infected cells. A separate part of the review is devoted to our previously published study on the formation of aggregates upon expression of the insect densovirus capsid protein in yeast cells. Based on the reviewed results of studies on NDs and related protein aggregation, as well as viral protein aggregation, a new experimental model system for the study of human NDs is proposed. The core of the proposed system is a comparative transcriptomic analysis of changes in signaling pathways during the expression of viral capsid proteins in yeast cells.

Identification of major hub genes involved in high-fat diet-induced obese visceral adipose tissue based on bioinformatics approach

High-fat diet (HFD) can cause obesity, inducing dysregulation of the visceral adipose tissue (VAT). This study aimed to explore potential biological pathways and hub genes involved in obese VAT, and for that, bioinformatic analysis of multiple datasets was performed. The expression profiles (GSE30247, GSE167311 and GSE79434) were downloaded from Gene Expression Omnibus. Overlapping differentially expressed genes (ODEGs) between normal diet and HFD groups in GSE30247 and GSE167311 were selected to run protein-protein interaction network, GO and KEGG analysis. The hub genes in ODEGs were screened by Cytoscape software and further verified in GSE79434 and obese mouse model. A total of 747 ODEGs (599 up-regulated and 148 down-regulated) were screened, and the GO and KEGG analysis showed that the up-regulated ODEGs were significantly enriched in inflammatory response and extracellular matrix receptor interaction pathways. On the other hand, the down-regulated ODEGs were involved in metabolic pathways; however, there were no significant KEGG pathways. Furthermore, six hub genes, Mki67, Rac2, Itgb2, Emr1, Tyrobp and Csf1r were acquired. These pathways and genes were verified in GSE79434 and VAT of obese mice. This study revealed that HFD induced VAT expansion, inflammation and fibrosis, and the hub genes could be used as therapeutic biomarkers in obesity.

Metabolic deregulation associated with aging modulates protein aggregation in the yeast model of Huntington's disease

Huntington's disease is associated with increased CAG repeat resulting in an expanded polyglutamine tract in the protein Huntingtin (HTT) leading to its aggregation resulting in neurodegeneration. Previous studies have shown that N-terminal HTT with 46Q aggregated in the stationary phase but not the logarithmic phase in the yeast model of HD. We carried out a metabolomic analysis of logarithmic and stationary phase yeast model of HD expressing different polyQ lengths attached to N-terminal HTT tagged with enhanced green fluorescent protein (EGFP). The results show significant changes in the metabolic profile and deregulated pathways in stationary phase cells compared to logarithmic phase cells. Comparison of metabolic pathways obtained from logarithmic phase 46Q versus 25Q with those obtained for presymptomatic HD patients from our previous study and drosophila model of HD showed considerable overlap. The arginine biosynthesis pathway emerged as one of the key pathways that is common in stationary phase yeast compared to logarithmic phase and HD patients. Treatment of yeast with arginine led to a significant decrease, while transfer to arginine drop-out media led to a significant increase in the size of protein aggregates in both logarithmic and stationary phase yeast model of HD. Knockout of arginine transporters in the endoplasmic reticulum and vacuole led to a significant decrease in mutant HTT aggregation. Overall our results highlight arginine as a critical metabolite that modulates the aggregation of mutant HTT and disease progression in HD.Communicated by Ramaswamy H. Sarma.

Saccharomyces cerevisiae as a research tool for RNA-mediated human disease

The budding yeast, Saccharomyces cerevisiae, has been used for decades as a powerful genetic tool to study a broad spectrum of biological topics. With its ease of use, economic utility, well-studied genome, and a highly conserved proteome across eukaryotes, it has become one of the most used model organisms. Due to these advantages, it has been used to study an array of complex human diseases. From broad, complex pathological conditions such as aging and neurodegenerative disease to newer uses such as SARS-CoV-2, yeast continues to offer new insights into how cellular processes are affected by disease and how affected pathways might be targeted in therapeutic settings. At the same time, the roles of RNA and RNA-based processes have become increasingly prominent in the pathology of many of these same human diseases, and yeast has been utilized to investigate these mechanisms, from aberrant RNA-binding proteins in amyotrophic lateral sclerosis to translation regulation in cancer. Here we review some of the important insights that yeast models have yielded into the molecular pathology of complex, RNA-based human diseases. This article is categorized under: RNA in Disease and Development > RNA in Disease.

Integrated clinical and metabolomic analysis of dengue infection shows molecular signatures associated with host-pathogen interaction in different phases of the disease

PURPOSE

Dengue is a mosquito vector-borne disease caused by the dengue virus, which affects 125 million people globally. The disease causes considerable morbidity. The disease, based on symptoms, is classified into three characteristic phases, which can further lead to complications in the second phase. Molecular signatures that are associated with the three phases have not been well characterized. We performed an integrated clinical and metabolomic analysis of our patient cohort and compared it with omics data from the literature to identify signatures unique to the different phases.

METHODS

The dengue patients are recruited by clinicians after standard-of-care diagnostic tests and evaluation of symptoms. Blood from the patients was collected. NS1 antigen, IgM, IgG antibodies, and cytokines in serum were analyzed using ELISA. Targeted metabolomics was performed using LC-MS triple quad. The results were compared with analyzed transcriptomic data from the GEO database and metabolomic data sets from the literature.

RESULTS

The dengue patients displayed characteristic features of the disease, including elevated NS1 levels. TNF-α was found to be elevated in all three phases compared to healthy controls. The metabolic pathways were found to be deregulated compared to healthy controls only in phases I and II of dengue patients. The pathways represent viral replication and host response mediated pathways. The major pathways include nucleotide metabolism of various amino acids and fatty acids, biotin, etc. CONCLUSION: The results show elevated TNF-α and metabolites that are characteristic of viral infection and host response. IL10 and IFN-γ were not significant, consistent with the absence of any complications.

Integrated Omic Analysis Delineates Pathways Modulating Toxic TDP-43 Protein Aggregates in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a multi-systemic, incurable, amyloid disease affecting the motor neurons, resulting in the death of patients. The disease is either sporadic or familial with SOD1, C9orf72, FUS, and TDP-43 constituting the majority of familial ALS. Multi-omics studies on patients and model systems like mice and yeast have helped in understanding the association of various signaling and metabolic pathways with the disease. The yeast model system has played a pivotal role in elucidating the gene amyloid interactions. We carried out an integrated transcriptomic and metabolomic analysis of the TDP-43 expressing yeast model to elucidate deregulated pathways associated with the disease. The analysis shows the deregulation of the TCA cycle, single carbon metabolism, glutathione metabolism, and fatty acid metabolism. Transcriptomic analysis of GEO datasets of TDP-43 expressing motor neurons from mice models of ALS and ALS patients shows considerable overlap with experimental results. Furthermore, a yeast model was used to validate the obtained results using metabolite addition and gene knock-out experiments. Taken together, our result shows a potential role for the TCA cycle, cellular redox pathway, NAD metabolism, and fatty acid metabolism in disease. Supplementation of reduced glutathione, nicotinate, and the keto diet might help to manage the disease.

Integrated multi-omics analysis of Alzheimer's disease shows molecular signatures associated with disease progression and potential therapeutic targets

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid plaques implicated in neuronal death. Genetics, age, and sex are the risk factors attributed to AD. Though omics studies have helped to identify pathways associated with AD, an integrated systems analysis with the available data could help to understand mechanisms, potential biomarkers, and therapeutic targets. Analysis of transcriptomic data sets from the GEO database, and proteomic and metabolomic data sets from literature was performed to identify deregulated pathways and commonality analysis identified overlapping pathways among the data sets. The deregulated pathways included those of neurotransmitter synapses, oxidative stress, inflammation, vitamins, complement, and coagulation pathways. Cell type analysis of GEO data sets showed microglia, endothelial, myeloid, and lymphoid cells are affected. Microglia are associated with inflammation and pruning of synapses with implications for memory and cognition. Analysis of the protein-cofactor network of B2, B6, and pantothenate shows metabolic pathways modulated by these vitamins which overlap with the deregulated pathways from the multi-omics analysis. Overall, the integrated analysis identified the molecular signature associated with AD. Treatment with anti-oxidants, B2, B6, and pantothenate in genetically susceptible individuals in the pre-symptomatic stage might help in better management of the disease.

Vitamin B6, B12 and folate modulate deregulated pathways and protein aggregation in yeast model of Huntington disease

Huntington's disease (HD) is an incurable and progressive neurodegenerative disease affecting the basal ganglia of the brain. HD is caused due to expansion of the polyglutamine tract in the protein Huntingtin resulting in aggregates. The increased PolyQ length results in aggregation of protein Huntingtin leading to neuronal cell death. Vitamin B6, B12 and folate are deficient in many neurodegenerative diseases. We performed an integrated analysis of transcriptomic, metabolomic and cofactor-protein network of vitamin B6, B12 and folate was performed. Our results show considerable overlap of pathways modulated by Vitamin B6, B12 and folate with those obtained from transcriptomic and metabolomic data of HD patients and model systems. Further, in yeast model of HD we showed treatment of B6, B12 or folate either alone or in combination showed impaired aggregate formation. Transcriptomic analysis of yeast model treated with B6, B12 and folate showed upregulation of pathways like ubiquitin mediated proteolysis, autophagy, peroxisome, fatty acid, lipid and nitrogen metabolism. Metabolomic analysis of yeast model shows deregulation of pathways like aminoacyl-tRNA biosynthesis, metabolism of various amino acids, nitrogen metabolism and glutathione metabolism. Integrated transcriptomic and metabolomic analysis of yeast model showed concordance in the pathways obtained. Knockout of Peroxisomal (PXP1 and PEX7) and Autophagy (ATG5) genes in yeast increased aggregates which is mitigated by vitamin B6, B12 and folate treatment. Taken together our results show a role for Vitamin B6, B12 and folate mediated modulation of pathways important for preventing protein aggregation with potential implications for HD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03525-y.

Structural systems biology approach delineate the functional implications of SNPs in exon junction complex interaction network

In eukaryotes, transcripts that carry premature termination codons (PTC) leading to truncated proteins are degraded by the Nonsense Mediated Decay (NMD) machinery. Missense and nonsense Single Nucleotide Polymorphisms (SNPs) in proteins belonging to Exon junction complex (EJC) and up-frameshift protein (UPF) will compromise NMD leading to the accumulation of truncated proteins in various diseases. The EJC and UPF which are involved in NMD is a good model system to study the effect of SNPs at a system level. Despite the availability of crystal structures, computational tools, and data on mutational and deletion studies, with functional implications, an integrated effort to understand the impact of SNPs at the systems level is lacking. To study the functional consequences of missense SNPs, sequence-based techniques like SIFT and PolyPhen which classify SNPs as deleterious or non-deleterious and structure-based methods like FoldX which calculate the Delta Delta G, (ddGs, ∆∆G) are used. Using FoldX, the ddG for mutations with experimentally validated functional effects is calculated and compared with those calculated for SNPs in the same protein-protein interaction interface. Further, a model is conceived to explain the functional implications of SNPs based on the effects observed for known mutants. The results are visualized in a network format. The effects of nonsense mutations are discerned by comparing with deletion mutation studies and loss of interaction in the crystal structure. The present work not only integrates genomics, proteomics, and classical genetics with 'Structural Biology' but also helps to integrate it into a 'systems-level functional network'.Communicated by Ramaswamy H. Sarma.

Systems biology approach delineates critical pathways associated with disease progression in rheumatoid arthritis

Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease leading to inflammation, cartilage cell death, synoviocyte proliferation, and increased and impaired differentiation of osteoclasts and osteoblasts leading to joint erosions and deformities. Transcriptomics, proteomics, and metabolomics datasets were analyzed to identify the critical pathways that drive the RA pathophysiology. Single nucleotide polymorphisms (SNPs) associated with RA were analyzed for the functional implications, clinical outcomes, and blood parameters later validated by literature. SNPs associated with RA were grouped into pathways that drive the immune response and cytokine production. Further gene set enrichment analysis (GSEA) was performed on gene expression omnibus (GEO) data sets of peripheral blood mononuclear cells (PBMCs), synovial macrophages, and synovial biopsies from RA patients showed enrichment of Th1, Th2, Th17 differentiation, viral and bacterial infections, metabolic signalling and immunological pathways with potential implications for RA. The proteomics data analysis presented pathways with genes involved in immunological signaling and metabolic pathways, including vitamin B12 and folate metabolism. Metabolomics datasets analysis showed significant pathways like amino-acyl tRNA biosynthesis, metabolism of amino acids (arginine, alanine aspartate, glutamate, glutamine, phenylalanine, and tryptophan), and nucleotide metabolism. Furthermore, our commonality analysis of multi-omics datasets identified common pathways with potential implications for joint remodeling in RA. Disease-modifying anti-rheumatic drugs (DMARDs) and biologics treatments were found to modulate many of the pathways that were deregulated in RA. Overall, our analysis identified molecular signatures associated with the observed symptoms, joint erosions, potential biomarkers, and therapeutic targets in RA. Communicated by Ramaswamy H. Sarma.