Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants.

SARS-CoV-2 infection hijacks signaling pathways and induces protein-protein interactions between human and viral proteins. Human genetic variation may impact SARS-CoV-2 infection and COVID-19 pathology; however, the genetic variation in these signaling networks remains uncharacterized. Here, we studied human missense single nucleotide variants (SNVs) altering phosphorylation sites modulated by SARS-CoV-2 infection, using machine learning to identify amino acid substitutions altering kinase-bound sequence motifs. We found 2,033 infrequent phosphorylation-associated SNVs (pSNVs) that are enriched in sequence motif alterations, potentially reflecting the evolution of signaling networks regulating host defenses. Proteins with pSNVs are involved in viral life cycle and host responses, including RNA splicing, interferon response (TRIM28), and glucose homeostasis (TBC1D4) with potential associations with COVID-19 comorbidities. pSNVs disrupt CDK and MAPK substrate motifs and replace these with motifs of Tank Binding Kinase 1 (TBK1) involved in innate immune responses, indicating consistent rewiring of signaling networks. Several pSNVs associate with severe COVID-19 and hospitalization (STARD13, ARFGEF2). Our analysis highlights potential genetic factors contributing to inter-individual variation of SARS-CoV-2 infection and COVID-19 and suggests leads for mechanistic and translational studies.

Transcriptome profile analysis reveals putative molecular mechanisms of 5-aminolevulinic acid toxicity.

5-aminolevulinic acid (5-ALA) is the first precursor of the heme biosynthesis pathway, accumulated in acute intermittent porphyria (AIP), an inherited metabolic disease characterized by porphobilinogen deaminase deficiency. An increased incidence of hepatocellular carcinoma (HCC) has been reported as a long-term manifestation in symptomatic AIP patients. 5-ALA is an α-aminoketone prone to oxidation, yielding reactive oxygen species and 4,5-dioxovaleric acid. A high concentration of 5-ALA presents deleterious pro-oxidant potential. It can induce apoptosis, DNA damage, mitochondrial dysfunction, and altered expression of carcinogenesis-related proteins. Several hypotheses of the increased risk of HCC rely on the harmful effect of elevated 5-ALA in the liver of AIP patients, which could promote a pro-carcinogenic environment. We investigated the global transcriptional changes and perturbed molecular pathways in HepG2 cells following exposure to 5-ALA 25 mM for 2 h and 24 h using DNA microarray. Distinct transcriptome profiles were observed. 5-ALA '25 mM-2h' upregulated 10 genes associated with oxidative stress response and carcinogenesis. Enrichment analysis of differentially expressed genes by KEGG, Reactome, MetaCore™, and Gene Ontology, showed that 5-ALA '25 mM-24h' enriched pathways involved in drug detoxification, oxidative stress, DNA damage, cell death/survival, cell cycle, and mitochondria dysfunction corroborating the pro-oxidant properties of 5-ALA. Furthermore, our results disclosed other possible processes such as senescence, immune responses, endoplasmic reticulum stress, and also some putative effectors, such as sequestosome, osteopontin, and lon peptidase 1. This study provided additional knowledge about molecular mechanisms of 5-ALA toxicity which is essential to a deeper understanding of AIP and HCC pathophysiology. Furthermore, our findings can contribute to improving the efficacy of current therapies and the development of novel biomarkers and targets for diagnosis, prognosis, and therapeutic strategies for AHP/AIP and associated HCC.

Transcriptomic changes in liver transplant recipients with non-alcoholic steatohepatitis indicate dysregulation of wound healing.

Background: Non-alcoholic steatohepatitis (NASH) has become a leading indication for liver transplantation. However, it often recurs in the graft and can also arise de novo in individuals transplanted for other indications. Post-transplant NASH (PT-NASH) is more aggressive and leads to accelerated fibrosis. The mechanistic basis of PT-NASH has not yet been defined and no specific therapeutic strategies are currently available. Methods: Here, we profiled the transcriptomes of livers with PT-NASH from liver transplant recipients to identify dysregulated genes, pathways, and molecular interaction networks. Results: Transcriptomic changes in the PI3K-Akt pathway were observed in association with metabolic alterations in PT-NASH. Other significant changes in gene expression were associated with DNA replication, cell cycle, extracellular matrix organization, and wound healing. A systematic comparison with non-transplant NASH (NT-NASH) liver transcriptomes indicated an increased activation of wound healing and angiogenesis pathways in the post-transplant condition. Conclusion: Beyond altered lipid metabolism, dysregulation of wound healing and tissue repair mechanisms may contribute to the accelerated development of fibrosis associated with PT-NASH. This presents an attractive therapeutic avenue to explore for PT-NASH to optimize the benefit and survival of the graft.

Mutational processes of tobacco smoking and APOBEC activity generate protein-truncating mutations in cancer genomes.

Mutational signatures represent a genomic footprint of endogenous and exogenous mutational processes through tumor evolution. However, their functional impact on the proteome remains incompletely understood. We analyzed the protein-coding impact of single-base substitution (SBS) signatures in 12,341 cancer genomes from 18 cancer types. Stop-gain mutations (SGMs) (i.e., nonsense mutations) were strongly enriched in SBS signatures of tobacco smoking, APOBEC cytidine deaminases, and reactive oxygen species. These mutational processes alter specific trinucleotide contexts and thereby substitute serines and glutamic acids with stop codons. SGMs frequently affect cancer hallmark pathways and tumor suppressors such as TP53, FAT1, and APC. Tobacco-driven SGMs in lung cancer correlate with smoking history and highlight a preventable determinant of these harmful mutations. APOBEC-driven SGMs are enriched in YTCA motifs and associate with APOBEC3A expression. Our study exposes SGM expansion as a genetic mechanism by which endogenous and carcinogenic mutational processes directly contribute to protein loss of function, oncogenesis, and tumor heterogeneity.

Differentiated Embryonic Neurospheres from Familial Alzheimer's Disease Model Show Innate Immune and Glial Cell Responses.

Proteins involved in the Alzheimer's disease (AD), such as amyloid precursor protein (APP) and presenilin-1 (PS1), play critical roles in early development of the central nervous system (CNS), as well as in innate immune and glial cell responses. Familial AD is associated with the presence of APPswe and PS1dE9 mutations. However, it is still unknown whether these mutations cause deficits in CNS development of carriers. We studied genome-wide gene expression profiles of differentiated neural progenitor cells (NPCs) from wild-type and APPswe/PS1dE9 mouse embryo telencephalon. The occurrence of strong innate immune and glial cell responses in APPswe/PS1dE9 neurospheres mainly involves microglial activation, inflammatory mediators and chemokines. APPswe/PS1dE9 neurospheres augmented up to 100-fold CCL12, CCL5, CCL3, C3, CX3CR1, TLR2 and TNF-alpha expression levels, when compared to WT neurospheres. Expression levels of the glia cell marker GFAP and microglia marker Iba-1 were up to 20-fold upregulated in APPswe/PS1dE9 neurospheres. The secretome of differentiated APPswe/PS1dE9 NPCs revealed enhanced chemoattraction of peripheral blood mononuclear cells. When evaluating the inferred protein interaction networks constructed from the array data, an improvement in astrocyte differentiation in APPswe/PS1dE9 neurospheres was evident in view of increased GFAP expression. Transgenic NPCs differentiated into neural phenotypes presented expression patterns of cytokine, glial cells, and inflammatory mediators characteristic of APPswe/PS1dE9 adult animals. Consequently, the neurogenic niche obtained from differentiation of embryonic APPswe/PS1dE9 neurospheres spontaneously presents several alterations observed in adult AD brains. Finally, our data strengthen pathophysiological hypotheses that propose an early neurodevelopmental origin for familial AD.

Annotation and functional characterization of long noncoding RNAs deregulated in pancreatic adenocarcinoma.

PURPOSE: Transcriptome analysis of pancreatic ductal adenocarcinoma (PDAC) has been useful to identify gene expression changes that sustain malignant phenotypes. Yet, most studies examined only tumor tissues and focused on protein-coding genes, leaving long non-coding RNAs (lncRNAs) largely underexplored. METHODS: We generated total RNA-Seq data from patient-matched tumor and nonmalignant pancreatic tissues and implemented a computational pipeline to survey known and novel lncRNAs. siRNA-mediated knockdown in tumor cell lines was performed to assess the contribution of PDAC-associated lncRNAs to malignant phenotypes. Gene co-expression network and functional enrichment analyses were used to assign deregulated lncRNAs to biological processes and molecular pathways. RESULTS: We detected 9,032 GENCODE lncRNAs as well as 523 unannotated lncRNAs, including transcripts significantly associated with patient outcome. Aberrant expression of a subset of novel and known lncRNAs was confirmed in patient samples and cell lines. siRNA-mediated knockdown of a subset of these lncRNAs (LINC01559, LINC01133, CCAT1, LINC00920 and UCA1) reduced cell proliferation, migration and invasion. Gene co-expression network analysis associated PDAC-deregulated lncRNAs with diverse biological processes, such as cell adhesion, protein glycosylation and DNA repair. Furthermore, UCA1 knockdown was shown to specifically deregulate co-expressed genes involved in DNA repair and to negatively impact DNA repair following damage induced by ionizing radiation. CONCLUSIONS: Our study expands the repertoire of lncRNAs deregulated in PDAC, thereby revealing novel candidate biomarkers for patient risk stratification. It also provides a roadmap for functional assays aimed to characterize novel mechanisms of action of lncRNAs in pancreatic cancer, which could be explored for therapeutic development.

ActiveDriverDB: Interpreting Genetic Variation in Human and Cancer Genomes Using Post-translational Modification Sites and Signaling Networks (2021 Update).

Deciphering the functional impact of genetic variation is required to understand phenotypic diversity and the molecular mechanisms of inherited disease and cancer. While millions of genetic variants are now mapped in genome sequencing projects, distinguishing functional variants remains a major challenge. Protein-coding variation can be interpreted using post-translational modification (PTM) sites that are core components of cellular signaling networks controlling molecular processes and pathways. ActiveDriverDB is an interactive proteo-genomics database that uses more than 260,000 experimentally detected PTM sites to predict the functional impact of genetic variation in disease, cancer and the human population. Using machine learning tools, we prioritize proteins and pathways with enriched PTM-specific amino acid substitutions that potentially rewire signaling networks via induced or disrupted short linear motifs of kinase binding. We then map these effects to site-specific protein interaction networks and drug targets. In the 2021 update, we increased the PTM datasets by nearly 50%, included glycosylation, sumoylation and succinylation as new types of PTMs, and updated the workflows to interpret inherited disease mutations. We added a recent phosphoproteomics dataset reflecting the cellular response to SARS-CoV-2 to predict the impact of human genetic variation on COVID-19 infection and disease course. Overall, we estimate that 16-21% of known amino acid substitutions affect PTM sites among pathogenic disease mutations, somatic mutations in cancer genomes and germline variants in the human population. These data underline the potential of interpreting genetic variation through the lens of PTMs and signaling networks. The open-source database is freely available at www.ActiveDriverDB.org.

Transcriptome profile analysis reveals putative molecular mechanisms of 5-aminolevulinic acid toxicity

5-aminolevulinic acid (5-ALA) is the first precursor of the heme biosynthesis pathway, accumulated in acute intermittent porphyria (AIP), an inherited metabolic disease characterized by porphobilinogen deaminase deficiency. An increased incidence of hepatocellular carcinoma (HCC) has been reported as a long-term manifestation in symptomatic AIP patients. 5-ALA is an α-aminoketone prone to oxidation, yielding reactive oxygen species and 4,5-dioxovaleric acid. A high concentration of 5-ALA presents deleterious pro-oxidant potential. It can induce apoptosis, DNA damage, mitochondrial dysfunction, and altered expression of carcinogenesis-related proteins. Several hypotheses of the increased risk of HCC rely on the harmful effect of elevated 5-ALA in the liver of AIP patients, which could promote a pro-carcinogenic environment. We investigated the global transcriptional changes and perturbed molecular pathways in HepG2 cells following exposure to 5-ALA 25 mM for 2 h and 24 h using DNA microarray. Distinct transcriptome profiles were observed. 5-ALA ’25 mM-2h′ upregulated 10 genes associated with oxidative stress response and carcinogenesis. Enrichment analysis of differentially expressed genes by KEGG, Reactome, MetaCore™, and Gene Ontology, showed that 5-ALA ‘25 mM-24h’ enriched pathways involved in drug detoxification, oxidative stress, DNA damage, cell death/survival, cell cycle, and mitochondria dysfunction corroborating the pro-oxidant properties of 5-ALA. Furthermore, our results disclosed other possible processes such as senescence, immune responses, endoplasmic reticulum stress, and also some putative effectors, such as sequestosome, osteopontin, and lon peptidase 1. This study provided additional knowledge about molecular mechanisms of 5-ALA toxicity which is essential to a deeper understanding of AIP and HCC pathophysiology. Furthermore, our findings can contribute to improving the efficacy of current therapies and the development of novel biomarkers and targets for diagnosis, prognosis, and therapeutic strategies for AHP/AIP and associated HCC.

Insights into the Function of Long Noncoding RNAs in Sepsis Revealed by Gene Co-Expression Network Analysis.

Sepsis is a major cause of death and its incidence and mortality increase exponentially with age. Most gene expression studies in sepsis have focused in protein-coding genes and the expression patterns, and potential roles of long noncoding RNAs (lncRNAs) have not been investigated yet. In this study, we performed co-expression network analysis of protein-coding and lncRNAs measured in neutrophil granulocytes from adult and elderly septic patients, along with age-matched healthy controls. We found that the genes displaying highest network similarity are predominantly differently expressed in sepsis and are enriched in loci encoding proteins with structural or regulatory functions related to protein translation and mitochondrial energetic metabolism. A number of lncRNAs are strongly connected to genes from these pathways and may take part in regulatory loops that are perturbed in sepsis. Among those, the ribosomal pseudogenes RP11-302F12.1 and RPL13AP7 are differentially expressed and appear to have a regulatory role on protein translation in both the elderly and adults, and lncRNAs MALAT1, LINC00355, MYCNOS, and AC010970.2 display variable connection strength and inverted expression patterns between adult and elderly networks, suggesting that they are the best candidates to be further studied to understand the mechanisms by which the immune response is impaired by age. In summary, we report the expression of lncRNAs that are deregulated in patients with sepsis, including subsets that display hub properties in molecular pathways relevant to the disease pathogenesis and that may participate in gene expression regulatory circuits related to the poorer disease outcome observed in elderly subjects.

Septic Shock in Advanced Age: Transcriptome Analysis Reveals Altered Molecular Signatures in Neutrophil Granulocytes.

Sepsis is one of the highest causes of mortality in hospitalized people and a common complication in both surgical and clinical patients admitted to hospital for non-infectious reasons. Sepsis is especially common in older people and its incidence is likely to increase substantially as a population ages. Despite its increased prevalence and mortality in older people, immune responses in the elderly during septic shock appear similar to that in younger patients. The purpose of this study was to conduct a genome-wide gene expression analysis of circulating neutrophils from old and young septic patients to better understand how aged individuals respond to severe infectious insult. We detected several genes whose expression could be used to differentiate immune responses of the elderly from those of young people, including genes related to oxidative phosphorylation, mitochondrial dysfunction and TGF-ß signaling, among others. Our results identify major molecular pathways that are particularly affected in the elderly during sepsis, which might have a pivotal role in worsening clinical outcomes compared with young people with sepsis.

Microarray gene expression analysis of neutrophils from elderly septic patients.

Sepsis is an especially common affliction in the elderly and despite its increased prevalence and mortality in older people, the immune response of the elderly during septic shock appears similar to that of younger patients. In the original study we conducted a global gene expression analysis of circulating neutrophils from elderly and young septic patients, as well as from age-matched healthy controls, to better understand how elder individuals respond to severe infectious insult (Pellegrina et al., 2015). Here we provide additional details pertaining processing and statistical analysis of the microarray data. Raw and normalized datasets linked to this project have been deposited in the Gene Expression Omnibus (GEO) database under accession number GSE67652.