Genomic and transcriptomic analysis of the recent Mpox outbreak.

The Mpox (formerly named Monkeypox) virus is the etiological cause of a recent multi-country outbreak, with thousands of distinct cases detected outside the endemic areas of Africa as of December 2023. In this article, we analyze the sequences of full genomes of Mpox virus from Europe and compare them with all available Mpox sequences of historical relevance, annotated by year and geographic origin, as well as related Cowpox and Variola (smallpox) virus sequences. Our results show that the recent outbreak is most likely originating from the West African clade of Mpox, with >99 % sequence identity with sequences derived from historical and recent cases, dating from 1971 to 2017. We analyze specific mutations occurring in viral proteins between the current outbreak, previous Mpox and Cowpox sequences, and the historical Variola virus. Genome-wide sequence analysis of the recent outbreak and other Mpox/Cowpox/Variola viruses shows a very high conservation, with 97.9 % (protein-based) and 97.8 % (nucleotide-based) sequence identity. We identified significant correlation in human transcriptional responses as well, with a conserved immune pathway response induced in human cell cultures by the three families of Pox virus. The similarities identified between the major strains of Pox viruses, as well as within the Mpox clades, both at the genomic and transcriptomic levels, provide a molecular basis for the observed efficacy of Variola vaccines in other Poxviruses.

Quantitative and qualitative detection of tRNAs, tRNA halves and tRFs in human cancer samples: Molecular grounds for biomarker development and clinical perspectives.

Transfer RNAs (tRNAs) are small non-coding RNAs playing a central role during protein synthesis. Besides translation, growing evidence suggests that in many contexts, precursor or mature tRNAs can also be processed into smaller fragments playing many non-canonical regulatory roles in different biological pathways with oncogenic relevance. Depending on the source, these molecules can be classified as tRNA halves (also known as tiRNAs) or tRNA-derived fragments (tRFs), and furtherly divided into 5'-tRNA and 3'-tRNA halves, or tRF-1, tRF-2, tRF-3, tRF-5, and i-tRF, respectively. Unlike DNA and mRNA, high-throughput sequencing of tRNAs is challenging, because of technical limitations of currently developed sequencing methods. In recent years, different sequencing approaches have been proposed allowing the quantification and identification of an increasing number of tRNA fragments with critical functions in distinct physiological and pathophysiological processes. In the present review, we discussed pros and cons of recent advances in different sequencing methods, also introducing the expanding repertoire of bioinformatics tool and resources specifically focused on tRNA research and discussing current issues in the study of these small RNA molecules. Furthermore, we discussed the potential value of tRNA fragments as diagnostic and prognostic biomarkers for different types of cancers.

Copper chelation suppresses epithelial-mesenchymal transition by inhibition of canonical and non-canonical TGF-ß signaling pathways in cancer.

BACKGROUND: Metastatic cancer cells exploit Epithelial-mesenchymal-transition (EMT) to enhance their migration, invasion, and resistance to treatments. Recent studies highlight that elevated levels of copper are implicated in cancer progression and metastasis. Clinical trials using copper chelators are associated with improved patient survival; however, the molecular mechanisms by which copper depletion inhibits tumor progression and metastasis are poorly understood. This remains a major hurdle to the clinical translation of copper chelators. Here, we propose that copper chelation inhibits metastasis by reducing TGF-ß levels and EMT signaling. Given that many drugs targeting TGF-ß have failed in clinical trials, partly because of severe side effects arising in patients, we hypothesized that copper chelation therapy might be a less toxic alternative to target the TGF-ß/EMT axis. RESULTS: Our cytokine array and RNA-seq data suggested a link between copper homeostasis, TGF-ß and EMT process. To validate this hypothesis, we performed single-cell imaging, protein assays, and in vivo studies. Here, we used the copper chelating agent TEPA to block copper trafficking. Our in vivo study showed a reduction of TGF-ß levels and metastasis to the lung in the TNBC mouse model. Mechanistically, TEPA significantly downregulated canonical (TGF-ß/SMAD2&3) and non-canonical (TGF-ß/PI3K/AKT, TGF-ß/RAS/RAF/MEK/ERK, and TGF-ß/WNT/ß-catenin) TGF-ß signaling pathways. Additionally, EMT markers of MMP-9, MMP-14, Vimentin, ß-catenin, ZEB1, and p-SMAD2 were downregulated, and EMT transcription factors of SNAI1, ZEB1, and p-SMAD2 accumulated in the cytoplasm after treatment. CONCLUSIONS: Our study suggests that copper chelation therapy represents a potentially effective therapeutic approach for targeting TGF-ß and inhibiting EMT in a diverse range of cancers.

A History of Repeated Alcohol Intoxication Promotes Cognitive Impairment and Gene Expression Signatures of Disease Progression in the 3xTg Mouse Model of Alzheimer's Disease.

The impact of alcohol abuse on Alzheimer's disease (AD) is poorly understood. Here, we show that the onset of neurocognitive impairment in a mouse model of AD is hastened by repeated alcohol intoxication through exposure to alcohol vapor, and we provide a comprehensive gene expression dataset of the prefrontal cortex by the single-nucleus RNA sequencing of 113,242 cells. We observed a broad dysregulation of gene expression that involves neuronal excitability, neurodegeneration, and inflammation, including interferon genes. Several genes previously associated with AD in humans by genome-wide association studies were differentially regulated in specific neuronal populations. The gene expression signatures of AD mice with a history of alcohol intoxication showed greater similarity to the signatures of older AD mice with advanced disease and cognitive impairment than did the gene expression signatures of AD mice not exposed to alcohol, suggesting that alcohol promotes transcriptional changes consistent with AD progression. Our gene expression dataset at the single-cell level provides a unique resource for investigations of the molecular bases of the detrimental role of excessive alcohol intake in AD.

The role of conventional radiography to assess the outcome of oncologic skeletal reconstructions of lower limbs aided by vascularized fibular autograft.

INTRODUCTION: Vascularized fibular autografts (VFA) are used in the oncologic skeletal reconstructions of long bones, alone or combined with massive bone allografts (MBA). Data regarding the role of imaging in assessing these complex skeletal reconstructions are lacking, and have mainly focused on Computed Tomography (CT). Our aim was to evaluate if early conventional radiography (CR) findings are correlated with the outcome of these skeletal reconstructions. MATERIALS AND METHODS: All consecutive patients who underwent oncologic resection of lower limbs long bones followed by VFA reconstruction were included in this single-center retrospective study. We compared the CR obtained immediately after surgery with the CR at the 6-month control, as well as the CR at 6 months with the CT at 6 months when available. The following scores were assigned to the VFA: 0 (unchanged), 1 (osteopenia-cortical bone thinning), 2 (increase in bone density-cortical thickening). We then investigated whether this score correlated with the implant outcome within 12 months (optimal integration, suboptimal integration, integration requiring further surgery or lack of integration) using Kaplan-Meier and Cox regression analyses, considering the occurrence of integration and the duration time before the surgical removal of the whole bone reconstruction. RESULTS: Forty-five patients were included (32 men [71.1%], mean age 14.6 years), 26 affected by osteosarcoma, 14 by Ewing sarcoma, 3 by adamantinoma and 2 operated for the failure of previous reconstructions for bone sarcoma. VFA changes on 6-month CR were significantly associated with optimal integration of the implants (log-rank P = 0.0137, multivariate Hazard ratio = 7.62, 95% confidence interval = 1.13-51.25). None of the other clinical and surgical features were associated with the implant outcome. The findings on 6-month CR and CT follow-up were not significantly different. CT at 6 months was available in 36 patients (80.0%). CONCLUSION: The assessment of VFA morphological changes on CR performed at 6 months can predict the outcome of the skeletal implant. This data should be considered for clinical decision-making, selecting patients requiring additional images (CT), and possible subsequent revision surgical procedures.

Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data.

Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as 'signaling hubs'. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called 'SURFACER'. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.

The R Language: An Engine for Bioinformatics and Data Science.

The R programming language is approaching its 30th birthday, and in the last three decades it has achieved a prominent role in statistics, bioinformatics, and data science in general. It currently ranks among the top 10 most popular languages worldwide, and its community has produced tens of thousands of extensions and packages, with scopes ranging from machine learning to transcriptome data analysis. In this review, we provide an historical chronicle of how R became what it is today, describing all its current features and capabilities. We also illustrate the major tools of R, such as the current R editors and integrated development environments (IDEs), the R Shiny web server, the R methods for machine learning, and its relationship with other programming languages. We also discuss the role of R in science in general as a driver for reproducibility. Overall, we hope to provide both a complete snapshot of R today and a practical compendium of the major features and applications of this programming language.

Escalated (Dependent) Oxycodone Self-Administration Is Associated with Cognitive Impairment and Transcriptional Evidence of Neurodegeneration in Human Immunodeficiency Virus (HIV) Transgenic Rats.

Substance use disorder is associated with accelerated disease progression in people with human immunodeficiency virus (HIV; PWH). Problem opioid use, including high-dose opioid therapy, prescription drug misuse, and opioid abuse, is high and increasing in the PWH population. Oxycodone is a broadly prescribed opioid in both the general population and PWH. Here, we allowed HIV transgenic (Tg) rats and wildtype (WT) littermates to intravenously self-administer oxycodone under short-access (ShA) conditions, which led to moderate, stable, "recreational"-like levels of drug intake, or under long-access (LgA) conditions, which led to escalated (dependent) drug intake. HIV Tg rats with histories of oxycodone self-administration under LgA conditions exhibited significant impairment in memory performance in the novel object recognition (NOR) paradigm. RNA-sequencing expression profiling of the medial prefrontal cortex (mPFC) in HIV Tg rats that self-administered oxycodone under ShA conditions exhibited greater transcriptional evidence of inflammation than WT rats that self-administered oxycodone under the same conditions. HIV Tg rats that self-administered oxycodone under LgA conditions exhibited transcriptional evidence of an increase in neuronal injury and neurodegeneration compared with WT rats under the same conditions. Gene expression analysis indicated that glucocorticoid-dependent adaptations contributed to the gene expression effects of oxycodone self-administration. Overall, the present results indicate that a history of opioid intake promotes neuroinflammation and glucocorticoid dysregulation, and excessive opioid intake is associated with neurotoxicity and cognitive impairment in HIV Tg rats.

Prediction of Metabolic Profiles from Transcriptomics Data in Human Cancer Cell Lines.

The Metabolome and Transcriptome are mutually communicating within cancer cells, and this interplay is translated into the existence of quantifiable correlation structures between gene expression and metabolite abundance levels. Studying these correlations could provide a novel venue of understanding cancer and the discovery of novel biomarkers and pharmacological strategies, as well as laying the foundation for the prediction of metabolite quantities by leveraging information from the more widespread transcriptomics data. In the current paper, we investigate the correlation between gene expression and metabolite levels in the Cancer Cell Line Encyclopedia dataset, building a direct correlation network between the two molecular ensembles. We show that a metabolite/transcript correlation network can be used to predict metabolite levels in different samples and datasets, such as the NCI-60 cancer cell line dataset, both on a sample-by-sample basis and in differential contrasts. We also show that metabolite levels can be predicted in principle on any sample and dataset for which transcriptomics data are available, such as the Cancer Genome Atlas (TCGA).

Corticosteroid sensitization drives opioid addiction.

The global crisis of opioid overdose fatalities has led to an urgent search to discover the neurobiological mechanisms of opioid use disorder (OUD). A driving force for OUD is the dysphoric and emotionally painful state (hyperkatifeia) that is produced during acute and protracted opioid withdrawal. Here, we explored a mechanistic role for extrahypothalamic stress systems in driving opioid addiction. We found that glucocorticoid receptor (GR) antagonism with mifepristone reduced opioid addiction-like behaviors in rats and zebrafish of both sexes and decreased the firing of corticotropin-releasing factor neurons in the rat amygdala (i.e., a marker of brain stress system activation). In support of the hypothesized role of glucocorticoid transcriptional regulation of extrahypothalamic GRs in addiction-like behavior, an intra-amygdala infusion of an antisense oligonucleotide that blocked GR transcriptional activity reduced addiction-like behaviors. Finally, we identified transcriptional adaptations of GR signaling in the amygdala of humans with OUD. Thus, GRs, their coregulators, and downstream systems may represent viable therapeutic targets to treat the "stress side" of OUD.

Structural genetics of circulating variants affecting the SARS-CoV-2 spike/human ACE2 complex.

SARS-CoV-2 entry in human cells is mediated by the interaction between the viral Spike protein and the human ACE2 receptor. This mechanism evolved from the ancestor bat coronavirus and is currently one of the main targets for antiviral strategies. However, there currently exist several Spike protein variants in the SARS-CoV-2 population as the result of mutations, and it is unclear if these variants may exert a specific effect on the affinity with ACE2 which, in turn, is also characterized by multiple alleles in the human population. In the current study, the GBPM analysis, originally developed for highlighting host-guest interaction features, has been applied to define the key amino acids responsible for the Spike/ACE2 molecular recognition, using four different crystallographic structures. Then, we intersected these structural results with the current mutational status, based on more than 295,000 sequenced cases, in the SARS-CoV-2 population. We identified several Spike mutations interacting with ACE2 and mutated in at least 20 distinct patients: S477N, N439K, N501Y, Y453F, E484K, K417N, S477I and G476S. Among these, mutation N501Y in particular is one of the events characterizing SARS-CoV-2 lineage B.1.1.7, which has recently risen in frequency in Europe. We also identified five ACE2 rare variants that may affect interaction with Spike and susceptibility to infection: S19P, E37K, M82I, E329G and G352V.Communicated by Ramaswamy H. Sarma.

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

BACKGROUND: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patients with breast cancer, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed 'SURFACER'. METHODS: Gene expression data from GTEx were used to build a normal breast network model as input to infer differential cell-surface proteins activity in BRCA tissue samples retrieved from TCGA versus normal samples. Data were stratified according to the PAM50 transcriptional subtypes (Luminal A, Luminal B, HER2 and Basal), while unsupervised clustering techniques were applied to define BRCA subtypes according to cell-surface proteins activity. RESULTS: Our approach led to the identification of 213 PAM50 subtypes-specific deregulated surface genes and the definition of five BRCA subtypes, whose prognostic value was assessed by survival analysis, identifying a cell-surface activity configuration at increased risk. The value of the SURFACER method in BRCA genotyping was tested by evaluating the performance of 11 different machine learning classification algorithms. CONCLUSIONS: BRCA patients can be stratified into five surface activity-specific groups having the potential to identify subtype-specific actionable targets to design tailored targeted therapies or for diagnostic purposes. SURFACER-defined subtypes show also a prognostic value, identifying surface-activity profiles at higher risk.

Exploiting the molecular basis of age and gender differences in outcomes of SARS-CoV-2 infections.

Motivation: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease, 2019; COVID-19) is associated with adverse outcomes in patients. It has been observed that lethality seems to be related to the age of patients. While ageing has been extensively demonstrated to be accompanied by some modifications at the gene expression level, a possible link with COVID-19 manifestation still need to be investigated at the molecular level. Objectives: This study aims to shed out light on a possible link between the increased COVID-19 lethality and the molecular changes that occur in elderly people. Methods: We considered public datasets of ageing-related genes and their expression at the tissue level. We selected human proteins interacting with viral ones that are known to be related to the ageing process. Finally, we investigated changes in the expression level of coding genes at the tissue, gender and age level. Results: We observed a significant intersection between some SARS-CoV-2 interactors and ageing-related genes, suggesting that those genes are particularly affected by COVID-19 infection. Our analysis evidenced that virus infection particularly involves ageing molecular mechanisms centred around proteins EEF2, NPM1, HMGA1, HMGA2, APEX1, CHEK1, PRKDC, and GPX4. We found that HMGA1 and NPM1 have different expressions in the lung of males, while HMGA1, APEX1, CHEK1, EEF2, and NPM1 present changes in expression in males due to ageing effects. Conclusion: Our study generated a mechanistic framework to clarify the correlation between COVID-19 incidence in elderly patients and molecular mechanisms of ageing. We also provide testable hypotheses for future investigation and pharmacological solutions tailored to specific age ranges.

The Transcriptome of SH-SY5Y at Single-Cell Resolution: A CITE-Seq Data Analysis Workflow.

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) is a recently established multimodal single cell analysis technique combining the immunophenotyping capabilities of antibody labeling and cell sorting with the resolution of single-cell RNA sequencing (scRNA-seq). By simply adding a 12-bp nucleotide barcode to antibodies (cell hashing), CITE-seq can be used to sequence antibody-bound tags alongside the cellular mRNA, thus reducing costs of scRNA-seq by performing it at the same time on multiple barcoded samples in a single run. Here, we illustrate an ideal CITE-seq data analysis workflow by characterizing the transcriptome of SH-SY5Y neuroblastoma cell line, a widely used model to study neuronal function and differentiation. We obtained transcriptomes from a total of 2879 single cells, measuring an average of 1600 genes/cell. Along with standard scRNA-seq data handling procedures, such as quality checks and cell filtering procedures, we performed exploratory analyses to identify most stable genes to be possibly used as reference housekeeping genes in qPCR experiments. We also illustrate how to use some popular R packages to investigate cell heterogeneity in scRNA-seq data, namely Seurat, Monocle, and slalom. Both the CITE-seq dataset and the code used to analyze it are freely shared and fully reusable for future research.

Preliminary report on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike mutation T478K.

Several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have emerged, posing a renewed threat to coronavirus disease 2019 containment and to vaccine and drug efficacy. In this study, we analyzed more than 1,000,000 SARS-CoV-2 genomic sequences deposited up to April 27, 2021, on the GISAID public repository, and identified a novel T478K mutation located on the SARS-CoV-2 Spike protein. The mutation is structurally located in the region of interaction with human receptor ACE2 and was detected in 11,435 distinct cases. We show that T478K has appeared and risen in frequency since January 2021, predominantly in Mexico and the United States, but we could also detect it in several European countries.

Copper: An Intracellular Achilles' Heel Allowing the Targeting of Epigenetics, Kinase Pathways, and Cell Metabolism in Cancer Therapeutics.

Copper is an essential transition metal frequently increased in cancer known to strongly influence essential cellular processes. Targeted therapy protocols utilizing both novel and repurposed drug agents initially demonstrate strong efficacy, before failing in advanced cancers as drug resistance develops and relapse occurs. Overcoming this limitation involves the development of strategies and protocols aimed at a wider targeting of the underlying molecular changes. Receptor Tyrosine Kinase signaling pathways, epigenetic mechanisms and cell metabolism are among the most common therapeutic targets, with molecular investigations increasingly demonstrating the strong influence each mechanism exerts on the others. Interestingly, all these mechanisms can be influenced by intracellular copper. We propose that copper chelating agents, already in clinical trial for multiple cancers, may simultaneously target these mechanisms across a wide variety of cancers, serving as an excellent candidate for targeted combination therapy. This review summarizes the known links between these mechanisms, copper, and copper chelation therapy.

Single-Cell Gene Network Analysis and Transcriptional Landscape of MYCN-Amplified Neuroblastoma Cell Lines.

Neuroblastoma (NBL) is a pediatric cancer responsible for more than 15% of cancer deaths in children, with 800 new cases each year in the United States alone. Genomic amplification of the MYC oncogene family member MYCN characterizes a subset of high-risk pediatric neuroblastomas. Several cellular models have been implemented to study this disease over the years. Two of these, SK-N-BE-2-C (BE2C) and Kelly, are amongst the most used worldwide as models of MYCN-Amplified human NBL. Here, we provide a transcriptome-wide quantitative measurement of gene expression and transcriptional network activity in BE2C and Kelly cell lines at an unprecedented single-cell resolution. We obtained 1105 Kelly and 962 BE2C unsynchronized cells, with an average number of mapped reads/cell of roughly 38,000. The single-cell data recapitulate gene expression signatures previously generated from bulk RNA-Seq. We highlight low variance for commonly used housekeeping genes between different cells (ACTB, B2M and GAPDH), while showing higher than expected variance for metallothionein transcripts in Kelly cells. The high number of samples, despite the relatively low read coverage of single cells, allowed for robust pathway enrichment analysis and master regulator analysis (MRA), both of which highlight the more mesenchymal nature of BE2C cells as compared to Kelly cells, and the upregulation of TWIST1 and DNAJC1 transcriptional networks. We further defined master regulators at the single cell level and showed that MYCN is not constantly active or expressed within Kelly and BE2C cells, independently of cell cycle phase. The dataset, alongside a detailed and commented programming protocol to analyze it, is fully shared and reusable.

Coronapp: A web application to annotate and monitor SARS-CoV-2 mutations.

The avalanche of genomic data generated from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus requires the development of tools to detect and monitor its mutations across the world. Here, we present a webtool, coronapp, dedicated to easily processing user-provided SARS-CoV-2 genomic sequences and visualizing the current worldwide status of SARS-CoV-2 mutations. The webtool allows users to highlight mutations and categorize them by frequency, country, genomic location and effect on protein sequences, and to monitor their presence in the population over time. The tool is available at http://giorgilab.unibo.it/coronannotator/ for the annotation of user-provided sequences. The full code is freely shared at https://github.com/federicogiorgi/giorgilab/tree/master/coronannotator.

Web tools to fight pandemics: the COVID-19 experience.

The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. Our focus was driven on tools drawing data from the fields of epidemiology, genomics, interactomics and pharmacology, in order to provide a meaningful depiction of the current state of the art of COVID-19 online resources.

Geographic and Genomic Distribution of SARS-CoV-2 Mutations.

The novel respiratory disease COVID-19 has reached the status of worldwide pandemic and large efforts are currently being undertaken in molecularly characterizing the virus causing it, SARS-CoV-2. The genomic variability of SARS-CoV-2 specimens scattered across the globe can underly geographically specific etiological effects. In the present study, we gather the 48,635 SARS-CoV-2 complete genomes currently available thanks to the collection endeavor of the GISAID consortium and thousands of contributing laboratories. We analyzed and annotated all SARS-CoV-2 mutations compared with the reference Wuhan genome NC_045512.2, observing an average of 7.23 mutations per sample. Our analysis shows the prevalence of single nucleotide transitions as the major mutational type across the world. There exist at least three clades characterized by geographic and genomic specificity. In particular, clade G, prevalent in Europe, carries a D614G mutation in the Spike protein, which is responsible for the initial interaction of the virus with the host human cell. Our analysis may facilitate custom-designed antiviral strategies based on the molecular specificities of SARS-CoV-2 in different patients and geographical locations.