A computer filtering method to drive out tiny genes from the yeast genome

The authors of the first yeast chromosome sequence defined a minimum threshold requirement of 100 codons, above which an open reading frame (ORF) is retained as a putative coding sequence. However, at least 58 yeast genes shorter than 100 codons have an assigned protein function. Therefore, the yeast genome may contain other tiny but functionally important genes that are discarded from analyses by this simple filtering rule. We have established discriminant functions from the in-phase hexamer frequencies of functional genes and of simulated ORFs derived from a stationary Markov chain model. Fifty-two out of the 58 genes were recognized as coding ORFs by our discriminating method. The test was also applied to all the small ORFs (36 to 100 codons) found in the intergenic regions of published chromosomes. It retained 140 new potential tiny coding sequences, among which we identified seven new genes by similarity searches. Our method, used conjointly with similarity searches, can also highlight sequencing errors resulting from the disruption of the coding frame of longer ORFs. This method, by its ability to detect potential coding ORFs, can be a very useful tool for functional analysis.     

Pan-Cancer Prediction of Cell-Line Drug Sensitivity Using Network-Based Methods

The development of reliable predictive models for individual cancer cell lines to identify an optimal cancer drug is a crucial step to accelerate personalized medicine, but vast differences in cancer cell lines and drug characteristics make it quite challenging to develop predictive models that result in high predictive power and explain the similarity of cell lines or drugs. Our study proposes a novel network-based methodology that breaks the problem into smaller, more interpretable problems to improve the predictive power of anti-cancer drug responses in cell lines. For the drug-sensitivity study, we used the GDSC database for 915 cell lines and 200 drugs. The theory of optimal mass transport was first used to separately cluster cell lines and drugs, using gene-expression profiles and extensive cheminformatic drug features, represented in a form of data networks. To predict cell-line specific drug responses, random forest regression modeling was separately performed for each cell-line drug cluster pair. Post-modeling biological analysis was further performed to identify potential biological correlates associated with drug responses. The network-based clustering method resulted in 30 distinct cell-line drug cluster pairs. Predictive modeling on each cell-line-drug cluster outperformed alternative computational methods in predicting drug responses. We found that among the four drugs top-ranked with respect to prediction performance, three targeted the PI3K/mTOR signaling pathway. Predictive modeling on clustered subsets of cell lines and drugs improved the prediction accuracy of cell-line specific drug responses. Post-modeling analysis identified plausible biological processes associated with drug responses.     

Interplay between Selenium,Selenoproteins and HIV-1 Replication in Human CD4 T-Lymphocytes

The infection of CD4 T-lymphocytes with human immunodeficiency virus (HIV), the etiological agent of acquired immunodeficiency syndrome (AIDS), disrupts cellular homeostasis, increases oxidative stress and interferes with micronutrient metabolism. Viral replication simultaneously increases the demand for micronutrients and causes their loss, as for selenium (Se). In HIV-infected patients, selenium deficiency was associated with a lower CD4 T-cell count and a shorter life expectancy. Selenium has an important role in antioxidant defense, redox signaling and redox homeostasis, and most of these biological activities are mediated by its incorporation in an essential family of redox enzymes, namely the selenoproteins. Here, we have investigated how selenium and selenoproteins interplay with HIV infection in different cellular models of human CD4 T lymphocytes derived from established cell lines (Jurkat and SupT1) and isolated primary CD4 T cells. First, we characterized the expression of the selenoproteome in various human T-cell models and found it tightly regulated by the selenium level of the culture media, which was in agreement with reports from non-immune cells. Then, we showed that selenium had no significant effect on HIV-1 protein production nor on infectivity, but slightly reduced the percentage of infected cells in a Jurkat cell line and isolated primary CD4 T cells. Finally, in response to HIV-1 infection, the selenoproteome was slightly altered.     

COVID-19 and Lung Mast Cells: The Kallikrein–Kinin Activation Pathway

Mast cells (MCs) have relevant participation in inflammatory and vascular hyperpermeability events, responsible for the action of the kallikrein–kinin system (KKS), that affect patients inflicted by the severe form of COVID-19. Given a higher number of activated MCs present in COVID-19 patients and their association with vascular hyperpermeability events, we investigated the factors that lead to the activation and degranulation of these cells and their harmful effects on the alveolar septum environment provided by the action of its mediators. Therefore, the pyroptotic processes throughout caspase-1 (CASP-1) and alarmin interleukin-33 (IL-33) secretion were investigated, along with the immunoexpression of angiotensin-converting enzyme 2 (ACE2), bradykinin receptor B1 (B1R) and bradykinin receptor B2 (B2R) on post-mortem lung samples from 24 patients affected by COVID-19. The results were compared to 10 patients affected by H1N1pdm09 and 11 control patients. As a result of the inflammatory processes induced by SARS-CoV-2, the activation by immunoglobulin E (IgE) and degranulation of tryptase, as well as Toluidine Blue metachromatic (TB)-stained MCs of the interstitial and perivascular regions of the same groups were also counted. An increased immunoexpression of the tissue biomarkers CASP-1, IL-33, ACE2, B1R and B2R was observed in the alveolar septum of the COVID-19 patients, associated with a higher density of IgE⁺ MCs, tryptase⁺ MCs and TB-stained MCs, in addition to the presence of intra-alveolar edema. These findings suggest the direct correlation of MCs with vascular hyperpermeability, edema and diffuse alveolar damage (DAD) events that affect patients with a severe form of this disease. The role of KKS activation in events involving the exacerbated increase in vascular permeability and its direct link with the conditions that precede intra-alveolar edema, and the consequent DAD, is evidenced. Therapy with drugs that inhibit the activation/degranulation of MCs can prevent the worsening of the prognosis and provide a better outcome for the patient.     

Solid Tumors and Kinase Inhibition: Management and Therapy Efficacy Evolution

The increasing numbers of cancer cases worldwide and the exceedingly high mortality rates of some tumor subtypes raise the question about if the current protocols for cancer management are effective and what has been done to improve upon oncologic patients’ prognoses. The traditional chemo-immunotherapy options for cancer treatment focus on the use of cytotoxic agents that are able to overcome neoplastic clones’ survival mechanisms and induce apoptosis, as well as on the ability to capacitate the host’s immune system to hinder the continuous growth of malignant cells. The need to avert the highly toxic profiles of conventional chemo-immunotherapy and to overcome the emerging cases of tumor multidrug resistance has fueled a growing interest in the field of precision medicine and targeted molecular therapies in the last couple of decades, although relatively new alternatives in oncologic practices, the increased specificity, and the positive clinical outcomes achieved through targeted molecular therapies have already consolidated them as promising prospects for the future of cancer management. In recent years, the development and application of targeted drugs as tyrosine kinase inhibitors have enabled cancer treatment to enter the era of specificity. In addition, the combined use of targeted therapy, immunotherapy, and traditional chemotherapy has innovated the standard treatment for many malignancies, bringing new light to patients with recurrent tumors. This article comprises a series of clinical trials that, in the past 5 years, utilized kinase inhibitors (KIs) as a monotherapy or in combination with other cytotoxic agents to treat patients afflicted with solid tumors. The results, with varying degrees of efficacy, are reported.     

Genome-Wide Association Analysis and Genomic Prediction of Thyroglobulin Plasma Levels

Thyroglobulin (Tg) is an iodoglycoprotein produced by thyroid follicular cells which acts as an essential substrate for thyroid hormone synthesis. To date, only one genome-wide association study (GWAS) of plasma Tg levels has been performed by our research group. Utilizing recent advancements in computation and modeling, we apply a Bayesian approach to the probabilistic inference of the genetic architecture of Tg. We fitted a Bayesian sparse linear mixed model (BSLMM) and a frequentist linear mixed model (LMM) of 7,289,083 variants in 1096 healthy European-ancestry participants of the Croatian Biobank. Meta-analysis with two independent cohorts (total n = 2109) identified 83 genome-wide significant single nucleotide polymorphisms (SNPs) within the ST6GAL1 gene (p<5×10−8). BSLMM revealed additional association signals on chromosomes 1, 8, 10, and 14. For ST6GAL1 and the newly uncovered genes, we provide physiological and pathophysiological explanations of how their expression could be associated with variations in plasma Tg levels. We found that the SNP-heritability of Tg is 17% and that 52% of this variation is due to a small number of 16 variants that have a major effect on Tg levels. Our results suggest that the genetic architecture of plasma Tg is not polygenic, but influenced by a few genes with major effects.     

In Vivo Behavior of Ultrasmall Spherical Nucleic Acids

The biological properties of spherical nucleic acids (SNAs) are largely independent of nanoparticle core identity but significantly affected by oligonucleotide surface density. Additionally, the payload-to-carrier (i.e., DNA-to-nanoparticle) mass ratio of SNAs is inversely proportional to core size. While SNAs with many core types and sizes have been developed, all in vivo analyses of SNA behavior have been limited to cores >10 nm in diameter. However, “ultrasmall” nanoparticle constructs (<10 nm diameter) can exhibit increased payload-to-carrier ratios, reduced liver accumulation, renal clearance, and enhanced tumor infiltration. Therefore, we hypothesized that SNAs with ultrasmall cores exhibit SNA-like properties, but with in vivo behavior akin to traditional ultrasmall nanoparticles. To investigate, we compared the behavior of SNAs with 1.4-nm Au₁₀₂ nanocluster cores (AuNC-SNAs) and SNAs with 10-nm gold nanoparticle cores (AuNP-SNAs). Significantly, AuNC-SNAs possess SNA-like properties (e.g., high cellular uptake, low cytotoxicity) but show distinct in vivo behavior. When intravenously injected in mice, AuNC-SNAs display prolonged blood circulation, lower liver accumulation, and higher tumor accumulation than AuNP-SNAs. Thus, SNA-like properties persist at the sub-10-nm length scale and oligonucleotide arrangement and surface density are responsible for the biological properties of SNAs. This work has implications for the design of new nanocarriers for therapeutic applications.     

Circadian Rhythm Dysregulation and Leukemia Development: The Role of Clock Genes as Promising Biomarkers

The circadian clock (CC) is a daily system that regulates the oscillations of physiological processes and can respond to the external environment in order to maintain internal homeostasis. For the functioning of the CC, the clock genes (CG) act in different metabolic pathways through the clock-controlled genes (CCG), providing cellular regulation. The CC’s interruption can result in the development of different diseases, such as neurodegenerative and metabolic disorders, as well as cancer. Leukemias correspond to a group of malignancies of the blood and bone marrow that occur when alterations in normal cellular regulatory processes cause the uncontrolled proliferation of hematopoietic stem cells. This review aimed to associate a deregulated CC with the manifestation of leukemia, looking for possible pathways involving CG and their possible role as leukemic biomarkers.