Unlocking the Potential of Acetazolamide: A Literature Review of an Adjunctive Approach in Heart Failure Management.

Background: Heart failure (HF) patients often experience persistent fluid overload despite standard diuretic therapy. The adjunctive use of acetazolamide, a carbonic anhydrase inhibitor, in combination with loop diuretics has shown promise in improving decongestion and diuretic efficacy. This literature review aims to analyze six studies evaluating the effectiveness of acetazolamide as an additive treatment for acute decompensated heart failure (ADHF) and its impact on various outcomes. Methods: We searched the PubMed database using the terms "acetazolamide heart failure". We refined our search with specific filters (as shown our PRISMA flow diagram) and exclusion criteria, narrowing down our results to five studies. We included an extra study via expert recommendation, ultimately including six studies for comprehensive analysis. Results: The review highlights the positive effects of acetazolamide on decongestion, natriuresis, and diuresis in HF patients. However, it also showcases the limitations of these trials. Discussion: While the reviewed studies demonstrate the potential benefits of acetazolamide in enhancing decongestion and diuretic efficiency, there are limitations to consider, including small sample sizes, lack of blinding, and limited external validity. Further research is needed to confirm these findings, compare acetazolamide with other diuretic combinations, and explore its effects in a broader population of heart failure patients, including those in the United States. The use of acetazolamide in HF management warrants continued investigation to optimize its role in improving decongestion and patient outcomes.

Mechanism of actin capping protein recruitment and turnover during clathrin-mediated endocytosis.

Clathrin-mediated endocytosis depends on polymerization of a branched actin network to provide force for membrane invagination. A key regulator in branched actin network formation is actin capping protein (CP), which binds to the barbed end of actin filaments to prevent the addition or loss of actin subunits. CP was thought to stochastically bind actin filaments, but recent evidence shows CP is regulated by a group of proteins containing CP-interacting (CPI) motifs. Importantly, how CPI motif proteins function together to regulate CP is poorly understood. Here, we show Aim21 and Bsp1 work synergistically to recruit CP to the endocytic actin network in budding yeast through their CPI motifs, which also allosterically modulate capping strength. In contrast, twinfilin works downstream of CP recruitment, regulating the turnover of CP through its CPI motif and a non-allosteric mechanism. Collectively, our findings reveal how three CPI motif proteins work together to regulate CP in a stepwise fashion during endocytosis.

Utilizing chemically induced dimerization of FKBP to analyze endocytosis by live-cell imaging in budding yeast.

Chemically induced dimerization (CID) is a useful tool for artificially inducing protein-protein interactions. Although CID has been used extensively for live-cell microscopy applications in mammalian systems, it is rarely utilized in yeast cell biology studies. Here, we present a step-by-step protocol for the utilization of a CID system in live-cell microscopy experiments of budding yeast endocytosis. While focusing on the study of endocytosis, this protocol framework is adaptable to the study of other cellular processes in Saccharomyces cerevisiae. For complete details on the use and execution of this protocol, please refer to Lamb et al. (2021).

Quantum sensing for gravity cartography.

The sensing of gravity has emerged as a tool in geophysics applications such as engineering and climate research1-3, including the monitoring of temporal variations in aquifers4 and geodesy5. However, it is impractical to use gravity cartography to resolve metre-scale underground features because of the long measurement times needed for the removal of vibrational noise6. Here we overcome this limitation by realizing a practical quantum gravity gradient sensor. Our design suppresses the effects of micro-seismic and laser noise, thermal and magnetic field variations, and instrument tilt. The instrument achieves a statistical uncertainty of 20 E (1 E = 10-9 s-2) and is used to perform a 0.5-metre-spatial-resolution survey across an 8.5-metre-long line, detecting a 2-metre tunnel with a signal-to-noise ratio of 8. Using a Bayesian inference method, we determine the centre to ±0.19 metres horizontally and the centre depth as (1.89 -0.59/+2.3) metres. The removal of vibrational noise enables improvements in instrument performance to directly translate into reduced measurement time in mapping. The sensor parameters are compatible with applications in mapping aquifers and evaluating impacts on the water table7, archaeology8-11, determination of soil properties12 and water content13, and reducing the risk of unforeseen ground conditions in the construction of critical energy, transport and utilities infrastructure14, providing a new window into the underground.

Crowdsourced mapping of unexplored target space of kinase inhibitors.

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound-kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome.

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery.

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information.

The dynein light chain protein Tda2 functions as a dimerization engine to regulate actin capping protein during endocytosis.

Clathrin- and actin-mediated endocytosis is a fundamental process in eukaryotic cells. Previously, we discovered Tda2 as a new yeast dynein light chain (DLC) that works with Aim21 to regulate actin assembly during endocytosis. Here we show Tda2 functions as a dimerization engine bringing two Aim21 molecules together using a novel binding surface different than the canonical DLC ligand binding groove. Point mutations on either protein that diminish the Tda2-Aim21 interaction in vitro cause the same in vivo phenotype as TDA2 deletion showing reduced actin capping protein (CP) recruitment and increased filamentous actin at endocytic sites. Remarkably, chemically induced dimerization of Aim21 rescues the endocytic phenotype of TDA2 deletion. We also uncovered a CP interacting motif in Aim21, expanding its function to a fundamental cellular pathway and showing such motif exists outside mammalian cells. Furthermore, specific disruption of this motif causes the same deficit of actin CP recruitment and increased filamentous actin at endocytic sites as AIM21 deletion. Thus, the data indicate the Tda2-Aim21 complex functions in actin assembly primarily through CP regulation. Collectively, our results provide a mechanistic view of the Tda2-Aim21 complex and its function in actin network regulation at endocytic sites.

De novo genome assembly and analysis unveil biosynthetic and metabolic potentials of Pseudomonas fragi A13BB.

OBJECTIVES: The role of rhizosphere microbiome in supporting plant growth under biotic stress is well documented. Rhizobacteria ward off phytopathogens through various mechanisms including antibiosis. We sought to recover novel antibiotic-producing bacterial strains from soil samples collected from the rhizosphere. Pseudomonas fragi A13BB was recovered as part of this effort, and the whole genome was sequenced to facilitate mining for potential antibiotic-encoding biosynthetic gene clusters. DATA DESCRIPTION: Here, we report the complete genome sequence of P. fragi A13BB obtained from de novo assembly of Illumina MiSeq and GridION reads. The 4.94 Mb genome consists of a single chromosome with a GC content of 59.40%. Genomic features include 4410 CDSs, 102 RNAs, 3 CRISPR arrays, 3 prophage regions, and 37 predicted genomic islands. Two ß-lactone biosynthetic gene clusters were identified; besides, metabolic products of these are known to show antibiotic and/or anticancer properties. A siderophore biosynthetic gene cluster was also identified even though P. fragi is considered a non-siderophore producing pseudomonad. Other gene clusters of broad interest identified include those associated with bioremediation, biocontrol, plant growth promotion, or environmental adaptation. This dataset unveils various un-/underexplored metabolic or biosynthetic potential of P. fragi and provides insight into molecular mechanisms underpinning these attributes.

PBRM1 Deficiency Confers Synthetic Lethality to DNA Repair Inhibitors in Cancer.

Inactivation of Polybromo 1 (PBRM1), a specific subunit of the PBAF chromatin remodeling complex, occurs frequently in cancer, including 40% of clear cell renal cell carcinomas (ccRCC). To identify novel therapeutic approaches to targeting PBRM1-defective cancers, we used a series of orthogonal functional genomic screens that identified PARP and ATR inhibitors as being synthetic lethal with PBRM1 deficiency. The PBRM1/PARP inhibitor synthetic lethality was recapitulated using several clinical PARP inhibitors in a series of in vitro model systems and in vivo in a xenograft model of ccRCC. In the absence of exogenous DNA damage, PBRM1-defective cells exhibited elevated levels of replication stress, micronuclei, and R-loops. PARP inhibitor exposure exacerbated these phenotypes. Quantitative mass spectrometry revealed that multiple R-loop processing factors were downregulated in PBRM1-defective tumor cells. Exogenous expression of the R-loop resolution enzyme RNase H1 reversed the sensitivity of PBRM1-deficient cells to PARP inhibitors, suggesting that excessive levels of R-loops could be a cause of this synthetic lethality. PARP and ATR inhibitors also induced cyclic GMP-AMP synthase/stimulator of interferon genes (cGAS/STING) innate immune signaling in PBRM1-defective tumor cells. Overall, these findings provide the preclinical basis for using PARP inhibitors in PBRM1-defective cancers. SIGNIFICANCE: This study demonstrates that PARP and ATR inhibitors are synthetic lethal with the loss of PBRM1, a PBAF-specific subunit, thus providing the rationale for assessing these inhibitors in patients with PBRM1-defective cancer. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/11/2888/F1.large.jpg.

The complete genome sequence of Hafnia alvei A23BA; a potential antibiotic-producing rhizobacterium.

OBJECTIVES: The urgent need for novel antibiotics cannot be overemphasized. Hafnia alvei A23BA was isolated from plant rhizosphere as part of an effort to recover novel antibiotic-producing bacterial strains from soil samples. The genome of the isolate was sequenced to facilitate mining for potential antibiotic-encoding biosynthetic gene clusters and to gain insights into how these gene clusters could be activated. DATA DESCRIPTION: Here, we report the complete genome sequence of H. alvei A23BA obtained from the hybrid assembly of Illumina HiSeq and GridION reads. The genome, consisting of a circular chromosome and a circular plasmid, is 4.77 Mb in size with a GC content of 48.77%. The assembly is 99.5% complete with genomic features including 4,217 CDSs, 125 RNAs, and 30 pseudogenes. Thiopeptide, beta-lactone, siderophore, and homoserine lactone biosynthetic gene clusters were also identified. Other gene clusters of interest include those associated with bioremediation, biocontrol, and plant growth promotion- all of which are reported for H. alvei for the first time. This dataset serves to expedite the exploration of the biosynthetic and metabolic potentials of the species. Furthermore, being the first published genome sequence of a soil isolate, this dataset enriches the comparative genomics study of H. alvei strains.

CRI iAtlas: an interactive portal for immuno-oncology research.

The Cancer Research Institute (CRI) iAtlas is an interactive web platform for data exploration and discovery in the context of tumors and their interactions with the immune microenvironment. iAtlas allows researchers to study immune response characterizations and patterns for individual tumor types, tumor subtypes, and immune subtypes. iAtlas supports computation and visualization of correlations and statistics among features related to the tumor microenvironment, cell composition, immune expression signatures, tumor mutation burden, cancer driver mutations, adaptive cell clonality, patient survival, expression of key immunomodulators, and tumor infiltrating lymphocyte (TIL) spatial maps. iAtlas was launched to accompany the release of the TCGA PanCancer Atlas and has since been expanded to include new capabilities such as (1) user-defined loading of sample cohorts, (2) a tool for classifying expression data into immune subtypes, and (3) integration of TIL mapping from digital pathology images. We expect that the CRI iAtlas will accelerate discovery and improve patient outcomes by providing researchers access to standardized immunogenomics data to better understand the tumor immune microenvironment and its impact on patient responses to immunotherapy.

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.

Composition-based prediction and rational manipulation of prion-like domain recruitment to stress granules.

Mutations in a number of stress granule-associated proteins have been linked to various neurodegenerative diseases. Several of these mutations are found in aggregation-prone prion-like domains (PrLDs) within these proteins. In this work, we examine the sequence features governing PrLD localization to stress granules upon stress. We demonstrate that many yeast PrLDs are sufficient for stress-induced assembly into microscopically visible foci that colocalize with stress granule markers. Additionally, compositional biases exist among PrLDs that assemble upon stress, and these biases are consistent across different stressors. Using these biases, we have developed a composition-based prediction method that accurately predicts PrLD assembly into foci upon heat shock. We show that compositional changes alter PrLD assembly behavior in a predictable manner, while scrambling primary sequence has little effect on PrLD assembly and recruitment to stress granules. Furthermore, we were able to design synthetic PrLDs that were efficiently recruited to stress granules, and found that aromatic amino acids, which have previously been linked to PrLD phase separation, were dispensable for this recruitment. These results highlight the flexible sequence requirements for stress granule recruitment and suggest that PrLD localization to stress granules is driven primarily by amino acid composition, rather than primary sequence.

Correction to: RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking.

Following publication of the original article [1], the authors provided an updated accession number in the "Availability of data and materials" section of the declarations.

Analysis of genetically driven alternative splicing identifies FBXO38 as a novel COPD susceptibility gene.

While many disease-associated single nucleotide polymorphisms (SNPs) are associated with gene expression (expression quantitative trait loci, eQTLs), a large proportion of complex disease genome-wide association study (GWAS) variants are of unknown function. Some of these SNPs may contribute to disease by regulating gene splicing. Here, we investigate whether SNPs that are associated with alternative splicing (splice QTL or sQTL) can identify novel functions for existing GWAS variants or suggest new associated variants in chronic obstructive pulmonary disease (COPD). RNA sequencing was performed on whole blood from 376 subjects from the COPDGene Study. Using linear models, we identified 561,060 unique sQTL SNPs associated with 30,333 splice sites corresponding to 6,419 unique genes. Similarly, 708,928 unique eQTL SNPs involving 15,913 genes were detected at 10% FDR. While there is overlap between sQTLs and eQTLs, 55.3% of sQTLs are not eQTLs. Co-localization analysis revealed that 7 out of 21 loci associated with COPD (p<1x10-6) in a published GWAS have at least one shared causal variant between the GWAS and sQTL studies. Among the genes identified to have splice sites associated with top GWAS SNPs was FBXO38, in which a novel exon was discovered to be protective against COPD. Importantly, the sQTL in this locus was validated by qPCR in both blood and lung tissue, demonstrating that splice variants relevant to lung tissue can be identified in blood. Other identified genes included CDK11A and SULT1A2. Overall, these data indicate that analysis of alternative splicing can provide novel insights into disease mechanisms. In particular, we demonstrated that SNPs in a known COPD GWAS locus on chromosome 5q32 influence alternative splicing in the gene FBXO38.

Whole blood RNA sequencing reveals a unique transcriptomic profile in patients with ARDS following hematopoietic stem cell transplantation.

BACKGROUND: The acute respiratory distress syndrome (ARDS) is characterized by the acute onset of hypoxemia and bilateral lung infiltrates in response to an inciting event, and is associated with high morbidity and mortality. Patients undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are at increased risk for ARDS. We hypothesized that HSCT patients with ARDS would have a unique transcriptomic profile identifiable in peripheral blood compared to those that did not undergo HSCT. METHODS: We isolated RNA from banked peripheral blood samples from a biorepository of critically ill ICU patients. RNA-Seq was performed on 11 patients with ARDS (5 that had undergone HSCT and 6 that had not) and 12 patients with sepsis without ARDS (5 that that had undergone HCST and 7 that had not). RESULTS: We identified 687 differentially expressed genes between ARDS and ARDS-HSCT (adjusted p-value < 0.01), including IFI44L, OAS3, LY6E, and SPATS2L that had increased expression in ARDS vs. ARDS-HSCT; these genes were not differentially expressed in sepsis vs sepsis-HSCT. Gene ontology enrichment analysis revealed that many differentially expressed genes were related to response to type I interferon. CONCLUSIONS: Our findings reveal significant differences in whole blood transcriptomic profiles of patients with non-HSCT ARDS compared to ARDS-HSCT patients and point toward different immune responses underlying ARDS and ARDS-HSCT that contribute to lung injury.

Integrative Genomics Analysis Identifies ACVR1B as a Candidate Causal Gene of Emphysema Distribution.

Genome-wide association studies (GWAS) have identified multiple associations with emphysema apicobasal distribution (EABD), but the biological functions of these variants are unknown. To characterize the functions of EABD-associated variants, we integrated GWAS results with 1) expression quantitative trait loci (eQTL) from the Genotype Tissue Expression (GTEx) project and subjects in the COPDGene (Genetic Epidemiology of COPD) study and 2) cell type epigenomic marks from the Roadmap Epigenomics project. On the basis of these analyses, we selected a variant near ACVR1B (activin A receptor type 1B) for functional validation. SNPs from 168 loci with P values less than 5 × 10-5 in the largest GWAS meta-analysis of EABD were analyzed. Eighty-four loci overlapped eQTL, with 12 of these loci showing greater than 80% likelihood of harboring a single, shared GWAS and eQTL causal variant. Seventeen cell types were enriched for overlap between EABD loci and Roadmap Epigenomics marks (permutation P < 0.05), with the strongest enrichment observed in CD4+, CD8+, and regulatory T cells. We selected a putative causal variant, rs7962469, associated with ACVR1B expression in lung tissue for additional functional investigation, and reporter assays confirmed allele-specific regulatory activity for this variant in human bronchial epithelial and Jurkat immune cell lines. ACVR1B expression levels exhibit a nominally significant association with emphysema distribution. EABD-associated loci are preferentially enriched in regulatory elements of multiple cell types, most notably T-cell subsets. Multiple EABD loci colocalize to regulatory elements that are active across multiple tissues and cell types, and functional analyses confirm the presence of an EABD-associated functional variant that regulates ACVR1B expression, indicating that transforming growth factor-ß signaling plays a role in the EABD phenotype. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

PARP inhibition enhances tumor cell-intrinsic immunity in ERCC1-deficient non-small cell lung cancer.

The cyclic GMP-AMP synthase/stimulator of IFN genes (cGAS/STING) pathway detects cytosolic DNA to activate innate immune responses. Poly(ADP-ribose) polymerase inhibitors (PARPi) selectively target cancer cells with DNA repair deficiencies such as those caused by BRCA1 mutations or ERCC1 defects. Using isogenic cell lines and patient-derived samples, we showed that ERCC1-defective non-small cell lung cancer (NSCLC) cells exhibit an enhanced type I IFN transcriptomic signature and that low ERCC1 expression correlates with increased lymphocytic infiltration. We demonstrated that clinical PARPi, including olaparib and rucaparib, have cell-autonomous immunomodulatory properties in ERCC1-defective NSCLC and BRCA1-defective triple-negative breast cancer (TNBC) cells. Mechanistically, PARPi generated cytoplasmic chromatin fragments with characteristics of micronuclei; these were found to activate cGAS/STING, downstream type I IFN signaling, and CCL5 secretion. Importantly, these effects were suppressed in PARP1-null TNBC cells, suggesting that this phenotype resulted from an on-target effect of PARPi on PARP1. PARPi also potentiated IFN-γ-induced PD-L1 expression in NSCLC cell lines and in fresh patient tumor cells; this effect was enhanced in ERCC1-deficient contexts. Our data provide a preclinical rationale for using PARPi as immunomodulatory agents in appropriately molecularly selected populations.

Blood eosinophil count thresholds and exacerbations in patients with chronic obstructive pulmonary disease.

BACKGROUND: Eosinophilic airway inflammation in patients with chronic obstructive pulmonary disease (COPD) is associated with exacerbations and responsivity to steroids, suggesting potential shared mechanisms with eosinophilic asthma. However, there is no consistent blood eosinophil count that has been used to define the increased exacerbation risk. OBJECTIVE: We sought to investigate blood eosinophil counts associated with exacerbation risk in patients with COPD. METHODS: Blood eosinophil counts and exacerbation risk were analyzed in patients with moderate-to-severe COPD by using 2 independent studies of former and current smokers with longitudinal data. The Genetic Epidemiology of COPD (COPDGene) study was analyzed for discovery (n = 1,553), and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study was analyzed for validation (n = 1,895). A subset of the ECLIPSE study subjects were used to assess the stability of blood eosinophil counts over time. RESULTS: COPD exacerbation risk increased with higher eosinophil counts. An eosinophil count threshold of 300 cells/µL or greater showed adjusted incidence rate ratios for exacerbations of 1.32 in the COPDGene study (95% CI, 1.10-1.63). The cutoff of 300 cells/µL or greater was validated for prospective risk of exacerbation in the ECLIPSE study, with adjusted incidence rate ratios of 1.22 (95% CI, 1.06-1.41) using 3-year follow-up data. Stratified analysis confirmed that the increased exacerbation risk associated with an eosinophil count of 300 cells/µL or greater was driven by subjects with a history of frequent exacerbations in both the COPDGene and ECLIPSE studies. CONCLUSIONS: Patients with moderate-to-severe COPD and blood eosinophil counts of 300 cells/µL or greater had an increased risk exacerbations in the COPDGene study, which was prospectively validated in the ECLIPSE study.