Nat Chem Biol. 2023 Feb 16. doi: 10.1038/s41589-022-01241-x. Online ahead of print.

NO ABSTRACT

PMID:36797402 | DOI:10.1038/s41589-022-01241-x

Nat Struct Mol Biol. 2023 Feb;30(2):129-130. doi: 10.1038/s41594-023-00924-w.

NO ABSTRACT

PMID:36797377 | DOI:10.1038/s41594-023-00924-w

NPJ Precis Oncol. 2023 Feb 16;7(1):18. doi: 10.1038/s41698-023-00360-5.

ABSTRACT

Endocrine therapy (ET) in combination with CDK4/6 inhibition is routinely used as first-line treatment for HR+/HER2- metastatic breast cancer (MBC) patients. However, 30-40% of patients quickly develop disease progression. In this open-label multicenter clinical trial, we utilized a hypothesis-driven protein/phosphoprotein-based approach to identify predictive markers of response to ET plus CDK4/6 inhibition in pre-treatment tissue biopsies. Pathway-centered signaling profiles were generated from microdissected tumor epithelia and surrounding stroma/immune cells using the reverse phase protein microarray. Phosphorylation levels of the CDK4/6 downstream substrates Rb (S780) and FoxM1 (T600) were higher in patients with progressive disease (PD) compared to responders (p = 0.02). Systemic PI3K/AKT/mTOR activation in tumor epithelia and stroma/immune cells was detected in patients with PD. This activation was not explained by underpinning genomic alterations alone. As the number of FDA-approved targeted compounds increases, functional protein-based signaling analyses may become a critical component of response prediction and treatment selection for MBC patients.

PMID:36797347 | DOI:10.1038/s41698-023-00360-5

Signal Transduct Target Ther. 2023 Feb 17;8(1):66. doi: 10.1038/s41392-022-01268-5.

ABSTRACT

Abnormal activation of Wnt/β-catenin-mediated transcription is closely associated with the malignancy of pancreatic cancer. Family with sequence similarity 83 member A (FAM83A) was shown recently to have oncogenic effects in a variety of cancer types, but the biological roles and molecular mechanisms of FAM83A in pancreatic cancer need further investigation. Here, we newly discovered that FAM83A binds directly to β-catenin and inhibits the assembly of the cytoplasmic destruction complex thus inhibiting the subsequent phosphorylation and degradation. FAM83A is mainly phosphorylated by the SRC non-receptor kinase family member BLK (B-lymphoid tyrosine kinase) at tyrosine 138 residue within the DUF1669 domain that mediates the FAM83A-β-catenin interaction. Moreover, FAM83A tyrosine 138 phosphorylation enhances oncogenic Wnt/β-catenin-mediated transcription through promoting β-catenin-TCF4 interaction and showed an elevated nucleus translocation, which inhibits the recruitment of histone deacetylases by TCF4. We also showed that FAM83A is a direct downstream target of Wnt/β-catenin signaling and correlates with the levels of Wnt target genes in human clinical pancreatic cancer tissues. Notably, the inhibitory peptides that target the FAM83A-β-catenin interaction significantly suppressed pancreatic cancer growth and metastasis in vitro and in vivo. Our results revealed that blocking the FAM83A cascade signaling defines a therapeutic target in human pancreatic cancer.

PMID:36797256 | DOI:10.1038/s41392-022-01268-5

Plant Cell. 2023 Feb 17:koad047. doi: 10.1093/plcell/koad047. Online ahead of print.

NO ABSTRACT

PMID:36797218 | DOI:10.1093/plcell/koad047

Handb Clin Neurol. 2023;192:73-86. doi: 10.1016/B978-0-323-85538-9.00007-9.

ABSTRACT

Neurodegenerative diseases are multifactorial. This means that several genetic, epigenetic, and environmental factors contribute to their emergence. Therefore, for the future management of these highly prevalent diseases, it is necessary to change perspective. If a holistic viewpoint is assumed, the phenotype (the clinicopathological convergence) emerges from the perturbation of a complex system of functional interactions among proteins (systems biology divergence). The systems biology top-down approach starts with the unbiased collection of sets of data generated through one or more -omics techniques and has the aim to identify the networks and the components that participate in the generation of a phenotype (disease), often without any available a priori knowledge. The principle behind the top-down method is that the molecular components that respond similarly to experimental perturbations are somehow functionally related. This allows the study of complex and relatively poorly characterized diseases without requiring extensive knowledge of the processes under investigation. In this chapter, the use of a global approach will be applied to the comprehension of neurodegeneration, with a particular focus on the two most prevalent ones, Alzheimer's and Parkinson's diseases. The final purpose is to distinguish disease subtypes (even with similar clinical manifestations) to launch a future of precision medicine for patients with these disorders.

PMID:36796949 | DOI:10.1016/B978-0-323-85538-9.00007-9

Handb Clin Neurol. 2023;192:101-118. doi: 10.1016/B978-0-323-85538-9.00003-1.

ABSTRACT

Through the understanding of multiple etiologies, pathologies, and disease progression trajectories, breast cancer shifted historically from a singular malignancy of the breast to a complex of molecular/biological entities, translating into individualized disease-modifying treatments. As a result, this led to various de-escalations of treatment compared with the gold standard in the era preceding systems biology: radical mastectomy. Targeted therapies have minimized morbidity from the treatments and mortality from the disease. Biomarkers further individualized tumor genetics and molecular biology to optimize treatments targeting specific cancer cells. Landmark discoveries in breast cancer management have evolved through histology, hormone receptors, human epidermal growth factor, single-gene prognostic markers, and multigene prognostic markers. Relevant to the reliance on histopathology in neurodegenerative disorders, histopathology evaluation in breast cancer can serve as a marker of overall prognosis rather than predict response to therapies. This chapter reviews the successes and failures of breast cancer research through history, with focus on the transition from a universal approach for all patients to divergent biomarker development and individualized targeted therapies, discussing future areas of growth in the field that may apply to neurodegenerative disorders.

PMID:36796936 | DOI:10.1016/B978-0-323-85538-9.00003-1

J Neurosci. 2023 Feb 15;43(7):1074-1088. doi: 10.1523/JNEUROSCI.1179-22.2022.

ABSTRACT

In recent years, the field of neuroscience has gone through rapid experimental advances and a significant increase in the use of quantitative and computational methods. This growth has created a need for clearer analyses of the theory and modeling approaches used in the field. This issue is particularly complex in neuroscience because the field studies phenomena that cross a wide range of scales and often require consideration at varying degrees of abstraction, from precise biophysical interactions to the computations they implement. We argue that a pragmatic perspective of science, in which descriptive, mechanistic, and normative models and theories each play a distinct role in defining and bridging levels of abstraction, will facilitate neuroscientific practice. This analysis leads to methodological suggestions, including selecting a level of abstraction that is appropriate for a given problem, identifying transfer functions to connect models and data, and the use of models themselves as a form of experiment.

PMID:36796842 | DOI:10.1523/JNEUROSCI.1179-22.2022

J Allergy Clin Immunol. 2023 Feb 14:S0091-6749(23)00208-7. doi: 10.1016/j.jaci.2023.01.028. Online ahead of print.

ABSTRACT

BACKGROUND: Inhaled corticosteroids (CS) are a backbone of asthma treatment, improving quality of life, exacerbation rates and mortality. Though effective for most, a subset of asthma patients experience CS resistant disease despite receipt of high medication doses.

OBJECTIVE: Our goal was to investigate the transcriptomic response of bronchial epithelial cells (BEC) to inhaled corticosteroids.

METHODS: Independent component analysis was performed on datasets detailing the transcriptional response of BECs to CS treatment. The expression of these CS response components was examined in two patient cohorts and investigated in relation to clinical parameters. Supervised learning was used to predict BEC CS responses using peripheral blood gene expression.

RESULTS: We identified a signature of CS response that was closely correlated with CS use in asthma patients. Participants could be separated based on CS response genes into groups with high and low signature expression. Patients with low expression of CS-response genes, particularly those with a severe asthma diagnosis, showed worse lung function and quality of life. These individuals demonstrated enrichment for T lymphocyte infiltration in endobronchial brushings. Supervised machine learning identified a 7 gene signature from peripheral blood that reliably identified patients with poor CS response expression in BECs.

CONCLUSION: Loss of CS transcriptional responses within bronchial epithelium was related to impaired lung function and poor quality of life, particularly in severe asthma. These individuals were identified using minimally invasive blood sampling, suggesting these findings may enable earlier triage to alternative treatments.

CLINICAL IMPLICATIONS: The specific transcriptional changes in BECs and blood identified here may guide early use of additional therapies.

PMID:36796454 | DOI:10.1016/j.jaci.2023.01.028

Science. 2023 Feb 17;379(6633):654-655. doi: 10.1126/science.adg5585. Epub 2023 Feb 16.

ABSTRACT

A mechanistic approach to overcoming treatment resistance reveals new targets.

PMID:36795815 | DOI:10.1126/science.adg5585

ACS Chem Biol. 2023 Feb 16. doi: 10.1021/acschembio.2c00908. Online ahead of print.

ABSTRACT

Biomolecular condensates formed by liquid-liquid phase separation have been implicated in multiple diseases. Modulation of condensate dynamics by small molecules has therapeutic potential, but so far, few condensate modulators have been disclosed. The SARS-CoV-2 nucleocapsid (N) protein forms phase-separated condensates that are hypothesized to play critical roles in viral replication, transcription, and packaging, suggesting that N condensation modulators might have anti-coronavirus activity across multiple strains and species. Here, we show that N proteins from all seven human coronaviruses (HCoVs) vary in their tendency to undergo phase separation when expressed in human lung epithelial cells. We developed a cell-based high-content screening platform and identified small molecules that both promote and inhibit condensation of SARS-CoV-2 N. Interestingly, these host-targeted small molecules exhibited condensate-modulatory effects across all HCoV Ns. Some have also been reported to exhibit antiviral activity against SARS-CoV-2, HCoV-OC43, and HCoV-229E viral infections in cell culture. Our work reveals that the assembly dynamics of N condensates can be regulated by small molecules with therapeutic potential. Our approach allows for screening based on viral genome sequences alone and might enable rapid paths to drug discovery with value for confronting future pandemics.

PMID:36795767 | DOI:10.1021/acschembio.2c00908

PLoS Pathog. 2023 Feb 16;19(2):e1011145. doi: 10.1371/journal.ppat.1011145. eCollection 2023 Feb.

NO ABSTRACT

PMID:36795674 | DOI:10.1371/journal.ppat.1011145

Elife. 2023 Feb 16;12:e86172. doi: 10.7554/eLife.86172.

ABSTRACT

A new method allows researchers to automatically assign cells into different cell types and tissues, a step which is critical for understanding complex organisms.

PMID:36795093 | DOI:10.7554/eLife.86172

Elife. 2023 Feb 16;12:e80918. doi: 10.7554/eLife.80918.

ABSTRACT

Electron microscopy (EM) provides a uniquely detailed view of cellular morphology, including organelles and fine subcellular ultrastructure. While the acquisition and (semi-)automatic segmentation of multicellular EM volumes are now becoming routine, large-scale analysis remains severely limited by the lack of generally applicable pipelines for automatic extraction of comprehensive morphological descriptors. Here, we present a novel unsupervised method for learning cellular morphology features directly from 3D EM data: a neural network delivers a representation of cells by shape and ultrastructure. Applied to the full volume of an entire three-segmented worm of the annelid Platynereis dumerilii, it yields a visually consistent grouping of cells supported by specific gene expression profiles. Integration of features across spatial neighbours can retrieve tissues and organs, revealing, for example, a detailed organisation of the animal foregut. We envision that the unbiased nature of the proposed morphological descriptors will enable rapid exploration of very different biological questions in large EM volumes, greatly increasing the impact of these invaluable, but costly resources.

PMID:36795088 | DOI:10.7554/eLife.80918

Bioinformatics. 2023 Feb 16:btad092. doi: 10.1093/bioinformatics/btad092. Online ahead of print.

ABSTRACT

MOTIVATION: Linkage disequilibrium (LD) matrices derived from large populations are widely used in population genetics in fine-mapping, LD score regression, and linear mixed models for Genome-wide Association Studies (GWAS). However, these matrices can reach large sizes when they are derived from millions of individuals; hence moving, sharing, and extracting granular information from this large amount of data can be very cumbersome.

RESULTS: We sought to address the need for compressing and easily querying large LD matrices by developing LDmat. LDmat is a standalone tool to compress large LD matrices in an HDF5 file format and query these compressed matrices. It can extract submatrices corresponding to a sub-region of the genome, a list of select loci, and loci within a minor allele frequency range. LDmat can also rebuild the original file formats from the compressed files.

AVAILABILITY AND IMPLEMENTATION: LDmat is implemented in python, and can be installed on Unix systems with the command 'pip install ldmat'. It can also be accessed through https://github.com/G2Lab/ldmat and https://pypi.org/project/ldmat/.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:36794924 | DOI:10.1093/bioinformatics/btad092

Elife. 2023 Feb 16;12:e82785. doi: 10.7554/eLife.82785. Online ahead of print.

ABSTRACT

Multiomics technologies improve the biological understanding of health status in people living with HIV on antiretroviral therapy (PLWH). Still, a systematic and in-depth characterization of metabolic risk profile during successful long-term treatment is lacking. Here, we used multi-omics (plasma lipidomic, metabolomic, and fecal 16S microbiome) data-driven stratification and characterization to identify the metabolic at-risk profile within PLWH. Through network analysis and similarity network fusion (SNF), we identified three groups of PLWH (SNF-1 to 3): healthy (HC)-like (SNF-1), mild at-risk (SNF-3), and severe at-risk (SNF-2). The PLWH in the SNF-2 (45%) had a severe at-risk metabolic profile with increased visceral adipose tissue, BMI, higher incidence of metabolic syndrome (MetS), and increased di- and triglycerides despite having higher CD4+ T-cell counts than the other two clusters. However, the HC-like and the severe at-risk group had a similar metabolic profile differing from HIV-negative controls (HNC), with dysregulation of amino acid metabolism. At the microbiome profile, the HC-like group had a lower α-diversity, a lower proportion of men having sex with men (MSM) and was enriched in Bacteroides. In contrast, in at-risk groups, there was an increase in Prevotella, with a high proportion of MSM, which could potentially lead to higher systemic inflammation and increased cardiometabolic risk profile. The multi-omics integrative analysis also revealed a complex microbial interplay of the microbiome-derived metabolites in PLWH. Those severely at-risk clusters may benefit from personalized medicine and lifestyle intervention to improve their dysregulated metabolic traits, aiming to achieve healthier aging.

PMID:36794912 | DOI:10.7554/eLife.82785

Curr Protoc. 2023 Feb;3(2):e667. doi: 10.1002/cpz1.667.

ABSTRACT

Oligonucleotide microarrays are used to investigate the interactome of nucleic acids. DNA microarrays are commercially available, whereas equivalent RNA microarrays are not. This protocol describes a method to convert DNA microarrays of any density and complexity into RNA microarrays using only readily available materials and reagents. This simple conversion protocol will facilitate the accessibility of RNA microarrays to a wide range of researchers. In addition to general considerations for the design of a template DNA microarray, this procedure describes the experimental steps of hybridization of an RNA primer to the immobilized DNA, followed by its covalent attachment via psoralen-mediated photocrosslinking. The subsequent enzymatic processing steps comprise the extension of the primer with T7 RNA polymerase to generate complementary RNA, and finally the removal of the DNA template with TURBO DNase. Beyond the conversion process, we also describe approaches to detect the RNA product either by internal labeling with fluorescently labeled NTPs or via hybridization to the product strand, a step that can then be complemented by an RNase H assay to confirm the nature of the product. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Conversion of a DNA microarray to an RNA microarray Alternate Protocol: Detection of RNA via incorporation of Cy3-UTP Support Protocol 1: Detection of RNA via hybridization Support Protocol 2: RNase H assay.

PMID:36794904 | DOI:10.1002/cpz1.667

Arterioscler Thromb Vasc Biol. 2023 Feb 16. doi: 10.1161/ATVBAHA.122.318731. Online ahead of print.

ABSTRACT

Cardiovascular diseases (CVD) are the leading cause of death worldwide and display complex phenotypic heterogeneity caused by many convergent processes, including interactions between genetic variation and environmental factors. Despite the identification of a large number of associated genes and genetic loci, the precise mechanisms by which these genes systematically influence the phenotypic heterogeneity of CVD are not well understood. In addition to DNA sequence, understanding the molecular mechanisms of CVD requires data from other omics levels, including the epigenome, the transcriptome, the proteome, as well as the metabolome. Recent advances in multiomics technologies have opened new precision medicine opportunities beyond genomics that can guide precise diagnosis and personalized treatment. At the same time, network medicine has emerged as an interdisciplinary field that integrates systems biology and network science to focus on the interactions among biological components in health and disease, providing an unbiased framework through which to integrate systematically these multiomics data. In this review, we briefly present such multiomics technologies, including bulk omics and single-cell omics technologies, and discuss how they can contribute to precision medicine. We then highlight network medicine-based integration of multiomics data for precision medicine and therapeutics in CVD. We also include a discussion of current challenges, potential limitations, and future directions in the study of CVD using multiomics network medicine approaches.

PMID:36794589 | DOI:10.1161/ATVBAHA.122.318731

Plant Physiol. 2023 Feb 16:kiad093. doi: 10.1093/plphys/kiad093. Online ahead of print.

ABSTRACT

Most studies investigating quantitative traits focus on mean levels per genotype rather than the variation between different individuals of one genotype or the variation elicited by different environments. Consequently, the genes that govern this effect are not well understood. The concept, named canalization, which describes a lack of variation, is well-known in the context of developmental processes but is poorly studied for quantitative traits such as metabolism. In this study, we selected eight putative candidate genes from previously identified canalized metabolic quantitative trait loci (cmQTL) and created genome-edited tomato (Solanum lycopersicum) mutants of these genes for experimental validation. Most lines showed wild-type morphology, except for an ADP-ribosylation factor (ARLB) mutant showing aberrant phenotypes in the form of scarred fruit cuticles. In greenhouse trials with different irrigation conditions, whole-plant traits showed a general increase of their level towards the more optimal irrigation conditions, whereas most metabolic traits showed an increase towards the other end of the gradient. Mutants of a PANTOTHENATE KINASE 4 (PANK4), the AIRP ubiquitin gene LOSS OF GDU2 (LOG2), and TRANSPOSON PROTEIN 1 (TRANSP1) grown under these conditions showed an overall improved plant performance. Additional effects, on both target and other metabolites in tomato fruits, regarding the mean level at specific conditions and, ergo, the cross-environment coefficient of variation (CV), were observed. However, variation between individuals remained unaffected. In conclusion, this study supports the idea of distinct sets of genes regulating different types of variation.

PMID:36794426 | DOI:10.1093/plphys/kiad093

Phage (New Rochelle). 2022 Dec 1;3(4):213-220. doi: 10.1089/phage.2022.0033. Epub 2022 Dec 19.

ABSTRACT

BACKGROUND: Gibson assembly and assembly-in-yeast are strategies to create long synthetic DNAs from diverse fragments, for example, when engineering bacteriophage genomes. Design for these methods requires terminal sequence overlaps in the fragments, determining the order of assembly. Design to rebuild a genomic fragment that is too long for a single PCR presents a puzzle since some candidate joint regions cannot yield satisfactory primers for the overlap. No existing overlap assembly design software is open-source, and none explicitly supports rebuilding.

METHODS: We describe here bigDNA software that solves the rebuilding puzzle by recursive backtracking, with options to remove or introduce genes; it also tests for mispriming on the template DNA. BigDNA was tested with 3082 prophages and other genomic islands (GIs), from 20 to 100 kb, and the synthetic Mycoplasma genitalium genome.

RESULTS: Rebuilding assembly design succeeded for all but ∼1% of GIs.

CONCLUSION: BigDNA will speed and standardize assembly design.

PMID:36793884 | PMC:PMC9917320 | DOI:10.1089/phage.2022.0033