Antioxidants (Basel). 2023 Jul 21;12(7):1468. doi: 10.3390/antiox12071468.

ABSTRACT

Malaria is still the most important parasitic infectious disease. Numerous substances are known to have antimalarial activity; among them, artemisinin is the most widely used one, and artemisinin-based combination therapy (ACT) is recommended for the treatment of Plasmodium falciparum (P.f.) malaria. Antitumor, immunomodulatory, and other therapeutic applications of artemisinin are under extensive study. Several different mechanisms of action were proposed for dihydroartemisinin (DHA), the active metabolite of artemisinin, such as eliciting oxidative stress in target cells. The goal of this study is to monitor the generation of reactive oxygen species (ROS) and lipid peroxidation product 4-hydroxynonenal (4-HNE) by DHA in P.f.-infected human erythrocytes. Checking ROS and 4-HNE-protein adducts kinetics along the maturation of the parasite, we detected the highest level of 4-HNE in ring forms of P.f. due to DHA treatment. Low micromolar concentrations of DHA quickly induced levels of 4-HNE-adducts which are supposed to be damaging. Mass spectrometry identified the P.f. protein cysteine proteinase falcipain-1 as being heavily modified by 4-HNE, and plausibly, 4-HNE conjugation with vital P.f. proteins might contribute to DHA-elicited parasite death. In conclusion, significant 4-HNE accumulation was detectable after DHA treatment, though, at concentrations well above pharmacologically effective ranges in malaria treatment, but at concentrations described for antitumor activity. Thus, lipid peroxidation with consequent 4-HNE conjugation of functionally relevant proteins might be considered as a uniform mechanism for how DHA potentiates antimalarials' action in ACT and controls the progression of tumors.

PMID:37508006 | DOI:10.3390/antiox12071468

J Transl Med. 2023 Jul 28;21(1):508. doi: 10.1186/s12967-023-04325-x.

ABSTRACT

Outcomes for patients with melanoma have improved over the past decade with the clinical development and approval of immunotherapies targeting immune checkpoint receptors such as programmed death-1 (PD-1), programmed death ligand 1 (PD-L1) or cytotoxic T lymphocyte antigen-4 (CTLA-4). Combinations of these checkpoint therapies with other agents are now being explored to improve outcomes and enhance benefit-risk profiles of treatment. Alternative inhibitory receptors have been identified that may be targeted for anti-tumor immune therapy, such as lymphocyte-activation gene-3 (LAG-3), as have several potential target oncogenes for molecularly targeted therapy, such as tyrosine kinase inhibitors. Unfortunately, many patients still progress and acquire resistance to immunotherapy and molecularly targeted therapies. To bypass resistance, combination treatment with immunotherapies and single or multiple TKIs have been shown to improve prognosis compared to monotherapy. The number of new combinations treatment under development for melanoma provides options for the number of patients to achieve a therapeutic benefit. Many diagnostic and prognostic assays have begun to show clinical applicability providing additional tools to optimize and individualize treatments. However, the question on the optimal algorithm of first- and later-line therapies and the search for biomarkers to guide these decisions are still under investigation. This year, the Melanoma Bridge Congress (Dec 1st-3rd, 2022, Naples, Italy) addressed the latest advances in melanoma research, focusing on themes of paramount importance for melanoma prevention, diagnosis and treatment. This included sessions dedicated to systems biology on immunotherapy, immunogenicity and gene expression profiling, biomarkers, and combination treatment strategies.

PMID:37507765 | DOI:10.1186/s12967-023-04325-x

Cell Discov. 2023 Jul 28;9(1):78. doi: 10.1038/s41421-023-00581-9.

ABSTRACT

The bat coronaviruses (CoV) BANAL-20-52 and BANAL-20-236 are two newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) closely related coronaviruses (SC2r-CoV) and the genome of BANAL-20-52 shares the highest homology with SARS-CoV-2. However, the risk of their potential zoonotic transmission has not been fully evaluated. Here, we determined their potential host susceptibility among 13 different bat species and 26 different animal species, and found that both might have extensive host ranges, indicating high zoonotic transmission potential. We also determined the cryo-EM structures of BANAL-20-52 and BANAL-20-236 S proteins at pH 5.5 and the complex of BANAL-20-236 S1 and Rhinolophus affinis ACE2, and found that both trimeric S proteins adopt all three receptor binding domains (RBDs) in "closed" conformation and are more compact than SARS-CoV-2. Strikingly, the unique sugar moiety at N370 of bat SC2r-CoVs acts like a "bolt" and crosses over two neighboring subunits, facilitating the S proteins in the locked conformation and underpinning the architecture stability. Removal of the glycosylation at N370 by a T372A substitution substantially enhances virus infectivity but becomes highly sensitive to trypsin digestion at pH 5.5, a condition roughly mimicking the insectivorous bat's stomach digestion. In contrast, WT S proteins of SC2r-CoVs showed considerable resistance to trypsin digestion at pH 5.5, indicating that the highly conserved T372 in bat CoVs might result from the selective advantages in stability during the fecal-oral transmission over A372. Moreover, the results of cross-immunogenicity among S proteins of SARS-CoV-2, BANAL-20-52, and BANAL-20-236 showed that A372 pseudoviruses are more sensitive to anti-S sera than T372, indicating that immune evasion might also play a role in the natural selection of T372 over A372 during evolution. Finally, residues 493 and 498 of the S protein affect host susceptibility, and residue 498 also influences the immunogenicity of the S protein. Together, our findings aid a better understanding of the molecular basis of CoV entry, selective evolution, and immunogenicity and highlight the importance of surveillance of susceptible hosts of these viruses to prevent potential outbreaks.

PMID:37507385 | DOI:10.1038/s41421-023-00581-9

New Phytol. 2023 Jul 28. doi: 10.1111/nph.19154. Online ahead of print.

ABSTRACT

Plants can rapidly mitigate the effects of suboptimal growth environments by phenotypic plasticity of fitness-traits. While genetic variation for phenotypic plasticity offers the means for breeding climate-resilient crop lines, accurate genomic prediction models for plasticity of fitness-related traits are still lacking. Here, we employed condition- and accession-specific metabolic models for 67 Arabidopsis thaliana accessions to dissect and predict plasticity of rosette growth to changes in nitrogen availability. We showed that specific reactions in photorespiration, linking carbon and nitrogen metabolism, as well as key pathways of central carbon metabolism exhibited substantial genetic variation for flux plasticity. We also demonstrated that, in comparison with a genomic prediction model for fresh weight (FW), genomic prediction of growth plasticity improves the predictability of FW under low nitrogen by 58.9% and by additional 15.4% when further integrating data on plasticity of metabolic fluxes. Therefore, the combination of metabolic and statistical modeling provides a stepping stone in understanding the molecular mechanisms and improving the predictability of plasticity for fitness-related traits.

PMID:37507350 | DOI:10.1111/nph.19154

Mol Oncol. 2023 Jul 28. doi: 10.1002/1878-0261.13496. Online ahead of print.

ABSTRACT

TWIST1 (TW) is a pro-oncogenic basic helix-loop-helix (bHLH) transcription factor and promotes the hallmark features of malignancy (e.g., cell invasion, cancer cell stemness and treatment resistance), which contribute to poor prognoses of glioblastoma (GBM). We previously reported that specific TW dimerization motifs regulate unique cellular phenotypes in GBM. For example, the TW:E12 heterodimer increases periostin (POSTN) expression and promotes cell invasion. TW dimer-specific transcriptional regulation requires binding to the regulatory E-box consensus sequences, but alternative bHLH dimers that balance TW dimer activity in regulating pro-oncogenic TW target genes are unknown. We leveraged the ENCODE DNase I hypersensitivity data to identify E-box sites and tethered TW:E12 and TW:TW proteins to validate dimer binding to E-boxes in vitro. Subsequently, TW knockdown revealed a novel TCF4:TCF12 bHLH dimer occupying the same TW E-box site that, when expressed as a tethered TCF4:TCF12 dimer, markedly repressed POSTN expression and extended animal survival. These observations support TCF4:TCF12 as a novel dimer with tumor-suppressor activity in GBM that functions in part through displacement of and/or competitive inhibition of pro-oncogenic TW dimers at E-box sites.

PMID:37507199 | DOI:10.1002/1878-0261.13496

Adv Microb Physiol. 2023;83:221-307. doi: 10.1016/bs.ampbs.2023.05.003. Epub 2023 Jun 27.

ABSTRACT

Gram-negative bacteria are uniquely equipped to defeat antibiotics. Their outermost layer, the cell envelope, is a natural permeability barrier that contains an array of resistance proteins capable of neutralizing most existing antimicrobials. As a result, its presence creates a major obstacle for the treatment of resistant infections and for the development of new antibiotics. Despite this seemingly impenetrable armor, in-depth understanding of the cell envelope, including structural, functional and systems biology insights, has promoted efforts to target it that can ultimately lead to the generation of new antibacterial therapies. In this article, we broadly overview the biology of the cell envelope and highlight attempts and successes in generating inhibitors that impair its function or biogenesis. We argue that the very structure that has hampered antibiotic discovery for decades has untapped potential for the design of novel next-generation therapeutics against bacterial pathogens.

PMID:37507160 | DOI:10.1016/bs.ampbs.2023.05.003

Brief Bioinform. 2023 Jul 28:bbad265. doi: 10.1093/bib/bbad265. Online ahead of print.

ABSTRACT

Advances in single-cell multi-omics technology provide an unprecedented opportunity to fully understand cellular heterogeneity. However, integrating omics data from multiple modalities is challenging due to the individual characteristics of each measurement. Here, to solve such a problem, we propose a contrastive and generative deep self-expression model, called single-cell multimodal self-expressive integration (scMSI), which integrates the heterogeneous multimodal data into a unified manifold space. Specifically, scMSI first learns each omics-specific latent representation and self-expression relationship to consider the characteristics of different omics data by deep self-expressive generative model. Then, scMSI combines these omics-specific self-expression relations through contrastive learning. In such a way, scMSI provides a paradigm to integrate multiple omics data even with weak relation, which effectively achieves the representation learning and data integration into a unified framework. We demonstrate that scMSI provides a cohesive solution for a variety of analysis tasks, such as integration analysis, data denoising, batch correction and spatial domain detection. We have applied scMSI on various single-cell and spatial multimodal datasets to validate its high effectiveness and robustness in diverse data types and application scenarios.

PMID:37507114 | DOI:10.1093/bib/bbad265

J Proteomics. 2023 Jul 26:104978. doi: 10.1016/j.jprot.2023.104978. Online ahead of print.

ABSTRACT

Protein C-termini containing valuable biological information plays a vital role in various physiological processes, such as protein localization, protein recognition, and signal transduction in organisms. However, C-terminal peptide identification is still challenging due to their low abundance and similar physicochemical properties to other digested peptides. Herein, we developed a simple and mild strategy for the enrichment of C-terminal peptides that incorporates selectively 2-pyridinecarbaldehyde (2-PCA) derivatization of α-amine with negative enrichment by NHS resin. Two synthesized peptides were utilized to evaluate the efficiency of 2-PCA derivatization and optimize the coupling conditions of NHS resin. The feasibility of the method was further validated by enriching the C-terminus of the bovine serum albumin (BSA). Finally, this method was successfully applied to the C-terminus analysis of mouse brain tissue, identifying 404 protein C-termini with physicochemical properties unbiasedly. Additionally, the GO and KEGG analyses revealed that these identified proteins are crucial for proper brain function. In summary, our proposed method is effective and has the potential to facilitate comprehensive C-terminal analysis of proteins. SIGNIFICANCE: Effective enrichment methods are essential for the identification of the proteins C-terminus. In this study, a mild and simple method for negative C-terminal enrichment combined with site-specific derivatization was developed. The enrichment process was simplified and minimized sample loss simultaneously, using 2-PCA derivatization which has high α-amino specificity. Up to 346C-terminal proteins were identified in mouse brain tissue unbiasedly and reliably. This approach has the potential to facilitate comprehensive analysis of protein C-termini in a variety of biological contexts.

PMID:37507008 | DOI:10.1016/j.jprot.2023.104978

Mol Cell. 2023 Jul 20:S1097-2765(23)00516-6. doi: 10.1016/j.molcel.2023.07.002. Online ahead of print.

ABSTRACT

Splicing of pre-mRNAs critically contributes to gene regulation and proteome expansion in eukaryotes, but our understanding of the recognition and pairing of splice sites during spliceosome assembly lacks detail. Here, we identify the multidomain RNA-binding protein FUBP1 as a key splicing factor that binds to a hitherto unknown cis-regulatory motif. By collecting NMR, structural, and in vivo interaction data, we demonstrate that FUBP1 stabilizes U2AF2 and SF1, key components at the 3' splice site, through multivalent binding interfaces located within its disordered regions. Transcriptional profiling and kinetic modeling reveal that FUBP1 is required for efficient splicing of long introns, which is impaired in cancer patients harboring FUBP1 mutations. Notably, FUBP1 interacts with numerous U1 snRNP-associated proteins, suggesting a unique role for FUBP1 in splice site bridging for long introns. We propose a compelling model for 3' splice site recognition of long introns, which represent 80% of all human introns.

PMID:37506698 | DOI:10.1016/j.molcel.2023.07.002

Immunity. 2023 Jul 19:S1074-7613(23)00315-1. doi: 10.1016/j.immuni.2023.07.001. Online ahead of print.

ABSTRACT

Conventional dendritic cells (cDCs) are professional antigen-presenting cells that control the adaptive immune response. Their subsets and developmental origins have been intensively investigated but are still not fully understood as their phenotypes, especially in the DC2 lineage and the recently described human DC3s, overlap with monocytes. Here, using LEGENDScreen to profile DC vs. monocyte lineages, we found sustained expression of FLT3 and CD45RB through the whole DC lineage, allowing DCs and their precursors to be distinguished from monocytes. Using fate mapping models, single-cell RNA sequencing and adoptive transfer, we identified a lineage of murine CD16/32+CD172a+ DC3, distinct from DC2, arising from Ly6C+ monocyte-DC progenitors (MDPs) through Lyz2+Ly6C+CD11c- pro-DC3s, whereas DC2s develop from common DC progenitors (CDPs) through CD7+Ly6C+CD11c+ pre-DC2s. Corresponding DC subsets, developmental stages, and lineages exist in humans. These findings reveal DC3 as a DC lineage phenotypically related to but developmentally different from monocytes and DC2s.

PMID:37506694 | DOI:10.1016/j.immuni.2023.07.001

Sci Adv. 2023 Jul 28;9(30):eadd8766. doi: 10.1126/sciadv.add8766. Epub 2023 Jul 28.

ABSTRACT

Soluble human lectins are critical components of innate immunity. Genetic models suggest that lectins influence host-resident microbiota, but their specificity for commensal and mutualist species is understudied. Elucidating lectins' roles in regulating microbiota requires an understanding of which microbial species they bind within native communities. To profile human lectin recognition, we developed Lectin-Seq. We apply Lectin-Seq to human fecal microbiota using the soluble mannose-binding lectin (MBL) and intelectin-1 (hItln1). Although each lectin binds a substantial percentage of the samples (10 to 20%), the microbial interactomes of MBL and hItln1 differ markedly in composition and diversity. MBL binding is highly selective for a small subset of species commonly associated with humans. In contrast, hItln1's interaction profile encompasses a broad range of lower-abundance species. Our data uncover stark differences in the commensal recognition properties of human lectins.

PMID:37506208 | DOI:10.1126/sciadv.add8766

Sci Immunol. 2023 Jul 28;8(85):eadd1591. doi: 10.1126/sciimmunol.add1591. Epub 2023 Jul 28.

ABSTRACT

Immune checkpoint inhibitor (ICI) therapies used to treat cancer, such as anti-PD-1 antibodies, can induce autoimmune conditions in some individuals. The T cell mechanisms mediating such iatrogenic autoimmunity and their overlap with spontaneous autoimmune diseases remain unclear. Here, we compared T cells from the joints of 20 patients with an inflammatory arthritis induced by ICI therapy (ICI-arthritis) with two archetypal autoimmune arthritides, rheumatoid arthritis (RA) and psoriatic arthritis (PsA). Single-cell transcriptomic and antigen receptor repertoire analyses highlighted clonal expansion of an activated effector CD8 T cell population in the joints and blood of patients with ICI-arthritis. These cells were identified as CD38hiCD127- CD8 T cells and were uniquely enriched in ICI-arthritis joints compared with RA and PsA and also displayed an elevated interferon signature. In vitro, type I interferon induced CD8 T cells to acquire the ICI-associated CD38hi phenotype and enhanced cytotoxic function. In a cohort of patients with advanced melanoma, ICI therapy markedly expanded circulating CD38hiCD127- T cells, which were frequently bound by the therapeutic anti-PD-1 drug. In patients with ICI-arthritis, drug-bound CD8 T cells in circulation showed marked clonal overlap with drug-bound CD8 T cells from synovial fluid. These results suggest that ICI therapy directly targets CD8 T cells in patients who develop ICI-arthritis and induces an autoimmune pathology that is distinct from prototypical spontaneous autoimmune arthritides.

PMID:37506196 | DOI:10.1126/sciimmunol.add1591

Immun Inflamm Dis. 2023 Jul;11(7):e914. doi: 10.1002/iid3.914.

ABSTRACT

AIM: Impaired apoptosis and proliferation resulted in autoreactive lymphocyte development and inflammation in Rheumatoid arthritis (RA). TP53, BAX, FOXO1, and RB1 are related genes in cell survival, proliferation, and inflammation which could be important in RA development and disease severity. Here we investigated their expression in peripheral blood mononuclear cells (PBMCs) from RA patients in comparison to healthy controls.

METHODS: Fifty healthy controls and 50 RA patients were selected. The quantitative real-time polymerase chain reaction was used to assess the gene expression level in PBMCs.

RESULTS: The mRNA expression of TP53 (FC = 0.65, p = .000), BAX (FC = 0.76, p = .008), FOXO1 (FC = 0.59, p = .000) and RB1 (FC = 0.50, p = .000) were significantly reduced in RA PBMCs. TP53 expression was negatively correlated with miR-16-5p (p = .032) and FOXO1 expression was negatively correlated with miR-335-5p (p = .005) and miR-34a-5p (p = .014). A positive correlation was seen between TP53 expression and its downstream gene, BAX (p = .001). FOXO1 expression was also negatively correlated with disease activity, DAS28 (p = .021).

CONCLUSION: All selected genes have downregulated expression in RA PBMCs which could be correlated with RA pathogenesis by regulating apoptosis, cell survival, inflammatory mediator production, and proliferation. Due to the correlation of miR-16-5p, miR-34a-5p, and miR-335-5p with TP53 and FOXO1 expression in RA PBMCs, they could be used as future therapeutic targets.

PMID:37506143 | DOI:10.1002/iid3.914

PLoS One. 2023 Jul 28;18(7):e0288595. doi: 10.1371/journal.pone.0288595. eCollection 2023.

ABSTRACT

Ecological Niche Modeling is widely used for animals, but rarely for understanding the parasite ecology. Trypanosoma cruzi is a heterogeneous and widely dispersed multi-host parasite. Didelphis aurita is a generalist species, both in terms of diet and environments. We modeled the D. aurita niche and T. cruzi infection in the Brazilian Atlantic Rainforest, using the models of two common vector species (Triatoma vitticeps and Panstrongylus megistus) as biotic variables, predicting their occurrence. Records of T. cruzi infected and non-infected D. aurita were analyzed through climate and landscape approaches by the Ecoland method. Models for each triatomine species and infected and noninfected D. aurita were produced considering climate and landscape: resolution of ~1km2 selected by Pearson's correlation [-0.7≤α≤0.7]. For modeling, seven algorithms available in ModleR package were used. True Skill Statistic was used to evaluate the models' performance (≥ 0.7). T. vitticeps indicates that there is a spatial dependence with warm areas in the southeastern region while P. megistus presented a distribution with high environmental suitability concentrated in the Southeast. High values of climatic suitability, landscape and potential presence of T. vitticeps and P. megistus were considered necessary, but not sufficient for the presence of D. aurita infected by T. cruzi. Climate models showed an ecological niche with suitability variations homogeneous, and landscape models showed a distribution of habitat conditions along the biome, with a fragmented profile and heterogeneous between locations. Ecoland demonstrated that D. aurita has different degrees of impact on its role in the enzootic cycle in different locations of the Atlantic Rainforest. Associating the models with the Ecoland method allowed the recognition of areas where D. aurita are important T. cruzi reservoirs. Areas of high suitability for the presence of marsupials are a necessary, but not sufficient for D. aurita to act as a reservoir for T. cruzi.

PMID:37506103 | DOI:10.1371/journal.pone.0288595

Toxins (Basel). 2023 Jul 9;15(7):451. doi: 10.3390/toxins15070451.

ABSTRACT

Venoms are a diverse and complex group of natural toxins that have been adapted to treat many types of human disease, but rigorous computational approaches for discovering new therapeutic activities are scarce. We have designed and validated a new platform-named VenomSeq-to systematically identify putative associations between venoms and drugs/diseases via high-throughput transcriptomics and perturbational differential gene expression analysis. In this study, we describe the architecture of VenomSeq and its evaluation using the crude venoms from 25 diverse animal species and 9 purified teretoxin peptides. By integrating comparisons to public repositories of differential expression, associations between regulatory networks and disease, and existing knowledge of venom activity, we provide a number of new therapeutic hypotheses linking venoms to human diseases supported by multiple layers of preliminary evidence.

PMID:37505720 | DOI:10.3390/toxins15070451

J Fungi (Basel). 2023 Jul 17;9(7):754. doi: 10.3390/jof9070754.

ABSTRACT

Repeated macrofungal explorations, followed by thorough examination of species through morphology and molecular phylogeny, have made it clear that European and American names of wild mushrooms were inadvertently misapplied quite often to Asian lookalikes by mycologists/taxonomists in the past. Therefore, in order to reveal this mushroom treasure, in recent years, taxonomical research on wild mushrooms has been intensified in Asian countries, including India, by undertaking a combined approach of morpho-taxonomy and multigene molecular phylogeny. Boletoid mushrooms (Boletaceae) are no exception. While working on boletoid mushrooms of the Indian Himalayas, authors recently came across six interesting species of boletoid mushrooms. In the present communication, four novel species, namely Leccinellum binderi, Cyanoboletus paurianus, Xerocomus uttarakhandae, and Xerocomellus himalayanus, are established based on morphology and molecular phylogenetic estimations. Moreover, Cyanoboletus macroporus and Xerocomus fraternus are also reported here for the first time in India.

PMID:37504742 | DOI:10.3390/jof9070754

Curr Issues Mol Biol. 2023 Jul 21;45(7):6097-6115. doi: 10.3390/cimb45070385.

ABSTRACT

Mitochondria in mammalian cardiomyocytes display considerable structural heterogeneity, the significance of which is not currently understood. We use electron microscopic tomography to analyze a dataset of 68 mitochondrial subvolumes to look for correlations among mitochondrial size and shape, crista morphology and membrane density, and organelle location within rat cardiac myocytes. A tomographic analysis guided the definition of four classes of crista morphology: lamellar, tubular, mixed and transitional, the last associated with remodeling between lamellar and tubular cristae. Correlations include an apparent bias for mitochondria with lamellar cristae to be located in the regions between myofibrils and a two-fold larger crista membrane density in mitochondria with lamellar cristae relative to mitochondria with tubular cristae. The examination of individual cristae inside mitochondria reveals local variations in crista topology, such as extent of branching, alignment of fenestrations and progressive changes in membrane morphology and packing density. The findings suggest both a rationale for the interfibrillar location of lamellar mitochondria and a pathway for crista remodeling from lamellar to tubular morphology.

PMID:37504301 | DOI:10.3390/cimb45070385

Curr Issues Mol Biol. 2023 Jul 14;45(7):5879-5901. doi: 10.3390/cimb45070372.

ABSTRACT

Multidisciplinary research efforts on potential COVID-19 vaccine and therapeutic candidates have increased since the pandemic outbreak of SARS-CoV-2 in 2019. This search has become imperative due to the increasing emergences and limited widely available medicines. The presence of bioactive anti-SARS-CoV-2 molecules was examined from various plant sources. Among them is a group of proteins called lectins that can bind carbohydrate moieties. In this article, we present ten novel, chitin-specific Hevein-like lectins that were derived from Selaginella moellendorffii v1.0's genome. The capacity of these lectin homologs to bind with the spike protein of SARS-CoV-2 was examined. Using the HDOCK server, 3D-modeled Hevein-domains were docked to the spike protein's receptor binding domain (RBD). The Smo446851, Smo125663, and Smo99732 interacted with Asn343-located complex N-glycan and RBD residues, respectively, with binding free energies of -17.5, -13.0, and -26.5 Kcal/mol. The molecular dynamics simulation using Desmond and the normal-state analyses via torsional coordinate association for the Smo99732-RBD complex using iMODS is characterized by overall higher stability and minimum deformity than the other lectin complexes. The three lectins interacting with carbohydrates were docked against five individual mutations that frequently occur in major SARS-CoV-2 variants. These were in the spike protein's receptor-binding motif (RBM), while Smo125663 and Smo99732 only interacted with the spike glycoprotein in a protein-protein manner. The precursors for the Hevein-like homologs underwent additional characterization, and their expressional profile in different tissues was studied. These in silico findings offered potential lectin candidates targeting key N-glycan sites crucial to the virus's virulence and infection.

PMID:37504288 | DOI:10.3390/cimb45070372

bioRxiv. 2023 Jul 21:2023.07.19.549722. doi: 10.1101/2023.07.19.549722. Preprint.

ABSTRACT

MOTIVATION: Annotations of biochemical models provide details of chemical species, documentation of chemical reactions, and other essential information. Unfortunately, the vast majority of biochemical models have few, if any, annotations, or the annotations provide insufficient detail to understand the limitations of the model. The quality and quantity of annotations can be improved by developing tools that recommend annotations. For example, recommender tools have been developed for annotations of genes. Although annotating genes is conceptually similar to annotating biochemical models, there are important technical differences that make it difficult to directly apply this prior work.

RESULTS: We present AMAS, a system that predicts annotations for elements of models represented in the Systems Biology Markup Language (SBML) community standard. We provide a general framework for predicting model annotations for a query element based on a database of annotated reference elements and a match score function that calculates the similarity between the query element and reference elements. The framework is instantiated to specific element types (e.g., species, reactions) by specifying the reference database (e.g., ChEBI for species) and the match score function (e.g., string similarity). We analyze the computational efficiency and prediction quality of AMAS for species and reactions in BiGG and BioModels and find that it has sub-second response times and accuracy between 80% and 95% depending on specifics of what is predicted. We have incorporated AMAS into an open-source, pip-installable Python package that can run as a command-line tool that predicts and adds annotations to species and reactions to an SBML model.

AVAILABILITY: Our project is hosted at https://github.com/sys-bio/AMAS , where we provide examples, documentation, and source code files. Our source code is licensed under the MIT open-source license.

CONTACT: hsauro@uw.edu.

SUPPLEMENTARY INFORMATION: Supplementary data are available online.

PMID:37503075 | PMC:PMC10370092 | DOI:10.1101/2023.07.19.549722

bioRxiv. 2023 Jul 11:2023.07.10.548432. doi: 10.1101/2023.07.10.548432. Preprint.

ABSTRACT

Protein copy numbers constrain systems-level properties of regulatory networks, but absolute proteomic data remain scarce compared to transcriptomics obtained by RNA sequencing. We addressed this persistent gap by relating mRNA to protein statistically using best-available data from quantitative proteomics-transcriptomics for 4366 genes in 369 cell lines. The approach starts with a central estimate of protein copy number and hierarchically appends mRNA-protein and mRNA-mRNA dependencies to define an optimal gene-specific model that links mRNAs to protein. For dozens of independent cell lines and primary prostate samples, these protein inferences from mRNA outmatch stringent null models, a count-based protein-abundance repository, and empirical protein-to-mRNA ratios. The optimal mRNA-to-protein relationships capture biological processes along with hundreds of known protein-protein interaction complexes, suggesting mechanistic relationships are embedded. We use the method to estimate viral-receptor abundances of CD55-CXADR from human heart transcriptomes and build 1489 systems-biology models of coxsackievirus B3 infection susceptibility. When applied to 796 RNA sequencing profiles of breast cancer from The Cancer Genome Atlas, inferred copy-number estimates collectively reclassify 26% of Luminal A and 29% of Luminal B tumors. Protein-based reassignments strongly involve a pharmacologic target for luminal breast cancer (CDK4) and an α-catenin that is often undetectable at the mRNA level (CTTNA2). Thus, by adopting a gene-centered perspective of mRNA-protein covariation across different biological contexts, we achieve accuracies comparable to the technical reproducibility limits of contemporary proteomics. The collection of gene-specific models is assembled as a web tool for users seeking mRNA-guided predictions of absolute protein abundance ( http://janeslab.shinyapps.io/Pinferna ).

SIGNIFICANCE STATEMENT: It is easier to quantify mRNA in cells than it is to quantify protein, but proteins are what execute most cellular functions. Even though protein is synthesized from mRNA in cells, relating a cellular quantity of mRNA to a quantity of protein is challenging. Here, we bring together quantitative measures of mRNA and protein for 4366 genes in 369 different cultured cell types to build equations that predict protein abundance from the abundance of mRNAs expressed. These equations capture facets of biological regulation and work better than existing alternatives that rely on consensus values or ratios. Since mRNA measurements are more widespread than protein, this study makes new analyses possible by protein estimation from mRNA.

PMID:37503057 | PMC:PMC10369941 | DOI:10.1101/2023.07.10.548432