Eur Heart J. 2023 Apr 3:ehad170. doi: 10.1093/eurheartj/ehad170. Online ahead of print.

ABSTRACT

There is a pandemic of physical inactivity that appears to parallel the widespread prevalence of cardiovascular disease (CVD). Yet, regular physical activity (PA) and exercise can play an important role not only in primary cardiovascular prevention but also in secondary prevention. This review discusses some of the main cardiovascular effects of PA/exercise and the mechanisms involved, including a healthier metabolic milieu with attenuation of systemic chronic inflammation, as well as adaptations at the vascular (antiatherogenic effects) and heart tissue (myocardial regeneration and cardioprotection) levels. The current evidence for safe implementation of PA and exercise in patients with CVD is also summarized.

PMID:37005351 | DOI:10.1093/eurheartj/ehad170

Biomed Pharmacother. 2023 Mar 31;162:114616. doi: 10.1016/j.biopha.2023.114616. Online ahead of print.

ABSTRACT

With an aging population and the numerous health impacts associated with old age, the identification of anti-aging drugs has become an important new research direction. Although mitochondria have been recognized to affect aging, anti-aging drugs specifically targeting the mitochondria are less well characterized. In this study, diphenyleneiodonium (DPI) was identified as a potential senomorphic drug that functions by promoting mitochondrial fission. DPI significantly reduced the number of senescence-associated β-galactosidase (SA-β-gal) positive cells and increased the number of proliferating Ki-67 positive cells in BrdU or irradiation stress-induced senescent NIH3T3 cells or IMR90 cells and mouse embryonic fibroblasts (MEFs) replicative senescent cells. Cell cycle arrest genes and senescence-associated secretory phenotype (SASP) factors were downregulated with DPI treatment. In addition, the oxygen consumption rate (OCR) of mitochondrial respiration showed that DPI significantly reduced senescence-associated hyper OCR. Mechanistically, DPI promoted mitochondrial fission by enhancing AMPK/MFF phosphorylation and DRP1 mitochondrial translocation. Inhibition of DRP1 by Mdivi-1 abolished DPI-induced mitochondrial fission and the anti-senescence phenotype. Importantly, Eighty-eight-week-old mice treated with DPI had significantly reduced numbers of SA-β-gal positive cells and reduced expression of cell cycle arrest genes and SASP factors in their livers and kidneys. Pathological and functional assays showed DPI treatment not only reduced liver fibrosis and immune cell infiltration but also improved aged-related physical impairments in aged mice. Taken together, our study identified a potential anti-aging compound that exerts its effects through modulation of mitochondrial morphology.

PMID:37004322 | DOI:10.1016/j.biopha.2023.114616

Curr Opin Biotechnol. 2023 Mar 31;81:102922. doi: 10.1016/j.copbio.2023.102922. Online ahead of print.

ABSTRACT

The reproducibility of scientific research is crucial to the success of the scientific method. Here, we review the current best practices when publishing mechanistic models in systems biology. We recommend, where possible, to use software engineering strategies such as testing, verification, validation, documentation, versioning, iterative development, and continuous integration. In addition, adhering to the Findable, Accessible, Interoperable, and Reusable modeling principles allows other scientists to collaborate and build off of each other's work. Existing standards such as Systems Biology Markup Language, CellML, or Simulation Experiment Description Markup Language can greatly improve the likelihood that a published model is reproducible, especially if such models are deposited in well-established model repositories. Where models are published in executable programming languages, the source code and their data should be published as open-source in public code repositories together with any documentation and testing code. For complex models, we recommend container-based solutions where any software dependencies and the run-time context can be easily replicated.

PMID:37004298 | DOI:10.1016/j.copbio.2023.102922

J Exp Bot. 2023 Apr 2:erad123. doi: 10.1093/jxb/erad123. Online ahead of print.

ABSTRACT

Lateral root initiation requires the accumulation of auxin in lateral root founder cells, yielding a local auxin maximum. The positioning of auxin maxima along the primary root determines the density and spacing of lateral roots. The GOLVEN6 (GLV6) and GLV10 signaling peptides and their receptors have been established as regulators of lateral root spacing via their inhibitory effect on lateral root initiation in Arabidopsis. However, it remained unclear how these GLV peptides interfere with auxin signaling or homeostasis. Here, we show that GLV6/10 signaling regulates the expression of a subset of auxin response genes, downstream of the canonical auxin signaling pathway, while simultaneously inhibiting the establishment of auxin maxima within xylem-pole pericycle cells that neighbor lateral root initiation sites. We present genetic evidence that this inhibitory effect relies on the activity of the PIN3 and PIN7 auxin export proteins. Furthermore, GLV6/10 peptide signaling was found to enhance PIN7 abundance in the plasma membranes of xylem-pole pericycle cells, which likely stimulates auxin efflux from these cells. Based on these findings, we propose a model in which the GLV6/10 signaling pathway serves as a negative feedback mechanism that contributes to the robust patterning of auxin maxima along the primary root.

PMID:37004244 | DOI:10.1093/jxb/erad123

Bioinformatics. 2023 Apr 2:btad158. doi: 10.1093/bioinformatics/btad158. Online ahead of print.

ABSTRACT

MOTIVATION: The problem of model inference is of fundamental importance to systems biology. Logical models (e.g., Boolean networks; BNs) represent a computationally attractive approach capable of handling large biological networks. The models are typically inferred from experimental data. However, even with a substantial amount of experimental data supported by some prior knowledge, existing inference methods often focus on a small sample of admissible candidate models only.

RESULTS: We propose Boolean network sketches as a new formal instrument for the inference of Boolean networks. A sketch integrates (typically partial) knowledge about the network's topology and the update logic (obtained through, e.g., a biological knowledge base or a literature search), as well as further assumptions about the properties of the network's transitions (e.g., the form of its attractor landscape), and additional restrictions on the model dynamics given by the measured experimental data. Our new BNs inference algorithm starts with an initial sketch which is extended by adding restrictions representing experimental data to a data-informed sketch and subsequently computes all BNs consistent with the data-informed sketch. Our algorithm is based on a symbolic representation and coloured model-checking. Our approach is unique in its ability to cover a broad spectrum of knowledge and efficiently produce a compact representation of all inferred BNs. We evaluate the method on a non-trivial collection of real-world and simulated data.

AVAILABILITY: All software and data are freely available as a reproducible artefact at https://doi.org/10.5281/zenodo.7688740.

SUPPLEMENTARY INFORMATION: Supplementary data available online through Bioinformatics.

PMID:37004199 | DOI:10.1093/bioinformatics/btad158

Bioinformatics. 2023 Apr 2:btad164. doi: 10.1093/bioinformatics/btad164. Online ahead of print.

ABSTRACT

MOTIVATION: Machine learning has shown extensive growth in recent years and is now routinely applied to sensitive areas. To allow appropriate verification of predictive models before deployment, models must be deterministic. Solely fixing all random seeds is not sufficient for deterministic machine learning, as major machine learning libraries default to the usage of non-deterministic algorithms based on atomic operations.

RESULTS: Various machine learning libraries released deterministic counterparts to the non-deterministic algorithms. We evaluated the effect of these algorithms on determinism and runtime. Based on these results, we formulated a set of requirements for deterministic machine learning and developed a new software solution, the mlf-core ecosystem, which aids machine learning projects to meet and keep these requirements. We applied mlf-core to develop deterministic models in various biomedical fields including a single cell autoencoder with TensorFlow, a PyTorch-based U-Net model for liver-tumor segmentation in CT scans, and a liver cancer classifier based on gene expression profiles with XGBoost.

AVAILABILITY: The complete data together with the implementations of the mlf-core ecosystem and use case models are available at https://github.com/mlf-core.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37004171 | DOI:10.1093/bioinformatics/btad164

Bioinformatics. 2023 Apr 2:btad165. doi: 10.1093/bioinformatics/btad165. Online ahead of print.

ABSTRACT

MOTIVATION: Single-cell RNA-sequencing (scRNA-seq) technologies provide an opportunity to infer cell-specific gene regulatory networks (GRNs) which is an important challenge in systems biology. Although numerous methods have been developed for inferring GRNs from scRNA-seq data, it is still a challenge to deal with cellular heterogeneity.

RESULTS: To address this challenge, we developed an interpretable transformer-based method namely STGRNS for inferring GRNs from scRNA-seq data. In this algorithm, gene expression motif (GEM) technique was proposed to convert gene pairs into contiguous sub-vectors which can be used as input for the transformer encoder. By avoiding missing phase-specific regulations in a network, GEM can improve the accuracy of GRN inference for different types of scRNA-seq data. To assess the performance of STGRNS, we implemented the comparative experiments with some popular methods on extensive benchmark datasets including 21 static and 27 time-series scRNA-seq dataset. All the results show that STGRNS is superior to other comparative methods. In addition, STGRNS was also proved to be more interpretable than "black box" deep learning methods which are well-known for the difficulty to explain the predictions clearly.

AVAILABILITY: The source code and data are available at https://github.com/zhanglab-wbgcas/STGRNS.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37004161 | DOI:10.1093/bioinformatics/btad165

Microb Genom. 2023 Apr;9(4). doi: 10.1099/mgen.0.000990.

ABSTRACT

Sesquiterpene cyclases (STC) catalyse the cyclization of the C15 molecule farnesyl diphosphate into a vast variety of mono- or polycyclic hydrocarbons and, for a few enzymes, oxygenated structures, with diverse stereogenic centres. The huge diversity in sesquiterpene skeleton structures in nature is primarily the result of the type of cyclization driven by the STC. Despite the phenomenal impact of fungal sesquiterpenes on the ecology of fungi and their potentials for applications, the fungal sesquiterpenome is largely untapped. The identification of fungal STC is generally based on protein sequence similarity with characterized enzymes. This approach has improved our knowledge on STC in a few fungal species, but it has limited success for the discovery of distant sequences. Besides, the tools based on secondary metabolite biosynthesis gene clusters have shown poor performance for terpene cyclases. Here, we used four sets of sequences of fungal STC that catalyse four types of cyclization, and specific amino acid motives to identify phylogenetically related sequences in the genomes of basidiomycetes fungi from the order Polyporales. We validated that four STC genes newly identified from the genome sequence of Leiotrametes menziesii, each classified in a different phylogenetic clade, catalysed a predicted cyclization of farnesyl diphosphate. We built HMM models and searched STC genes in 656 fungal genomes genomes. We identified 5605 STC genes, which were classified in one of the four clades and had a predicted cyclization mechanism. We noticed that the HMM models were more accurate for the prediction of the type of cyclization catalysed by basidiomycete STC than for ascomycete STC.

PMID:37073784 | DOI:10.1099/mgen.0.000990

J Mol Cell Cardiol. 2023 Mar 30:S0022-2828(23)00062-7. doi: 10.1016/j.yjmcc.2023.03.015. Online ahead of print.

ABSTRACT

Ca2+ transients (CaT) underlying cardiomyocyte (CM) contraction require efficient Ca2+ coupling between sarcolemmal Ca2+ channels and sarcoplasmic reticulum (SR) ryanodine receptor Ca2+ channels (RyR) for their generation; reduced coupling in disease contributes to diminished CaT and arrhythmogenic Ca2+ events. SR Ca2+ release also occurs via inositol 1,4,5-trisphosphate receptors (InsP3R) in CM. While this pathway contributes negligeably to Ca2+ handling in healthy CM, rodent studies support a role in altered Ca2+ dynamics and arrhythmogenic Ca2+ release involving InsP3R crosstalk with RyRs in disease. Whether this mechanism persists in larger mammals with lower T-tubular density and coupling of RyRs is not fully resolved. We have recently shown an arrhythmogenic action of InsP3-induced Ca2+ release (IICR) in end stage human heart failure, often associated with underlying ischemic heart disease (IHD). How IICR contributes to early stages of disease is however not determined but highly relevant. To access this stage, we chose a porcine model of IHD, which shows substantial remodelling of the area adjacent to the infarct. In cells from this region, IICR preferentially augmented Ca2+ release from non-coupled RyR clusters that otherwise showed delayed activation during the CaT. IICR in turn synchronised Ca2+ release during the CaT but also induced arrhythmogenic delayed afterdepolarizations and action potentials. Nanoscale imaging identified co-clustering of InsP3Rs and RyRs, thereby allowing Ca2+-mediated channel crosstalk. Mathematical modelling supported and further delineated this mechanism of enhanced InsP3R-RyRs coupling in MI. Our findings highlight the role of InsP3R-RyR channel crosstalk in Ca2+ release and arrhythmia during post-MI remodelling.

PMID:37003353 | DOI:10.1016/j.yjmcc.2023.03.015

Lancet Healthy Longev. 2023 Apr;4(4):e166-e175. doi: 10.1016/S2666-7568(23)00021-1.

ABSTRACT

Periodontitis results from dysbiosis of the oral microbiome and affects up to 70% of US adults aged 65 years and older. More than 50 systemic inflammatory disorders and comorbidities are associated with periodontitis, many of which overlap with immunotherapy-associated toxicities. Despite the increasing use of immunotherapy for the treatment of cancer, uncertainty remains as to whether the microbial shift associated with periodontal disease can influence response rates and tolerance to cancer immunotherapy. We herein review the pathophysiology of periodontitis and the local and systemic inflammatory conditions related to oral dysbiosis, and discuss the overlapping adverse profiles of periodontitis and immunotherapy. The effects of the presence of Porphyromonas gingivalis, a key pathogen in periodontitis, highlight how the oral microbiome can affect the hosts' systemic immune responses, and further research into the local and systemic influence of other microorganisms causing periodontal disease is necessary. Addressing periodontitis in an ageing population of people with cancer could have potential implications for the clinical response to (and tolerability of) immunotherapy and warrants further investigation.

PMID:37003275 | DOI:10.1016/S2666-7568(23)00021-1

CPT Pharmacometrics Syst Pharmacol. 2023 Mar 31. doi: 10.1002/psp4.12961. Online ahead of print.

ABSTRACT

Oncology treatments require continuous individual adjustment based on the measurement of multiple clinical parameters. Prediction tools exploiting the patterns present in the clinical data could be used to assist decision making and ease the burden associated to the interpretation of all these parameters. The goal of this study was to predict the evolution of patients with pancreatic cancer at their next visit using information routinely recorded in health records, providing a decision-support system for clinicians. We selected hematological variables as the visit's clinical outcomes, under the assumption that they can be predictive of the evolution of the patient. Multivariate models based on regression trees were generated to predict next-visit values for each of the clinical outcomes selected, based on the longitudinal clinical data as well as on molecular data sets streaming from in silico simulations of individual patient status at each visit. The models predict, with a mean prediction score (balanced accuracy) of 0.79, the evolution trends of eosinophils, leukocytes, monocytes, and platelets. Time span between visits and neutropenia were among the most common factors contributing to the predicted evolution. The inclusion of molecular variables from the systems-biology in silico simulations provided a molecular background for the observed variations in the selected outcome variables, mostly in relation to the regulation of hematopoiesis. In spite of its limitations, this study serves as a proof of concept for the application of next-visit prediction tools in real-world settings, even when available data sets are small.

PMID:37002678 | DOI:10.1002/psp4.12961

Sci Rep. 2023 Mar 31;13(1):5238. doi: 10.1038/s41598-023-32245-9.

ABSTRACT

Thousands of RNA-binding proteins (RBPs) crosslink to cellular mRNA. Among these are numerous unconventional RBPs (ucRBPs)-proteins that associate with RNA but lack known RNA-binding domains (RBDs). The vast majority of ucRBPs have uncharacterized RNA-binding specificities. We analyzed 492 human ucRBPs for intrinsic RNA-binding in vitro and identified 23 that bind specific RNA sequences. Most (17/23), including 8 ribosomal proteins, were previously associated with RNA-related function. We identified the RBDs responsible for sequence-specific RNA-binding for several of these 23 ucRBPs and surveyed whether corresponding domains from homologous proteins also display RNA sequence specificity. CCHC-zf domains from seven human proteins recognized specific RNA motifs, indicating that this is a major class of RBD. For Nudix, HABP4, TPR, RanBP2-zf, and L7Ae domains, however, only isolated members or closely related homologs yielded motifs, consistent with RNA-binding as a derived function. The lack of sequence specificity for most ucRBPs is striking, and we suggest that many may function analogously to chromatin factors, which often crosslink efficiently to cellular DNA, presumably via indirect recruitment. Finally, we show that ucRBPs tend to be highly abundant proteins and suggest their identification in RNA interactome capture studies could also result from weak nonspecific interactions with RNA.

PMID:37002329 | DOI:10.1038/s41598-023-32245-9

Anal Chem. 2023 Mar 31. doi: 10.1021/acs.analchem.3c00426. Online ahead of print.

ABSTRACT

The localized surface plasmon resonance (LSPR) property, depending on the structure (morphology and assembly) of nanoparticles, is very sensitive to the environmental fluctuation. Retaining the colorimetric effect derived from the LSPR property while introducing new optical properties (such as fluorescence) that provide supplementary information is an effective means to improve the controllability in structures and reproducibility in optical properties. DNA as a green and low-cost etching agent has been demonstrated to effectively control the morphology and optical properties (the blue shift of the LSPR peak) of the plasmonic nanoparticles. Herein, taking silver nanotriangles (AgNTs) as a proof of concept, we report a novel strategy to induce precisely tunable LSPR and fluorescence-composited dual-mode signals by using mono-DNA first as an etching agent for etching the morphology of AgNTs and later as a template for synthesizing fluorescent silver nanoclusters (AgNCs). In addition, common templates for synthesizing AgNCs, such as l-glutathione and bovine serum albumin, were demonstrated to have the capability to serve as etching agents. More importantly, these biomolecules as dual-functional capping agents (etching agents and templates) follow the size-dependent rule: as the size of the thiolated biomolecule increases, the blue shift of the LSPR peak increases; at the same time, the fluorescence intensity increases. The enzyme that can change the molecular weight (size) of the biomolecular substrates (DNA, peptides, and proteins) through an enzymatic cleavage reaction was explored to regulate the LSPR and fluorescent properties of the resulting nanoparticles (by etching of AgNTs and synthesis of AgNCs), achieving excellent performance in detection of cancer-related proteases. This study can be expanded to other biopolymers to impact both fundamental nanoscience and applications and provide powerful new tools for bioanalytical biosensors and nanomedicine.

PMID:37002208 | DOI:10.1021/acs.analchem.3c00426

Semin Cell Dev Biol. 2023 Mar 29:S1084-9521(23)00070-8. doi: 10.1016/j.semcdb.2023.03.007. Online ahead of print.

ABSTRACT

The Calvin Benson cycle in phototrophic and chemolithoautotrophic bacteria has ecological and biotechnological importance, which has motivated study of its regulation. I review recent advances in our understanding of how the Calvin Benson cycle is regulated in bacteria and the technologies used to elucidate regulation and modify it, and highlight differences between and photoautotrophic and chemolithoautotrophic models. Systems biology studies have shown that in oxygenic phototrophic bacteria, Calvin Benson cycle enzymes are extensively regulated at post-transcriptional and post-translational levels, with multiple enzyme activities connected to cellular redox status through thioredoxin. In chemolithoautotrophic bacteria, regulation is primarily at the transcriptional level, with effector metabolites transducing cell status, though new methods should now allow facile, proteome-wide exploration of biochemical regulation in these models. A biotechnological objective is to enhance CO2 fixation in the cycle and partition that carbon to a product of interest. Flux control of CO2 fixation is distributed over multiple enzymes, and attempts to modulate gene Calvin cycle gene expression show a robust homeostatic regulation of growth rate, though the synthesis rates of products can be significantly increased. Therefore, de-regulation of cycle enzymes through protein engineering may be necessary to increase fluxes. Non-canonical Calvin Benson cycles, if implemented with synthetic biology, could have reduced energy demand and enzyme loading, thus increasing the attractiveness of these bacteria for industrial applications.

PMID:37002131 | DOI:10.1016/j.semcdb.2023.03.007

Cell Syst. 2023 Mar 28:S2405-4712(23)00057-1. doi: 10.1016/j.cels.2023.03.001. Online ahead of print.

ABSTRACT

Antigen-specific T cell receptor (TCR) sequences can have prognostic, predictive, and therapeutic value, but decoding the specificity of TCR recognition remains challenging. Unlike DNA strands that base pair, TCRs bind to their targets with different orientations and different lengths, which complicates comparisons. We present scanning parametrized by normalized TCR length (SPAN-TCR) to analyze antigen-specific TCR CDR3 sequences and identify patterns driving TCR-pMHC specificity. Using entropic analysis, SPAN-TCR identifies 2-mer motifs that decrease the diversity (entropy) of CDR3s. These motifs are the most common patterns that can predict CDR3 composition, and we identify "essential" motifs that decrease entropy in the same CDR3 α or β chain containing the 2-mer, and "super-essential" motifs that decrease entropy in both chains. Molecular dynamics analysis further suggests that these motifs may play important roles in binding. We then employ SPAN-TCR to resolve similarities in TCR repertoires against different antigens using public databases of TCR sequences.

PMID:37001518 | DOI:10.1016/j.cels.2023.03.001

Cell. 2023 Mar 30;186(7):1448-1464.e20. doi: 10.1016/j.cell.2023.02.032.

ABSTRACT

Neutrophils accumulate in solid tumors, and their abundance correlates with poor prognosis. Neutrophils are not homogeneous, however, and could play different roles in cancer therapy. Here, we investigate the role of neutrophils in immunotherapy, leading to tumor control. We show that successful therapies acutely expanded tumor neutrophil numbers. This expansion could be attributed to a Sellhi state rather than to other neutrophils that accelerate tumor progression. Therapy-elicited neutrophils acquired an interferon gene signature, also seen in human patients, and appeared essential for successful therapy, as loss of the interferon-responsive transcription factor IRF1 in neutrophils led to failure of immunotherapy. The neutrophil response depended on key components of anti-tumor immunity, including BATF3-dependent DCs, IL-12, and IFNγ. In addition, we found that a therapy-elicited systemic neutrophil response positively correlated with disease outcome in lung cancer patients. Thus, we establish a crucial role of a neutrophil state in mediating effective cancer therapy.

PMID:37001504 | DOI:10.1016/j.cell.2023.02.032

Talanta. 2023 Mar 23;259:124477. doi: 10.1016/j.talanta.2023.124477. Online ahead of print.

ABSTRACT

Direct-infusion tandem mass spectrometry (DI-MS/MS) is an excellent tool for large cohort high-throughput quantitative metabolomics, MS imaging and single cell studies but incapable of discriminating isomers/isobars with similar MS spectral features. With experimental and density-functional theory (DFT) approaches, here, we comprehensively investigated the fragmentation pathways and characteristics of differential ion-mobility spectrometry (DMS) for three citrate isomers (citrate, isocitrate, glucaro-1,4-lactone) and an isobar (quinate) co-existing in biological sample such as urine. Results showed that all these compounds gave better MS spectra in negative-ion mode than positive-ion one and had numerous fragment ions under collision-induced dissociation (CID) with sequential losses of H2O and CO2. All observed fragment ions were assignable by combining experimental with DFT calculation results. A DI-DMS-MS/MS method was then developed to simultaneously quantify these four isomers/isobars with m/z 191-87 (CoV, -5.5 V), 191-73 (CoV, -3.5 V), 191-85 (CoV, -29.5 V) and m/z 191-93 (CoV, -41.5 V) for citrate, isocitrate, glucaro-1,4-lactone and quinate, respectively. The low limit-of-quantification was below 5.5 nM whilst accuracy was above 94% for all above compounds. The urinary concentrations of them in human and C57BL/6 mouse samples were further quantified showing clear inter-individual and inter-species level differences with significantly higher levels of isocitrate, glucaro-1,4-lactone and quinate in human urine samples than mouse ones. This provides an approach to understand the detailed fragmentation pathways for organic isomers/isobars and a high-throughput MS strategy to quantify them in complex mixtures for metabolomics, lipidomics, foodomics and exposomics especially when chromatographic separations are not useable.

PMID:37001399 | DOI:10.1016/j.talanta.2023.124477

Curr Opin Virol. 2023 Mar 29;60:101316. doi: 10.1016/j.coviro.2023.101316. Online ahead of print.

ABSTRACT

Inspite of the available antiviral therapy, hepatitis C virus (HCV) remains a global health burden and a prophylactic vaccine would help to eliminate the risk to develop chronic liver diseases. Structural insights into the function of the glycoproteins E1 and E2 in virus entry and the interplay with the host's humoral immune response are key for informed vaccine development. We review recently reported structural insights into receptor binding of HCV glycoproteins and the assembly of an intact membrane-bound E1-E2 heterodimer. These data are used together with available functional data to draw a simplified model of virus entry, which highlights gaps in our current knowledge that warrant further research to fully understand this process at the atomic level.

PMID:37001334 | DOI:10.1016/j.coviro.2023.101316

Diagn Microbiol Infect Dis. 2023 Mar 6;106(2):115930. doi: 10.1016/j.diagmicrobio.2023.115930. Online ahead of print.

ABSTRACT

BACKGROUND: The dissemination of NDM-1 carbapenemases (New Delhi Metallo-β-lactamase) is a global public health problem, mainly in developing countries. The aim of this study was to characterize the spread of NDM-producing bacteria in the Southern Brazilian states analyzing epidemiological, molecular, and antimicrobial susceptibility aspects.

METHODS: A total of 10,684 carbapenem-resistant isolates of Enterobacterales, Pseudomonas spp. and Acinetobacter spp. obtained from several hospitals in eight cities in Southern Brazil were screened, and 486 NDM-producing bacteria were selected.

RESULTS: The incidence varied from 0.5 to 77 cases/100.000 habitants. ST11, ST15, ST340 and ST674 were the most common in K. pneumoniae. A total of 5 plasmids were identified in one K. pneumoniae strain: Col440I, Col440II, IncFIA(HI1), IncFIB(K), IncFIB(pQil)/ IncFII(K), and IncR.

CONCLUSIONS: The number of patients with NDM-producing bacteria has increased in Southern Brazil, whose gene is present in different plasmids, explaining the expansion of this enzyme.

PMID:37001228 | DOI:10.1016/j.diagmicrobio.2023.115930

J Phys Chem B. 2023 Mar 31. doi: 10.1021/acs.jpcb.3c00429. Online ahead of print.

ABSTRACT

Although Venezuelan equine encephalitis virus (VEEV) is a life-threatening pathogen with a capacity for epidemic outbreaks, there are no FDA-approved VEEV antivirals for humans. VEEV cytotoxicity is partially attributed to the formation of a tetrameric complex between the VEEV capsid protein, the nuclear import proteins importin-α and importin-β, and the nuclear export protein CRM1, which together block trafficking through the nuclear pore complex. Experimental studies have identified small molecules from the CL6662 scaffold as potential inhibitors of the viral nuclear localization signal (NLS) sequence binding to importin-α. However, little is known about the molecular mechanism of CL6662 inhibition. To address this issue, we employed all-atom replica exchange molecular dynamics simulations to probe, in atomistic detail, the binding mechanism of CL6662 ligands to importin-α. Three ligands, including G281-1485 and two congeners with varying hydrophobicities, were considered. We investigated the distribution of ligand binding poses, their locations, and ligand specificities measured by the strength of binding interactions. We found that G281-1485 binds nonspecifically without forming well-defined binding poses throughout the NLS binding site. Binding of the less hydrophobic congener becomes strongly on-target with respect to the NLS binding site but remains nonspecific. However, a more hydrophobic congener is a strongly specific binder and the only ligand out of three to form a well-defined binding pose, while partially overlapping with the NLS binding site. On the basis of free energy estimates, we argue that all three ligands weakly compete with the viral NLS sequence for binding to importin-α in an apparent compromise to preserve host NLS binding. We further show that all-atom replica exchange binding simulations are a viable tool for studying ligands binding nonspecifically without forming well-defined binding poses.

PMID:37001021 | DOI:10.1021/acs.jpcb.3c00429