Cell. 2024 May 2:S0092-8674(24)00403-3. doi: 10.1016/j.cell.2024.04.008. Online ahead of print.

ABSTRACT

Hepatitis B virus (HBV) is a small double-stranded DNA virus that chronically infects 296 million people. Over half of its compact genome encodes proteins in two overlapping reading frames, and during evolution, multiple selective pressures can act on shared nucleotides. This study combines an RNA-based HBV cell culture system with deep mutational scanning (DMS) to uncouple cis- and trans-acting sequence requirements in the HBV genome. The results support a leaky ribosome scanning model for polymerase translation, provide a fitness map of the HBV polymerase at single-nucleotide resolution, and identify conserved prolines adjacent to the HBV polymerase termination codon that stall ribosomes. Further experiments indicated that stalled ribosomes tether the nascent polymerase to its template RNA, ensuring cis-preferential RNA packaging and reverse transcription of the HBV genome.

PMID:38723628 | DOI:10.1016/j.cell.2024.04.008

Cell. 2024 May 2:S0092-8674(24)00410-0. doi: 10.1016/j.cell.2024.04.015. Online ahead of print.

ABSTRACT

The quality and quantity of tumor-infiltrating lymphocytes, particularly CD8+ T cells, are important parameters for the control of tumor growth and response to immunotherapy. Here, we show in murine and human cancers that these parameters exhibit circadian oscillations, driven by both the endogenous circadian clock of leukocytes and rhythmic leukocyte infiltration, which depends on the circadian clock of endothelial cells in the tumor microenvironment. To harness these rhythms therapeutically, we demonstrate that efficacy of chimeric antigen receptor T cell therapy and immune checkpoint blockade can be improved by adjusting the time of treatment during the day. Furthermore, time-of-day-dependent T cell signatures in murine tumor models predict overall survival in patients with melanoma and correlate with response to anti-PD-1 therapy. Our data demonstrate the functional significance of circadian dynamics in the tumor microenvironment and suggest the importance of leveraging these features for improving future clinical trial design and patient care.

PMID:38723627 | DOI:10.1016/j.cell.2024.04.015

Virus Genes. 2024 May 9. doi: 10.1007/s11262-024-02068-5. Online ahead of print.

ABSTRACT

H6 avian influenza virus is widely prevalent in wild birds and poultry and has caused human infection in 2013 in Taiwan, China. During our active influenza surveillance program in wild waterfowl at Poyang Lake, Jiangxi Province, an H6N2 AIV was isolated and named A/bean goose/JiangXi/452-4/2013(H6N2). The isolate was characterized as a typical low pathogenic avian influenza virus (LPAIV) due to the presence of the amino acid sequence PQIETR↓GLFGAI at the cleavage site of the hemagglutinin (HA) protein. The genetic evolution analysis revealed that the NA gene of the isolate originated from North America and exhibited the highest nucleotide identity (99.29%) with a virus recovered from wild bird samples in North America, specifically A/bufflehead/California/4935/2012(H11N2). Additionally, while the HA and PB1 genes belonged to the Eurasian lineage, they displayed frequent genetic interactions with the North American lineage. The remaining genes showed close genetic relationships with Eurasian viruses. The H6N2 isolate possessed a complex genome, indicating it is a multi-gene recombinant virus with genetic material from both Eurasian and North American lineages.

PMID:38722491 | DOI:10.1007/s11262-024-02068-5

Infect Immun. 2024 May 9:e0014124. doi: 10.1128/iai.00141-24. Online ahead of print.

ABSTRACT

The human-specific bacterial pathogen group A Streptococcus (GAS) is a significant cause of morbidity and mortality. Macrophages are important to control GAS infection, but previous data indicate that GAS can persist in macrophages. In this study, we detail the molecular mechanisms by which GAS survives in THP-1 macrophages. Our fluorescence microscopy studies demonstrate that GAS is readily phagocytosed by macrophages, but persists within phagolysosomes. These phagolysosomes are not acidified, which is in agreement with our findings that GAS cannot survive in low pH environments. We find that the secreted pore-forming toxin Streptolysin O (SLO) perforates the phagolysosomal membrane, allowing leakage of not only protons but also large proteins including the lysosomal protease cathepsin B. Additionally, GAS recruits CD63/LAMP-3, which may contribute to lysosomal permeabilization, especially in the absence of SLO. Thus, although GAS does not inhibit fusion of the lysosome with the phagosome, it has multiple mechanisms to prevent proper phagolysosome function, allowing for persistence of the bacteria within the macrophage. This has important implications for not only the initial response but also the overall functionality of the macrophages, which may lead to the resulting pathologies in GAS infection. Our data suggest that therapies aimed at improving macrophage function may positively impact patient outcomes in GAS infection.

PMID:38722166 | DOI:10.1128/iai.00141-24

Microbiol Spectr. 2024 May 9:e0362323. doi: 10.1128/spectrum.03623-23. Online ahead of print.

ABSTRACT

The vaginal microbiota plays a pivotal role in reproductive, sexual, and perinatal health and disease. Unlike the well-established connections between diet, metabolism, and the intestinal microbiota, parallel mechanisms influencing the vaginal microbiota and pathogen colonization remain overlooked. In this study, we combine a mouse model of Streptococcus agalactiae strain COH1 [group B Streptococcus (GBS)] vaginal colonization with a mouse model of pubertal-onset obesity to assess diet as a determinant of vaginal microbiota composition and its role in colonization resistance. We leveraged culture-dependent assessment of GBS clearance and culture-independent, sequencing-based reconstruction of the vaginal microbiota in relation to diet, obesity, glucose tolerance, and microbial dynamics across time scales. Our findings demonstrate that excessive body weight gain and glucose intolerance are not associated with vaginal GBS density or timing of clearance. Diets high in fat and low in soluble fiber are associated with vaginal GBS persistence, and changes in vaginal microbiota structure and composition due to diet contribute to GBS clearance patterns in nonpregnant mice. These findings underscore a critical need for studies on diet as a key determinant of vaginal microbiota composition and its relevance to reproductive and perinatal outcomes.IMPORTANCEThis work sheds light on diet as a key determinant influencing the composition of vaginal microbiota and its involvement in group B Streptococcus (GBS) colonization in a mouse model. This study shows that mice fed diets with different nutritional composition display differences in GBS density and timing of clearance in the female reproductive tract. These findings are particularly significant given clear links between GBS and adverse reproductive and neonatal outcomes, advancing our understanding by identifying critical connections between dietary components, factors originating from the intestinal tract, vaginal microbiota, and reproductive outcomes.

PMID:38722155 | DOI:10.1128/spectrum.03623-23

Elife. 2024 May 9;12:RP89947. doi: 10.7554/eLife.89947.

ABSTRACT

Imputing data is a critical issue for machine learning practitioners, including in the life sciences domain, where missing clinical data is a typical situation and the reliability of the imputation is of great importance. Currently, there is no canonical approach for imputation of clinical data and widely used algorithms introduce variance in the downstream classification. Here we propose novel imputation methods based on determinantal point processes (DPP) that enhance popular techniques such as the multivariate imputation by chained equations and MissForest. Their advantages are twofold: improving the quality of the imputed data demonstrated by increased accuracy of the downstream classification and providing deterministic and reliable imputations that remove the variance from the classification results. We experimentally demonstrate the advantages of our methods by performing extensive imputations on synthetic and real clinical data. We also perform quantum hardware experiments by applying the quantum circuits for DPP sampling since such quantum algorithms provide a computational advantage with respect to classical ones. We demonstrate competitive results with up to 10 qubits for small-scale imputation tasks on a state-of-the-art IBM quantum processor. Our classical and quantum methods improve the effectiveness and robustness of clinical data prediction modeling by providing better and more reliable data imputations. These improvements can add significant value in settings demanding high precision, such as in pharmaceutical drug trials where our approach can provide higher confidence in the predictions made.

PMID:38722146 | DOI:10.7554/eLife.89947

Small. 2024 May 9:e2400930. doi: 10.1002/smll.202400930. Online ahead of print.

ABSTRACT

The self-assembly yield of DNA nanostructures can be exponentially lower with increasing structural complexity. Few optimizing strategies are available in the DNA nanotechnology field for the assembly yield improvement. Here, betaine and its analogs are applied as supplementary ingredients in DNA self-assembly. Such a simple implementation results in effective yield improvement. Through a comprehensive investigation, a reliable yield improvement of two- to threefold is achieved for a number of DNA nanostructures with considerable complexity.

PMID:38721967 | DOI:10.1002/smll.202400930

Int J Health Sci (Qassim). 2024 May-Jun;18(3):6-14.

ABSTRACT

OBJECTIVE: Information theory has been successfully employed to identify optimal pathway networks, mutual information (MI), and entropy as a dynamic response in statistical methods and estimate input and output information in systems biology. This research aims to investigate potentially integrated gene signatures for bone metastasis using graph-based information theory from the dynamic interaction interphase.

METHODS: The expression dataset with the series ID GSE26964 for bone metastasis from prostate cancer was retrieved. The dataset was segregated for differentially expressed genes (DEGs) using the Human Cancer Metastasis Database. MI was considered to capture non-linear connections to classify the key DEGs from the collected dataset using gene-gene statistical analysis and then a protein-protein interaction network (PPIN). The PPIN was used to calculate centrality metrics, bottlenecks, and functional annotations.

RESULTS: A total of 531 DEGs were identified. Thirteen genes were classified as highly correlated based on their gene expression data matrix. The extended PPIN of the 13 genes comprised 53 nodes and 372 edges. A total of four DEGs were identified as hubs. One novel gene was identified with strong network connectivity.

CONCLUSION: The novel biomarkers for metastasis may provide information on cancer metastasis to the bone by implying MI and information theory.

PMID:38721137 | PMC:PMC11075445

Discov Oncol. 2024 May 8;15(1):148. doi: 10.1007/s12672-024-00982-6.

ABSTRACT

INTRODUCTION: As proteins that promote immune cell differentiation, chemokines have attracted great interest regarding their role in anti-tumor immune responses within the cancer environment. However, the exact role of CXCL10, a chemokine, in bladder cancer (BLCA) is still not fully elucidated.

METHOD: In the present study, we employed bioinformatics approaches to examine the expression pattern, prognostic value, and immune infiltration of CXCL10 in BLCA. Furthermore, we focused on examining the impact of CXCL10 on immune therapy in BLCA. Additionally, we validated the expression of CXCL10 in various BLCA cell lines using PCR techniques.

RESULTS: We observed an upregulation of CXCL10 in BLCA tissues as well as in different cell lines. Additionally, upregulation of CXCL10 indicates a better prognosis for BLCA patients. ESTIMATE and CIBERSORT algorithms suggest that CXCL10 is closely associated with the immune microenvironment of BLCA. Through multiple immune therapy cohorts, we also identified that CXCL10 has shown promising predictive value for assessing the efficacy of immune therapy in in BLCA.

CONCLUSION: Our study indicates that CXCL10 has the potential to serve as a favorable prognostic factor and is strongly associated with immune infiltration in BLCA.

PMID:38720149 | DOI:10.1007/s12672-024-00982-6

Nature. 2024 May 8. doi: 10.1038/s41586-024-07388-y. Online ahead of print.

ABSTRACT

In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1-3. Therefore, somatic mutations are likely to alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. Here, to chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed genotyping of targeted loci with single-cell chromatin accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from patients with myeloproliferative neoplasms with JAK2V617F-mutated haematopoiesis. Differential accessibility analysis between wild-type and JAK2V617F-mutant progenitors revealed both cell-intrinsic and cell-state-specific shifts within mutant haematopoietic precursors, including cell-intrinsic pro-inflammatory signatures in haematopoietic stem cells, and a distinct profibrotic inflammatory chromatin landscape in megakaryocytic progenitors. Integration of mitochondrial genome profiling and cell-surface protein expression measurement allowed expansion of genotyping onto DOGMA-seq through imputation, enabling single-cell capture of genotypes, chromatin accessibility, RNA expression and cell-surface protein expression. Collectively, we show that the JAK2V617F mutation leads to epigenetic rewiring in a cell-intrinsic and cell type-specific manner, influencing inflammation states and differentiation trajectories. We envision that GoT-ChA will empower broad future investigations of the critical link between somatic mutations and epigenetic alterations across clonal populations in malignant and non-malignant contexts.

PMID:38720070 | DOI:10.1038/s41586-024-07388-y

Nature. 2024 May 8. doi: 10.1038/s41586-024-07345-9. Online ahead of print.

ABSTRACT

QS-21 is a potent vaccine adjuvant and remains the only saponin-based adjuvant that has been clinically approved for use in humans1,2. However, owing to the complex structure of QS-21, its availability is limited. Today, the supply depends on laborious extraction from the Chilean soapbark tree or on low-yielding total chemical synthesis3,4. Here we demonstrate the complete biosynthesis of QS-21 and its precursors, as well as structural derivatives, in engineered yeast strains. The successful biosynthesis in yeast requires fine-tuning of the host's native pathway fluxes, as well as the functional and balanced expression of 38 heterologous enzymes. The required biosynthetic pathway spans seven enzyme families-a terpene synthase, P450s, nucleotide sugar synthases, glycosyltransferases, a coenzyme A ligase, acyl transferases and polyketide synthases-from six organisms, and mimics in yeast the subcellular compartmentalization of plants from the endoplasmic reticulum membrane to the cytosol. Finally, by taking advantage of the promiscuity of certain pathway enzymes, we produced structural analogues of QS-21 using this biosynthetic platform. This microbial production scheme will allow for the future establishment of a structure-activity relationship, and will thus enable the rational design of potent vaccine adjuvants.

PMID:38720067 | DOI:10.1038/s41586-024-07345-9

Life Sci Alliance. 2024 May 7;7(7):e202302443. doi: 10.26508/lsa.202302443. Print 2024 Jul.

ABSTRACT

The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.

PMID:38719747 | DOI:10.26508/lsa.202302443

Biotechnol J. 2024 May;19(5):e2300664. doi: 10.1002/biot.202300664.

ABSTRACT

CYP116B5 is a class VII P450 in which the heme domain is linked to a FMN and 2Fe2S-binding reductase. Our laboratory has proved that the CYP116B5 heme domain (CYP116B5-hd) is capable of catalyzing the oxidation of substrates using H2O2. Recently, the Molecular Lego approach was applied to join the heme domain of CYP116B5 to sarcosine oxidase (SOX), which provides H2O2 in-situ by the sarcosine oxidation. In this work, the chimeric self-sufficient fusion enzyme CYP116B5-SOX was heterologously expressed, purified, and characterized for its functionality by absorbance and fluorescence spectroscopy. Differential scanning calorimetry (DSC) experiments revealed a TM of 48.4 ± 0.04 and 58.3 ± 0.02°C and a enthalpy value of 175,500 ± 1850 and 120,500 ± 1350 cal mol-1 for the CYP116B5 and SOX domains respectively. The fusion enzyme showed an outstanding chemical stability in presence of up to 200 mM sarcosine or 5 mM H2O2 (4.4 ± 0.8 and 11.0 ± 2.6% heme leakage respectively). Thanks to the in-situ H2O2 generation, an improved kcat/KM for the p-nitrophenol conversion was observed (kcat of 20.1 ± 0.6 min-1 and KM of 0.23 ± 0.03 mM), corresponding to 4 times the kcat/KM of the CYP116B5-hd. The aim of this work is the development of an engineered biocatalyst to be exploited in bioremediation. In order to tackle this challenge, an E. coli strain expressing CYP116B5-SOX was employed to exploit this biocatalyst for the oxidation of the wastewater contaminating-drug tamoxifen. Data show a 12-fold increase in tamoxifen N-oxide production-herein detected for the first time as CYP116B5 metabolite-compared to the direct H2O2 supply, equal to the 25% of the total drug conversion.

PMID:38719620 | DOI:10.1002/biot.202300664

Biotechnol J. 2024 May;19(5):e2400081. doi: 10.1002/biot.202400081.

ABSTRACT

Translation initiation is the primary determinant of the rate of protein production. The variation in the rate with which this step occurs can cause up to three orders of magnitude differences in cellular protein levels. Several mRNA features, including mRNA stability in proximity to the start codon, coding sequence length, and presence of specific motifs in the mRNA molecule, have been shown to influence the translation initiation rate. These molecular factors acting at different strengths allow precise control of in vivo translation initiation rate and thus the rate of protein synthesis. However, despite the paramount importance of translation initiation rate in protein synthesis, accurate prediction of the absolute values of initiation rate remains a challenge. In fact, as of now, there is no available model for predicting the initiation rate in Saccharomyces cerevisiae. To address this, we train a machine learning model for predicting the in vivo initiation rate in S. cerevisiae transcripts. The model is trained using a diverse set of mRNA transcripts, enabling the comparison of initiation rates across different transcripts. Our model exhibited excellent accuracy in predicting the translation initiation rate and demonstrated its effectiveness with both endogenous and exogenous transcripts. Then, by combining the machine learning model with the Monte-Carlo search algorithm, we have also devised a method to optimize the nucleotide sequence of any gene to achieve a specific target initiation rate. The machine learning model we've developed for predicting translation initiation rates, along with the gene optimization method, are deployed as a web server. Both web servers are accessible for free at the following link: ajeetsharmalab.com/TIRPredictor. Thus, this research advances our fundamental understanding of translation initiation processes, with direct applications in biotechnology.

PMID:38719586 | DOI:10.1002/biot.202400081

Environ Int. 2024 May 3;187:108714. doi: 10.1016/j.envint.2024.108714. Online ahead of print.

ABSTRACT

BACKGROUND: Ultrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated.

OBJECTIVES: This study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved.

METHODS: A longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses.

RESULTS: Short-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0-3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7-12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism.

DISCUSSION: This study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

PMID:38718674 | DOI:10.1016/j.envint.2024.108714

Int Immunopharmacol. 2024 May 7;134:112148. doi: 10.1016/j.intimp.2024.112148. Online ahead of print.

ABSTRACT

BACKGROUND: Vascular inflammation is the key event in early atherogenesis. Pro-inflammatory endothelial cells induce monocyte recruitment into the sub-endothelial layer of the artery. This requires endothelial expression of adhesion molecules namely intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), alongside chemokines production. Christia vespertilionis (L.f.) Bakh.f. (CV) possesses anti-inflammatory property. However, its potential anti-atherogenic effect in the context of vascular inflammation has yet to be explored.

PURPOSE: To evaluate the anti-atherogenic mechanism of 80% ethanol extract of CV leaves on tumor necrosis factor-α (TNF-α)-activated human umbilical vein endothelial cells (HUVECs).

METHODS: Qualitative analysis of the CV extract was carried out by using liquid chromatography with tandem mass spectrometry (LC-MS/MS). The cell viability of HUVECs treated with CV extract was determined by MTT assay. The effect of CV extract on monocyte adhesion was determined by monocyte-endothelial adhesion assay. Protein expressions of ICAM-1, VCAM-1 and nuclear factor-kappa B (NF-κB) signaling pathway were determined by western blot while production of monocyte chemoattractant protein-1 (MCP-1) was determined by ELISA.

RESULTS: LC-MS/MS analysis showed that CV extract composed of five main compounds, including schaftoside, orientin, isovitexin, 6-caffeoyl-D-glucose, and 3,3'-di-O-methyl ellagic acid. Treatment of CV extract at a concentration range from 5 to 60 µg/mL for 24 h maintained HUVECs viability above 90 %, therefore concentrations of 20, 40 and 60 μg/mL were selected for the subsequent experiments. All concentrations of CV extract showed a significant inhibitory effect on monocyte adhesion to TNF-α-activated HUVECs (p < 0.05). In addition, the protein expressions of ICAM-1 and VCAM-1 were significantly attenuated by CV in a concentration dependent manner (p < 0.001). At all tested concentrations, CV extract also exhibited significant inhibition on the production of MCP-1 (p < 0.05). Moreover, CV extract significantly inhibited TNF-α-induced phosphorylation of inhibitor of nuclear factor-κB kinase alpha/beta (IKKα/β), inhibitor kappa B-alpha (IκBα), NF-κB and nuclear translocation of NF-κB (p < 0.05).

CONCLUSION: CV extract inhibited monocyte adhesion to endothelial cells by suppressing protein expressions of cell adhesion molecules and production of chemokines through downregulation of NF-κB signaling pathway. Thus, CV has the potential to be developed as an anti-atherogenic agent for early treatment of atherosclerosis.

PMID:38718657 | DOI:10.1016/j.intimp.2024.112148

Sci Adv. 2024 May 10;10(19):eadn1547. doi: 10.1126/sciadv.adn1547. Epub 2024 May 8.

ABSTRACT

Pre-mRNA splicing is a fundamental step in gene expression, conserved across eukaryotes, in which the spliceosome recognizes motifs at the 3' and 5' splice sites (SSs), excises introns, and ligates exons. SS recognition and pairing is often influenced by protein splicing factors (SFs) that bind to splicing regulatory elements (SREs). Here, we describe SMsplice, a fully interpretable model of pre-mRNA splicing that combines models of core SS motifs, SREs, and exonic and intronic length preferences. We learn models that predict SS locations with 83 to 86% accuracy in fish, insects, and plants and about 70% in mammals. Learned SRE motifs include both known SF binding motifs and unfamiliar motifs, and both motif classes are supported by genetic analyses. Our comparisons across species highlight similarities between non-mammals, increased reliance on intronic SREs in plant splicing, and a greater reliance on SREs in mammalian splicing.

PMID:38718117 | DOI:10.1126/sciadv.adn1547

Curr Protoc. 2024 May;4(5):e1046. doi: 10.1002/cpz1.1046.

ABSTRACT

Whole-genome sequencing is widely used to investigate population genomic variation in organisms of interest. Assorted tools have been independently developed to call variants from short-read sequencing data aligned to a reference genome, including single nucleotide polymorphisms (SNPs) and structural variations (SVs). We developed SNP-SVant, an integrated, flexible, and computationally efficient bioinformatic workflow that predicts high-confidence SNPs and SVs in organisms without benchmarked variants, which are traditionally used for distinguishing sequencing errors from real variants. In the absence of these benchmarked datasets, we leverage multiple rounds of statistical recalibration to increase the precision of variant prediction. The SNP-SVant workflow is flexible, with user options to tradeoff accuracy for sensitivity. The workflow predicts SNPs and small insertions and deletions using the Genome Analysis ToolKit (GATK) and predicts SVs using the Genome Rearrangement IDentification Software Suite (GRIDSS), and it culminates in variant annotation using custom scripts. A key utility of SNP-SVant is its scalability. Variant calling is a computationally expensive procedure, and thus, SNP-SVant uses a workflow management system with intermediary checkpoint steps to ensure efficient use of resources by minimizing redundant computations and omitting steps where dependent files are available. SNP-SVant also provides metrics to assess the quality of called variants and converts between VCF and aligned FASTA format outputs to ensure compatibility with downstream tools to calculate selection statistics, which are commonplace in population genomics studies. By accounting for both small and large structural variants, users of this workflow can obtain a wide-ranging view of genomic alterations in an organism of interest. Overall, this workflow advances our capabilities in assessing the functional consequences of different types of genomic alterations, ultimately improving our ability to associate genotypes with phenotypes. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Predicting single nucleotide polymorphisms and structural variations Support Protocol 1: Downloading publicly available sequencing data Support Protocol 2: Visualizing variant loci using Integrated Genome Viewer Support Protocol 3: Converting between VCF and aligned FASTA formats.

PMID:38717471 | DOI:10.1002/cpz1.1046

J Phys Chem A. 2024 May 8. doi: 10.1021/acs.jpca.4c01287. Online ahead of print.

ABSTRACT

Atomic partial charges are crucial parameters in molecular dynamics simulation, dictating the electrostatic contributions to intermolecular energies and thereby the potential energy landscape. Traditionally, the assignment of partial charges has relied on surrogates of ab initio semiempirical quantum chemical methods such as AM1-BCC and is expensive for large systems or large numbers of molecules. We propose a hybrid physical/graph neural network-based approximation to the widely popular AM1-BCC charge model that is orders of magnitude faster while maintaining accuracy comparable to differences in AM1-BCC implementations. Our hybrid approach couples a graph neural network to a streamlined charge equilibration approach in order to predict molecule-specific atomic electronegativity and hardness parameters, followed by analytical determination of optimal charge-equilibrated parameters that preserve total molecular charge. This hybrid approach scales linearly with the number of atoms, enabling for the first time the use of fully consistent charge models for small molecules and biopolymers for the construction of next-generation self-consistent biomolecular force fields. Implemented in the free and open source package EspalomaCharge, this approach provides drop-in replacements for both AmberTools antechamber and the Open Force Field Toolkit charging workflows, in addition to stand-alone charge generation interfaces. Source code is available at https://github.com/choderalab/espaloma-charge.

PMID:38717302 | DOI:10.1021/acs.jpca.4c01287

Vector Borne Zoonotic Dis. 2024 May 7. doi: 10.1089/vbz.2024.0018. Online ahead of print.

ABSTRACT

Background: Chikungunya is a zoonotic disease caused by the Chikungunya virus (CHIKV), primarily transmitted to humans through infected Aedes mosquitoes. The infection is characterized by symptoms such as high fever, musculoskeletal pain, polyarthritis, and a rash, which can lead to severe complications such as encephalitis, meningitis, and even fatalities. While many disease manifestations resemble those of other viral infections, chronic arthritis caused by CHIKV is unique, and its molecular mechanisms remain ill-defined. Materials and Methods: Proteomics data from both cellular and patient levels of CHIKV infection were curated from PubMed and screened using inclusion and exclusion criteria. Patient serum proteomics data obtained from P RIDE underwent reanalysis using Proteome Discoverer 2.2. Enrichment and protein-protein interaction network analysis were conducted on differentially expressed proteins from both serum and cellular datasets. Metabolite data from CHIKV-infected patients were further retrieved, and their protein binding partners were identified using BindingDB. The protein-metabolite interaction pathway was further developed using MetaboAnalyst. Results: The proteomics data analysis revealed differential expression of proteins involved in critical host mechanisms, such as cholesterol metabolism and mRNA splicing, during CHIKV infection. Consistent upregulation of two actin cytoskeleton proteins, TAGLN2 and PFN1, was noted in both serum and cellular datasets, and their upregulations are associated with arthritis. Furthermore, alterations in purine metabolism were observed in the integrative proteome-metabolome analysis, correlating with cytoskeletal remodelling. Conclusion: Collectively, this integrative view sheds light on the involvement of actin cytoskeleton remodeling proteins and purine metabolic pathways in the development of arthritis during CHIKV infection.

PMID:38717066 | DOI:10.1089/vbz.2024.0018