Front Fungal Biol. 2022 Feb 1;3:827704. doi: 10.3389/ffunb.2022.827704. eCollection 2022.

ABSTRACT

Production of heterologous proteins, especially biopharmaceuticals and industrial enzymes, in living cell factories consumes cellular resources. Such resources are reallocated from normal cellular processes toward production of the heterologous protein that is often of no benefit to the host cell. This competition for resources is a burden to host cells, has a negative impact on cell fitness, and may consequently trigger stress responses. Importantly, this often causes a reduction in final protein titers. Engineering strategies to generate more burden resilient production strains offer sustainable opportunities to increase production and profitability for this growing billion-dollar global industry. We review recently reported impacts of burden derived from resource competition in two commonly used protein-producing yeast cell factories: Saccharomyces cerevisiae and Komagataella phaffii (syn. Pichia pastoris). We dissect possible sources of burden in these organisms, from aspects related to genetic engineering to protein translation and export of soluble protein. We also summarize advances as well as challenges for cell factory design to mitigate burden and increase overall heterologous protein production from metabolic engineering, systems biology, and synthetic biology perspectives. Lastly, future profiling and engineering strategies are highlighted that may lead to constructing robust burden-resistant cell factories. This includes incorporation of systems-level data into mathematical models for rational design and engineering dynamical regulation circuits in production strains.

PMID:37746199 | PMC:PMC10512257 | DOI:10.3389/ffunb.2022.827704

Front Fungal Biol. 2022 Dec 20;3:1117910. doi: 10.3389/ffunb.2022.1117910. eCollection 2022.

NO ABSTRACT

PMID:37746195 | PMC:PMC10512361 | DOI:10.3389/ffunb.2022.1117910

Front Genet. 2023 Sep 6;14:1200770. doi: 10.3389/fgene.2023.1200770. eCollection 2023.

ABSTRACT

Introduction: The African Goat Improvement Network Image Collection Protocol (AGIN-ICP) is an accessible, easy to use, low-cost procedure to collect phenotypic data via digital images. The AGIN-ICP collects images to extract several phenotype measures including health status indicators (anemia status, age, and weight), body measurements, shapes, and coat color and pattern, from digital images taken with standard digital cameras or mobile devices. This strategy is to quickly survey, record, assess, analyze, and store these data for use in a wide variety of production and sampling conditions. Methods: The work was accomplished as part of the multinational African Goat Improvement Network (AGIN) collaborative and is presented here as a case study in the AGIN collaboration model and working directly with community-based breeding programs (CBBP). It was iteratively developed and tested over 3 years, in 12 countries with over 12,000 images taken. Results and discussion: The AGIN-ICP development is described, and field implementation and the quality of the resulting images for use in image analysis and phenotypic data extraction are iteratively assessed. Digital body measures were validated using the PreciseEdge Image Segmentation Algorithm (PE-ISA) and software showing strong manual to digital body measure Pearson correlation coefficients of height, length, and girth measures (0.931, 0.943, 0.893) respectively. It is critical to note that while none of the very detailed tasks in the AGIN-ICP described here is difficult, every single one of them is even easier to accidentally omit, and the impact of such a mistake could render a sample image, a sampling day's images, or even an entire sampling trip's images difficult or unusable for extracting digital phenotypes. Coupled with tissue sampling and genomic testing, it may be useful in the effort to identify and conserve important animal genetic resources and in CBBP genetic improvement programs by providing reliably measured phenotypes with modest cost. Potential users include farmers, animal husbandry officials, veterinarians, regional government or other public health officials, researchers, and others. Based on these results, a final AGIN-ICP is presented, optimizing the costs, ease, and speed of field implementation of the collection method without compromising the quality of the image data collection.

PMID:37745840 | PMC:PMC10512022 | DOI:10.3389/fgene.2023.1200770

bioRxiv. 2023 Sep 12:2023.09.11.557227. doi: 10.1101/2023.09.11.557227. Preprint.

ABSTRACT

This paper addresses two topics in systems biology, the hypothesis that biological systems are modular and the problem of relating structure and function of biological systems. The focus here is on gene regulatory networks, represented by Boolean network models, a commonly used tool. Most of the research on gene regulatory network modularity has focused on network structure, typically represented through either directed or undirected graphs. But since gene regulation is a highly dynamic process as it determines the function of cells over time, it is natural to consider functional modularity as well. One of the main results is that the structural decomposition of a network into modules induces an analogous decomposition of the dynamic structure, exhibiting a strong relationship between network structure and function. An extensive simulation study provides evidence for the hypothesis that modularity might have evolved to increase phenotypic complexity while maintaining maximal dynamic robustness to external perturbations.

PMID:37745485 | PMC:PMC10515856 | DOI:10.1101/2023.09.11.557227

bioRxiv. 2023 Sep 17:2023.09.17.557982. doi: 10.1101/2023.09.17.557982. Preprint.

ABSTRACT

Cells are fundamental units of life. Recent technical advances have revolutionized our ability to quantify the state and identity of individual cells, and intercellular regulatory programs. However, these static measurements alone are limited in their ability to predict the complex collective behaviors that emerge from populations of many interacting cells over time. Mathematical models have a proven record of successfully predicting the behaviors of dynamic biological systems, e.g., therapeutic responses in cancer. Simulations from these models enable in silico visualization, examination, and refinement of biological models and can be used to generate new hypotheses about cells and their collective behavior. Agent-based modeling is particularly well-suited to studying communities of interacting cells, as it is intuitive to map a single cell to a single agent. Thus, we have developed a conceptual framing (with a reference implementation in the widely-used PhysiCell agent-based modeling framework) that can be initialized directly from single cell and spatial transcriptomic data, and that can be easily populated with interactive rules. Because the expert mathematical and computational knowledge required to build agent-based models has limited their widespread adoption in the biomedical research community, we engineered this framework to specify complex cellular responses to signals (or stimuli) using a single line of human-readable text. This plain language text encodes cellular phenotypes and regulatory mechanisms from high throughput data and published literature, using a novel concept of hypothesis grammar. We motivate and fully describe this grammar and its philosophy, and then present a series of five example reference models of tumor growth and response to immunotherapy. Biologically, these examples demonstrate how mathematical models can predict from single cell and spatial transcriptomic data the cellular phenotypes responsible for tumor cell invasion and the simulation of immunotherapy treatment to overcome tumor cell growth. Computationally, these examples are designed to demonstrate how this conceptual framing and software implementation empower interdisciplinary teams to build an agent-based model of their experimental system, leveraging prior biological knowledge alone or in combination with information from spatial multiomics technologies. Altogether, this approach provides an interface to bridge biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.

PMID:37745323 | PMC:PMC10516032 | DOI:10.1101/2023.09.17.557982

Curr Pediatr Rep. 2022 Sep;10(3):109-124. doi: 10.1007/s40124-022-00265-0. Epub 2022 Jun 22.

ABSTRACT

PURPOSE OF REVIEW: Review comprehensive data on rates of toxoplasmosis in Panama and Colombia.

RECENT FINDINGS: Samples and data sets from Panama and Colombia, that facilitated estimates regarding seroprevalence of antibodies to Toxoplasma and risk factors, were reviewed.

SUMMARY: Screening maps, seroprevalence maps, and risk factor mathematical models were devised based on these data. Studies in Ciudad de Panamá estimated seroprevalence at between 22 and 44%. Consistent relationships were found between higher prevalence rates and factors such as poverty and proximity to water sources. Prenatal screening rates for anti-Toxoplasma antibodies were variable, despite existence of a screening law. Heat maps showed a correlation between proximity to bodies of water and overall Toxoplasma seroprevalence. Spatial epidemiological maps and mathematical models identify specific regions that could most benefit from comprehensive, preventive healthcare campaigns related to congenital toxoplasmosis and Toxoplasma infection.

PMID:37744780 | PMC:PMC10516319 | DOI:10.1007/s40124-022-00265-0

Iran J Public Health. 2023 Aug;52(8):1758-1763. doi: 10.18502/ijph.v52i8.13415.

ABSTRACT

BACKGROUND: Salmonella is one of the most leading causes of food-born infection and death among infants and people with the poor immunity system. Because Salmonella spp. have diversity in the genome composition and pathogenicity, access to rapid identification and genotyping is necessary to control of salmonellosis. The CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) typing is a genotyping method that checks these variable sequences in the bacterial genome in a specific species. This study aimed to differentiate Salmonella strains using CRISPR region.

METHODS: Salmonella isolates, previously identified via standard microbiological and molecular tests, were subjected to the study. Bacterial DNA was extracted and PCR was done using specific primers. The different PCR products were sequenced and the repeats patterns were used to identify additional or degenerate repeat clusters in the CRISPR region. All different sequences were analyzed using CRISPRtionary tool for dendrogram generation using the binary file.

RESULTS: Overall, 119 strains of various Salmonella serovars were used. The result showed unique CRISPR and diversity in spacer both in sequence and the number. Analysis of the extracted sequence and band patterns illustrated that, except for S. infantis, both S. enteritidis and S. typhimurium isolates were classified as a separate cluster.

CONCLUSION: CRISPR genotyping could provide serotype/spacers dictionary and it is performed at low cost and high speed in comparison to the other typing methods. Therefore, the assessment of CRISPR and spacer content can be considered as a powerful and practical discriminatory method for subtyping of Salmonella isolates.

PMID:37744550 | PMC:PMC10512146 | DOI:10.18502/ijph.v52i8.13415

Iran J Public Health. 2023 Aug;52(8):1764-1772. doi: 10.18502/ijph.v52i8.13416.

ABSTRACT

BACKGROUND: Cystic echinococcosis (CE) is an important zoonotic parasitic disease caused by the larval stage or metacestode of the tapeworm Echinococcus granulosus sensu lato. Due to treatment protocols for different liver cysts, diagnosis of cyst stages is very important. Different antigens have been used for CE diagnosis. However, each one is more sensitive and effective for the diagnosis of specific CE stages is not known well. We aimed to compare Native Hydatid Cyst Fluid (HCF), Lyophilized Hydatid Cyst Fluid (LHCF), antigen B (AgB) and Lyophilized antigen B (LAgB) originated from E. granulosus sensu stricto (G1-G3) genotype, for sero- diagnosis of active, transitional and inactive human liver CE using ELISA technique.

METHODS: The HCF was collected aseptically from liver CE cysts of sheep slaughtered from 2018 to 2019 in Shiraz slaughterhouse, Southern, Iran. The cysts were characterized by PCR and sequencing for genotype specification. Four types of antigens were used: HCF, LHCF, AgB and LAgB originated from E. granulosus sensu stricto (G1-G3) genotype. Thirty-three serum samples from active, transitional, and inactive human cysts were collected. Overall, 48 samples from other parasitic diseases and 60 samples from healthy subjects as negative controls were checked using four antigens by ELISA method.

RESULTS: The best diagnostic sensitivity with 96.97% was observed by anti-LHCF IgG ELISA test. The best specificity with 95.37% was observed in ELISA test using LAgB.

CONCLUSION: Simultaneous test of sera with anti-LHCF IgG ELISA and anti-LAgB IgG ELISA would be the best in the diagnosis of human liver cystic echinococcosis.

PMID:37744545 | PMC:PMC10512133 | DOI:10.18502/ijph.v52i8.13416

Oncol Res. 2023 Sep 15;31(6):989-1005. doi: 10.32604/or.2023.030395. eCollection 2023.

ABSTRACT

Hepatocellular carcinoma (HCC) is the leading cause of cancer death worldwide; nevertheless, current therapeutic options are limited or ineffective for many patients. Therefore, elucidation of molecular mechanisms in HCC biology could yield important insights for the intervention of novel therapies. Recently, various studies have reported dysregulation of long non-coding RNAs (lncRNAs) in the initiation and progression of HCC, including H19; however, the biological function of H19 in HCC remains unclear. Here, we show that knockdown of H19 disrupted HCC cell growth, impaired the G1-to-S phase transition, and promoted apoptosis, while overexpression of H19 yielded the opposite results. Screening for expression of cell cycle-related genes revealed a significant downregulation of CDK6 at both RNA and protein levels upon H19 suppression. Bioinformatic analysis of the H19 sequence and the 3' untranslated region (3' UTR) of CDK6 transcripts showed several binding sites for microRNA-107 (miR-107), and the dual luciferase reporter assay confirmed their direct interaction with miR-107. Consistently, blockage of miR-107 activity alleviated the growth suppression phenotypes induced by H19 downregulation, suggesting that H19 serves as a molecular sponge for miR-107 to promote CDK6 expression and cell cycle progression. Together, this study demonstrates a mechanistic function of H19 in driving the proliferation of HCC cells and suggests H19 suppression as a novel approach for HCC treatment.

PMID:37744274 | PMC:PMC10513943 | DOI:10.32604/or.2023.030395

Front Fungal Biol. 2021 Aug 9;2:708358. doi: 10.3389/ffunb.2021.708358. eCollection 2021.

ABSTRACT

Anaerobic fungi are a potential biotechnology platform to produce biomass-degrading enzymes. Unlike model fungi such as yeasts, stress responses that are relevant during bioprocessing have not yet been established for anaerobic fungi. In this work, we characterize both the heat shock and unfolded protein responses of four strains of anaerobic fungi (Anaeromyces robustus, Caecomyces churrovis, Neocallimastix californiae, and Piromyces finnis). The inositol-requiring 1 (Ire1) stress sensor, which typically initiates the fungal UPR, was conserved in all four genomes. However, these genomes also encode putative transmembrane kinases with catalytic domains that are similar to the metazoan stress-sensing enzyme PKR-like endoplasmic reticulum kinase (PERK), although whether they function in the UPR of anaerobic fungi remains unclear. Furthermore, we characterized the global transcriptional responses of Anaeromyces robustus and Neocallimastix californiae to a transient heat shock. Both fungi exhibited the hallmarks of ER stress, including upregulation of genes with functions in protein folding, ER-associated degradation, and intracellular protein trafficking. Relative to other fungi, the genomes of Neocallimastigomycetes contained the greatest gene percentage of HSP20 and HSP70 chaperones, which may serve to stabilize their asparagine-rich genomes. Taken together, these results delineate the unique stress response of anaerobic fungi, which is an important step toward their development as a biotechnology platform to produce enzymes and valuable biomolecules.

PMID:37744151 | PMC:PMC10512342 | DOI:10.3389/ffunb.2021.708358

Front Fungal Biol. 2021 Apr 26;2:638595. doi: 10.3389/ffunb.2021.638595. eCollection 2021.

ABSTRACT

Fungal species resistant to current antifungal agents are considered as a serious threat to human health, the dilemma that has dragged attentions toward other sources of antifungals such as antimicrobial peptides (AMPs). In order to improve biological activity of a recently described antifungal peptide MCh-AMP1 from Matricaria chamomilla flowers, MCh-AMP1dimer (DiMCh-AMP1), containing 61 amino acid residues connected by flexible linker (GPDGSGPDESGPDES), was designed and expressed in Escherichia coli, and its structure was analyzed using bioinformatics tools. DiMCh-AMP1 synthetic gene was cloned into pET-28a expression vector, which was then used to transform E. coli BL21 (DE3) strain. His-tag purification was achieved using metal-chelate affinity chromatography. Because there is no methionine residue in the DiMCh-AMP1 sequence, cyanogen bromide was successfully used to separate the target product from the tag. Reverse-phase high-performance liquid chromatography was used as the final step of purification. Results showed that recombinant peptide was produced in considerable amounts (0.9 mg/L) with improved antifungal activity toward both yeasts and molds compared to its monomeric counterpart. The minimum inhibition concentration and minimum fungicidal concentration values of DiMCh-AMP1 against Candida and Aspergillus species were reported in the range of 1.67-6.66 μM and 3.33-26.64 μM, respectively. Our results showed that while antifungal activity of dimerized peptide was improved considerably, its cytotoxicity was decreased, implying that DiMCh-AMP1 could be a potential candidate to design an effective antifungal agent against pathogenic yeasts and molds.

PMID:37744143 | PMC:PMC10512307 | DOI:10.3389/ffunb.2021.638595

Front Fungal Biol. 2020 Dec 8;1:626551. doi: 10.3389/ffunb.2020.626551. eCollection 2020.

NO ABSTRACT

PMID:37743876 | PMC:PMC10512378 | DOI:10.3389/ffunb.2020.626551

New Phytol. 2023 Sep 25. doi: 10.1111/nph.19284. Online ahead of print.

ABSTRACT

Lateral root (LR) positioning and development rely on the dynamic interplay between auxin production, transport but also inactivation. Nonetheless, how the latter affects LR organogenesis remains largely uninvestigated. Here, we systematically analyze the impact of the major auxin inactivation pathway defined by GRETCHEN HAGEN3-type (GH3) auxin conjugating enzymes and DIOXYGENASE FOR AUXIN OXIDATION1 (DAO1) in all stages of LR development using reporters, genetics and inhibitors in Arabidopsis thaliana. Our data demonstrate that the gh3.1/2/3/4/5/6 hextuple (gh3hex) mutants display a higher LR density due to increased LR initiation and faster LR developmental progression, acting epistatically over dao1-1. Grafting and local inhibitor applications reveal that root and shoot GH3 activities control LR formation. The faster LR development in gh3hex is associated with GH3 expression domains in and around developing LRs. The increase in LR initiation is associated with accelerated auxin response oscillations coinciding with increases in apical meristem size and LR cap cell death rates. Our research reveals how GH3-mediated auxin inactivation attenuates LR development. Local GH3 expression in LR primordia attenuates development and emergence, whereas GH3 effects on pre-initiation stages are indirect, by modulating meristem activities that in turn coordinate root growth with LR spacing.

PMID:37743759 | DOI:10.1111/nph.19284

Genomics Proteomics Bioinformatics. 2023 Sep 22:S1672-0229(23)00105-5. doi: 10.1016/j.gpb.2023.03.006. Online ahead of print.

ABSTRACT

Epigenetic alterations are widespread in cancer and can complement genetic alterations to influence cancer progression and treatment outcome. To determine the potential contribution of DNA methylation alterations to tumor phenotype in non-small cell lung cancer (NSCLC) in both smoker and never-smoker patients, we performed genome-wide profiling of DNA methylation in 17 primary NSCLC tumors and 10 matched normal lung samples using the complementary assays methylation DNA immunoprecipitation (MeDIP-seq) and methylation sensitive restriction enzyme digestion followed by sequencing (MRE-seq). We reported recurrent methylation changes of several gene promoters, many previously implicated in cancer, including FAM83A and SEPT9 (hypomethylation), as well as PCDH7, NKX2-1, and SOX17 (hypermethylation). Although many methylation changes between tumors and their paired normal samples were shared across patients, several were specific to a particular smoking status. For example, never-smokers displayed a greater proportion of hypomethylated differentially methylated regions (hypoDMRs) and a greater number of recurrently hypomethylated promoters, including those of ASPSCR1, TOP2A, DPP9, and USP39, all previously linked to cancer. Changes outside of promoters were also widespread and often recurrent, particularly methylation loss over repetitive elements, highly enriched for ERV1 subfamilies. Recurrent hypoDMRs were enriched for several transcription factor binding motifs, often for genes involved in signaling and cell proliferation. For example, 71% of recurrent promoter hypoDMRs contained a motif for NKX2-1. Finally, the majority of DMRs were located within an active chromatin state in tissues profiled using the Roadmap Epigenome data, suggesting that methylation changes may contribute to altered regulatory programs through the adaptation of cell type-specific expression programs.

PMID:37742993 | DOI:10.1016/j.gpb.2023.03.006

J Alzheimers Dis. 2023 Sep 22. doi: 10.3233/JAD-230458. Online ahead of print.

ABSTRACT

BACKGROUND: A carbohydrate-restricted diet aimed at lowering insulin levels has the potential to slow Alzheimer's disease (AD). Restricting carbohydrate consumption reduces insulin resistance, which could improve glucose uptake and neural health. A hallmark feature of AD is widespread cortical thinning; however, no study has demonstrated that lower net carbohydrate (nCHO) intake is linked to attenuated cortical atrophy in patients with AD and confirmed amyloidosis.

OBJECTIVE: We tested the hypothesis that individuals with AD and confirmed amyloid burden eating a carbohydrate-restricted diet have thicker cortex than those eating a moderate-to-high carbohydrate diet.

METHODS: A total of 31 patients (mean age 71.4±7.0 years) with AD and confirmed amyloid burden were divided into two groups based on a 130 g/day nCHO cutoff. Cortical thickness was estimated from T1-weighted MRI using FreeSurfer. Cortical surface analyses were corrected for multiple comparisons using cluster-wise probability. We assessed group differences using a two-tailed two-independent sample t-test. Linear regression analyses using nCHO as a continuous variable, accounting for confounders, were also conducted.

RESULTS: The lower nCHO group had significantly thicker cortex within somatomotor and visual networks. Linear regression analysis revealed that lower nCHO intake levels had a significant association with cortical thickness within the frontoparietal, cingulo-opercular, and visual networks.

CONCLUSIONS: Restricting carbohydrates may be associated with reduced atrophy in patients with AD. Lowering nCHO to under 130 g/day would allow patients to follow the well-validated MIND diet while benefiting from lower insulin levels.

PMID:37742646 | DOI:10.3233/JAD-230458

BMC Med. 2023 Sep 25;21(1):364. doi: 10.1186/s12916-023-03067-3.

ABSTRACT

BACKGROUND: Epigenetic age is an estimator of biological age based on DNA methylation; its discrepancy from chronologic age warrants further investigation. We recently reported that greater polyphenol intake benefitted ectopic fats, brain function, and gut microbiota profile, corresponding with elevated urine polyphenols. The effect of polyphenol-rich dietary interventions on biological aging is yet to be determined.

METHODS: We calculated different biological aging epigenetic clocks of different generations (Horvath2013, Hannum2013, Li2018, Horvath skin and blood2018, PhenoAge2018, PCGrimAge2022), their corresponding age and intrinsic age accelerations, and DunedinPACE, all based on DNA methylation (Illumina EPIC array; pre-specified secondary outcome) for 256 participants with abdominal obesity or dyslipidemia, before and after the 18-month DIRECT PLUS randomized controlled trial. Three interventions were assigned: healthy dietary guidelines, a Mediterranean (MED) diet, and a polyphenol-rich, low-red/processed meat Green-MED diet. Both MED groups consumed 28 g walnuts/day (+ 440 mg/day polyphenols). The Green-MED group consumed green tea (3-4 cups/day) and Mankai (Wolffia globosa strain) 500-ml green shake (+ 800 mg/day polyphenols). Adherence to the Green-MED diet was assessed by questionnaire and urine polyphenols metabolomics (high-performance liquid chromatography quadrupole time of flight).

RESULTS: Baseline chronological age (51.3 ± 10.6 years) was significantly correlated with all methylation age (mAge) clocks with correlations ranging from 0.83 to 0.95; p < 2.2e - 16 for all. While all interventions did not differ in terms of changes between mAge clocks, greater Green-Med diet adherence was associated with a lower 18-month relative change (i.e., greater mAge attenuation) in Li and Hannum mAge (beta = - 0.41, p = 0.004 and beta = - 0.38, p = 0.03, respectively; multivariate models). Greater Li mAge attenuation (multivariate models adjusted for age, sex, baseline mAge, and weight loss) was mostly affected by higher intake of Mankai (beta = - 1.8; p = 0.061) and green tea (beta = - 1.57; p = 0.0016) and corresponded with elevated urine polyphenols: hydroxytyrosol, tyrosol, and urolithin C (p < 0.05 for all) and urolithin A (p = 0.08), highly common in green plants. Overall, participants undergoing either MED-style diet had ~ 8.9 months favorable difference between the observed and expected Li mAge at the end of the intervention (p = 0.02).

CONCLUSIONS: This study showed that MED and green-MED diets with increased polyphenols intake, such as green tea and Mankai, are inversely associated with biological aging. To the best of our knowledge, this is the first clinical trial to indicate a potential link between polyphenol intake, urine polyphenols, and biological aging.

TRIAL REGISTRATION: ClinicalTrials.gov, NCT03020186.

PMID:37743489 | DOI:10.1186/s12916-023-03067-3

Cell Rep. 2023 Sep 22;42(10):113173. doi: 10.1016/j.celrep.2023.113173. Online ahead of print.

ABSTRACT

G protein-coupled receptors (GPCRs) convert extracellular stimuli into intracellular signaling by coupling to heterotrimeric G proteins of four classes: Gi/o, Gq, Gs, and G12/13. However, our understanding of the G protein selectivity of GPCRs is incomplete. Here, we quantitatively measure the enzymatic activity of GPCRs in living cells and reveal the G protein selectivity of 124 GPCRs with the exact rank order of their G protein preference. Using this information, we establish a classification of GPCRs by functional selectivity, discover the existence of a G12/13-coupled receptor, G15-coupled receptors, and a variety of subclasses for Gi/o-, Gq-, and Gs-coupled receptors, culminating in development of the predictive algorithm of G protein selectivity. We further identify the structural determinants of G protein selectivity, allowing us to synthesize non-existent GPCRs with de novo G protein selectivity and efficiently identify putative pathogenic variants.

PMID:37742189 | DOI:10.1016/j.celrep.2023.113173

Brief Bioinform. 2023 Sep 22;24(6):bbad330. doi: 10.1093/bib/bbad330.

ABSTRACT

The emergence of multidrug-resistant bacteria is a critical global crisis that poses a serious threat to public health, particularly with the rise of multidrug-resistant Staphylococcus aureus. Accurate assessment of drug resistance is essential for appropriate treatment and prevention of transmission of these deadly pathogens. Early detection of drug resistance in patients is critical for providing timely treatment and reducing the spread of multidrug-resistant bacteria. This study aims to develop a novel risk assessment framework for S. aureus that can accurately determine the resistance to multiple antibiotics. The comprehensive 7-year study involved ˃20 000 isolates with susceptibility testing profiles of six antibiotics. By incorporating mass spectrometry and machine learning, the study was able to predict the susceptibility to four different antibiotics with high accuracy. To validate the accuracy of our models, we externally tested on an independent cohort and achieved impressive results with an area under the receiver operating characteristic curve of 0. 94, 0.90, 0.86 and 0.91, and an area under the precision-recall curve of 0.93, 0.87, 0.87 and 0.81, respectively, for oxacillin, clindamycin, erythromycin and trimethoprim-sulfamethoxazole. In addition, the framework evaluated the level of multidrug resistance of the isolates by using the predicted drug resistance probabilities, interpreting them in the context of a multidrug resistance risk score and analyzing the performance contribution of different sample groups. The results of this study provide an efficient method for early antibiotic decision-making and a better understanding of the multidrug resistance risk of S. aureus.

PMID:37742050 | DOI:10.1093/bib/bbad330

Parasit Vectors. 2023 Sep 23;16(1):334. doi: 10.1186/s13071-023-05947-2.

ABSTRACT

BACKGROUND: Interruption of parasite reproduction by targeting migrating schistosomula is a promising strategy for managing schistosomiasis. Hepatic schistosomula proteins previously identified based on second-generation schistosome DNA sequencing were found to hold excellent potential for schistosomiasis japonica diagnosis and as vaccine candidates. However, there are still many unknown schistosomula proteins that warrant further investigations. Herein, a novel schistosomula protein, the Schistosoma japonicum erythroid Krüppel-like factor (SjEKLF/KLF1), was explored.

METHODS: Sequence alignment was carried out to detect the amino acid sequence characteristics of SjEKLF. The expression profile of SjEKLF was determined by western blot and immunofluorescence analysis. Enzyme-linked immunosorbent assay was used to determine the antigenicity of SjEKLF in hosts. Mice immunised with recombinant SjEKLF were challenged to test the potential value of the protein as an immunoprotective target.

RESULTS: SjEKLF is defined as EKLF/KLF1 for its C-terminal DNA-binding domain. SjEKLF is mainly expressed in hepatic schistosomula and male adults and located within the intestinal intima of the parasites. Notably, high levels of SjEKLF-specific antibodies were detected in host sera and SjEKLF exhibited outstanding sensitivity and specificity for schistosomiasis japonica immunodiagnosis but failed to distinguish between ongoing infection and previous exposure. In addition, SjEKLF immunisation reduced the infection in vivo, resulting in decreased worm and egg counts, and alleviated body weight loss and hepatomegaly in infected mice.

CONCLUSIONS: Overall, these findings demonstrate that SjEKLF is critical for the infection of S. japonicum and may be a potential target to help control S. japonicum infection and transmission.

PMID:37742024 | DOI:10.1186/s13071-023-05947-2

J Transl Med. 2023 Sep 24;21(1):663. doi: 10.1186/s12967-023-04508-6.

ABSTRACT

BACKGROUND: There is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, although the mechanisms causing this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to vulnerabilities that are already present. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides.

METHODS: Urinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated.

RESULTS: In the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death [adjusted HR 1.2 (95% CI 1.17-1.24)]. The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% [adjusted HR 1.61 (95% CI 1.47-1.76)], consistent with adjusted meta-analytic HR estimate of 1.55 [95% CI 1.39-1.73]. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I (I).

CONCLUSION: The COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. This prediction is mainly based on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as a basis for proteomics-guided intervention aiming towards manipulating/ improving collagen turnover, thereby reducing the risk of death.

PMID:37741989 | DOI:10.1186/s12967-023-04508-6