Methods Mol Biol. 2024;2787:293-303. doi: 10.1007/978-1-0716-3778-4_20.

ABSTRACT

Phosphopeptide enrichment is the main bottleneck of every phosphorylation study. Therefore, in this chapter, a general workflow tries to overbridge the hurdles of plant sample handling from sample collection to protein extraction, protein solubilization, enzymatic digestion, and enrichment step prior to mass spectrometry. The workflow provides information to perform global proteomics as well as phosphoproteomics enabling the researcher to use the protocol in both fields.

PMID:38656498 | DOI:10.1007/978-1-0716-3778-4_20

Methods Mol Biol. 2024;2787:69-80. doi: 10.1007/978-1-0716-3778-4_4.

ABSTRACT

This chapter presents a holistic and quantitative approach to the carbon cycle in plant systems biology. It includes (rapid) phenotyping and monitoring of physiological key interactions of plants with its respective soil and atmospheric environment (soil plant atmospheric continuum-SPAC). The approach aims at qualifying and quantifying key components of this microhabitat as influenced by a single plant or a local group of plants in order to contribute to a flux-based modelling approach. The toolset consists of plant biometry, gas exchange, metabolomics, ionomics, root exudate characterization as well as soil biological and physical-chemical characterization. The results are presented as a basic interaction and input-output model aka conceptual system model employing H. T. Odum-style plots based on empirical data.

PMID:38656482 | DOI:10.1007/978-1-0716-3778-4_4

Clin Pharmacol Ther. 2024 Apr 24. doi: 10.1002/cpt.3274. Online ahead of print.

ABSTRACT

Warfarin dosing remains challenging due to substantial inter-individual variability, which can lead to unsafe or ineffective therapy with standard dosing. Model-informed precision dosing (MIPD) can help individualize warfarin dosing, requiring the selection of a suitable model. For models developed from clinical data, the dependence on the study design and population raises questions about generalizability. Quantitative system pharmacology (QSP) models promise better extrapolation abilities; however, their complexity and lack of validation on clinical data raise questions about applicability in MIPD. We have previously derived a mechanistic warfarin/international normalized ratio (INR) model from a blood coagulation QSP model. In this article, we evaluated the predictive performance of the warfarin/INR model in the context of MIPD using an external dataset with INR data from patients starting warfarin treatment. We assessed the accuracy and precision of model predictions, benchmarked against an empirically based reference model. Additionally, we evaluated covariate contributions and assessed the predictive performance separately in the more challenging outpatient data. The warfarin/INR model performed comparably to the reference model across various measures despite not being calibrated with warfarin initiation data. Including CYP2C9 and/or VKORC1 genotypes as covariates improved the prediction quality of the warfarin/INR model, even after assimilating 4 days of INR data. The outpatient INR exhibited higher unexplained variability, and predictions slightly exceeded observed values, suggesting that model adjustments might be necessary when transitioning from an inpatient to an outpatient setting. Overall, this research underscores the potential of QSP-derived models for MIPD, offering a complementary approach to empirical model development.

PMID:38655898 | DOI:10.1002/cpt.3274

J Proteome Res. 2024 Apr 24. doi: 10.1021/acs.jproteome.4c00020. Online ahead of print.

ABSTRACT

To prevent doping practices in sports, the World Anti-Doping Agency implemented the Athlete Biological Passport (ABP) program, monitoring biological variables over time to indirectly reveal the effects of doping rather than detect the doping substance or the method itself. In the context of this program, a highly multiplexed mass spectrometry-based proteomics assay for 319 peptides corresponding to 250 proteins was developed, including proteins associated with blood-doping practices. "Baseline" expression profiles of these potential biomarkers in capillary blood (dried blood spots (DBS)) were established using multiple reaction monitoring (MRM). Combining DBS microsampling with highly multiplexed MRM assays is the best-suited technology to enhance the effectiveness of the ABP program, as it represents a cost-effective and robust alternative analytical method with high specificity and selectivity of targets in the attomole range. DBS data were collected from 10 healthy athlete volunteers over a period of 140 days (28 time points per participant). These comprehensive findings provide a personalized targeted blood proteome "fingerprint" showcasing that the targeted proteome is unique to an individual and likely comparable to a DNA fingerprint. The results can serve as a baseline for future studies investigating doping-related perturbations.

PMID:38655860 | DOI:10.1021/acs.jproteome.4c00020

Adv Healthc Mater. 2024 Apr 24:e2304299. doi: 10.1002/adhm.202304299. Online ahead of print.

ABSTRACT

The mortality caused by tuberculosis (TB) infections is a global concern, and there is a need to improve our understanding of the disease. Current in vitro infection models to study the disease have limitations, such as short investigation durations and divergent transcriptional signatures. This study aims to overcome these limitations by developing a 3D collagen culture system that mimics the biomechanical and extracellular matrix (ECM) of lung microenvironment (collagen fibers, stiffness comparable to in vivo conditions), as the infection primarily manifests in the lungs. The system incorporates Mycobacterium tuberculosis (Mtb) infected human THP-1 or primary monocytes/macrophages. Dual RNA sequencing revealed higher mammalian gene expression similarity with patient samples than 2D macrophage infections. Similarly, bacterial gene expression more accurately recapitulated in vivo gene expression patterns compared to bacteria in 2D infection models. Key phenotypes observed in humans, such as foamy macrophages and mycobacterial cords, were reproduced in the model. This biomaterial system overcomes challenges associated with traditional platforms by modulating immune cells and closely mimicking in vivo infection conditions, including showing efficacy with clinically relevant concentrations of anti-TB drug pyrazinamide, not seen in any other in vitro infection model, making it reliable and readily adoptable for tuberculosis studies and drug screening. This article is protected by copyright. All rights reserved.

PMID:38655817 | DOI:10.1002/adhm.202304299

RSC Adv. 2024 Apr 23;14(19):13209-13217. doi: 10.1039/d4ra01516a. eCollection 2024 Apr 22.

ABSTRACT

Human flavin-containing monooxygenase 3 (FMO3) is a drug-metabolizing enzyme (DME) which is known to be highly polymorphic. Some of its polymorphic variants are associated with inter-individual differences that contribute to drug response. In order to measure these differences, the implementation of a quick and efficient in vitro assay is highly desirable. To this end, in this work a microfluidic immobilized enzyme reactor (μ-IMER) was developed with four separate serpentines where FMO3 and its two common polymorphic variants (V257M and E158K) were covalently immobilized via glutaraldehyde cross-linking in the presence of a polylysine coating. Computational fluid dynamics simulations were performed to calculate the selected substrate retention time in serpentines with different surface areas at various flow rates. The oxidation of tamoxifen, an anti-breast cancer drug, was used as a model reaction to characterize the new device in terms of available surface area for immobilization, channel coating, and applied flow rate. The highest amount of product was obtained when applying a 10 μL min-1 flow rate on polylysine-coated serpentines with a surface area of 90 mm2 each. Moreover, these conditions were used to test the device as a multi-enzymatic platform by simultaneously assessing the conversion of tamoxifen by FMO3 and its two polymorphic variants immobilized on different serpentines of the same chip. The results obtained demonstrate that the differences observed in the conversion of tamoxifen within the chip are similar to those already published (E158K > WT > V257M). Therefore, this microfluidic platform provides a feasible option for fabricating devices for personalised medicine.

PMID:38655484 | PMC:PMC11037025 | DOI:10.1039/d4ra01516a

Heliyon. 2024 Apr 15;10(8):e29598. doi: 10.1016/j.heliyon.2024.e29598. eCollection 2024 Apr 30.

ABSTRACT

BACKGROUND: Intestinal bacteria significantly contribute to the metabolism of intestinal epithelial tissues. As the occurrence and development of radiation enteritis (RE) depend on the "co-metabolism" microenvironment formed by the host and intestinal microbiota, which involves complex influencing factors and strong correlations, ordinary techniques struggle to fully explain the underlying mechanisms. However, given that it is based on systems biology, metabolomics analysis is well-suited to address these issues. This study aimed to analyze the metabolomic changes in urine, serum, and fecal samples during volumetric modulated arc therapy (VMAT) for cervical cancer and screen for characteristic metabolites of severe acute radiation enteritis (SARE) and RE.

METHODS: We enrolled 50 patients who received radiotherapy for cervical cancer. Urine, serum, and fecal samples of patients were collected at one day before radiotherapy and the second week, fourth week, and sixth week after the start of radiotherapy. Control group samples were collected during the baseline period. Differential metabolites were identified by metabolomics analysis; co-metabolic pathways were clarified. We used the mini-SOM library for incorporating characteristic metabolites, and established metabolite classification models for predicting SARE and RE.

RESULTS: Urine and serum sample data showed remarkable clustering effect; metabolomics data of the fecal supernatant were evidently disturbed. Patient sample analyses during VMAT revealed the following. Urine samples: Downregulation of the pyrimidine and riboflavin metabolism pathways as well as initial upregulation followed by downregulation of arginine and proline metabolism pathways and the arginine biosynthesis pathway. Fecal samples: Upregulation of linoleic acid and phenylalanine metabolic pathways and initial downregulation followed by upregulation of arachidonic acid (AA) metabolic pathways. Serum samples: Initial upregulation followed by downregulation of the arginine biosynthesis pathway and downregulation of glutathione, AA, and arginine and proline metabolic pathways.

CONCLUSION: Patients with cervical cancer exhibited characteristic metabolic pathways and characteristic metabolites predicting RE and SARE were screened out. An effective RE mini-SOM classification model was successfully established.

PMID:38655340 | PMC:PMC11036041 | DOI:10.1016/j.heliyon.2024.e29598

Front Cell Dev Biol. 2024 Apr 5;12:1324584. doi: 10.3389/fcell.2024.1324584. eCollection 2024.

ABSTRACT

ASCL1 is a transcription factor that directs neural progenitors towards lineage differentiation. Although many of the molecular mechanisms underlying its action have been described, several of its targets remain unidentified. We identified in the chick genome a putative enhancer (cE1) upstream of the transcription factor Scratch2 (Scrt2) locus with a predicted heterodimerization motif for ASCL1 and POU3F2. In this study, we investigated the role of ASCL1 and this enhancer in regulating the expression of the Scrt2 in the embryonic spinal cord. We confirmed that cE1 region interacted with the Scrt2 promoter. cE1 was sufficient to mediate ASCL1-driven expression in the neural tube through the heterodimerization sites. Moreover, Scrt2 expression was inhibited when we removed cE1 from the genome. These findings strongly indicate that ASCL1 regulates Scrt2 transcription in the neural tube through cE1.

PMID:38655067 | PMC:PMC11036302 | DOI:10.3389/fcell.2024.1324584

Front Genet. 2024 Apr 9;15:1399127. doi: 10.3389/fgene.2024.1399127. eCollection 2024.

NO ABSTRACT

PMID:38655051 | PMC:PMC11036335 | DOI:10.3389/fgene.2024.1399127

Front Plant Sci. 2024 Apr 9;15:1399420. doi: 10.3389/fpls.2024.1399420. eCollection 2024.

NO ABSTRACT

PMID:38654906 | PMC:PMC11035879 | DOI:10.3389/fpls.2024.1399420

BMC Biol. 2024 Apr 23;22(1):93. doi: 10.1186/s12915-024-01887-0.

ABSTRACT

BACKGROUND: The human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case-control results has made the identification of consistent and generalizable URT-disease associations difficult.

RESULTS: In order to address this issue, we assembled 26 independent 16S rRNA gene amplicon sequencing data sets from case-control URT studies, with approximately 2-3 studies per respiratory condition and ten distinct conditions covering common chronic and acute respiratory diseases. We leveraged the healthy control data across studies to investigate URT associations with age, sex, and geographic location, in order to isolate these associations from health and disease states.

CONCLUSIONS: We found several robust genus-level associations, across multiple independent studies, with either health or disease status. We identified disease associations specific to a particular respiratory condition and associations general to all conditions. Ultimately, we reveal robust associations between the URT microbiome, health, and disease, which hold across multiple studies and can help guide follow-up work on potential URT microbiome diagnostics and therapeutics.

PMID:38654335 | DOI:10.1186/s12915-024-01887-0

Sci Rep. 2024 Apr 23;14(1):9298. doi: 10.1038/s41598-024-59781-2.

ABSTRACT

Agaricales, Russulales and Boletales are dominant orders among the wild mushrooms in Basidiomycota. Boletaceae, one of the major functional elements in terrestrial ecosystem and mostly represented by ectomycorrhizal symbionts of trees in Indian Himalaya and adjoining hills, are extraordinarily diverse and represented by numerous genera and species which are unexplored or poorly known. Therefore, their hidden diversity is yet to be revealed. Extensive macrofungal exploration by the authors to different parts of Himalaya and surroundings, followed by through morphological studies and multigene molecular phylogeny lead to the discovery of five new species of wild mushrooms: Leccinellum bothii sp. nov., Phylloporus himalayanus sp. nov., Phylloporus smithii sp. nov., Porphyrellus uttarakhandae sp. nov., and Retiboletus pseudoater sp. nov. Present communication deals with morphological details coupled with illustrations and phylogenetic inferences. Besides, Leccinellum sinoaurantiacum and Xerocomus rugosellus are also reported for the first time from this country.

PMID:38654032 | DOI:10.1038/s41598-024-59781-2

Brief Bioinform. 2024 Mar 27;25(3):bbae180. doi: 10.1093/bib/bbae180.

ABSTRACT

There is a growing interest in inferring context specific gene regulatory networks from single-cell RNA sequencing (scRNA-seq) data. This involves identifying the regulatory relationships between transcription factors (TFs) and genes in individual cells, and then characterizing these relationships at the level of specific cell types or cell states. In this study, we introduce scGATE (single-cell gene regulatory gate) as a novel computational tool for inferring TF-gene interaction networks and reconstructing Boolean logic gates involving regulatory TFs using scRNA-seq data. In contrast to current Boolean models, scGATE eliminates the need for individual formulations and likelihood calculations for each Boolean rule (e.g. AND, OR, XOR). By employing a Bayesian framework, scGATE infers the Boolean rule after fitting the model to the data, resulting in significant reductions in time-complexities for logic-based studies. We have applied assay for transposase-accessible chromatin with sequencing (scATAC-seq) data and TF DNA binding motifs to filter out non-relevant TFs in gene regulations. By integrating single-cell clustering with these external cues, scGATE is able to infer context specific networks. The performance of scGATE is evaluated using synthetic and real single-cell multi-omics data from mouse tissues and human blood, demonstrating its superiority over existing tools for reconstructing TF-gene networks. Additionally, scGATE provides a flexible framework for understanding the complex combinatorial and cooperative relationships among TFs regulating target genes by inferring Boolean logic gates among them.

PMID:38653489 | DOI:10.1093/bib/bbae180

Cell Rep. 2024 Apr 21;43(5):114128. doi: 10.1016/j.celrep.2024.114128. Online ahead of print.

ABSTRACT

Shifts in the magnitude and nature of gut microbial metabolites have been implicated in Alzheimer's disease (AD), but the host receptors that sense and respond to these metabolites are largely unknown. Here, we develop a systems biology framework that integrates machine learning and multi-omics to identify molecular relationships of gut microbial metabolites with non-olfactory G-protein-coupled receptors (termed the "GPCRome"). We evaluate 1.09 million metabolite-protein pairs connecting 408 human GPCRs and 335 gut microbial metabolites. Using genetics-derived Mendelian randomization and integrative analyses of human brain transcriptomic and proteomic profiles, we identify orphan GPCRs (i.e., GPR84) as potential drug targets in AD and that triacanthine experimentally activates GPR84. We demonstrate that phenethylamine and agmatine significantly reduce tau hyperphosphorylation (p-tau181 and p-tau205) in AD patient induced pluripotent stem cell-derived neurons. This study demonstrates a systems biology framework to uncover the GPCR targets of human gut microbiota in AD and other complex diseases if broadly applied.

PMID:38652661 | DOI:10.1016/j.celrep.2024.114128

Cell Rep. 2024 Apr 21;43(5):114139. doi: 10.1016/j.celrep.2024.114139. Online ahead of print.

ABSTRACT

Glioblastoma (GBM) is a deadly brain tumor, and the kinesin motor KIF11 is an attractive therapeutic target with roles in proliferation and invasion. Resistance to KIF11 inhibitors, which has mainly been studied in animal models, presents significant challenges. We use lineage-tracing barcodes and single-cell RNA sequencing to analyze resistance in patient-derived GBM neurospheres treated with ispinesib, a potent KIF11 inhibitor. Similar to GBM progression in patients, untreated cells lose their neural lineage identity and become mesenchymal, which is associated with poor prognosis. Conversely, cells subjected to long-term ispinesib treatment exhibit a proneural phenotype. We generate patient-derived xenografts and show that ispinesib-resistant cells form less aggressive tumors in vivo, even in the absence of drug. Moreover, treatment of human ex vivo GBM slices with ispinesib demonstrates phenotypic alignment with in vitro responses, underscoring the clinical relevance of our findings. Finally, using retrospective lineage tracing, we identify drugs that are synergistic with ispinesib.

PMID:38652658 | DOI:10.1016/j.celrep.2024.114139

J Clin Invest. 2024 Apr 23:e176466. doi: 10.1172/JCI176466. Online ahead of print.

ABSTRACT

BACKGROUND: Features of consumptive coagulopathy and thromboinflammation are prominent in cerebral malaria (CM). We hypothesized that thrombogenic autoantibodies contribute to a procoagulant state in CM.

METHODS: Plasma from children with uncomplicated malaria (UM, n = 124) and CM (n = 136) was analyzed by ELISA for a panel of 8 autoantibodies including anti-Platelet Factor 4/polyanion (anti-PF4/P), anti-Phospholipid, anti-Phosphatidylserine, anti-Myeloperoxidase, anti-Proteinase 3, anti-dsDNA, anti-Beta-2-Glycoprotein I (β2GPI), and anti-Cardiolipin. Non-malaria coma (NMC, n = 49) and healthy controls (HC, n = 56) were assayed for comparison. Associations with clinical and immune biomarkers were determined using univariate and logistic regression analyses.

RESULTS: Median anti-PF4/P and anti-PS IgG levels were elevated with malaria infection relative to HC (P < 0.001) and NMC (PF4/P: P < 0.001). Anti-PF4/P IgG levels were elevated in CM (median = 0.27, IQR: 0.19-0.41) compared to UM (median = 0.19, IQR: 0.14-0.22, P ≤ 0.0001). Anti-PS IgG levels did not differ between UM and CM (P = 0.39). When CM cases were stratified by malaria retinopathy (Ret) status, levels of anti-PF4/P IgG correlated negatively with peripheral platelet count in Ret+ CM cases (Rs = 0.201, P = 0.04) and associated positively with mortality (OR = 15.2, 95% CI: 1.02-275, P = 0.048). Plasma from CM patients induced a greater platelet activation capacity in an ex-vivo assay relative to plasma from UM patients (P = 0.02). Platelet activation was associated with anti-PF4/P IgG levels (Rs = 0.293, P = 0.035).

CONCLUSIONS: Thrombosis mediated by elevated anti-PF4/P autoantibodies may be one mechanism contributing to the clinical complications of CM.

PMID:38652559 | DOI:10.1172/JCI176466

Microbiol Spectr. 2024 Apr 23:e0400623. doi: 10.1128/spectrum.04006-23. Online ahead of print.

ABSTRACT

Cystic fibrosis (CF), an inherited genetic disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator gene, results in sticky and thick mucosal fluids. This environment facilitates the colonization of various microorganisms, some of which can cause acute and chronic lung infections, while others may positively impact the disease. Rothia mucilaginosa, an oral commensal, is relatively abundant in the lungs of CF patients. Recent studies have unveiled its anti-inflammatory properties using in vitro three-dimensional lung epithelial cell cultures and in vivo mouse models relevant to chronic lung diseases. Apart from this, R. mucilaginosa has been associated with severe infections. However, its metabolic capabilities and genotype-phenotype relationships remain largely unknown. To gain insights into its cellular metabolism and genetic content, we developed the first manually curated genome-scale metabolic model, iRM23NL. Through growth kinetics and high-throughput phenotypic microarray testings, we defined its complete catabolic phenome. Subsequently, we assessed the model's effectiveness in accurately predicting growth behaviors and utilizing multiple substrates. We used constraint-based modeling techniques to formulate novel hypotheses that could expedite the development of antimicrobial strategies. More specifically, we detected putative essential genes and assessed their effect on metabolism under varying nutritional conditions. These predictions could offer novel potential antimicrobial targets without laborious large-scale screening of knockouts and mutant transposon libraries. Overall, iRM23NL demonstrates a solid capability to predict cellular phenotypes and holds immense potential as a valuable resource for accurate predictions in advancing antimicrobial therapies. Moreover, it can guide metabolic engineering to tailor R. mucilaginosa's metabolism for desired performance.IMPORTANCECystic fibrosis (CF) is a genetic disorder characterized by thick mucosal secretions, leading to chronic lung infections. Rothia mucilaginosa is a common bacterium found in various parts of the human body, acting as a normal part of the flora. In people with weakened immune systems, it can become an opportunistic pathogen, while it is prevalent and active in CF airways. Recent studies have highlighted its anti-inflammatory properties in the lower pulmonary system, indicating the intricate relationship between microbes and human health. Herein, we have developed the first manually curated metabolic model of R. mucilaginosa. Our study examined the previously unknown relationships between the bacterium's genotype and phenotype and identified essential genes that impact the metabolism under various conditions. With this, we opt for paving the way for developing new strategies in antimicrobial therapy and metabolic engineering, leading to enhanced therapeutic outcomes in cystic fibrosis and related conditions.

PMID:38652457 | DOI:10.1128/spectrum.04006-23

Daru. 2024 Apr 23. doi: 10.1007/s40199-024-00507-0. Online ahead of print.

ABSTRACT

PURPOSE: Identifying the molecular mechanisms behind SARS-CoV-2 disparities and similarities will help find new treatments. The present study determines networks' shared and non-shared (specific) crucial elements in response to HCoV-229E and SARS-CoV-2 viruses to recommend candidate medications.

METHODS: We retrieved the omics data on respiratory cells infected with HCoV-229E and SARS-CoV-2, constructed PPIN and GRN, and detected clusters and motifs. Using a drug-gene interaction network, we determined the similarities and disparities of mechanisms behind their host response and drug-repurposed.

RESULTS: CXCL1, KLHL21, SMAD3, HIF1A, and STAT1 were the shared DEGs between both viruses' protein-protein interaction network (PPIN) and gene regulatory network (GRN). The NPM1 was a specific critical node for HCoV-229E and was a Hub-Bottleneck shared between PPI and GRN in HCoV-229E. The HLA-F, ADCY5, TRIM14, RPF1, and FGA were the seed proteins in subnetworks of the SARS-CoV-2 PPI network, and HSPA1A and RPL26 proteins were the seed in subnetworks of the PPI network of HCOV-229E. TRIM14, STAT2, and HLA-F played the same role for SARS-CoV-2. Top enriched KEGG pathways included cell cycle and proteasome in HCoV-229E and RIG-I-like receptor, Chemokine, Cytokine-cytokine, NOD-like receptor, and TNF signaling pathways in SARS-CoV-2. We suggest some candidate medications for COVID-19 patient lungs, including Noscapine, Isoetharine mesylate, Cycloserine, Ethamsylate, Cetylpyridinium, Tretinoin, Ixazomib, Vorinostat, Venetoclax, Vorinostat, Ixazomib, Venetoclax, and epoetin alfa for further in-vitro and in-vivo investigations.

CONCLUSION: We suggested CXCL1, KLHL21, SMAD3, HIF1A, and STAT1, ADCY5, TRIM14, RPF1, and FGA, STAT2, and HLA-F as critical genes and Cetylpyridinium, Cycloserine, Noscapine, Ethamsylate, Epoetin alfa, Isoetharine mesylate, Ribavirin, and Tretinoin drugs to study further their importance in treating COVID-19 lung complications.

PMID:38652363 | DOI:10.1007/s40199-024-00507-0

Future Microbiol. 2024 Apr 23. doi: 10.2217/fmb-2024-0043. Online ahead of print.

ABSTRACT

Aim: Proof-of-concept study, highlighting the clinical diagnostic ability of FT-IR compared with MALDI-TOF MS, combined with WGS. Materials & methods: 104 pathogenic isolates of Neisseria meningitidis, Streptococcus pneumoniae, Streptococcus pyogenes and Staphylococcus aureus were analyzed. Results: Overall prediction accuracy was 99.6% in FT-IR and 95.8% in MALDI-TOF-MS. Analysis of N. meningitidis serogroups was superior in FT-IR compared with MALDI-TOF-MS. Phylogenetic relationship of S. pyogenes was similar by FT-IR and WGS, but not S. aureus or S. pneumoniae. Clinical severity was associated with the zinc ABC transporter and DNA repair genes in S. pneumoniae and cell wall proteins (biofilm formation, antibiotic and complement permeability) in S. aureus via WGS. Conclusion: FT-IR warrants further clinical evaluation as a promising diagnostic tool.

PMID:38652264 | DOI:10.2217/fmb-2024-0043

Elife. 2024 Apr 23;12:RP88742. doi: 10.7554/eLife.88742.

ABSTRACT

Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.

PMID:38652107 | DOI:10.7554/eLife.88742