Microb Cell Fact. 2024 Jun 18;23(1):180. doi: 10.1186/s12934-024-02459-1.

ABSTRACT

Nowadays, biofuels, especially bioethanol, are becoming increasingly popular as an alternative to fossil fuels. Zymomonas mobilis is a desirable species for bioethanol production due to its unique characteristics, such as low biomass production and high-rate glucose metabolism. However, several factors can interfere with the fermentation process and hinder microbial activity, including lignocellulosic hydrolysate inhibitors, high temperatures, an osmotic environment, and high ethanol concentration. Overcoming these limitations is critical for effective bioethanol production. In this review, the stress response mechanisms of Z. mobilis are discussed in comparison to other ethanol-producing microbes. The mechanism of stress response is divided into physiological (changes in growth, metabolism, intracellular components, and cell membrane structures) and molecular (up and down-regulation of specific genes and elements of the regulatory system and their role in expression of specific proteins and control of metabolic fluxes) changes. Systemic metabolic engineering approaches, such as gene manipulation, overexpression, and silencing, are successful methods for building new metabolic pathways. Therefore, this review discusses systems metabolic engineering in conjunction with systems biology and synthetic biology as an important method for developing new strains with an effective response mechanism to fermentation stresses during bioethanol production. Overall, understanding the stress response mechanisms of Z. mobilis can lead to more efficient and effective bioethanol production.

PMID:38890644 | DOI:10.1186/s12934-024-02459-1

Mol Syst Biol. 2024 Jun 18. doi: 10.1038/s44320-024-00041-w. Online ahead of print.

ABSTRACT

Correlation is not causation: this simple and uncontroversial statement has far-reaching implications. Defining and applying causality in biomedical research has posed significant challenges to the scientific community. In this perspective, we attempt to connect the partly disparate fields of systems biology, causal reasoning, and machine learning to inform future approaches in the field of systems biology and molecular medicine.

PMID:38890548 | DOI:10.1038/s44320-024-00041-w

Nat Med. 2024 Jun 18. doi: 10.1038/s41591-024-03030-6. Online ahead of print.

ABSTRACT

The pathogenesis of allograft (dys)function has been increasingly studied using 'omics'-based technologies, but the focus on individual organs has created knowledge gaps that neither unify nor distinguish pathological mechanisms across allografts. Here we present a comprehensive study of human pan-organ allograft dysfunction, analyzing 150 datasets with more than 12,000 samples across four commonly transplanted solid organs (heart, lung, liver and kidney, n = 1,160, 1,241, 1,216 and 8,853 samples, respectively) that we leveraged to explore transcriptomic differences among allograft dysfunction (delayed graft function, acute rejection and fibrosis), tolerance and stable graft function. We identified genes that correlated robustly with allograft dysfunction across heart, lung, liver and kidney transplantation. Furthermore, we developed a transfer learning omics prediction framework that, by borrowing information across organs, demonstrated superior classifications compared to models trained on single organs. These findings were validated using a single-center prospective kidney transplant cohort study (a collective 329 samples across two timepoints), providing insights supporting the potential clinical utility of our approach. Our study establishes the capacity for machine learning models to learn across organs and presents a transcriptomic transplant resource that can be employed to develop pan-organ biomarkers of allograft dysfunction.

PMID:38890530 | DOI:10.1038/s41591-024-03030-6

Nat Genet. 2024 Jun 18. doi: 10.1038/s41588-024-01785-9. Online ahead of print.

ABSTRACT

Tumor genomic profiling is increasingly seen as a prerequisite to guide the treatment of patients with cancer. To explore the value of whole-genome sequencing (WGS) in broadening the scope of cancers potentially amenable to a precision therapy, we analysed whole-genome sequencing data on 10,478 patients spanning 35 cancer types recruited to the UK 100,000 Genomes Project. We identified 330 candidate driver genes, including 74 that are new to any cancer. We estimate that approximately 55% of patients studied harbor at least one clinically relevant mutation, predicting either sensitivity or resistance to certain treatments or clinical trial eligibility. By performing computational chemogenomic analysis of cancer mutations we identify additional targets for compounds that represent attractive candidates for future clinical trials. This study represents one of the most comprehensive efforts thus far to identify cancer driver genes in the real world setting and assess their impact on informing precision oncology.

PMID:38890488 | DOI:10.1038/s41588-024-01785-9

Leukemia. 2024 Jun 18. doi: 10.1038/s41375-024-02305-8. Online ahead of print.

NO ABSTRACT

PMID:38890446 | DOI:10.1038/s41375-024-02305-8

Cell Discov. 2024 Jun 18;10(1):68. doi: 10.1038/s41421-024-00691-y.

NO ABSTRACT

PMID:38890333 | DOI:10.1038/s41421-024-00691-y

Nat Commun. 2024 Jun 18;15(1):5218. doi: 10.1038/s41467-024-49365-z.

ABSTRACT

Technologies that generate precise combinatorial genome modifications are well suited to dissect the polygenic basis of complex phenotypes and engineer synthetic genomes. Genome modifications with engineered nucleases can lead to undesirable repair outcomes through imprecise homology-directed repair, requiring non-cleavable gene editing strategies. Eukaryotic multiplex genome engineering (eMAGE) generates precise combinatorial genome modifications in Saccharomyces cerevisiae without generating DNA breaks or using engineered nucleases. Here, we systematically optimize eMAGE to achieve 90% editing frequency, reduce workflow time, and extend editing distance to 20 kb. We further engineer an inducible dominant negative mismatch repair system, allowing for high-efficiency editing via eMAGE while suppressing the elevated background mutation rate 17-fold resulting from mismatch repair inactivation. We apply these advances to construct a library of cancer-associated mutations in the ligand-binding domains of human estrogen receptor alpha and progesterone receptor to understand their impact on ligand-independent autoactivation. We validate that this yeast model captures autoactivation mutations characterized in human breast cancer models and further leads to the discovery of several previously uncharacterized autoactivating mutations. This work demonstrates the development and optimization of a cleavage-free method of genome editing well suited for applications requiring efficient multiplex editing with minimal background mutations.

PMID:38890276 | DOI:10.1038/s41467-024-49365-z

Cell Rep Methods. 2024 Jun 17;4(6):100800. doi: 10.1016/j.crmeth.2024.100800.

ABSTRACT

The tumor microenvironment harbors a variety of different cell types that differentially impact tumor biology. In this issue of Cell Reports Methods, Raffo-Romero et al. standardized and optimized 3D tumor organoids to model the interactions between tumor-associated macrophages and tumor cells in vitro.

PMID:38889689 | DOI:10.1016/j.crmeth.2024.100800

Cell Rep Methods. 2024 Jun 17;4(6):100799. doi: 10.1016/j.crmeth.2024.100799.

ABSTRACT

The cellular components of tumors and their microenvironment play pivotal roles in tumor progression, patient survival, and the response to cancer treatments. Unveiling a comprehensive cellular profile within bulk tumors via single-cell RNA sequencing (scRNA-seq) data is crucial, as it unveils intrinsic tumor cellular traits that elude identification through conventional cancer subtyping methods. Our contribution, scBeacon, is a tool that derives cell-type signatures by integrating and clustering multiple scRNA-seq datasets to extract signatures for deconvolving unrelated tumor datasets on bulk samples. Through the employment of scBeacon on the The Cancer Genome Atlas (TCGA) cohort, we find cellular and molecular attributes within specific tumor categories, many with patient outcome relevance. We developed a tumor cell-type map to visually depict the relationships among TCGA samples based on the cell-type inferences.

PMID:38889686 | DOI:10.1016/j.crmeth.2024.100799

Cell Rep Methods. 2024 Jun 17;4(6):100797. doi: 10.1016/j.crmeth.2024.100797.

ABSTRACT

Cancer of unknown primary (CUP) represents metastatic cancer where the primary site remains unidentified despite standard diagnostic procedures. To determine the tumor origin in such cases, we developed BPformer, a deep learning method integrating the transformer model with prior knowledge of biological pathways. Trained on transcriptomes from 10,410 primary tumors across 32 cancer types, BPformer achieved remarkable accuracy rates of 94%, 92%, and 89% in primary tumors and primary and metastatic sites of metastatic tumors, respectively, surpassing existing methods. Additionally, BPformer was validated in a retrospective study, demonstrating consistency with tumor sites diagnosed through immunohistochemistry and histopathology. Furthermore, BPformer was able to rank pathways based on their contribution to tumor origin identification, which helped to classify oncogenic signaling pathways into those that are highly conservative among different cancers versus those that are highly variable depending on their origins.

PMID:38889685 | DOI:10.1016/j.crmeth.2024.100797

Curr Biol. 2024 Jun 17;34(12):R573-R575. doi: 10.1016/j.cub.2024.05.011.

ABSTRACT

The fate of transcribed RNA dictates cellular function. A new study finds that mutations in specific RNA processing machinery genes result in de-silencing of a transcript encoding a subunit of the mitochondrial electron transport chain and rescue of a mitochondrial respiratory complex I defect.

PMID:38889679 | DOI:10.1016/j.cub.2024.05.011

Bioinformatics. 2024 Jun 18:btae374. doi: 10.1093/bioinformatics/btae374. Online ahead of print.

ABSTRACT

MOTIVATION: Single-cell omics technologies have enabled the quantification of molecular profiles in individual cells at an unparalleled resolution. Deep learning, a rapidly evolving sub-field of machine learning, has instilled a significant interest in single-cell omics research due to its remarkable success in analysing heterogeneous high-dimensional single-cell omics data. Nevertheless, the inherent multi-layer nonlinear architecture of deep learning models often makes them 'black boxes' as the reasoning behind predictions is often unknown and not transparent to the user. This has stimulated an increasing body of research for addressing the lack of interpretability in deep learning models, especially in single-cell omics data analyses, where the identification and understanding of molecular regulators are crucial for interpreting model predictions and directing downstream experimental validations.

RESULTS: In this work, we introduce the basics of single-cell omics technologies and the concept of interpretable deep learning. This is followed by a review of the recent interpretable deep learning models applied to various single-cell omics research. Lastly, we highlight the current limitations and discuss potential future directions.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:38889275 | DOI:10.1093/bioinformatics/btae374

PLoS One. 2024 Jun 18;19(6):e0305673. doi: 10.1371/journal.pone.0305673. eCollection 2024.

ABSTRACT

Microbial fuel cells (MFCs) are innovative eco-friendly technologies that advance a circular economy by enabling the conversion of both organic and inorganic substances in wastewater to electricity. While conceptually promising, there are lingering questions regarding the performance and stability of MFCs in real industrial settings. To address this research gap, we investigated the influence of specific operational settings, regarding the hydraulic retention time (HRT) and organic loading rate (OLR) on the performance of MFCs used for treating sulfide-rich wastewater from a canned pineapple factory. Experiments were performed at varying hydraulic retention times (2 days and 4 days) during both low and high seasonal production. Through optimization, we achieved a current density generation of 47±15 mA/m2, a COD removal efficiency of 91±9%, and a sulfide removal efficiency of 86±10%. Microbiome analysis revealed improved MFC performance when there was a substantial presence of electrogenic bacteria, sulfide-oxidizing bacteria, and methanotrophs, alongside a reduced abundance of sulfate-reducing bacteria and methanogens. In conclusion, we recommend the following operational guidelines for applying MFCs in industrial wastewater treatment: (i) Careful selection of the microbial inoculum, as this step significantly influences the composition of the MFC microbial community and its overall performance. (ii) Initiating MFC operation with an appropriate OLR is essential. This helps in establishing an effective and adaptable microbial community within the MFCs, which can be beneficial when facing variations in OLR due to seasonal production changes. (iii) Identifying and maintaining MFC-supporting microbes, including those identified in this study, should be a priority. Keeping these microbes as an integral part of the system's microbial composition throughout the operation enhances and stabilizes MFC performance.

PMID:38889113 | DOI:10.1371/journal.pone.0305673

J Antimicrob Chemother. 2024 Jun 18:dkae176. doi: 10.1093/jac/dkae176. Online ahead of print.

ABSTRACT

OBJECTIVES: MDR and XDR Neisseria gonorrhoeae strains remain major public health concerns internationally, and quality-assured global gonococcal antimicrobial resistance (AMR) surveillance is imperative. The WHO global Gonococcal Antimicrobial Surveillance Programme (GASP) and WHO Enhanced GASP (EGASP), including metadata and WGS, are expanding internationally. We present the phenotypic, genetic and reference genome characteristics of the 2024 WHO gonococcal reference strains (n = 15) for quality assurance worldwide. All superseded WHO gonococcal reference strains (n = 14) were identically characterized.

MATERIAL AND METHODS: The 2024 WHO reference strains include 11 of the 2016 WHO reference strains, which were further characterized, and four novel strains. The superseded WHO reference strains include 11 WHO reference strains previously unpublished. All strains were characterized phenotypically and genomically (single-molecule PacBio or Oxford Nanopore and Illumina sequencing).

RESULTS: The 2024 WHO reference strains represent all available susceptible and resistant phenotypes and genotypes for antimicrobials currently and previously used (n = 22), or considered for future use (n = 3) in gonorrhoea treatment. The novel WHO strains include internationally spreading ceftriaxone resistance, ceftriaxone resistance due to new penA mutations, ceftriaxone plus high-level azithromycin resistance and azithromycin resistance due to mosaic MtrRCDE efflux pump. AMR, serogroup, prolyliminopeptidase, genetic AMR determinants, plasmid types, molecular epidemiological types and reference genome characteristics are presented for all strains.

CONCLUSIONS: The 2024 WHO gonococcal reference strains are recommended for internal and external quality assurance in laboratory examinations, especially in the WHO GASP, EGASP and other GASPs, but also in phenotypic and molecular diagnostics, AMR prediction, pharmacodynamics, epidemiology, research and as complete reference genomes in WGS analysis.

PMID:38889110 | DOI:10.1093/jac/dkae176

J Cell Biol. 2024 Sep 2;223(9):e202401110. doi: 10.1083/jcb.202401110. Epub 2024 Jun 18.

ABSTRACT

Macropinocytosis mediates the non-selective bulk uptake of extracellular fluid, enabling cells to survey the environment and obtain nutrients. A conserved set of signaling proteins orchestrates the actin dynamics that lead to membrane ruffling and macropinosome formation across various eukaryotic organisms. At the center of this signaling network are Ras GTPases, whose activation potently stimulates macropinocytosis. However, how Ras signaling is initiated and spatiotemporally regulated during macropinocytosis is not well understood. By using the model system Dictyostelium and a proteomics-based approach to identify regulators of macropinocytosis, we uncovered Leep2, consisting of Leep2A and Leep2B, as a RasGAP complex. The Leep2 complex specifically localizes to emerging macropinocytic cups and nascent macropinosomes, where it modulates macropinosome formation by regulating the activities of three Ras family small GTPases. Deletion or overexpression of the complex, as well as disruption or sustained activation of the target Ras GTPases, impairs macropinocytic activity. Our data reveal the critical role of fine-tuning Ras activity in directing macropinosome formation.

PMID:38888895 | DOI:10.1083/jcb.202401110

Hepatol Int. 2024 Jun 18. doi: 10.1007/s12072-024-10665-7. Online ahead of print.

ABSTRACT

BACKGROUND: The associations between sleep patterns or behaviors and the risk of cirrhosis and the influence of genetic susceptibility on these associations among NAFLD participants remain inadequately elucidated.

METHODS: This study conducted a prospective follow-up of 112,196 NAFLD participants diagnosed at baseline from the UK Biobank cohort study. Five sleep behaviors were collected to measure a healthy sleep score. Five genetic variants were used to construct a polygenic risk score. We used Cox proportional hazard model to assess hazard ratios (HR) and 95% confidence intervals (CIs) for incidence of cirrhosis.

RESULTS: During the follow-up, 592 incident cirrhosis cases were documented. Healthy sleep pattern was associated with reduced risk of cirrhosis in a dose-response manner (ptrend < 0.001). Participants with favourable sleep score (versus unfavourable sleep score) had an HR of 0.55 for cirrhosis risk (95% CI 0.39-0.78). Multivariable-adjusted HRs (95% CIs) of cirrhosis incidence for NAFLDs with no frequent insomnia, sleeping for 7-8 h per day, and no excessive daytime dozing behaviors were 0.73 (0.61-0.87), 0.79 (0.66-0.93), and 0.69 (0.50-0.95), respectively. Compared with participants with favourable sleep pattern and low genetic risk, those with unfavourable sleep pattern and high genetic risk had higher risks of cirrhosis incidence (HR 3.16, 95% CI 1.88-5.33). In addition, a significant interaction between chronotype and genetic risk was detected for the incidence of cirrhosis (p for multiplicative interaction = 0.004).

CONCLUSION: An association was observed between healthy sleep pattern and decreased risk of cirrhosis among NAFLD participants, regardless of low or high genetic risk.

PMID:38888882 | DOI:10.1007/s12072-024-10665-7

J Agric Food Chem. 2024 Jun 18. doi: 10.1021/acs.jafc.4c02342. Online ahead of print.

ABSTRACT

Beyond the key bitter compound kaempferol 3-O-(2‴-O-sinapoyl-β-d-sophoroside) previously described in the literature (1), eight further bitter and astringent-tasting kaempferol glucosides (2-9) have been identified in rapeseed protein isolates (Brassica napus L.). The bitterness and astringency of these taste-active substances have been described with taste threshold concentrations ranging from 3.3 to 531.7 and 0.3 to 66.4 μmol/L, respectively, as determined by human sensory experiments. In this study, the impact of 1 and kaempferol 3-O-β-d-glucopyranoside (8) on TAS2R-linked proton secretion by HGT-1 cells was analyzed by quantification of the intracellular proton index. mRNA levels of bitter receptors TAS2R3, 4, 5, 13, 30, 31, 39, 40, 43, 45, 46, 50 and TAS2R8 were increased after treatment with compounds 1 and 8. Using quantitative UHPLC-MS/MSMRM measurements, the concentrations of 1-9 were determined in rapeseed/canola seeds and their corresponding protein isolates. Depending on the sample material, compounds 1, 3, and 5-9 exceeded dose over threshold (DoT) factors above one for both bitterness and astringency in selected protein isolates. In addition, an increase in the key bitter compound 1 during industrial protein production (apart from enrichment) was observed, allowing the identification of the potential precursor of 1 to be kaempferol 3-O-(2‴-O-sinapoyl-β-d-sophoroside)-7-O-β-d-glucopyranoside (3). These results may contribute to the production of less bitter and astringent rapeseed protein isolates through the optimization of breeding and postharvest downstream processing.

PMID:38888424 | DOI:10.1021/acs.jafc.4c02342

Int J Dermatol. 2024 Jun 17. doi: 10.1111/ijd.17295. Online ahead of print.

ABSTRACT

BACKGROUND: CELF2 belongs to the CELF RNA-binding protein family and exhibits antitumor activity in various tumor models. Analysis of the pan-cancer TCGA database reveals that CELF2 expression strongly correlates with favorable prognosis among cancer patients. The function of CELF2 in nonmelanoma skin cancer has not been studied.

METHODS: We used shRNA-mediated knockdown (KD) of CELF2 expression in human squamous cell carcinoma (SCC) cells to investigate how CELF2 impacted SCC cell proliferation, survival, and xenograft tumor growth. We determined CELF2 expression in human SCC tissues and adjacent normal skin using immunofluorescence staining. Additionally, we investigated the changes in CELF2 and its target gene expression during UV-induced and chemical-induced skin tumorigenesis by western blotting.

RESULTS: CELF2 KD significantly increased SCC cell proliferation, colony growth, and SCC xenograft tumor growth in immunodeficient mice. CELF2 KD in SCC cells led to activation of KRT80 and GDF15, which can potentially promote cell proliferation and tumor growth. While control SCC cells were sensitive to anticancer drugs such as doxorubicin, SCC cells with CELF2 KD became resistant to drug-induced tumor growth retardation. Finally, we found CELF2 expression diminished during both UV- and chemical-induced skin tumorigenesis in mice, consistent with reduced CELF2 expression in human SCC tumors compared to adjacent normal skin.

CONCLUSION: This study shows for the first time that CELF2 loss occurs during skin tumorigenesis and increases drug resistance in SCC cells, highlighting the possibility of targeting CELF2-regulated pathways in skin cancer prevention and therapies.

PMID:38887832 | DOI:10.1111/ijd.17295

Front Plant Sci. 2024 Jun 3;15:1394799. doi: 10.3389/fpls.2024.1394799. eCollection 2024.

ABSTRACT

This study evaluated the potential impact of climate change on the distribution of Forsythia suspensa, a valuable traditional Chinese medicinal plant, using the MaxEnt model integrated with Geographic Information System (GIS). By analyzing occurrence data from various databases and environmental variables including climate and soil factors, we forecasted the present and future (2050s and 2070s) habitat suitability of F. suspensa under different greenhouse gas emission scenarios (RCP8.5, RCP4.5, RCP2.6). Results indicated that the suitable habitats for F. suspensa were primarily located in North, East, Central, Northwest, and Southwest China, with a significant potential expansion of suitable habitats anticipated by the 2070s, particularly under the high emission scenario. The study identified precipitation and temperature as the primary environmental drivers impacting the distribution of F. suspensa. Furthermore, a northward shift in the centroid of suitable habitats under future climate scenarios suggested a potential migration response to global warming. This work provides crucial insights into the future conservation and cultivation strategies for F. suspensa amidst changing climatic conditions.

PMID:38887460 | PMC:PMC11180877 | DOI:10.3389/fpls.2024.1394799

Front Immunol. 2024 Jun 3;15:1375485. doi: 10.3389/fimmu.2024.1375485. eCollection 2024.

ABSTRACT

BACKGROUND: The impact of chronic hepatic infection on antigen non-specific immune cells in circulation remains poorly understood. We reported lasting global hyperfunction of peripheral CD8 T cells in HCV-infected individuals with cirrhosis. Whether gene expression patterns in bulk CD8 T cells are associated with the severity of liver fibrosis in HCV infection is not known.

METHODS: RNA sequencing of blood CD8 T cells from treatment naïve, HCV-infected individuals with minimal (Metavir F0-1 ≤ 7.0 kPa) or advanced fibrosis or cirrhosis (F4 ≥ 12.5 kPa), before and after direct-acting antiviral therapy, was performed. CD8 T cell function was assessed by flow cytometry.

RESULTS: In CD8 T cells from pre-DAA patients with advanced compared to minimal fibrosis, Gene Ontology analysis and Gene Set Enrichment Analysis identified differential gene expression related to cellular function and metabolism, including upregulated Hedgehog (Hh) signaling, IFN-α, -γ, TGF-β response genes, apoptosis, apical surface pathways, phospholipase signaling, phosphatidyl-choline/inositol activity, and second-messenger-mediated signaling. In contrast, genes in pathways associated with nuclear processes, RNA transport, cytoskeletal dynamics, cMyc/E2F regulation, oxidative phosphorylation, and mTOR signaling, were reduced. Hh signaling pathway was the top featured gene set upregulated in cirrhotics, wherein hallmark genes GLI1 and PTCH1 ranked highly. Inhibition of Smo-dependent Hh signaling ablated the expression of IFN-γ and perforin in stimulated CD8 T cells from chronic HCV-infected patients with advanced compared to minimal fibrosis. CD8 T cell gene expression profiles post-DAA remained clustered with pre-DAA profiles and disparately between advanced and minimal fibrosis, suggesting a persistent perturbation of gene expression long after viral clearance.

CONCLUSIONS: This analysis of bulk CD8 T cell gene expression in chronic HCV infection suggests considerable reprogramming of the CD8 T cell pool in the cirrhotic state. Increased Hh signaling in cirrhosis may contribute to generalized CD8 T cell hyperfunction observed in chronic HCV infection. Understanding the lasting nature of immune cell dysfunction may help mitigate remaining clinical challenges after HCV clearance and more generally, improve long term outcomes for individuals with severe liver disease.

PMID:38887299 | PMC:PMC11180750 | DOI:10.3389/fimmu.2024.1375485