Plant Methods. 2024 May 3;20(1):60. doi: 10.1186/s13007-024-01193-4.

ABSTRACT

BACKGROUND: Despite major efforts over the last decades, the rising demands of the growing global population makes it of paramount importance to increase crop yields and reduce losses caused by plant pathogens. One way to tackle this is to screen novel resistant genotypes and immunity-inducing agents, which must be conducted in a high-throughput manner.

RESULTS: Colour-analyzer is a free web-based tool that can be used to rapidly measure the formation of lesions on leaves. Pixel colour values are often used to distinguish infected from healthy tissues. Some programs employ colour models, such as RGB, HSV or L*a*b*. Colour-analyzer uses two colour models, utilizing both HSV (Hue, Saturation, Value) and L*a*b* values. We found that the a* b* values of the L*a*b* colour model provided the clearest distinction between infected and healthy tissue, while the H and S channels were best to distinguish the leaf area from the background.

CONCLUSION: By combining the a* and b* channels to determine the lesion area, while using the H and S channels to determine the leaf area, Colour-analyzer provides highly accurate information on the size of the lesion as well as the percentage of infected tissue in a high throughput manner and can accelerate the plant immunity research field.

PMID:38698422 | DOI:10.1186/s13007-024-01193-4

J Nanobiotechnology. 2024 May 3;22(1):222. doi: 10.1186/s12951-024-02456-x.

ABSTRACT

BACKGROUND: Aging is a very complex physiological phenomenon, and sEVs are involved in the regulation of this mechanism. Serum samples from healthy individuals under 30 and over 60 years of age were collected to analyze differences in sEVs proteomics.

RESULTS: Based on PBA analysis, we found that sEVs from the serum of elderly individuals highly express TACSTD2 and identified a subpopulation marked by TACSTD2. Using ELISA, we verified the upregulation of TACSTD2 in serum from elderly human and aged mouse. In addition, we discovered that TACSTD2 was significantly increased in samples from tumor patients and had better diagnostic value than CEA. Specifically, 9 of the 13 tumor groups exhibited elevated TACSTD2, particularly for cervical cancer, colon cancer, esophageal carcinoma, liver cancer and thyroid carcinoma. Moreover, we found that serum sEVs from the elderly (especially those with high TACSTD2 levels) promoted tumor cell (SW480, HuCCT1 and HeLa) proliferation and migration.

CONCLUSION: TACSTD2 was upregulated in the serum of elderly individuals and patients with tumors, and could serve as a dual biomarker for aging and tumors.

PMID:38698420 | DOI:10.1186/s12951-024-02456-x

Nat Microbiol. 2024 May 2. doi: 10.1038/s41564-024-01680-3. Online ahead of print.

ABSTRACT

The detection of oral bacteria in faecal samples has been associated with inflammation and intestinal diseases. The increased relative abundance of oral bacteria in faeces has two competing explanations: either oral bacteria invade the gut ecosystem and expand (the 'expansion' hypothesis), or oral bacteria transit through the gut and their relative increase marks the depletion of other gut bacteria (the 'marker' hypothesis). Here we collected oral and faecal samples from mouse models of gut dysbiosis (antibiotic treatment and DSS-induced colitis) and used 16S ribosomal RNA sequencing to determine the abundance dynamics of oral bacteria. We found that the relative, but not absolute, abundance of oral bacteria increases, reflecting the 'marker' hypothesis. Faecal microbiome datasets from diverse patient cohorts, including healthy individuals and patients with allogeneic haematopoietic cell transplantation or inflammatory bowel disease, consistently support the 'marker' hypothesis and explain associations between oral bacterial abundance and patient outcomes consistent with depleted gut microbiota. By distinguishing between the two hypotheses, our study guides the interpretation of microbiome compositional data and could potentially identify cases where therapies are needed to rebuild the resident microbiome rather than protect against invading oral bacteria.

PMID:38698178 | DOI:10.1038/s41564-024-01680-3

Cell Death Discov. 2024 May 2;10(1):211. doi: 10.1038/s41420-024-01929-0.

ABSTRACT

Forkhead box protein M1 (FOXM1) is often overexpressed in human cancers and strongly associated with therapy resistance and less good patient survival. The chemotherapy options for patients with the most aggressive types of solid cancers remain very limited because of the acquired drug resistance, making the therapy less effective. NPM1 mutation through the inactivation of FOXM1 via FOXM1 relocalization to the cytoplasm confers more favorable treatment outcomes for AML patients, confirming FOXM1 as a crucial target to overcome drug resistance. Pharmacological inhibition of FOXM1 could be a promising approach to sensitize therapy-resistant cancers. Here, we explore a novel FOXM1 inhibitor STL001, a first-generation modification drug of our previously reported FOXM1 inhibitor STL427944. STL001 preserves the mode of action of the STL427944; however, STL001 is up to 50 times more efficient in reducing FOXM1 activity in a variety of solid cancers. The most conventional cancer therapies studied here induce FOXM1 overexpression in solid cancers. The therapy-induced FOXM1 overexpression may explain the failure or reduced efficacy of these drugs in cancer patients. Interestingly, STL001 increased the sensitivity of cancer cells to conventional cancer therapies by suppressing both the high-endogenous and drug-induced FOXM1. Notably, STL001 does not provide further sensitization to FOXM1-KD cancer cells, suggesting that the sensitization effect is conveyed specifically through FOXM1 suppression. RNA-seq and gene set enrichment studies revealed prominent suppression of FOXM1-dependent pathways and gene ontologies. Also, gene regulation by STL001 showed extensive overlap with FOXM1-KD, suggesting a high selectivity of STL001 toward the FOXM1 regulatory network. A completely new activity of FOXM1, mediated through steroid/cholesterol biosynthetic process and protein secretion in cancer cells was also detected. Collectively, STL001 offers intriguing translational opportunities as combination therapies targeting FOXM1 activity in a variety of human cancers driven by FOXM1.

PMID:38697979 | DOI:10.1038/s41420-024-01929-0

Life Sci. 2024 May 1:122679. doi: 10.1016/j.lfs.2024.122679. Online ahead of print.

NO ABSTRACT

PMID:38697877 | DOI:10.1016/j.lfs.2024.122679

Biomarkers. 2024 May 2:1-15. doi: 10.1080/1354750X.2024.2350714. Online ahead of print.

ABSTRACT

Background: Despite numerous reports on the alterations of microRNA-1246 (miR-1246) expression level in digestive system cancers, its role in gastrointestinal cancers (GICs) remains unclear. This meta-analysis aimed to assess the diagnostic potential of circulating miR-1246 in GICs.Methods: Meta-disc V.1.4 and Comprehensive Meta-Analysis V.3.7 software were used to calculate pooled sensitivity, specificity, likelihood ratios, diagnostic odds ratio, AUC, Q*index, and SROC. Subgroup analyses were conducted for cancer type, sample type, and geographical region. Publication bias was assessed using Begg's and Egger's tests.Results: A total of 14 articles involving 18 studies and 1,526 participants (972 cases and 554 controls) were included. The diagnostic accuracy of miRNA-1246 in GICs was as follows: pooled sensitivity: 0.81 (95% CI: 0.79 - 0.83), specificity: 0.74 (95% CI: 0.71 - 0.77), PLR: 3.315 (95% CI: 2.33 - 4.72), NLR: 0.221 (95% CI: 0.153 - 0.319), DOR: 16.87 (95% CI: 9.45 - 30.09), AUC: 0.891, and Q*-index: 0.807. No publication bias was found based on Begg's (p = 0.172) and Egger's (p = 0.113) tests.Conclusion: Circulating miR-1246 shows promise as a non-invasive biomarker for early detection of GICs.

PMID:38696280 | DOI:10.1080/1354750X.2024.2350714

Elife. 2024 May 2;13:e85749. doi: 10.7554/eLife.85749.

ABSTRACT

The reconstruction of complete microbial metabolic pathways using 'omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from the KEGG module database, MetaPathPredict employs deep learning models to predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as a Python module, and both options are designed to be run locally or on a compute cluster. Benchmarks show that MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes.

PMID:38696239 | DOI:10.7554/eLife.85749

mSystems. 2024 May 2:e0010924. doi: 10.1128/msystems.00109-24. Online ahead of print.

ABSTRACT

Polymyxin is used as a last resort antibiotics for infections caused by multi-drug resistant (MDR) Gram-negative bacteria and is often combined with other antibiotics to improve clinical effectiveness. However, the synergism of colistin and other antibiotics remains obscure. Here, we revealed a notable synergy between colistin and flavomycin, which was traditionally used as an animal growth promoter and has limited activity against Gram-negative bacteria, using checkerboard assay and time-kill curve analyses. The importance of membrane penetration induced by colistin was assessed by examining the intracellular accumulation of flavomycin and its antimicrobial impact on Escherichia coli (E. coli) strains with truncated lipopolysaccharides. Besides, a mutation in the flavomycin binding site was created to confirm its role in the observed synergy. This synergy is manifested as an augmented penetration of the E. coli outer membrane by colistin, leading to increased intracellular accumulation of flavomycin and enhanced cell killing thereafter. The observed synergy was dependent on the antimicrobial activity of flavomycin, as mutation of its binding site abolished the synergy. In vivo studies confirmed the efficacy of colistin combined with flavomycin against MDR E. coli infections. This study is the first to demonstrate the synergistic effect between colistin and flavomycin, shedding light on their respective roles in this synergism. Therefore, we propose flavomycin as an adjuvant to enhance the potency of colistin against MDR Gram-negative bacteria.

IMPORTANCE: Colistin is a critical antibiotic in combating multi-drug resistant Gram-negative bacteria, but the emergence of mobilized colistin resistance (mcr) undermines its effectiveness. Previous studies have found that colistin can synergy with various drugs; however, its exact mechanisms with hydrophobic drugs are still unrevealed. Generally, the membrane destruction of colistin is thought to be the essential trigger for its interactions with its partner drugs. Here, we use clustered regularly interspaced palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) for specifically mutating the binding site of one hydrophobic drug (flavomycin) and show that antimicrobial activity of flavomycin is critical for the synergy. Our results first give the evidence that the synergy is set off by colistin's membrane destruction and operated the final antimicrobial function by its partner drugs.

PMID:38695565 | DOI:10.1128/msystems.00109-24

J Chem Inf Model. 2024 May 2. doi: 10.1021/acs.jcim.4c00107. Online ahead of print.

ABSTRACT

Machine learning, and representation learning in particular, has the potential to facilitate drug discovery by screening a large chemical space in silico. A successful approach for representing molecules is to treat them as graphs and utilize graph neural networks. One of the key limitations of such methods is the necessity to represent compounds with different numbers of atoms, which requires aggregating the atom's information. Common aggregation operators, such as averaging, result in a loss of information at the atom level. In this work, we propose a novel aggregating approach where each atom is weighted nonlinearly using the Boltzmann distribution with a hyperparameter analogous to temperature. We show that using this weighted aggregation improves the ability of the gold standard message-passing neural network to predict antibiotic activity. Moreover, by changing the temperature hyperparameter, our approach can reveal the atoms that are important for activity prediction in a smooth and consistent way, thus providing a novel regulated attention mechanism for graph neural networks. We further validate our method by showing that it recapitulates the functional group in β-lactam antibiotics. The ability of our approach to rank the atoms' importance for a desired function can be used within any graph neural network to provide interpretability of the results and predictions at the node level.

PMID:38695490 | DOI:10.1021/acs.jcim.4c00107

Front Endocrinol (Lausanne). 2024 Apr 17;15:1331231. doi: 10.3389/fendo.2024.1331231. eCollection 2024.

ABSTRACT

A subset of neuroendocrine tumors (NETs) can cause an excessive secretion of hormones, neuropeptides, and biogenic amines into the bloodstream. These so-called functional NETs evoke a hormone-related disease and lead to several different syndromes, depending on the factors released. One of the most common functional syndromes, carcinoid syndrome, is characterized mainly by over-secretion of serotonin. However, what distinguishes functional from non-functional tumors on a molecular level remains unknown. Here, we demonstrate that the expression of sortilin, a widely expressed transmembrane receptor involved in intracellular protein sorting, is significantly increased in functional compared to non-functional NETs and thus can be used as a biomarker for functional NETs. Furthermore, using a cell line model of functional NETs, as well as organoids, we demonstrate that inhibition of sortilin reduces cellular serotonin concentrations and may therefore serve as a novel therapeutic target to treat patients with carcinoid syndrome.

PMID:38694940 | PMC:PMC11061435 | DOI:10.3389/fendo.2024.1331231

Biodivers Data J. 2024 Apr 23;12:e116921. doi: 10.3897/BDJ.12.e116921. eCollection 2024.

ABSTRACT

BACKGROUND: This paper describes two datasets: species occurrences, which were determined by environmental DNA (eDNA) metabarcoding and their associated DNA sequences, originating from a research project which was carried out along the Houdong River (), Jiaoxi Township, Yilan, Taiwan. The Houdong River begins at an elevation of 860 m and flows for approximately 9 km before it empties into the Pacific Ocean. Meandering through mountains, hills, plains and alluvial valleys, this short river system is representative of the fluvial systems in Taiwan. The primary objective of this study was to determine eukaryotic species occurrences in the riverine ecosystem through the use of the eDNA analysis. The second goal was, based on the current dataset, to establish a metabarcoding eDNA data template that will be useful and replicable for all users, particularly the Taiwan community. The species occurrence data are accessible at the Global Biodiversity Information Facility (GBIF) portal and its associated DNA sequences have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI, respectively. A total of 12 water samples from the study yielded an average of 1.5 million reads. The subsequent species identification from the collected samples resulted in the classification of 432 Operational Taxonomic Units (OTUs) out of a total of 2,734. Furthermore, a total of 1,356 occurrences with taxon matches in GBIF were documented (excluding 4,941 incertae sedis, accessed 05-12-2023). These data will be of substantial importance for future species and habitat monitoring within the short river, such as assessment of biodiversity patterns across different elevations, zonations and time periods and its correlation to water quality, land uses and anthropogenic activities. Further, these datasets will be of importance for regional ecological studies, in particular the freshwater ecosystem and its status in the current global change scenarios.

NEW INFORMATION: The datasets are the first species diversity description of the Houdong River system using either eDNA or traditional monitoring processes.

PMID:38694844 | PMC:PMC11061556 | DOI:10.3897/BDJ.12.e116921

J Pharm Anal. 2024 Apr;14(4):100914. doi: 10.1016/j.jpha.2023.12.004. Epub 2023 Dec 9.

ABSTRACT

Recent trends suggest that Chinese herbal medicine formulas (CHM formulas) are promising treatments for complex diseases. To characterize the precise syndromes, precise diseases and precise targets of the precise targets between complex diseases and CHM formulas, we developed an artificial intelligence-based quantitative predictive algorithm (DeepTCM). DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling, molecular and theoretical levels of traditional Chinese medicine (TCM). As an example, our model simulated the optimal CHM formulas for the treatment of coronary heart disease (CHD) with depression, and through model sensitivity analysis, we calculated the balanced scoring of the formulas. Furthermore, we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions. Finally, we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice. This novel multiscale model opened up a new avenue to combine "disease syndrome" and "macro micro" system modeling to facilitate translational research in CHM formulas.

PMID:38694562 | PMC:PMC11061219 | DOI:10.1016/j.jpha.2023.12.004

Front Immunol. 2024 Apr 17;15:1386719. doi: 10.3389/fimmu.2024.1386719. eCollection 2024.

ABSTRACT

INTRODUCTION: B-cell activation triggers the release of endoplasmic reticulum calcium stores through the store-operated calcium entry (SOCE) pathway resulting in calcium influx by calcium release-activated calcium (CRAC) channels on the plasma membrane. B-cell-specific murine knockouts of SOCE do not impact humoral immunity suggesting that alternative channels may be important.

METHODS: We identified a member of the calcium-permeable transient receptor potential (TRP) ion channel family, TRPV5, as a candidate channel expressed in B cells by a quantitative polymerase chain reaction (qPCR) screen. To further investigate the role of TRPV5 in B-cell responses, we generated a murine TRPV5 knockout (KO) by CRISPR-Cas9.

RESULTS: We found TRPV5 polarized to B-cell receptor (BCR) clusters upon stimulation in a PI3K-RhoA-dependent manner. TRPV5 KO mice have normal B-cell development and mature B-cell numbers. Surprisingly, calcium influx upon BCR stimulation in primary TRPV5 KO B cells was not impaired; however, differential expression of other calcium-regulating proteins, such as ORAI1, may contribute to a compensatory mechanism for calcium signaling in these cells. We demonstrate that TRPV5 KO B cells have impaired spreading and contraction in response to membrane-bound antigen. Consistent with this, TRPV5 KO B cells have reduced BCR signaling measured through phospho-tyrosine residues. Lastly, we also found that TRPV5 is important for early T-dependent antigen specific responses post-immunization.

DISCUSSION: Thus, our findings identify a role for TRPV5 in BCR signaling and B-cell activation.

PMID:38694510 | PMC:PMC11061418 | DOI:10.3389/fimmu.2024.1386719

Int J Biol Macromol. 2024 Apr 29:131973. doi: 10.1016/j.ijbiomac.2024.131973. Online ahead of print.

ABSTRACT

Medium-chain-length poly-3-hydroxyalkanoates (mcl-PHAs) with varied monomeric compositions were biosynthesized by producer bacteria fed with different fatty acids as carbon source. Octanoic-, lauric-, stearic-, and oleic acids were used to produce four types of mcl-PHAs viz. PHA-OC, PHA-LA, PHA-ST, and PHA-OL, respectively. The mcl-PHAs as film-casted preparations exhibit distinct traits e.g., PHA-OC and PHA-ST films are less flexible than PHA-LA while PHA-OL is a sticky, glue-like material; PHA-ST is opaque whereas PHA-OC, PHA-LA, and PHA-OL displayed transparent layers. The observation is attributed to polymer chain packing and side chain crystallization. A structure-property investigation of these biopolymers was carried out employing different spectroscopic and microscopic analyses in addition to thermal analyses. Comparative analyses of the results were applied in the interpretation and discussion of structure-property relationship.

PMID:38692536 | DOI:10.1016/j.ijbiomac.2024.131973

Neuron. 2024 Apr 25:S0896-6273(24)00247-2. doi: 10.1016/j.neuron.2024.04.009. Online ahead of print.

ABSTRACT

Genome-wide association studies (GWASs) have uncovered over 75 genomic loci associated with risk for late-onset Alzheimer's disease (LOAD), but identification of the underlying causal genes remains challenging. Studies of induced pluripotent stem cell (iPSC)-derived neurons from LOAD patients have demonstrated the existence of neuronal cell-intrinsic functional defects. Here, we searched for genetic contributions to neuronal dysfunction in LOAD using an integrative systems approach that incorporated multi-evidence-based gene mapping and network-analysis-based prioritization. A systematic perturbation screening of candidate risk genes in Caenorhabditis elegans (C. elegans) revealed that neuronal knockdown of the LOAD risk gene orthologs vha-10 (ATP6V1G2), cmd-1 (CALM3), amph-1 (BIN1), ephx-1 (NGEF), and pho-5 (ACP2) alters short-/intermediate-term memory function, the cognitive domain affected earliest during LOAD progression. These results highlight the impact of LOAD risk genes on evolutionarily conserved memory function, as mediated through neuronal endosomal dysfunction, and identify new targets for further mechanistic interrogation.

PMID:38692279 | DOI:10.1016/j.neuron.2024.04.009

Nature. 2024 May;629(8010):26-28. doi: 10.1038/d41586-024-01200-7.

NO ABSTRACT

PMID:38693406 | DOI:10.1038/d41586-024-01200-7

Nat Genet. 2024 May 1. doi: 10.1038/s41588-024-01737-3. Online ahead of print.

ABSTRACT

Zygnematophyceae are the algal sisters of land plants. Here we sequenced four genomes of filamentous Zygnematophyceae, including chromosome-scale assemblies for three strains of Zygnema circumcarinatum. We inferred traits in the ancestor of Zygnematophyceae and land plants that might have ushered in the conquest of land by plants: expanded genes for signaling cascades, environmental response, and multicellular growth. Zygnematophyceae and land plants share all the major enzymes for cell wall synthesis and remodifications, and gene gains shaped this toolkit. Co-expression network analyses uncover gene cohorts that unite environmental signaling with multicellular developmental programs. Our data shed light on a molecular chassis that balances environmental response and growth modulation across more than 600 million years of streptophyte evolution.

PMID:38693345 | DOI:10.1038/s41588-024-01737-3

Commun Biol. 2024 Apr 30;7(1):516. doi: 10.1038/s42003-024-06161-1.

ABSTRACT

The success of deep learning in various applications depends on task-specific architecture design choices, including the types, hyperparameters, and number of layers. In computational biology, there is no consensus on the optimal architecture design, and decisions are often made using insights from more well-established fields such as computer vision. These may not consider the domain-specific characteristics of genome sequences, potentially limiting performance. Here, we present GenomeNet-Architect, a neural architecture design framework that automatically optimizes deep learning models for genome sequence data. It optimizes the overall layout of the architecture, with a search space specifically designed for genomics. Additionally, it optimizes hyperparameters of individual layers and the model training procedure. On a viral classification task, GenomeNet-Architect reduced the read-level misclassification rate by 19%, with 67% faster inference and 83% fewer parameters, and achieved similar contig-level accuracy with ~100 times fewer parameters compared to the best-performing deep learning baselines.

PMID:38693292 | DOI:10.1038/s42003-024-06161-1

Ecotoxicol Environ Saf. 2024 Apr 30;278:116408. doi: 10.1016/j.ecoenv.2024.116408. Online ahead of print.

NO ABSTRACT

PMID:38691880 | DOI:10.1016/j.ecoenv.2024.116408

ACS Chem Neurosci. 2024 May 1. doi: 10.1021/acschemneuro.4c00138. Online ahead of print.

ABSTRACT

PDZ domains are modular domains that conventionally bind to C terminal or internal motifs of target proteins to control cellular functions through the regulation of protein complex assemblies. Almost all reported structures of PDZ-target protein complexes rely on fragments or peptides as target proteins. No intact target protein complexed with PDZ was structurally characterized. In this study, we used NMR spectroscopy and other biochemistry and biophysics tools to uncover insights into structural coupling between the PDZ domain of protein interacting with C-kinase 1 (PICK1) and α7 nicotinic acetylcholine receptors (α7 nAChR). Notably, the intracellular domains of both α7 nAChR and PICK1 PDZ exhibit a high degree of plasticity in their coupling. Specifically, the MA helix of α7 nAChR interacts with residues lining the canonical binding site of the PICK1 PDZ, while flexible loops also engage in protein-protein interactions. Both hydrophobic and electrostatic interactions mediate the coupling. Overall, the resulting structure of the α7 nAChR-PICK1 complex reveals an unconventional PDZ binding mode, significantly expanding the repertoire of functionally important PDZ interactions.

PMID:38691676 | DOI:10.1021/acschemneuro.4c00138