Viruses. 2024 Jul 23;16(8):1180. doi: 10.3390/v16081180.

ABSTRACT

The COVID-19 pandemic has altered respiratory infection patterns in pediatric populations. The emergence of the SARS-CoV-2 Omicron variant and relaxation of public health measures have increased the likelihood of coinfections. Previous studies show conflicting results regarding the impact of viral and bacterial coinfections with SARS-CoV-2 on severity of pediatric disease. This study investigated the prevalence and clinical impact of coinfections among children hospitalized with COVID-19 during the Omicron wave. A retrospective analysis was conducted on 574 hospitalized patients aged under 18 years in Russia, from January 2022 to March 2023. Samples from patients were tested for SARS-CoV-2 and other respiratory pathogens using qRT-PCR, bacterial culture tests and mass spectrometry, and ELISA. Approximately one-third of COVID-19 cases had coinfections, with viral and bacterial coinfections occurring at similar rates. Adenovirus and Staphylococcus aureus were the most common viral and bacterial coinfections, respectively. Viral coinfections were associated with higher fevers and increased bronchitis, while bacterial coinfections correlated with longer duration of illness and higher pneumonia rates. Non-SARS-CoV-2 respiratory viruses were linked to more severe lower respiratory tract complications than SARS-CoV-2 monoinfection. These findings suggest that during the Omicron wave, seasonal respiratory viruses may have posed a greater threat to children's health than SARS-CoV-2.

PMID:39205154 | DOI:10.3390/v16081180

Sensors (Basel). 2024 Aug 6;24(16):5081. doi: 10.3390/s24165081.

ABSTRACT

Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol (THC) is a main target for its therapeutic effects. As the global cannabis industry and research into cannabinoids expands, more efficient and cost-effective analysis methods for determining cannabinoid concentrations will be beneficial to increase efficiencies and maximize productivity. The utilization of machine learning tools to develop near-infrared (NIR) spectroscopy-based prediction models, which have been validated from accurate and sensitive chemical analysis, such as gas chromatography (GC) or liquid chromatography mass spectroscopy (LCMS), is essential. Previous research on cannabinoid prediction models targeted decarboxylated cannabinoids, such as THC, rather than the naturally occurring precursor, tetrahydrocannabinolic acid (THCA), and utilize finely ground cannabis inflorescence. The current study focuses on building prediction models for THCA concentrations in whole cannabis inflorescences prior to harvest, by employing non-destructive screening techniques so cultivators may rapidly characterize high-performing cultivars for chemotype in real time, thus facilitating targeted optimization of crossbreeding efforts. Using NIR spectroscopy and LCMS to create prediction models we can differentiate between high-THCA and even ratio classes with 100% prediction accuracy. We have also developed prediction models for THCA concentration with a R2 = 0.78 with a prediction error average of 13%. This study demonstrates the viability of a portable handheld NIR device to predict THCA concentrations on whole cannabis samples before harvest, allowing the evaluation of cannabinoid profiles to be made earlier, therefore increasing high-throughput and rapid capabilities.

PMID:39204779 | DOI:10.3390/s24165081

Plants (Basel). 2024 Aug 14;13(16):2261. doi: 10.3390/plants13162261.

ABSTRACT

Strawberry fruit is highly appreciated worldwide for its organoleptic and healthy properties. However, this plant is attacked by many pathogenic fungi, which significantly affect fruit production and quality at pre- and post-harvest stages, making chemical applications the most effective but undesirable strategy to control diseases that has been found so far. Alternatively, genetic manipulation, employing plant key genes involved in defense, such as members of the NPR-like gene family, has been successful in many crops to improve resistance. The identification and use of the endogenous counterpart genes in the plant of interest (as it is the case of strawberry) is desirable as it would increase the favorable outcome and requires prior knowledge of their defense-related function. Using RNAi technology in strawberry, transient silencing of Fragaria ananassa NPR3 members in fruit significantly reduced tissue damage after Colletotrichum acutatum infection, whereas the ectopic expression of either FaNPR3.1 or FaNPR3.2 did not have an apparent effect. Furthermore, the ectopic expression of FaNPR3.2 in Arabidopsis thaliana double-mutant npr3npr4 reverted the disease resistance phenotype to Pseudomonas syringe to wild-type levels. Therefore, the results revealed that members of the strawberry FaNPR3 clade negatively regulate the defense response to pathogens, as do their Arabidopsis AtNPR3/AtNPR4 orthologs. Also, evidence was found showing that FaNPR3 members act in strawberry (F. ananassa) as positive regulators of WRKY genes, FaWRKY19 and FaWRKY24; additionally, in Arabidopsis, FaNPR3.2 negatively regulates its orthologous genes AtNPR3/AtNPR4. We report for the first time the functional characterization of FaNPR3 members in F. ananassa, which provides a relevant molecular basis for the improvement of resistance in this species through new breeding technologies.

PMID:39204697 | DOI:10.3390/plants13162261

Plants (Basel). 2024 Aug 13;13(16):2247. doi: 10.3390/plants13162247.

ABSTRACT

Sugarcane holds global promise as a biofuel feedstock, necessitating a deep understanding of factors that influence biomass yield. This study unravels the intricate dynamics of plant hormones that govern growth and development in sugarcane. Transcriptome analysis of F2 introgression hybrids, derived from the cross of Saccharum officinarum "LA Purple" and wild Saccharum robustum "MOL5829", was conducted, utilizing the recently sequenced allele-specific genome of "LA Purple" as a reference. A total of 8059 differentially expressed genes were categorized into gene models (21.5%), alleles (68%), paralogs (10%), and tandemly duplicated genes (0.14%). KEGG analysis highlighted enrichment in auxin (IAA), jasmonic acid (JA), and abscisic acid (ABA) pathways, revealing regulatory roles of hormone repressor gene families (Aux/IAA, PP2C, and JAZ). Signaling pathways indicated that downregulation of AUX/IAA and PP2C and upregulation of JAZ repressor genes in high biomass segregants act as key players in influencing downstream growth regulatory genes. Endogenous hormone levels revealed higher concentrations of IAA and ABA in high biomass, which contrasted with lower levels of JA. Weighted co-expression network analysis demonstrated strong connectivity between hormone-related key genes and cell wall structural genes in high biomass genotypes. Expression analysis confirmed the upregulation of genes involved in the synthesis of structural carbohydrates and the downregulation of inflorescence and senescence-related genes in high biomass, which suggested an extended vegetative growth phase. The study underscores the importance of cumulative gene expression, including gene models, dominant alleles, paralogs, and tandemly duplicated genes and activators and repressors of disparate hormone (IAA, JA, and ABA) signaling pathways are the points of hormone crosstalk in contrasting biomass F2 segregants and could be applied for engineering high biomass acquiring varieties.

PMID:39204683 | DOI:10.3390/plants13162247

Nutrients. 2024 Aug 17;16(16):2745. doi: 10.3390/nu16162745.

ABSTRACT

Wheat gluten is responsible for the unique baking properties of wheat flour, but it also causes wheat-related disorders in predisposed individuals. Different commercially available gluten materials are commonly used for a variety of assays, but a detailed characterization of their composition is missing in many cases. This is why we aimed to provide an in-depth analysis of three commonly used gliadin and gluten materials from two different batches using gel electrophoretic and chromatographic techniques. The gliadin material did not show the typical qualitative and quantitative protein composition and does not appear to be representative of wheat gliadin. The two gluten materials had the expected protein composition, but both showed large batch-to-batch variability regarding total protein content. Since these variations result in different biochemical, immunological, and functional behaviors, it is important to analyze at least the total protein content of each material and each batch.

PMID:39203881 | DOI:10.3390/nu16162745

Nutrients. 2024 Aug 14;16(16):2700. doi: 10.3390/nu16162700.

ABSTRACT

Serving size may be the appropriate reference for calculating food nutritional value. We aimed to assess the nutritional values of Japanese foods based on serving sizes rather than per 100 g by adapting the Meiji Nutritional Profiling System (Meiji NPS). Given the variability in serving sizes across countries, we used Japanese serving sizes to calculate the Meiji NPS scores. We confirmed the convergent validity of the Meiji NPS scores per serving size with the Nutrient-Rich Food Index 9.3 using Spearman's correlation coefficients (r = 0.51, p < 0.001). Food groups recommended by official guidelines, such as pulses, nuts and seeds, fish and seafood, fruits, vegetables, and milk and milk products, scored relatively high. Furthermore, the nutrient density scores of food items with small serving sizes, such as mushrooms, algae, seasonings, and fats and oils, were moderated when calculated by per serving size, despite having considerably higher or lower scores per 100 g. These results indicate that calculating NPS per serving size allows for the assessment of the nutritional value of food items in accordance with actual consumption quantities. Therefore, the Meiji NPS calculated per serving size, alongside the per 100 g version, may be useful for dietary management depending on specific purposes.

PMID:39203836 | DOI:10.3390/nu16162700

Microorganisms. 2024 Aug 20;12(8):1720. doi: 10.3390/microorganisms12081720.

ABSTRACT

Prochlorococcus, a cyanobacteria genus of the smallest and most abundant oceanic phototrophs, encompasses ecotype strains adapted to high-light (HL) and low-light (LL) niches. To elucidate the adaptive evolution of this genus, we analyzed 40 Prochlorococcus marinus ORFeomes, including two cornerstone strains, MED4 and NATL1A. Employing deep learning with robust statistical methods, we detected new protein family distributions in the strains and identified key genes differentiating the HL and LL strains. The HL strains harbor genes (ABC-2 transporters) related to stress resistance, such as DNA repair and RNA processing, while the LL strains exhibit unique chlorophyll adaptations (ion transport proteins, HEAT repeats). Additionally, we report the finding of variable, depth-dependent endogenous viral elements in the 40 strains. To generate biological resources to experimentally study the HL and LL adaptations, we constructed the ORFeomes of two representative strains, MED4 and NATL1A synthetically, covering 99% of the annotated protein-coding sequences of the two species, totaling 3976 cloned, sequence-verified open reading frames (ORFs). These comparative genomic analyses, paired with MED4 and NATL1A ORFeomes, will facilitate future genotype-to-phenotype mappings and the systems biology exploration of Prochlorococcus ecology.

PMID:39203562 | DOI:10.3390/microorganisms12081720

Materials (Basel). 2024 Aug 17;17(16):4086. doi: 10.3390/ma17164086.

ABSTRACT

The purpose of this in vitro study was to develop calcium sulfate (CS)-based disks infused with an antimicrobial drug, which can be used as a post-surgical treatment modality for osteomyelitis. CS powder was embedded with 10% antibiotic, amoxicillin (AMX) or moxifloxacin (MFX), to form composite disks 11 mm in diameter that were tested for their degradation and antibiotic release profiles. For the disk degradation study portion, the single drug-loaded disks were placed in individual meshes, subsequently submerged in phosphate-buffered saline (PBS), and incubated at 37 °C. The disks were weighed once every seven days and analyzed via Fourier-transform infrared spectroscopy, X-ray diffraction, energy dispersive X-ray spectroscopy, and scanning electron microscopy. During the antibiotic release analysis, composite disks were placed in PBS solution, which was changed every 3 days, and analyzed for antibiotic activity and efficacy. The antibacterial effects of these sustained-release composites were tested by agar diffusion assay using Streptococcus mutans (S. mutans) UA 159 as an indicator strain. The degradation data showed significant increases in the degradation of all disks with the addition of antibiotics. Following PBS incubation, there were significant increases in the amount of phosphate and decreases in the amount of sulfate. The agar diffusion assay demonstrated that the released concentrations of the respective antibiotics from the disks were significantly higher than the minimum inhibitory concentration exhibited against S. mutans over a 2-3-week period. In conclusion, CS-antibiotic composite disks can potentially serve as a resorbable, osteoconductive, and antibacterial therapy in the treatment of bone defects and osteomyelitis.

PMID:39203264 | DOI:10.3390/ma17164086

Life (Basel). 2024 Aug 5;14(8):979. doi: 10.3390/life14080979.

ABSTRACT

Atherosclerosis, a leading cause of cardiovascular disease, necessitates advanced and innovative modeling techniques to better understand and predict plaque dynamics. The present work presents two distinct hypothetical models inspired by different research fields: the logistic map from chaos theory and Markov models from stochastic processes. The logistic map effectively models the nonlinear progression and sudden changes in plaque stability, reflecting the chaotic nature of atherosclerotic events. In contrast, Markov models, including traditional Markov chains, spatial Markov models, and Markov random fields, provide a probabilistic framework to assess plaque stability and transitions. Spatial Markov models, visualized through heatmaps, highlight the spatial distribution of transition probabilities, emphasizing local interactions and dependencies. Markov random fields incorporate complex spatial interactions, inspired by advances in physics and computational biology, but present challenges in parameter estimation and computational complexity. While these hypothetical models offer promising insights, they require rigorous validation with real-world data to confirm their accuracy and applicability. This study underscores the importance of interdisciplinary approaches in developing theoretical models for atherosclerotic plaques.

PMID:39202721 | DOI:10.3390/life14080979

J Pers Med. 2024 Aug 6;14(8):831. doi: 10.3390/jpm14080831.

ABSTRACT

Chronic Lymphocytic Leukemia (CLL) is the most common B-cell malignancy in the Western world, characterized by frequent relapses despite temporary remissions. Our study integrated publicly available proteomic, transcriptomic, and patient survival datasets to identify key differences between healthy and CLL samples. We exposed approximately 1000 proteins that differentiate healthy from cancerous cells, with 608 upregulated and 415 downregulated in CLL cases. Notable upregulated proteins include YEATS2 (an epigenetic regulator), PIGR (Polymeric immunoglobulin receptor), and SNRPA (a splicing factor), which may serve as prognostic biomarkers for this disease. Key pathways implicated in CLL progression involve RNA processing, stress resistance, and immune response deficits. Furthermore, we identified three existing drugs-Bosutinib, Vorinostat, and Panobinostat-for potential further investigation in drug repurposing in CLL. We also found limited correlation between transcriptomic and proteomic data, emphasizing the importance of proteomics in understanding gene expression regulation mechanisms. This generally known disparity highlights once again that mRNA levels do not accurately predict protein abundance due to many regulatory factors, such as protein degradation, post-transcriptional modifications, and differing rates of translation. These results demonstrate the value of integrating omics data to uncover deregulated proteins and pathways in cancer and suggest new therapeutic avenues for CLL.

PMID:39202022 | DOI:10.3390/jpm14080831

Int J Mol Sci. 2024 Aug 21;25(16):9082. doi: 10.3390/ijms25169082.

ABSTRACT

Kynurenic acid (KYNA) is an antioxidant degradation product of tryptophan that has been shown to have a variety of cytoprotective, neuroprotective and neuronal signalling properties. However, mammalian transporters and receptors display micromolar binding constants; these are consistent with its typically micromolar tissue concentrations but far above its serum/plasma concentration (normally tens of nanomolar), suggesting large gaps in our knowledge of its transport and mechanisms of action, in that the main influx transporters characterized to date are equilibrative, not concentrative. In addition, it is a substrate of a known anion efflux pump (ABCC4), whose in vivo activity is largely unknown. Exogeneous addition of L-tryptophan or L-kynurenine leads to the production of KYNA but also to that of many other co-metabolites (including some such as 3-hydroxy-L-kynurenine and quinolinic acid that may be toxic). With the exception of chestnut honey, KYNA exists at relatively low levels in natural foodstuffs. However, its bioavailability is reasonable, and as the terminal element of an irreversible reaction of most tryptophan degradation pathways, it might be added exogenously without disturbing upstream metabolism significantly. Many examples, which we review, show that it has valuable bioactivity. Given the above, we review its potential utility as a nutraceutical, finding it significantly worthy of further study and development.

PMID:39201768 | DOI:10.3390/ijms25169082

Rapid Commun Mass Spectrom. 2024 Nov 15;38(21):e9903. doi: 10.1002/rcm.9903.

ABSTRACT

RATIONALE: Shiduqing Capsules, a well-known Chinese patent medicine, are widely used clinically for the treatment of pruritus. However, to date, there is a lack of research on its pharmacological substances and mechanisms of action.

METHODS: In the current study, the chemical components of Shiduqing Capsules were identified using UHPLC-QE-Orbitrap-MS technology. Molecular network analysis was employed to identify structurally similar compounds to the known chemical components. The potential molecular targets of the active ingredients were predicted using the SwissTargetPrediction website. The identified targets were further analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis through the DAVID database. Molecular docking was used to validate the network pharmacology results.

RESULTS: Ultimately, A total of 51 chemical components of Shiduqing Capsules were identified. Molecular network analysis identified 21 flavonoids and 13 terpenoids. The core targets of these ingredients include TP53, AKT1, and STAT3. GO and KEGG enrichment analysis revealed 1,371 different biological functions and 177 signaling pathways. Molecular docking confirmed the high affinity between multiple core active ingredients of Shiduqing Capsules and pruritus targets.

CONCLUSION: In conclusion, the effective ingredients of Shiduqing Capsules exert a multifaceted therapeutic effect on pruritus through multiple targets and pathways.

PMID:39198930 | DOI:10.1002/rcm.9903

Nat Immunol. 2024 Aug 28. doi: 10.1038/s41590-024-01918-6. Online ahead of print.

ABSTRACT

The efficacy of antitumor immunity is associated with the metabolic state of cytotoxic T cells, which is sensitive to the tumor microenvironment. Whether ionic signals affect adaptive antitumor immune responses is unclear. In the present study, we show that there is an enrichment of sodium in solid tumors from patients with breast cancer. Sodium chloride (NaCl) enhances the activation state and effector functions of human CD8+ T cells, which is associated with enhanced metabolic fitness. These NaCl-induced effects translate into increased tumor cell killing in vitro and in vivo. Mechanistically, NaCl-induced changes in CD8+ T cells are linked to sodium-induced upregulation of Na+/K+-ATPase activity, followed by membrane hyperpolarization, which magnifies the electromotive force for T cell receptor (TCR)-induced calcium influx and downstream TCR signaling. We therefore propose that NaCl is a positive regulator of acute antitumor immunity that might be modulated for ex vivo conditioning of therapeutic T cells, such as CAR T cells.

PMID:39198632 | DOI:10.1038/s41590-024-01918-6

NPJ Syst Biol Appl. 2024 Aug 28;10(1):98. doi: 10.1038/s41540-024-00423-8.

ABSTRACT

In this review paper we summarize a recent progress on the problem of describing range of dynamics supported by a network. We show that there is natural connection between network models consisting of collections of multivalued monotone boolean functions and ordinary differential equations models. We show how to construct such collections and use them to answer questions about prevalence of cellular phenotypes that correspond to equilibria of network models.

PMID:39198512 | PMC:PMC11358538 | DOI:10.1038/s41540-024-00423-8

Nat Commun. 2024 Aug 28;15(1):7416. doi: 10.1038/s41467-024-51062-w.

ABSTRACT

The human gut pathogen Clostridioides difficile displays substantial inter-strain genetic variability and confronts a changeable nutrient landscape in the gut. We examined how human gut microbiota inter-species interactions influence the growth and toxin production of various C. difficile strains across different nutrient environments. Negative interactions influencing C. difficile growth are prevalent in an environment containing a single highly accessible resource and sparse in an environment containing C. difficile-preferred carbohydrates. C. difficile toxin production displays significant community-context dependent variation and does not trend with growth-mediated inter-species interactions. C. difficile strains exhibit differences in interactions with Clostridium scindens and the ability to compete for proline. Further, C. difficile shows substantial differences in transcriptional profiles in co-culture with C. scindens or Clostridium hiranonis. C. difficile exhibits massive alterations in metabolism and other cellular processes in co-culture with C. hiranonis, reflecting their similar metabolic niches. C. hiranonis uniquely inhibits the growth and toxin production of diverse C. difficile strains across different nutrient environments and robustly ameliorates disease severity in mice. In sum, understanding the impact of C. difficile strain variability and nutrient environments on inter-species interactions could help improve the effectiveness of anti-C. difficile strategies.

PMID:39198411 | PMC:PMC11358386 | DOI:10.1038/s41467-024-51062-w

Nat Commun. 2024 Aug 28;15(1):7451. doi: 10.1038/s41467-024-51759-y.

ABSTRACT

Resource partitioning is central to the incredible productivity of microbial communities, including gigatons in annual methane emissions through syntrophic interactions. Previous work revealed how a sulfate reducer (Desulfovibrio vulgaris, Dv) and a methanogen (Methanococcus maripaludis, Mm) underwent evolutionary diversification in a planktonic context, improving stability, cooperativity, and productivity within 300-1000 generations. Here, we show that mutations in just 15 Dv and 7 Mm genes within a minimal assemblage of this evolved community gave rise to co-existing ecotypes that were spatially enriched within a few days of culturing in a fluidized bed reactor. The spatially segregated communities partitioned resources in the simulated subsurface environment, with greater lactate utilization by attached Dv but partial utilization of resulting H2 by low affinity hydrogenases of Mm in the same phase. The unutilized H2 was scavenged by high affinity hydrogenases of planktonic Mm, producing copious amounts of methane. Our findings show how a few mutations can drive resource partitioning amongst niche-differentiated ecotypes, whose interplay synergistically improves productivity of the entire mutualistic community.

PMID:39198408 | PMC:PMC11358416 | DOI:10.1038/s41467-024-51759-y

Nat Commun. 2024 Aug 28;15(1):7359. doi: 10.1038/s41467-024-50498-4.

ABSTRACT

DNA hypomethylating agents (HMAs) are used for the treatment of myeloid malignancies, although their therapeutic effects have been unsatisfactory. Here we show that CRISPR-Cas9 screening reveals that knockout of topoisomerase 1-binding arginine/serine-rich protein (TOPORS), which encodes a ubiquitin/SUMO E3 ligase, augments the efficacy of HMAs on myeloid leukemic cells with little effect on normal hematopoiesis, suggesting that TOPORS is involved in resistance to HMAs. HMAs are incorporated into the DNA and trap DNA methyltransferase-1 (DNMT1) to form DNA-DNMT1 crosslinks, which undergo SUMOylation, followed by proteasomal degradation. Persistent crosslinking is cytotoxic. The TOPORS RING finger domain, which mediates ubiquitination, is responsible for HMA resistance. In TOPORS knockout cells, DNMT1 is stabilized by HMA treatment due to inefficient ubiquitination, resulting in the accumulation of unresolved SUMOylated DNMT1. This indicates that TOPORS ubiquitinates SUMOylated DNMT1, thereby promoting the resolution of DNA-DNMT1 crosslinks. Consistently, the ubiquitination inhibitor, TAK-243, and the SUMOylation inhibitor, TAK-981, show synergistic effects with HMAs through DNMT1 stabilization. Our study provides a novel HMA-based therapeutic strategy that interferes with the resolution of DNA-DNMT1 crosslinks.

PMID:39198387 | PMC:PMC11358161 | DOI:10.1038/s41467-024-50498-4

Crit Rev Biotechnol. 2024 Aug 28:1-19. doi: 10.1080/07388551.2024.2390089. Online ahead of print.

ABSTRACT

Microbes have been extensively utilized for their sustainable and scalable properties in synthesizing desired bio-products. However, insufficient knowledge about intracellular metabolism has impeded further microbial applications. The genome-scale metabolic models (GEMs) play a pivotal role in facilitating a global understanding of cellular metabolic mechanisms. These models enable rational modification by exploring metabolic pathways and predicting potential targets in microorganisms, enabling precise cell regulation without experimental costs. Nonetheless, simplified GEM only considers genome information and network stoichiometry while neglecting other important bio-information, such as enzyme functions, thermodynamic properties, and kinetic parameters. Consequently, uncertainties persist particularly when predicting microbial behaviors in complex and fluctuant systems. The advent of the omics era with its massive quantification of genes, proteins, and metabolites under various conditions has led to the flourishing of multi-constrained models and updated algorithms with improved predicting power and broadened dimension. Meanwhile, machine learning (ML) has demonstrated exceptional analytical and predictive capacities when applied to training sets of biological big data. Incorporating the discriminant strength of ML with GEM facilitates mechanistic modeling efficiency and improves predictive accuracy. This paper provides an overview of research innovations in the GEM, including multi-constrained modeling, analytical approaches, and the latest applications of ML, which may contribute comprehensive knowledge toward genetic refinement, strain development, and yield enhancement for a broad range of biomolecules.

PMID:39198033 | DOI:10.1080/07388551.2024.2390089

Curr Biol. 2024 Aug 22:S0960-9822(24)01069-8. doi: 10.1016/j.cub.2024.07.098. Online ahead of print.

ABSTRACT

Capsicum (pepper) is among the most economically important species worldwide, and its fruits accumulate specialized metabolites with essential roles in plant environmental interaction and human health benefits as well as in conferring their unique taste. However, the genetics underlying differences in metabolite presence/absence and/or accumulation remain largely unknown. In this study, we carried out a genome-wide association study as well as generating and characterizing a novel backcross inbred line mapping population to determine the genetic architecture of the pepper metabolome. This genetic analysis provided over 1,000 metabolic quantitative trait loci (mQTL) for over 250 annotated metabolites. We identified 92 candidate genes involved in various mQTLs. Among the identified loci, we described and validated a gene cluster of eleven UDP-glycosyltransferases (UGTs) involved in monomeric capsianoside biosynthesis. We additionally constructed the gene-by-gene-based biosynthetic pathway of pepper capsianoside biosynthesis, including both core and decorative reactions. Given that one of these decorative pathways, namely the glycosylation of acyclic diterpenoid glycosides, contributes to plant resistance, these data provide new insights and breeding resources for pepper. They additionally provide a blueprint for the better understanding of the biosynthesis of species-specific natural compounds in general.

PMID:39197460 | DOI:10.1016/j.cub.2024.07.098

Cell Host Microbe. 2024 Aug 18:S1931-3128(24)00286-5. doi: 10.1016/j.chom.2024.07.027. Online ahead of print.

ABSTRACT

Aberrant preterm infant gut microbiota assembly predisposes to early-life disorders and persistent health problems. Here, we characterize gut microbiome dynamics over the first 3 months of life in 236 preterm infants hospitalized in three neonatal intensive care units using shotgun metagenomics of 2,512 stools and metatranscriptomics of 1,381 stools. Strain tracking, taxonomic and functional profiling, and comprehensive clinical metadata identify Enterobacteriaceae, enterococci, and staphylococci as primarily exploiting available niches to populate the gut microbiome. Clostridioides difficile lineages persist between individuals in single centers, and Staphylococcus epidermidis lineages persist within and, unexpectedly, between centers. Collectively, antibiotic and non-antibiotic medications influence gut microbiome composition to greater extents than maternal or baseline variables. Finally, we identify a persistent low-diversity gut microbiome in neonates who develop necrotizing enterocolitis after day of life 40. Overall, we comprehensively describe gut microbiome dynamics in response to medical interventions in preterm, hospitalized neonates.

PMID:39197454 | DOI:10.1016/j.chom.2024.07.027