Disulfide bridge-targeted metabolome mining unravels an antiparkinsonian peptide

Peptides are a particular molecule class with inherent attributes of some small-molecule drugs and macromolecular biologics, thereby inspiring continuous searches for peptides with therapeutic and/or agrochemical potentials. However, the success rate is decreasing, presumably because many interesting but less-abundant peptides are so scarce or labile that they are likely 'overlooked' during the characterization effort. Here, we present the biochemical characterization and druggability improvement of an unprecedented minor fungal RiPP (ribosomally synthesized and post-translationally modified peptide), named acalitide, by taking the relevant advantages of metabolomics approach and disulfide-bridged substructure which is more frequently imprinted in the marketed peptide drug molecules. Acalitide is biosynthetically unique in the macrotricyclization via two disulfide bridges and a protease (AcaB)-catalyzed lactamization of AcaA, an unprecedented precursor peptide. Such a biosynthetic logic was successfully re-edited for its sample supply renewal to facilitate the identification of the in vitro and in vivo antiparkinsonian efficacy of acalitide which was further confirmed safe and rendered brain-targetable by the liposome encapsulation strategy. Taken together, the work updates the mining strategy and biosynthetic complexity of RiPPs to unravel an antiparkinsonian drug candidate valuable for combating Parkinson's disease that is globally prevailing in an alarming manner.

Nanopore sequencing of full rRNA operon improves resolution in mycobiome analysis and reveals high diversity in both human gut and environments

High-throughput sequencing has substantially improved our understanding of fungal diversity. However, the short read (<500 bp) length of current second-generation sequencing approaches provides limited taxonomic and phylogenetic resolution for species discrimination. Longer sequences containing more information are highly desired to provide greater taxonomic resolution. Here, we amplified full-length rRNA operons (~5.5 kb) and established a corresponding fungal rRNA operon database for ONT sequences (FRODO), which contains ONT sequences representing eight phyla, 41 classes, 109 orders, 256 families, 524 genera and 1116 species. We also benchmarked the optimal method for sequence classification and determined that the RDP classifier based on our FRODO database was capable of improving the classification of ONT reads, with an average of 98%-99% reads correctly classified at the genus or species level. We investigated the applicability of our approach in three representative mycobiomes, namely, the soil, marine and human gut mycobiomes, and found that the gut contains the largest number of unknown species (over 90%), followed by the marine (42%) and soil (33.8%) mycobiomes. We also observed a distinct difference in the composition of the marine and soil mycobiomes, with the highest richness and diversity detected in soils. Overall, our study provides a systematic approach for mycobiome studies and revealed that the previous methods might have underestimated the diversity of mycobiome species. Future application of this method will lead to a better understanding of the taxonomic and functional diversity of fungi in environmental and health-related mycobiomes.

Bacillus velezensis BV01 Has Broad-Spectrum Biocontrol Potential and the Ability to Promote Plant Growth

To evaluate the potential of a bacterial strain as a fungal disease control agent and plant growth promoter, its inhibitory effects on phytopathogens such as Bipolaris sorokiniana, Botrytis cinerea, Colletotrichum capsici, Fusarium graminearum, F. oxysporum, Neocosmospora rubicola, Rhizoctonia solani, and Verticillium dahliae were investigated. The results showed that the inhibitory rates in dual-culture and sterile filtrate assays against these eight phytopathogens ranged from 57% to 83% and from 36% to 92%. The strain was identified as Bacillus velezensis based on morphological and physiological characterization as well as phylogenetic analyses of 16S rRNA and the gyrase subunit A protein (gyrA) regions. The results demonstrated that B. velezensis was able to produce fungal cell-wall-degrading enzymes, namely, protease, cellulase, and β-1,3-glucanase, and the growth-promotion substances indole-3-acetic acid (IAA) and siderophore. Furthermore, B. velezensis BV01 had significant control effects on wheat root rot and pepper Fusarium wilt in a greenhouse. Potted growth-promotion experiments displayed that BV01 significantly increased the height, stem diameter, and aboveground fresh and dry weights of wheat and pepper. The results imply that B. velezensis BV01, a broad-spectrum biocontrol bacterium, is worth further investigation regarding its practical applications in agriculture.

Channel Prediction-Based Security Authentication for Artificial Intelligence of Things

The emerging physical-layer unclonable attribute-aided authentication (PLUA) schemes are capable of outperforming traditional isolated approaches, with the advantage of having reliable fingerprints. However, conventional PLUA methods face new challenges in artificial intelligence of things (AIoT) applications owing to their limited flexibility. These challenges arise from the distributed nature of AIoT devices and the involved information, as well as the requirement for short end-to-end latency. To address these challenges, we propose a security authentication scheme that utilizes intelligent prediction mechanisms to detect spoofing attack. Our approach is based on a dynamic authentication method using long short term memory (LSTM), where the edge computing node observes and predicts the time-varying channel information of access devices to detect clone nodes. Additionally, we introduce a Savitzky-Golay filter-assisted high order cumulant feature extraction model (SGF-HOCM) for preprocessing channel information. By utilizing future channel attributes instead of relying solely on previous channel information, our proposed approach enables authentication decisions. We have conducted extensive experiments in actual industrial environments to validate our prediction-based security strategy, which has achieved an accuracy of 97%.

Non-linear relationship between dietary vitamin E intake and cognitive performance in older adults

OBJECTIVES

This study aimed to explore the relationship between dietary vitamin E (VE) intake and cognitive function in older adults.

STUDY DESIGN

This was a cross-sectional study.

METHODS

We applied data from the National Health and Nutrition Examination Survey obtained during 2011-2014 that met our requirements. The cognitive ability assessments included the Consortium to Establish a Registry for Alzheimer's Disease Word Learning (CERAD-WL) and Delayed Recall (CERAD-DR) tests, the animal fluency test, the Digit Symbol Substitution Test, and a composite z-score calculated by summing z-scores of individual tests. We used binary logistic regression analysis to explore the relationship between VE intake and cognitive performance. The results are reported using odds ratios and 95% confidence intervals. Our study also included sex-stratified analyses and sensitivity analysis. A restricted cubic splines model was used to evaluate the dose-response relationship between dietary VE intake and cognitive function.

RESULTS

This study found that a higher intake of dietary VE was associated with a lower risk of cognitive impairment in patients. Sensitivity analysis shows stable results. The results of the gender stratification analysis showed that dietary VE intake was negatively related to the risk of cognitive disorder among females. An irregular L-shaped dose-response relationship was observed between dietary VE intake and cognitive impairment risk.

CONCLUSIONS

Dietary VE intake was negatively related to the risk of cognitive disorder in older adults, with a higher VE intake lowering the risk.

Spirocitrinols A and B, citrinin derivatives with a spiro[chromane-2,3'-isochromane] skeleton from Penicillium citrinum

Spirocitrinols A (1) and B (2), two new citrinin-derived metabolites possessing a spiro[chromane-2,3'-isochromane] skeleton, were isolated from cultures of Penicillium citrinum. Their structures were elucidated primarily by NMR experiments. The absolute configurations of 1 and 2 were assigned by electronic circular dichroism calculations. Compound 2 is the first naturally occurring trimeric citrinin derivative with a spiro[chromane-2,3'-isochromane] core. Compound 1 showed modest cytotoxicity against A549 human tumor cells.

Differential uptake of nitrogen forms by two herbs in the Gurbantunggut desert, Central Asia

Understanding how plants adjust their requirements for different N forms can help elucidate plant coexistence strategies in N-limited desert ecosystems. To understand the mechanisms involved, we investigated whether two desert herbs can directly absorb dissolved organic nitrogen (N) and tested whether the patterns changed over different growth stages. Two dominant herbaceous species, Astragalus arpilobus and Arnebia decumbens, from the southern edge of the Gurbantunggut desert, China, were selected. Short-term (24 h) ¹⁵ N-labelled tracer (¹⁵ N-NO₃ , ¹⁵ N-NH₄ , 2-¹³ C-¹⁵ N-Glycine) treatments were conducted at two soil depths (0-5 cm and 5-15 cm) in the season of rapid growth (June) and in the peak biomass season (July). Enrichment in ¹³ C and ¹⁵ N was assessed in the two species receiving glycine. The ratio ¹³ C:¹⁵ N was 0.21-1.39 at the 24-h harvest, suggesting that approximately 10.5-69.5% of glycine had been absorbed. The amount of absorbed ¹⁵ N was significantly affected by species, month, soil depth and N form. The two species absorbed most ¹⁵ N from the 0-5 cm soil layer, and the absorption rate in July was higher than that in June. The absorption of ¹⁵ N-NO₃ and ¹⁵ N-NH₄ was significantly higher than that of 2-¹³ C-¹⁵ N-Glycine. The results indicate that these herbs could use amino acids in the N-deficient desert ecosystem. The two co-existing species used different forms of inorganic N for their requirements and maintained a specific preference throughout various growth stages.

Seasonal nitrogen uptake strategies in a temperate desert ecosystem depends on N form and plant species

Symbiotic plants might be able to regulate a limited nitrogen (N) pool, thus avoiding and reducing competition for resources, through the uptake of different chemical N forms. Our aim was to see whether coexisting herbs showed preference for different forms of N in a temperate desert. We conducted a situ experiment using the ¹⁵ N labeling method in the Gurbantunggut Desert of Northwestern China dominated by Erodium oxyrrhynchum, Hyalea pulchella, Nonea caspica and Lactuca undulata during their growing period (April and May). Four desert herb species preferentially relied on ¹⁵ N-NO₃ for their N nutrition. Multi-factor analysis of variance (ANOVA) analysis results showed that species, N forms, months, and soil depths strongly affected N uptake rate. The uptake rate by herbs was higher in May than in April, and higher at 0-5 cm than at 5-15 cm soil layers. Erodium oxyrrhynchum, N. caspica and L. undulata showed different preference on N form over months. Erodium oxyrrhynchum and L. undulata changed their uptake preference from more ¹⁵ N-Glycine in April to more ¹⁵ N-NH4 in May. Although the N uptake rate of four desert herbs varied across different soil depths and months, all species absorbed more inorganic N compared with organic N. The higher preference for ¹⁵ N-NO₃ and ¹⁵ N-NH4 over ¹⁵ N-Gly possibly reflects adaptation to different N forms in temperate desert.

Comparing the efficacy of targeted next-generation sequencing in the identification of somatic mutations in circulating tumor DNA from different stages of lung cancer

This study aims to assess the potential clinical application of targeted next generation sequencing (NGS)-based deep sequencing for the detection of clinically relevant mutations in circulating tumor DNA (ctDNA) obtained from non-small cell lung cancer (NSCLC) patients. Targeted deep sequencing was performed to identify High Confidence Somatic Variants (HCSVs) in matched tumor tissue DNA (tDNA) and ctDNA in 50 NSCLC patients. Our results demonstrated that NSCLC patients with Stage IV (61.5%) exhibited a higher concordance rate at the mutation level between plasma ctDNA and tDNA samples than those with Stage I-III (14.5%). Moreover, it is noteworthy that the allele frequency of these detected HCSVs in ctDNA increased with the advance in tumor stage. Besides, using tDNA as a reference, the sensitivity of plasma ctDNA analyzed by deep NGS for actionable EGFR was much higher in patients with Stage IV (66.6%) than those with Stage I-III (7.7%). In conclusion, it appears that ctDNA NGS-based deep sequencing is a feasible approach to identify mutations in patients with Stage IV NSCLC. However, additional methods with higher sensitivity and specificity are needed to improve the successful application of this platform in the earlier stages of NSCLC.

Pseudonectrins A–D, heptaketides from an endophytic fungus Nectria pseudotrichia

The new heptaketides, pseudonectrins A–D (1–4), were isolated from a plant endophyte Nectria pseudotrichia. Compounds 1–3 showed moderate cytotoxicity towards human tumor cells.