Biology subjects

Xi, M.

Publications and source records attributed to Xi, M..

5 recordsLinked to original sources

bioRxiv2026

Stool Metabolomics Reveals Catecholamine and Tryptophan-NAD+ Pathway Alterations in Autism Spectrum Disorder

Gut-brain axis dysregulation and microbiome-linked metabolic disturbances have been implicated in autism spectrum disorder (ASD), yet gut-derived neuroactive metabolites remain incompletely characterized. We applied targeted liquid chromatography-tandem mass spectrometry in a cross-sectional case-control study to quantify 18 stool metabolites related to catecholamine synthesis, GABAergic signaling, and tryptophan (Trp) and NAD+ metabolism in 59 participants (32 ASD, 27 non-ASD controls). Group differences were evaluated using log2 fold change and covariate-adjusted linear models. Random forest classifiers with five-fold cross-validation assessed multivariate discriminative performance, and within-group Spearman correlations examined metabolic network organization. Norepinephrine exhibited the largest elevation in ASD, while dopamine and tetrahydrobiopterin showed nominal group effects consistent with altered BH4-dependent catecholamine metabolism. Among individual metabolites, tetrahydrobiopterin, GABA, and kynurenine were the most informative, and their combination achieved an area under the receiver operating characteristic curve of 0.737 (95% confidence interval, 0.603 to 0.871). Correlation analyses revealed conserved lithocholic acid-deoxycholic acid coupling in both groups. In controls, Trp correlated with kynurenine, whereas ASD showed expanded Trp associations with GABA, norepinephrine, anandamide, and nicotinic acid, consistent with reorganization of Trp-NAD+ precursor pathways. These findings identify coordinated, gut-linked metabolic differences in ASD and define a metabolite signature reflecting altered catecholaminergic and Trp-related network structure. ImportanceAutism spectrum disorder is currently diagnosed using behavioral assessments, and objective biological measures are limited. The gut microbiome produces many small molecules that can influence brain development and function, but the specific metabolites involved in ASD remain unclear. Using targeted analysis of stool samples, we identified changes in metabolites related to neurotransmitter synthesis and tryptophan metabolism and showed that their relationships form distinct metabolic networks in individuals with ASD. A small panel of metabolites provided moderate ability to distinguish ASD from controls. These results suggest that gut-derived metabolites capture biologically meaningful variation in ASD and may help guide future studies aimed at understanding gut-brain communication and developing noninvasive biomarkers.

microbiology↗

bioRxiv2026

Genetic analysis and mapping of adult plant stripe rust resistance loci in CIMMYT wheat 'Kijil under Mexican and Chinese field environments

Stripe rust, caused by Puccinia striiformis f. sp. tritici, can cause severe yield losses in wheat (Triticum aestivum L.) during epidemics. Breeding resistant wheat varieties remains the most cost-effective approach to manage this disease; and the identification of new resistance loci is essential for maintaining genetic diversity. The CIMMYT-derived wheat line Kijil was highly resistant to stripe rust in both Mexican and Chinese environments. A population of 153 F recombinant inbred lines (RILs) was derived from a cross between Kijil and the susceptible parent Apav#1. The population was phenotyped for stripe rust resistance across seven environments in two countries and genotyped using a genotyping-by-sequencing (GBS) platform. Inclusive composite interval mapping (ICIM) was uesd to construct a genetic map and identify significant resistance quantitative trait loci (QTLs) using 5,468 polymorphic markers. Mapping revealed the known resistance loci Yr29, Yr30 and QYr.hzau-3AS, along with two novel loci, QYr.hzau-2BS and QYr.hzau-5DL, across both Chinese and Mexican rust environments. Among these, QYr.hzau-2BS accounted for 11.75% to 19.19% of the phenotypic variance. A corresponding KASP marker, KASP_2BS, was developed to facilitate maker-assisted selection. Based on the mapping interval, four candidate genes underlying this locus were predicted. Further analysis revealed that Yr29 showed significant additive effects with other stripe rust resistance genes/loci, and the combination of Yr29, Yr30, and QYr.hzau-2BS reduced disease severity by up to 67.8%. Our findings suggest that Kijil and RILs carrying Yr29, Yr30, and QYr.hzau-2BS can serve as valuable donors for breeding wheat varieties with improved stripe rust resistance. Author summaryStripe rust is an important disease that seriously threatens the yield and quality of wheat. It is crucial to explore new resistant resources and cultivate durable resistant varieties in the current breeding programme. In this study, we analysed the genetic basis of resistance to stripe rust in the wheat line "Kijil", which has broad-spectrum resistance to stripe rust. Through genetic mapping, we identified five quantitative trait loci for stripe rust, including two new resistance loci. A closely linked KASP marker, KASP_2BS, was developed for the QYr.hzau-2BS, which can be used for rapid and accurate screening of resistant plants in early breeding populations. Meanwhile, within this QTL region, we screened four candidate genes based on expression analysis. In addition, it was found that polymerization of QYr.hzau-2BS with known resistance genes, Yr29 and Yr30, significantly enhanced resistance and reduced disease severity to low levels and near immunity. In conclusion, this study provides new genetic resources, practical molecular markers and effective gene polymerization strategies for breeding wheat for stripe rust resistance. Kijil and the lines containing resistance loci have important breeding utilization value.

plant biology↗

bioRxiv2024

A method for recognizing motor imagery EEG signals based on high-quality lead selection

In the application of motor imagery brain-computer interface system, high-density leads bring redundant noise, which leads to time-consuming system operation and poor performance. A channel selection strategy based on brain function network is proposed. This method introduces Synchronization likelihood was used as a connection index to construct a motor imagery brain functional network, and the centrality analysis of the constructed network was used to select the combination of strong motor-related leads. Experiments were carried out on the EEG datasets dataset IVa of the 3rd International Brain-Computer Interface Competition and dataset I of the 4th International Brain-Computer Interface Competition, and 27 high-quality channels were selected from the 118 channels of dataset IVa, as well as 16 high-quality channels were selected from the 59 channels of dataset I. Finally, the CSP algorithm and support vector machine are used to extract features and classify. The experimental results show that the proposed channel selection strategy can greatly reduce the number of channels while obtaining higher recognition accuracy, which verifies the practicability and effectiveness of the proposed method.

bioengineering↗

bioRxiv2023

Linking root-associated fungal and bacterial functions to root economics

Tree roots form symbioses with soil microbes to acquire nutrients, but the relationships between root nutrient acquisition strategies and microbial community composition remain poorly understood. Here, we measured root traits and root-associated fungal and bacterial guilds in 336 trees of 52 species from a subtropical forest. We found a fungal gradient from ectomycorrhizal to saprotrophic dominance, which corresponded with a shift from organic to mineral nutrient economics. This fungal gradient was aligned with the increase of root nitrogen concentration, suggesting a linkage from simple root trait to fungal-mediated carbon-nutrient cycling. We also found that the functional composition of fungal and bacterial communities was closely correlated with host root-zone pH, which often varied among coexisting trees. Root-zone pH was independent of the common root traits, underpinning a potential new gradient in the root trait space. Our findings integrate microbial functions into the root economics framework, thereby advancing the understanding of diversity of nutrient acquisition strategies across forest trees.

ecology↗

bioRxiv2022

Arbuscular mycorrhizal fungal composition across US citrus orchards, management strategies, and disease severity spectrum

Arbuscular mycorrhizal fungi (AMF) remain understudied in perennial cropping systems. Citrus is a globally grown fruit tree and under threat by the pandemic Huanglongbing (HLB) disease. Here, we assessed in what capacity geographical location, management strategies and disease affect AMF citrus root communities. Root samples were collected from 88 trees in ten orchards located in the two major citrus producing states in the US. Orchards were selected based on conventional or organic practices in California and based on HLB symptom severity in Florida. We used AMF-specific amplicon sequencing primers to capture community composition and diversity. Taxa names were assigned based on a phylogenetic analysis that comprised a backbone of AMF references sequences from Mycobank and virtual taxa from the MaarjAM database. AMF were detected in 78% of citrus root samples with taxa belonging to six known (Dominikia, Funneliformis, Glomus, Rhizophagus, Sclerocystis, Septoglomus) and unknown Glomeraceae genera. Geographical location affected AMF community composition but not richness, whereas management practice and disease influenced both richness and composition. Our approach indicated that perennial agroecosystems share a set of AMF generalist and specialist taxa. Some taxa could improve environmental fitness and be exploited for agricultural purposes.

microbiology↗