Showing papers by "South Dakota State University published in 2019"

Review of Challenges and Research Opportunities for Voltage Control in Smart Grids

Abstract: In this paper, we review the emerging challenges and research opportunities for voltage control in smart grids. For transmission grids, the voltage control for accommodating wind and solar power, fault-induced delayed voltage recovery, and measurement-based Thevenin equivalent for voltage stability analysis are reviewed. For distribution grids, the impact of high penetration of distributed energy resources is analyzed, typical control strategies are reviewed, and the challenges for local inverter Volt–Var control is discussed. In addition, the motivation, state-of-the-art, and future directions of the coordination of transmission system operators (TSO) and distribution system operators (DSO) are also thoroughly discussed.

Taxonomy of the order Mononegavirales: update 2019.

Abstract: In February 2019, following the annual taxon ratification vote, the order Mononegavirales was amended by the addition of four new subfamilies and 12 new genera and the creation of 28 novel species. This article presents the updated taxonomy of the order Mononegavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV).

A Multistage Game in Smart Grid Security: A Reinforcement Learning Solution

Abstract: Existing smart grid security research investigates different attack techniques and cascading failures from the attackers’ viewpoints, while the defenders’ or the operators’ protection strategies are somehow neglected. Game theoretic methods are applied for the attacker–defender games in the smart grid security area. Yet, most of the existing works only use the one-shot game and do not consider the dynamic process of the electric power grid. In this paper, we propose a new solution for a multistage game (also called a dynamic game) between the attacker and the defender based on reinforcement learning to identify the optimal attack sequences given certain objectives (e.g., transmission line outages or generation loss). Different from a one-shot game, the attacker here learns a sequence of attack actions applying for the transmission lines and the defender protects a set of selected lines. After each time step, the cascading failure will be measured, and the line outage (and/or generation loss) will be used as the feedback for the attacker to generate the next action. The performance is evaluated on W&W 6-bus and IEEE 39-bus systems. A comparison between a multistage attack and a one-shot attack is conducted to show the significance of the multistage attack. Furthermore, different protection strategies are evaluated in simulation, which shows that the proposed reinforcement learning solution can identify optimal attack sequences under several attack objectives. It also indicates that attacker’s learned information helps the defender to enhance the security of the system.

Crop Residue Management Challenges: A Special Issue Overview

Abstract: The amount of crop residues that can be sustainability removed is highly variable and is a function of many factors including the soil, climatic, and plant characteristics. For example, leaving an insufficient amount of crop residue on the soil surface can be detrimental for soil quality, result in loss of soil organic matter (SOM), and increase soil erosion, whereas leaving excessive amounts can impair soil-seed contact, immobilize N, and/or keep soils cool and wet. This special issue evolved as an outcome of, “Crop Residues for Advanced Biofuels: Effects on Soil Carbon” workshop held in Sacramento, CA, in 2017. The goal of the special issue is to provide a forum for identifying knowledge gaps associated with crop residue management and to expand the discussion from a regional Midwestern U.S. to a global perspective. Several crop residue experiments as well as simulation modeling studies are included to examine effects of tillage, crop rotation, livestock grazing, and cover crops on greenhouse gas (GHG) emissions, crop yield, and soil or plant health. The special issue is divided into 4 sections that include (i) Estimating Crop Residue Removal and Modeling; (ii) Cultural Practice Impact on Soil Health; (iii) Residue Removal Impact on Soil and Plant Health; and (iv) Cultural Practice Impact on Carbon Storage and Greenhouse Gas Emissions.

Development of an Agrobacterium-delivered CRISPR/Cas9 system for wheat genome editing.

Abstract: CRISPR/Cas9 has been widely used for genome editing in many organisms, including important crops like wheat. Despite the tractability in designing CRISPR/Cas9, efficacy in the application of this powerful genome editing tool also depends on DNA delivery methods. In wheat, the biolistics based transformation is the most used method for delivery of the CRISPR/Cas9 complex. Due to the high frequency of gene silencing associated with co-transferred plasmid backbone and low edit rate in wheat, a large T0 transgenic plant population are required for recovery of desired mutations, which poses a bottleneck for many genome editing projects. Here, we report an Agrobacterium-delivered CRISPR/Cas9 system in wheat, which includes a wheat codon optimized Cas9 driven by a maize ubiquitin gene promoter and a guide RNA cassette driven by wheat U6 promoters in a single binary vector. Using this CRISPR/Cas9 system, we have developed 68 edit mutants for four grain-regulatory genes, TaCKX2-1, TaGLW7, TaGW2, and TaGW8, in T0 , T1 , and T2 generation plants at an average edit rate of 10% without detecting off-target mutations in the most Cas9-active plants. Homozygous mutations can be recovered from a large population in a single generation. Different from most plant species, deletions over 10 bp are the dominant mutation types in wheat. Plants homozygous of 1160-bp deletion in TaCKX2-D1 significantly increased grain number per spikelet. In conclusion, our Agrobacterium-delivered CRISPR/Cas9 system provides an alternative option for wheat genome editing, which requires a small number of transformation events because CRISPR/Cas9 remains active for novel mutations through generations.

Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

Abstract: Big data has potential to unlock novel groundbreaking opportunities in power grid that enhances a multitude of technical, social, and economic gains. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data. In particular, computational complexity, data security, and operational integration of big data into power system planning and operational frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. In this context, suitable big data analytics combined with visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into power system planning and operational frameworks. Detailed information for utilities looking to apply big data analytics and insights on how utilities can enhance revenue streams and bring disruptive innovation are discussed. General guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.

Protein-protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique.

Abstract: MOTIVATION The prediction of protein-protein interaction (PPI) sites is a key to mutation design, catalytic reaction and the reconstruction of PPI networks. It is a challenging task considering the significant abundant sequences and the imbalance issue in samples. RESULTS A new ensemble learning-based method, Ensemble Learning of synthetic minority oversampling technique (SMOTE) for Unbalancing samples and RF algorithm (EL-SMURF), was proposed for PPI sites prediction in this study. The sequence profile feature and the residue evolution rates were combined for feature extraction of neighboring residues using a sliding window, and the SMOTE was applied to oversample interface residues in the feature space for the imbalance problem. The Multi-dimensional Scaling feature selection method was implemented to reduce feature redundancy and subset selection. Finally, the Random Forest classifiers were applied to build the ensemble learning model, and the optimal feature vectors were inserted into EL-SMURF to predict PPI sites. The performance validation of EL-SMURF on two independent validation datasets showed 77.1% and 77.7% accuracy, which were 6.2-15.7% and 6.1-18.9% higher than the other existing tools, respectively. AVAILABILITY AND IMPLEMENTATION The source codes and data used in this study are publicly available at http://github.com/QUST-AIBBDRC/EL-SMURF/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Interpretation of differential gene expression results of RNA-seq data: review and integration

Abstract: Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many applications of RNA-seq data analysis. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE results analysis from a functional point of view for various visualizations. We also provide an R/Bioconductor package, Visualization of Differential Gene Expression Results using R, which generates information-rich visualizations for the interpretation of DGE results from three widely used tools, Cuffdiff, DESeq2 and edgeR. The implemented functions are also tested on five real-world data sets, consisting of one human, one Malus domestica and three Vitis riparia data sets.

The unique composition of Indian gut microbiome, gene catalogue, and associated fecal metabolome deciphered using multi-omics approaches

Abstract: BACKGROUND Metagenomic studies carried out in the past decade have led to an enhanced understanding of the gut microbiome in human health; however, the Indian gut microbiome has not been well explored. We analyzed the gut microbiome of 110 healthy individuals from two distinct locations (North-Central and Southern) in India using multi-omics approaches, including 16S rRNA gene amplicon sequencing, whole-genome shotgun metagenomic sequencing, and metabolomic profiling of fecal and serum samples. RESULTS The gene catalogue established in this study emphasizes the uniqueness of the Indian gut microbiome in comparison to other populations. The gut microbiome of the cohort from North-Central India, which was primarily consuming a plant-based diet, was found to be associated with Prevotella and also showed an enrichment of branched chain amino acid (BCAA) and lipopolysaccharide biosynthesis pathways. In contrast, the gut microbiome of the cohort from Southern India, which was consuming an omnivorous diet, showed associations with Bacteroides, Ruminococcus, and Faecalibacterium and had an enrichment of short chain fatty acid biosynthesis pathway and BCAA transporters. This corroborated well with the metabolomics results, which showed higher concentration of BCAAs in the serum metabolome of the North-Central cohort and an association with Prevotella. In contrast, the concentration of BCAAs was found to be higher in the fecal metabolome of the Southern-India cohort and showed a positive correlation with the higher abundance of BCAA transporters. CONCLUSIONS The study reveals the unique composition of the Indian gut microbiome, establishes the Indian gut microbial gene catalogue, and compares it with the gut microbiome of other populations. The functional associations revealed using metagenomic and metabolomic approaches provide novel insights on the gut-microbe-metabolic axis, which will be useful for future epidemiological and translational researches.

Satellite detection of cumulative and lagged effects of drought on autumn leaf senescence over the Northern Hemisphere

Abstract: Climate change has substantial influences on autumn leaf senescence, that is, the end of the growing season (EOS). Relative to the impacts of temperature and precipitation on EOS, the influence of drought is not well understood, especially considering that there are apparent cumulative and lagged effects of drought on plant growth. Here, we investigated the cumulative and lagged effects of drought (in terms of the Standardized Precipitation-Evapotranspiration Index, SPEI) on EOS derived from the normalized difference vegetation index (NDVI3g) data over the Northern Hemisphere extra-tropical ecosystems (>30°N) during 1982-2015. The cumulative effect was determined by the number of antecedent months at which SPEI showed the maximum correlation with EOS (i.e., Rmax-cml ) while the lag effect was determined by a month during which the maximum correlation between 1-month SPEI and EOS occurred (i.e., Rmax-lag ). We found cumulative effect of drought on EOS for 27.2% and lagged effect for 46.2% of the vegetated land area. For the dominant time scales where the Rmax-cml and Rmax-lag occurred, we observed 1-4 accumulated months for the cumulative effect and 2-6 lagged months for the lagged effect. At the biome level, drought had stronger impacts on EOS in grasslands, savannas, and shrubs than in forests, which may be related to the different root functional traits among vegetation types. Considering hydrological conditions, the mean values of both Rmax-cml and Rmax-lag decreased along the gradients of annual SPEI and its slope, suggesting stronger cumulative and lagged effects in drier regions as well as in areas with decreasing water availability. Furthermore, the average accumulated and lagged months tended to decline along the annual SPEI gradient but increase with increasing annual SPEI. Our results revealed that drought has strong cumulative and lagged effects on autumn phenology, and considering these effects could provide valuable information on the vegetation response to a changing climate.

Fine-Grained Analysis of Spontaneous Mutation Spectrum and Frequency in Arabidopsis thaliana.

Abstract: Mutations are the ultimate source of all genetic variation. However, few direct estimates of the contribution of mutation to molecular genetic variation are available. To address this issue, we first analyzed the rate and spectrum of mutations in the Arabidopsis thaliana reference accession after 25 generations of single-seed descent. We then compared the mutation profile in these mutation accumulation (MA) lines against genetic variation observed in the 1001 Genomes Project. The estimated haploid single nucleotide mutation (SNM) rate for A. thaliana is 6.95 × 10−9 (SE ± 2.68 × 10−10) per site per generation, with SNMs having higher frequency in transposable elements (TEs) and centromeric regions. The estimated indel mutation rate is 1.30 × 10−9 (±1.07 × 10−10) per site per generation, with deletions being more frequent and larger than insertions. Among the 1694 unique SNMs identified in the MA lines, the positions of 389 SNMs (23%) coincide with biallelic SNPs from the 1001 Genomes population, and in 289 (17%) cases the changes are identical. Of the 329 unique indels identified in the MA lines, 96 (29%) overlap with indels from the 1001 Genomes dataset, and 16 indels (5% of the total) are identical. These overlap frequencies are significantly higher than expected, suggesting that de novo mutations are not uniformly distributed and arise at polymorphic sites more frequently than assumed. These results suggest that high mutation rate potentially contributes to high polymorphism and low mutation rate to reduced polymorphism in natural populations providing insights of mutational inputs in generating natural genetic diversity.

Coronavirus Endoribonuclease Activity in Porcine Epidemic Diarrhea Virus Suppresses Type I and Type III Interferon Responses

Abstract: Identifying viral antagonists of innate immunity and determining if they contribute to pathogenesis are critical for developing effective strategies to control emerging viruses. Previously, we reported that an endoribonuclease (EndoU) encoded by murine coronavirus plays a pivotal role in evasion of host innate immune defenses in macrophages. Here, we asked if the EndoU activity of porcine epidemic diarrhea coronavirus (PEDV), which causes acute diarrhea in swine, plays a role in antagonizing the innate response in porcine epithelial cells and macrophages, the sites of viral replication. We constructed an infectious clone of PEDV-Colorado strain (icPEDV-wt) and an EndoU-mutant PEDV (icPEDV-EnUmt) by changing the codon for a catalytic histidine residue of EndoU to alanine (His226Ala). We found that both icPEDV-wt and icPEDV-EnUmt propagated efficiently in interferon (IFN)-deficient Vero cells. In contrast, the propagation of icPEDV-EnUmt was impaired in porcine epithelial cells (LLC-PK1), where we detected an early and robust transcriptional activation of type I and type III IFNs. Infection of piglets with the parental Colorado strain, icPEDV-wt, or icPEDV-EnUmt revealed that all viruses replicated in the gut and induced diarrhea; however, there was reduced viral shedding and mortality in the icPEDV-EnUmt-infected animals. These results demonstrate that EndoU activity is not required for PEDV replication in immortalized, IFN-deficient Vero cells, but is important for suppressing the IFN response in epithelial cells and macrophages, which facilitates replication, shedding, and pathogenesis in vivo We conclude that PEDV EndoU activity is a key virulence factor that suppresses both type I and type III IFN responses.IMPORTANCE Coronaviruses (CoVs) can emerge from an animal reservoir into a naive host species to cause pandemic respiratory or gastrointestinal diseases with significant mortality in humans or domestic animals. Porcine epidemic diarrhea virus (PEDV), an alphacoronavirus (alpha-CoV), infects gut epithelial cells and macrophages, inducing diarrhea and resulting in high mortality in piglets. How PEDV suppresses the innate immune response was unknown. We found that mutating a viral endoribonuclease, EndoU, results in a virus that activates both the type I interferon response and the type III interferon response in macrophages and epithelial cells. This activation of interferon resulted in limited viral replication in epithelial cell cultures and was associated with reduced virus shedding and mortality in piglets. This study reveals a role for EndoU activity as a virulence factor in PEDV infection and provides an approach for generating live-attenuated vaccine candidates for emerging coronaviruses.

Inhibition of bacterial ubiquitin ligases by SidJ–calmodulin catalysed glutamylation

Abstract: The family of bacterial SidE enzymes catalyses phosphoribosyl-linked serine ubiquitination and promotes infectivity of Legionella pneumophila, a pathogenic bacteria that causes Legionnaires’ disease1–3. SidE enzymes share the genetic locus with the Legionella effector SidJ that spatiotemporally opposes the toxicity of these enzymes in yeast and mammalian cells, through a mechanism that is currently unknown4–6. Deletion of SidJ leads to a substantial defect in the growth of Legionella in both its natural hosts (amoebae) and in mouse macrophages4,5. Here we demonstrate that SidJ is a glutamylase that modifies the catalytic glutamate in the mono-ADP ribosyl transferase domain of the SdeA, thus blocking the ubiquitin ligase activity of SdeA. The glutamylation activity of SidJ requires interaction with the eukaryotic-specific co-factor calmodulin, and can be regulated by intracellular changes in Ca2+ concentrations. The cryo-electron microscopy structure of SidJ in complex with human apo-calmodulin revealed the architecture of this heterodimeric glutamylase. We show that, in cells infected with L. pneumophila, SidJ mediates the glutamylation of SidE enzymes on the surface of vacuoles that contain Legionella. We used quantitative proteomics to uncover multiple host proteins as putative targets of SidJ-mediated glutamylation. Our study reveals the mechanism by which SidE ligases are inhibited by a SidJ–calmodulin glutamylase, and opens avenues for exploring an understudied protein modification (glutamylation) in eukaryotes. In cells infected with Legionella pneumophila, the pseudo kinase SidJ is activated upon forming a complex with human calmodulin and catalyses glutamylation of SidE ubiquitin ligases, which abolishes the activity of these enzymes.

Association of Flavonifractor plautii, a Flavonoid-Degrading Bacterium, with the Gut Microbiome of Colorectal Cancer Patients in India.

Abstract: Recently, dysbiosis in the human gut microbiome and shifts in the relative abundances of several bacterial species have been recognized as important factors in colorectal cancer (CRC). However, these studies have been carried out mainly in developed countries where CRC has a high incidence, and it is unclear whether the host-microbiome relationships deduced from these studies can be generalized to the global population. To test if the documented associations between the microbiome and CRC are conserved in a distinct context, we performed metagenomic and metabolomic association studies on fecal samples from 30 CRC patients and 30 healthy controls from two different locations in India, followed by a comparison of CRC data available from other populations. We confirmed the association of Bacteroides and other bacterial taxa with CRC that have been previously reported in other studies. However, the association of CRC with Flavonifractor plautii in Indian patients emerged as a novel finding. The plausible role of F. plautii appears to be linked with the degradation of beneficial anticarcinogenic flavonoids, which was also found to be significantly correlated with the enzymes and modules involved in flavonoid degradation within Indian CRC samples. Thus, we hypothesize that the degradation of beneficial flavonoids might be playing a role in cancer progression within this Indian cohort. We also identified 20 potential microbial taxonomic markers and 33 potential microbial gene markers that discriminate the Indian CRC from healthy microbiomes with high accuracy based on machine learning approaches.IMPORTANCE This study provides novel insights on the CRC-associated microbiome of a unique cohort in India, reveals the potential role of a new bacterium in CRC, and identifies cohort-specific biomarkers, which can potentially be used in noninvasive diagnosis of CRC. The study gains additional significance, as India is among the countries with a very low incidence of CRC, and the diet and lifestyle in India have been associated with a distinct gut microbiome in healthy Indians compared to other global populations. Thus, in this study, we hypothesize a unique relationship between CRC and the gut microbiome in an Indian population.

Ultrahigh-Areal-Capacitance Flexible Supercapacitor Electrodes Enabled by Conformal P3MT on Horizontally Aligned Carbon-Nanotube Arrays

Abstract: Nanocarbon electronic conductors combined with pseudocapacitive materials, such as conducting polymers, display outstanding electrochemical properties and mechanical flexibility. These characteristics enable the fabrication of flexible electrodes for energy-storage devices; that is, supercapacitors that are wearable or can be formed into shapes that are easily integrated into vehicle parts. To date, most nanocarbon materials such as nanofibers are randomly dispersed as a network in a flexible matrix. This morphology inhibits ion transport, particularly under the high current density necessary for devices requiring high power density. Novel flexible densified horizontally aligned carbon nanotube arrays (HACNTs) with controlled nanomorphology for improved ion transport are introduced and combined with conformally coated poly(3-methylthiophene) (P3MT) conducting polymer to impart pseudocapacitance. The resulting P3MT/HACNT nanocomposite electrodes exhibit high areal capacitance of 3.1 F cm-2 at 5 mA cm-2 , with areal capacitance remaining at 1.8 F cm-2 even at a current density of 200 mA cm-2 . The asymmetric supercapacitor cell also delivers more than 1-2 orders of magnitude improvement in both areal energy and power density over state-of-the-art cells. Furthermore, little change in cell performance is observed under high strain, demonstrating the mechanical and electrochemical stability of the electrodes.

LncFinder: an integrated platform for long non-coding RNA identification utilizing sequence intrinsic composition, structural information and physicochemical property.

Abstract: Discovering new long non-coding RNAs (lncRNAs) has been a fundamental step in lncRNA-related research. Nowadays, many machine learning-based tools have been developed for lncRNA identification. However, many methods predict lncRNAs using sequence-derived features alone, which tend to display unstable performances on different species. Moreover, the majority of tools cannot be re-trained or tailored by users and neither can the features be customized or integrated to meet researchers' requirements. In this study, features extracted from sequence-intrinsic composition, secondary structure and physicochemical property are comprehensively reviewed and evaluated. An integrated platform named LncFinder is also developed to enhance the performance and promote the research of lncRNA identification. LncFinder includes a novel lncRNA predictor using the heterologous features we designed. Experimental results show that our method outperforms several state-of-the-art tools on multiple species with more robust and satisfactory results. Researchers can additionally employ LncFinder to extract various classic features, build classifier with numerous machine learning algorithms and evaluate classifier performance effectively and efficiently. LncFinder can reveal the properties of lncRNA and mRNA from various perspectives and further inspire lncRNA-protein interaction prediction and lncRNA evolution analysis. It is anticipated that LncFinder can significantly facilitate lncRNA-related research, especially for the poorly explored species. LncFinder is released as R package (https://CRAN.R-project.org/package=LncFinder). A web server (http://bmbl.sdstate.edu/lncfinder/) is also developed to maximize its availability.

A review on strategies addressing interface incompatibilities in inorganic all-solid-state lithium batteries

Abstract: High flammability, susceptibility to unstable interfacial reactions and lithium dendrite growth make currently employed liquid electrolyte systems in lithium batteries prone to severe safety concerns. Replacing the liquid electrolytes by solid-state versions is believed to be the ultimate solution to address the safety issues. Many research efforts have been dedicated to find solid-state electrolytes with excellent ionic conductivity comparable to that of the liquid counterparts and tremendous success has been achieved, especially with ceramic sulfide-based and oxide-based solid-state electrolytes. However, another major constraint inhibiting the practical development of such solid-state batteries is the solid–solid interfaces. This review summarizes the notable approaches that have been implemented to address the interface incompatibilities of ceramic solid-state electrolytes with battery electrodes. The focus will be on interfaces of sulfide and oxide solid electrolytes with both cathodes and metallic lithium anodes.

Assessing Variation in US Soybean Seed Composition (Protein and Oil)

Abstract: Soybean [Glycine max (L.) Merr.] seed composition and yield are a function of genetics (G), environment (E), and management (M) practices, but contribution of each factor to seed composition and yield are not well understood. The goal of this synthesis-analysis was to identify the main effects of G, E, and M factors on seed composition (protein and oil concentration) and yield. The entire dataset (13,574 data points) consisted of 21 studies conducted across the United States (US) between 2002 and 2017 with varying treatments and all reporting seed yield and composition. Environment (E), defined as site-year, was the dominant factor accounting for more than 70% of the variation for both seed composition and yield. Of the crop management factors: (i) delayed planting date decreased oil concentration by 0.007 to 0.06% per delayed week (R 2∼0.70) and a 0.01 to 0.04 Mg ha-1 decline in seed yield per week, mainly in northern latitudes (40-45 N); (ii) crop rotation (corn-soybean) resulted in an overall positive impact for both seed composition and yield (1.60 Mg ha-1 positive yield difference relative to continuous soybean); and (iii) other management practices such as no-till, seed treatment, foliar nutrient application, and fungicide showed mixed results. Fertilizer N application in lower quantities (10-50 kg N ha-1) increased both oil and protein concentration, but seed yield was improved with rates above 100 kg N ha-1. At southern latitudes (30-35 N), trends of reduction in oil and increases in protein concentrations with later maturity groups (MG, from 3 to 7) was found. Continuing coordinated research is critical to advance our understanding of G × E × M interactions.

Grape Seed Proanthocyanidin Affects Lipid Metabolism via Changing Gut Microflora and Enhancing Propionate Production in Weaned Pigs.

Abstract: BACKGROUND It is not clear whether dietary grape seed proanthocyanidin (GSP) affects mammalian lipid metabolism via the gut microbiota. OBJECTIVE The aim of this study was to evaluate the contribution of the gut microbiota to the effect of dietary GSP. METHODS This study was divided into 3 separate experiments using Duroc × Landrace × Yorkshire pigs (50% male) weaned at day 28 and then fed the same basal diet (NC). In Experiment 1, 90 pigs were fed NC or NC with 250 mg GSP/kg (GSP) or 400 mg betaine/kg [positive control (PC)] for 28 d. In Experiment 2, 30 pigs were fed NC, GSP, or GSP with antibiotics (GSP + Abx) diets for 14 d. In Experiment 3, pigs were fed NC, NC plus 1 g sodium propionate/kg (SP), or NC plus 1 g sodium butyrate/kg (SB) diet for 14 d. Serum biochemical indexes, SCFA concentrations, and microbial composition were determined. RESULTS In Experiment 1, compared with the GSP group, visceral adipocyte area was higher in the NC (28.6%) and PC (18.2%) groups (P ≤ 0.05). Colonic propionate and butyrate concentrations were 30.2% and 3.6% higher in the GSP group than in the NC group, respectively (P ≤ 0.05). In Experiment 2, compared with the GSP group, the NC group had a 108% higher Firmicutes to Bacteroidetes ratio and had 50.4%, 61.2%, and 82.3% lower abundance of Akkermansia, Alistipes, and Bacteroides, respectively (P ≤ 0.05); antibiotics removed these effects of GSP. In Experiment 3, serum peptide YY was 19.5% higher in the SP group than in the NC group (P ≤ 0.05), and it did not differ between the SB and NC groups (P > 0.05). CONCLUSIONS GSP affected lipid metabolism in weaned pigs, which is associated with changed gut microbiota and enhanced microbial propionate production. These findings provide potential mechanisms for GSP intake to improve lipid metabolism.