Exploiting protein language models for the precise classification of ion channels and ion transporters.

This study introduces TooT-PLM-ionCT, a comprehensive framework that consolidates three distinct systems, each meticulously tailored for one of the following tasks: distinguishing ion channels (ICs) from membrane proteins (MPs), segregating ion transporters (ITs) from MPs, and differentiating ICs from ITs. Drawing upon the strengths of six Protein Language Models (PLMs)-ProtBERT, ProtBERT-BFD, ESM-1b, ESM-2 (650M parameters), and ESM-2 (15B parameters), TooT-PLM-ionCT employs a combination of traditional classifiers and deep learning models for nuanced protein classification. Originally validated on an existing dataset by previous researchers, our systems demonstrated superior performance in identifying ITs from MPs and distinguishing ICs from ITs, with the IC-MP discrimination achieving state-of-the-art results. In light of recommendations for additional validation, we introduced a new dataset, significantly enhancing the robustness and generalization of our models across bioinformatics challenges. This new evaluation underscored the effectiveness of TooT-PLM-ionCT in adapting to novel data while maintaining high classification accuracy. Furthermore, this study explores critical factors affecting classification accuracy, such as dataset balancing, the impact of using frozen versus fine-tuned PLM representations, and the variance between half and full precision in floating-point computations. To facilitate broader application and accessibility, a web server (https://tootsuite.encs.concordia.ca/service/TooT-PLM-ionCT) has been developed, allowing users to evaluate unknown protein sequences through our specialized systems for IC-MP, IT-MP, and IC-IT classification tasks.

The Membrane Proteome of Spores and Vegetative Cells of the Food-Borne Pathogen Bacillus cereus.

Membrane proteins are fascinating since they play an important role in diverse cellular functions and constitute many drug targets. Membrane proteins are challenging to analyze. The spore, the most resistant form of known life, harbors a compressed inner membrane. This membrane acts not only as a barrier for undesired molecules but also as a scaffold for proteins involved in signal transduction and the transport of metabolites during spore germination and subsequent vegetative growth. In this study, we adapted a membrane enrichment method to study the membrane proteome of spores and cells of the food-borne pathogen Bacillus cereus using quantitative proteomics. Using bioinformatics filtering we identify and quantify 498 vegetative cell membrane proteins and 244 spore inner membrane proteins. Comparison of vegetative and spore membrane proteins showed there were 54 spore membrane-specific and 308 cell membrane-specific proteins. Functional characterization of these proteins showed that the cell membrane proteome has a far larger number of transporters, receptors and proteins related to cell division and motility. This was also reflected in the much higher expression level of many of these proteins in the cellular membrane for those proteins that were in common with the spore inner membrane. The spore inner membrane had specific expression of several germinant receptors and spore-specific proteins, but also seemed to show a preference towards the use of simple carbohydrates like glucose and fructose owing to only expressing transporters for these. These results show the differences in membrane proteome composition and show us the specific proteins necessary in the inner membrane of a dormant spore of this toxigenic spore-forming bacterium to survive adverse conditions.

iMPT-FDNPL: Identification of Membrane Protein Types with Functional Domains and a Natural Language Processing Approach.

Membrane protein is an important kind of proteins. It plays essential roles in several cellular processes. Based on the intramolecular arrangements and positions in a cell, membrane proteins can be divided into several types. It is reported that the types of a membrane protein are highly related to its functions. Determination of membrane protein types is a hot topic in recent years. A plenty of computational methods have been proposed so far. Some of them used functional domain information to encode proteins. However, this procedure was still crude. In this study, we designed a novel feature extraction scheme to obtain informative features of proteins from their functional domain information. Such scheme termed domains as words and proteins, represented by its domains, as sentences. The natural language processing approach, word2vector, was applied to access the features of domains, which were further refined to protein features. Based on these features, RAndom k-labELsets with random forest as the base classifier was employed to build the multilabel classifier, namely, iMPT-FDNPL. The tenfold cross-validation results indicated the good performance of such classifier. Furthermore, such classifier was superior to other classifiers based on features derived from functional domains via one-hot scheme or derived from other properties of proteins, suggesting the effectiveness of protein features generated by the proposed scheme.

First Survey of SNPs in TMEM154, TLR9, MYD88 and CCR5 Genes in Sheep Reared in Italy and Their Association with Resistance to SRLVs Infection.

Maedi-visna virus (MVV) and caprine arthritis encephalitis virus (CAEV), referred to as small ruminant lentiviruses (SRLVs), belong to the genus Lentivirus of the Retroviridae family. SRLVs infect both sheep and goats, causing significant economic losses and animal welfare damage. Recent findings suggest an association between serological status and allelic variants of different genes such as TMEM154, TLR9, MYD88 and CCR5. The aim of this work was to investigate the role of specific polymorphisms of these genes in SRLVs infection in some sheep flocks in Italy. In addition to those already known, novel variants in the TMEM154 (P7H, I74V, I105V) gene were detected in this study. The risk of infection was determined finding an association between the serological status and polymorphisms P7H, E35K, N70I, I74V, I105V of TMEM154, R447Q, A462S and G520R in TLR9 gene, H176H* and K190K* in MYD88 genes, while no statistical association was observed for the 4-bp deletion of the CCR5 gene. Since no vaccines or treatments have been developed, a genetically based approach could be an innovative strategy to prevent and to control SRLVs infection. Our findings are an important starting point in order to define the genetic resistance profile towards SRLVs infection.

Drosophila oocyte proteome composition covaries with female mating status.

Oocyte composition can directly influence offspring fitness, particularly in oviparous species such as most insects, where it is the primary form of parental investment. Oocyte production is also energetically costly, dependent on female condition and responsive to external cues. Here, we investigated whether mating influences mature oocyte composition in Drosophila melanogaster using a quantitative proteomic approach. Our analyses robustly identified 4,485 oocyte proteins and revealed that stage-14 oocytes from mated females differed significantly in protein composition relative to oocytes from unmated females. Proteins forming a highly interconnected network enriched for translational machinery and transmembrane proteins were increased in oocytes from mated females, including calcium binding and transport proteins. This mating-induced modulation of oocyte maturation was also significantly associated with proteome changes that are known to be triggered by egg activation. We propose that these compositional changes are likely to have fitness consequences and adaptive implications given the importance of oocyte protein composition, rather than active gene expression, to the maternal-to-zygotic transition and early embryogenesis.

Lipids and membrane-associated proteins in autophagy.

Autophagy is essential for the maintenance of cellular homeostasis and its dysfunction has been linked to various diseases. Autophagy is a membrane driven process and tightly regulated by membrane-associated proteins. Here, we summarized membrane lipid composition, and membrane-associated proteins relevant to autophagy from a spatiotemporal perspective. In particular, we focused on three important membrane remodeling processes in autophagy, lipid transfer for phagophore elongation, membrane scission for phagophore closure, and autophagosome-lysosome membrane fusion. We discussed the significance of the discoveries in this field and possible avenues to follow for future studies. Finally, we summarized the membrane-associated biochemical techniques and assays used to study membrane properties, with a discussion of their applications in autophagy.

IFITMs of African Green Monkey Can Inhibit Replication of SFTSV but Not MNV In Vitro.

Interferon-induced transmembrane proteins (IFITMs) are transmembrane proteins induced by interferon that can provide broad-spectrum antiviral activities. However, there are few reports on the antiviral activity of monkey-derived IFITMs. In this study, the IFITM1 and IFITM3 genes of African green monkey (AGM) were cloned and overexpressed in Vero cells, followed by infection with mouse norovirus (MNV) and severe fever with thrombocytopenia syndrome virus (SFTSV). The results showed that monkey IFITM1 and IFITM3 can be stably overexpressed in Vero cells. Both IFITM1 and IFITM3 from AGM could effectively restrict infection by SFTSV, and the viral inhibition rate of IFITM3 was more obvious compared with IFITM1. However, both monkey IFITM1 and IFITM3 had no significant effect on the replication of MNV. These results indicate that different IFITMs have different functions, which may be related to the structure of the host IFITMs and the types of pathogens.

Cascading classifier application for topology prediction of transmembrane beta-barrel proteins.

Membrane proteins are a major focus for new drug discovery. Transmembrane beta-barrel (TMB) proteins play key roles in the translocation machinery, pore formation, membrane anchoring and ion exchange. Given their key roles and the difficulty in membrane protein structure determination, the use of computational modeling is essential. This paper focuses on the topology prediction of TMB proteins. In the field of bioinformatics, many years of research has been spent on the topology prediction of transmembrane alpha-helices. The efforts to TMB proteins topology prediction have been overshadowed and the prediction accuracy could be improved with further research. Various methodologies have been developed in the past for the prediction of TMB protein topology, however, the use of cascading classifier has never been fully explored. This research presents a novel approach to TMB topology prediction with the use of a cascading classifier. The MATLAB computer simulation results show that the proposed methodology predicts TMB proteins topologies with high accuracy for randomly selected proteins. By using the cascading classifier approach, the best overall accuracy is 76.3% with a precision of 0.831 and recall or probability of detection of 0.799 for TMB topology prediction. The accuracy of 76.3% is achieved using a two-layers cascading classifier.

Classification of membrane protein using Tetra Peptide Pattern.

Membrane proteins play an important role in the life activities of organisms. The mechanism of cell structures and biological activities can be identified only by knowing the functional types of membrane proteins which accelerate the process. Therefore, it is greatly necessary to build up computational approaches for timely and accurate prediction of the functional types of membrane protein. The proposed method analyzes the structure of the membrane proteins using novel Tetra Peptide Pattern (TPP)-based feature extraction technique. A frequency occurrence matrix is created from which a feature vector is formed. This feature vector captures the pattern among amino acids in a membrane protein sequence. The feature vector is reduced in the dimension using General Kernel-based Supervised Principal Component Analysis (GKSPCA). Stacked Restricted Boltzmann Machines (RBM) in Deep Belief Network (DBN) is used for classification. The RBM is the building block of Deep Belief Network. The proposed method achieves good results on two datasets. The performance of the proposed method was analyzed using Accuracy, Specificity, Sensitivity and Mathew's correlation coefficient. The proposed method achieves good results when compared to other state-of-the-art techniques.

Genome-wide identification and characterization of multiple C2 domains and transmembrane region proteins in Gossypium hirsutum.

BACKGROUND: Multiple C2 domains and transmembrane region proteins (MCTPs) may act as transport mediators of other regulators. Although increased number of MCTPs in higher plants implies their diverse and specific functions in plant growth and development, only a few plant MCTPs have been studied and no study on the MCTPs in cotton has been reported. RESULTS: In this study, we identified 31 MCTPs in G. hirsutum, which were classified into five subfamilies according to the phylogenetic analysis. GhMCTPs from subfamily V exhibited isoelectric points (pIs) less than 7, whereas GhMCTPs from subfamily I, II, III and IV exhibited pIs more than 7.5, implying their distinct biological functions. In addition, GhMCTPs within subfamily III, IV and V exhibited more diverse physicochemical properties, domain architectures and expression patterns than GhMCTPs within subfamily I and II, suggesting that GhMCTPs within subfamily III, IV and V diverged to perform more diverse and specific functions. Analyses of conserved motifs and pIs indicated that the N-terminus was more divergent than the C-terminus and GhMCTPs' functional divergence might be mainly contributed by the N-terminus. Furthermore, yeast two-hybrid assay indicated that the N-terminus was responsible to interact with target proteins. Phylogenetic analysis classified multiple N-terminal C2 domains into four subclades, suggesting that these C2 domains performed different molecular functions in mediating the transport of target proteins. CONCLUSIONS: Our systematic characterization of MCTPs in G. hirsutum will provide helpful information to further research GhMCTPs' molecular roles in mediating other regulators' transport to coordinate growth and development of various cotton tissues.

Expansion of the Major Facilitator Superfamily (MFS) to include novel transporters as well as transmembrane-acting enzymes.

The Major Facilitator Superfamily (MFS) is currently the largest characterized superfamily of transmembrane secondary transport proteins. Its diverse members are found in essentially all organisms in the biosphere and function by uniport, symport, and/or antiport mechanisms. In 1993 we first named and described the MFS which then consisted of 5 previously known families that had not been known to be related, and by 2012 we had identified a total of 74 families, classified phylogenetically within the MFS, all of which included only transport proteins. This superfamily has since expanded to 89 families, all included under TC# 2.A.1, and a few transporter families outside of TC# 2.A.1 were identified as members of the MFS. In this study, we assign nine previously unclassified protein families in the Transporter Classification Database (TCDB; http://www.tcdb.org) to the MFS based on multiple criteria and bioinformatic methodologies. In addition, we find integral membrane domains distantly related to partial or full-length MFS permeases in Lysyl tRNA Synthases (TC# 9.B.111), Lysylphosphatidyl Glycerol Synthases (TC# 4.H.1), and cytochrome b561 transmembrane electron carriers (TC# 5.B.2). Sequence alignments, overlap of hydropathy plots, compatibility of repeat units, similarity of complexity profiles of transmembrane segments, shared protein domains and 3D structural similarities between transport proteins were analyzed to assist in inferring homology. The MFS now includes 105 families.

New approach for membrane protein reconstitution into peptidiscs and basis for their adaptability to different proteins.

Previously we introduced peptidiscs as an alternative to detergents to stabilize membrane proteins in solution (Carlson et al., 2018). Here, we present 'on-gradient' reconstitution, a new gentle approach for the reconstitution of labile membrane-protein complexes, and used it to reconstitute Rhodobacter sphaeroides reaction center complexes, demonstrating that peptidiscs can adapt to transmembrane domains of very different sizes and shapes. Using the conventional 'on-bead' approach, we reconstituted Escherichia coli proteins MsbA and MscS and find that peptidiscs stabilize them in their native conformation and allow for high-resolution structure determination by cryo-electron microscopy. The structures reveal that peptidisc peptides can arrange around transmembrane proteins differently, thus revealing the structural basis for why peptidiscs can stabilize such a large variety of membrane proteins. Together, our results establish the gentle and easy-to-use peptidiscs as a potentially universal alternative to detergents as a means to stabilize membrane proteins in solution for structural and functional studies.

Genome-based analysis reveals a novel SNMP group of the Coleoptera and chemosensory receptors in Rhaphuma horsfieldi.

Through an exhaustive homology-based approach, coupled with manual efforts, we annotated and characterized 128 sensory neuron membrane proteins (SNMPs) from genomes and transcriptomes of 22 coleopteran species, with 107 novel candidates. Remarkably, we discovered, for the first time, a novel SNMP group, defined as Group 4 based on the phylogeny, sequence characteristics, gene structure and organization. The lineage-specific expansions in SNMPs occurred mainly in the family Scarabaeidae, harboring 12 representatives in Onthophagus taurus as a typical gene duplication and the most massive set of SNMPs in insects to date. Transcriptome sequencing of Rhaphuma horsfieldi resulted in the yields of approximately 611.9 million clean reads that were further assembled into 543,841 transcripts and 327,550 unigenes, respectively. From the transcriptome, 177 transcripts encoding 84 odorant (ORs), 62 gustatory (GRs), 20 ionotropic (IRs), and 11 ionotropic glutamate (iGluRs) receptors were identified. Phylogenetic analysis classified RhorORs into six groups, RhorGRs into four subfamilies, and RhorIRs into 10 conserved antennal IRs and one divergent IRs. Expression profiles revealed that over 80% of chemosensory genes were specifically or highly transcribed in antennae or tarsi, suggestive of their olfactory and/or gustatory roles. This study has greatly complemented the resources for chemosensory genes in the cerambycid beetles, and most importantly, identifies a novel group of SNMPs in Coleoptera.

Preliminary investigation demonstrating the GHITM gene probably involved in apoptosis and growth of the golden apple snail (Pomacea canaliculata).

BACKGROUND: Growth hormone inducible transmembrane protein (GHITM) is a highly conserved transmembrane protein. This study was conducted to investigate the role of GHITM gene in the apoptosis and growth of the golden apple snail Pomacea canaliculate. RESULTS: The complete cDNA of this gene was cloned using the rapid amplification of cDNA ends (RACE) method and subjected to bioinformatics analysis. The full-length cDNA was 2242 bp, including an open reading frame of 1021 bp that encoded a protein of 342 amino acid residues. The mRNA expression profiles of GHITM gene in different tissues (liver, kidney, gonad and foot) and different growth phases (6-months old and 2-years old) showed that it was expressed in various tissues and different growth phases. Silencing of the GHITM gene by RNAi (RNA interference) experiments revealed that the GHITM gene possibly plays a role in inhibiting apoptosis through detecting the Caspase (Cysteine-requiring Aspartate Protease)-3 activity. In addition, the aperture width and body whorl length of the snail was significantly affected by RNAi, suggesting that this gene plays a significant role in promoting the growth of the organism. CONCLUSIONS: These results demonstrated that the GHITM gene was involved in apoptosis and growth in golden apple snail.

Hemagglutinin Cleavability, Acid Stability, and Temperature Dependence Optimize Influenza B Virus for Replication in Human Airways.

Influenza A virus (IAV) and influenza B virus (IBV) cause yearly epidemics with significant morbidity and mortality. When zoonotic IAVs enter the human population, the viral hemagglutinin (HA) requires adaptation to achieve sustained virus transmission. In contrast, IBV has been circulating in humans, its only host, for a long period of time. Whether this entailed adaptation of IBV HA to the human airways is unknown. To address this question, we compared two seasonal IAVs (A/H1N1 and A/H3N2) and two IBVs (B/Victoria and B/Yamagata lineages) with regard to host-dependent activity of HA as the mediator of membrane fusion during viral entry. We first investigated proteolytic activation of HA by covering all type II transmembrane serine protease (TTSP) and kallikrein enzymes, many of which proved to be present in human respiratory epithelium. The IBV HA0 precursor is cleaved by a broader panel of TTSPs and activated with much higher efficiency than IAV HA0. Accordingly, knockdown of a single protease, TMPRSS2, abrogated spread of IAV but not IBV in human respiratory epithelial cells. Second, the HA fusion pH values proved similar for IBV and human-adapted IAVs (with one exception being the HA of 1918 IAV). Third, IBV HA exhibited higher expression at 33°C, a temperature required for membrane fusion by B/Victoria HA. This indicates pronounced adaptation of IBV HA to the mildly acidic pH and cooler temperature of human upper airways. These distinct and intrinsic features of IBV HA are compatible with extensive host adaptation during prolonged circulation of this respiratory virus in the human population.IMPORTANCE Influenza epidemics are caused by influenza A and influenza B viruses (IAV and IBV, respectively). IBV causes substantial disease; however, it is far less studied than IAV. While IAV originates from animal reservoirs, IBV circulates in humans only. Virus spread requires that the viral hemagglutinin (HA) is active and sufficiently stable in human airways. We resolve here how these mechanisms differ between IBV and IAV. Whereas human IAVs rely on one particular protease for HA activation, this is not the case for IBV. Superior activation of IBV by several proteases should enhance shedding of infectious particles. IBV HA exhibits acid stability and a preference for 33°C, indicating pronounced adaptation to the human upper airways, where the pH is mildly acidic and a cooler temperature exists. These adaptive features are rationalized by the long existence of IBV in humans and may have broader relevance for understanding the biology and evolution of respiratory viruses.

Efficient utilization on PSSM combining with recurrent neural network for membrane protein types prediction.

Position-Specific Scoring Matrix (PSSM) is an excellent feature extraction method that was proposed early in protein classifying prediction, but within the restriction of feature shape in PSSM, researchers make a lot attempts to process it so that PSSM can be input to the traditional machine learning algorithms. These processes drop information provided by PSSM in a way thus the feature representation is limited. Moreover, the high-dimensional feature representation of PSSM makes it incompatible with other feature extraction methods. We use the PSSM as the input of Recurrent Neural Network without any post-processing, the amino acids in protein sequences are regarded as time step in RNN. This way takes full advantage of the information that PSSM provides. In this study, the PSSM is input to the model directly and the internal information of PSSM is fully utilized, we propose an end-to-end solution and achieve state-of-the-art performance. Ultimately, the exploration of how to combine PSSM with traditional feature extraction methods is carried out and achieve slightly improved performance. Our network architecture is implemented in Python and is available at https://github.com/YellowcardD/RNN-for-membrane-protein-types-prediction.

Molecular phenotyping of the surfaceome of migratory chondroprogenitors and mesenchymal stem cells using biotinylation, glycocapture and quantitative LC-MS/MS proteomic analysis.

The complement of cell surface proteins, collectively referred to as the surfaceome, is a useful indicator of normal differentiation processes, and the development of pathologies such as osteoarthritis (OA). We employed biochemical and proteomic tools to explore the surfaceome and to define biomarkers in chondrogenic progenitor cells (CPC) derived from human OA knee articular cartilage. These cells have great therapeutic potential, but their unexplored biology limits their clinical application. We performed biotinylation combined with glycocapture and high throughput shotgun proteomics to define the surface proteome of human bone marrow mesenchymal stem cells (MSCs) and human CPCs. We prepared cell surface protein-enriched fractions from MSCs and CPCs, and then a proteomic approach was used to compare and evaluate protein changes between undifferentiated MSCs and CPCs. 1256 proteins were identified in the study, of which 791 (63%) were plasma membrane, cell surface or extracellular matrix proteins. Proteins constituting the surfaceome were annotated and categorized. Our results provide, for the first time, a repository of quantitative proteomic data on the surfaceome of two closely related cell types relevant to cartilage biology and OA. These results may provide novel insights into the transformation of the surfaceome during chondrogenic differentiation and phenotypic changes during OA development.

PAC, an evolutionarily conserved membrane protein, is a proton-activated chloride channel.

Severe local acidosis causes tissue damage and pain, and is one of the hallmarks of many diseases including ischemia, cancer, and inflammation. However, the molecular mechanisms of the cellular response to acid are not fully understood. We performed an unbiased RNA interference screen and identified PAC (TMEM206) as being essential for the widely observed proton-activated Cl- (PAC) currents (I Cl,H). Overexpression of human PAC in PAC knockout cells generated I Cl,H with the same characteristics as the endogenous ones. Zebrafish PAC encodes a PAC channel with distinct properties. Knockout of mouse Pac abolished I Cl,H in neurons and attenuated brain damage after ischemic stroke. The wide expression of PAC suggests a broad role for this conserved Cl- channel family in physiological and pathological processes associated with acidic pH.

Molecular and antigenic characterization of Trypanosoma cruzi TolT proteins.

BACKGROUND: TolT was originally described as a Trypanosoma cruzi molecule that accumulated on the trypomastigote flagellum bearing similarity to bacterial TolA colicins receptors. Preliminary biochemical studies indicated that TolT resolved in SDS-PAGE as ~3-5 different bands with sizes between 34 and 45 kDa, and that this heterogeneity could be ascribed to differences in polypeptide glycosylation. However, the recurrent identification of TolT-deduced peptides, and variations thereof, in trypomastigote proteomic surveys suggested an intrinsic TolT complexity, and prompted us to undertake a thorough reassessment of this antigen. METHODS/PRINCIPLE FINDINGS: Genome mining exercises showed that TolT constitutes a larger-than-expected family of genes, with at least 12 polymorphic members in the T. cruzi CL Brener reference strain and homologs in different trypanosomes. According to structural features, TolT deduced proteins could be split into three robust groups, termed TolT-A, TolT-B, and TolT-C, all of them showing marginal sequence similarity to bacterial TolA proteins and canonical signatures of surface localization/membrane association, most of which were herein experimentally validated. Further biochemical and microscopy-based characterizations indicated that this grouping may have a functional correlate, as TolT-A, TolT-B and TolT-C molecules showed differences in their expression profile, sub-cellular distribution, post-translational modification(s) and antigenic structure. We finally used a recently developed fluorescence magnetic beads immunoassay to validate a recombinant protein spanning the central and mature region of a TolT-B deduced molecule for Chagas disease serodiagnosis. CONCLUSION/SIGNIFICANCE: This study unveiled an unexpected genetic and biochemical complexity within the TolT family, which could be exploited for the development of novel T. cruzi biomarkers with diagnostic/therapeutic applications.

Anti-inflammation effects of fucosylated chondroitin sulphate from Acaudina molpadioides by altering gut microbiota in obese mice.

This study evaluated the possible prebiotic effects of dietary fucosylated chondroitin sulfate from Acaudina molpadioides (Am-CHS) on the modulation of the gut microbiota and the improvement in the risk factors for chronic inflammation in high fat diet-fed mice. The results showed that the Am-CHS treatment greatly modified the gut microbiota, including the decrease in Bacteroidetes, increase in Firmicutes, elevation in Lactobacillus (intestinal barrier protector) and short chain fatty acid (SCFA)-producing bacteria (Lactobacillus, Bifidobacterium, and Lachnospiraceae NK4A136 group), and reduction in the lipopolysaccharide (LPS) producer (Escherichia coli). This modulation inhibited inflammatory response, manifesting the decreases in circulating proinflammatory cytokines and their mRNA expression, and the increases in interleukin-10. Dietary Am-CHS caused reductions in serum and fecal LPS concentrations and inhibition of transcription of toll-like receptor 4 (TLR4) and its downstream proteins. In addition, there were increases in the portal levels of fecal SCFAs, which probably contributed to an increase in the adenosine monophosphate-activated protein kinase (AMPK) protein in Am-CHS-treated mice. These results suggest that modulation of gut microbiota by Am-CHS can improve chronic inflammation by reducing LPS levels and TLR4 signaling. Modulation also appears to increase the levels of fecal SCFAs, which activates AMPK and finally leads to inflammation resistance.