Machine learning aided construction of the quorum sensing communication network for human gut microbiota

Roles and opportunities of quorum sensing in natural and engineered anaerobic digestion systems

Anaerobic digestion (AD) is a biological process in which anaerobic microorganisms convert organic matter into methane-rich gas, contributing to the cycling of carbon and other nutrients. Quorum sensing (QS), a microbial communication mechanism, plays a critical role in regulating population-level behaviors within AD systems. This review systematically examines the roles and applications of QS in AD, emphasizing its importance in enhancing process efficiency. The review begins by exploring the pathways and characteristics of QS in key functional microorganisms involved in AD. We analyze the response mechanisms of QS to key environmental variables and their effects on the structure and function of microbe communities and extracellular polymeric substances secretion. Potential applications of QS in engineered AD systems are discussed, with a focus on promoting system startup, improving operational efficiency, and enhancing resistance and stability. The use of exogenous signaling molecules and quorum quenching reagents to optimize AD performance is also evaluated. Additionally, the ecological significance of QS in natural environments, such as seafloor sediments and wetlands, is explored, emphasizing its role in regulating AD-related microorganisms within complex microbial communities. Finally, the review identifies current knowledge gaps and outlines future research directions in AD, including QS database development, QS-engineered bacteria excavation, and advanced analytical methods assistants. This comprehensive review aims to bridge existing gaps in QS-related knowledge in AD and provide fresh perspectives for studying microbial communication and collaboration through QS.

Supramolecular Switching-Enabled Quorum Sensing Trap for Pathogen-Specific Recognition and Eradication to Treat Enteritis

Intestinal bacterial infections have become a significant threat to human health. However, the current typical antibiotic-based therapies not only contribute to drug resistance but also disrupt gut microbiota balance, resulting in additional adverse effects on life activities. There is an urgent need to develop new antibacterial materials that selectively eliminate pathogenic bacteria without disrupting beneficial bacterial communities or promoting drug resistance. Herein, we utilize bacterial quorum sensing (QS), a universal mechanism for regulating community behavior, to develop a supramolecular QS trap by encapsulating cucurbit[7]uril (CB[7]) on 1-vinyl-3-pentylimidazolium bromide ([VPIM]Br) to form a supramolecular switch ([VPIM]Br⊂CB[7]) through host-guest interactions followed by grafting it onto bacterial cell surfaces using atom transfer radical polymerization. Subsequently, the matched pathogens are recognized and aggregated through interbacterial QS signals. Furthermore, the addition of amantadine (AD) facilitates the release of [VPIM]Br by competitive binding of CB[7] on [VPIM]Br⊂CB[7] for sterilization. This QS trap specifically triggers the self-aggregation and efficient elimination of matched bacteria. The [VPIM]Br⊂CB[7]-based trap can increase the diversity and abundance of intestinal microorganisms in mice, effectively treating Escherichia coli K88-induced intestinal damage without perturbing gut microbiota balance. This supramolecular-switched QS trap opens up a promising avenue to specifically recognize and eradicate pathogens for the antibiotic-free treatment of intestinal bacterial infections and other inflammatory diseases.

Targeting quorum sensing for manipulation of commensal microbiota

Bacteria communicate through the accumulation of autoinducer (AI) molecules that regulate gene expression at critical densities in a process called quorum sensing (QS). Extensive work using simple systems and single strains of bacteria have revealed a role for QS in the regulation of virulence factors and biofilm formation; however, less is known about QS dynamics among communities, especially in vivo. In this review, we summarize the diversity of QS signals as well as their ability to influence "non-target" behaviors among species that have receptors but not synthases for those signals. We highlight host-microbe interactions facilitated by QS and describe cross-talk between QS and the mammalian endocrine and immune systems, as well as host surveillance of QS. Further, we describe emerging evidence for the role of QS in non-infectious, chronic, microbially associated diseases including inflammatory bowel diseases and cancers. Finally, we describe potential therapeutic approaches that involve leveraging QS signals as well as quorum quenching approaches to block signaling in vivo to mitigate deleterious consequences to the host. Ultimately, QS offers a previously underexplored target that may be leveraged for precision modification of the microbiota without deleterious bactericidal consequences.

Rore: robust and efficient antioxidant protein classification via a novel dimensionality reduction strategy based on learning of fewer features

In protein identification, researchers increasingly aim to achieve efficient classification using fewer features. While many feature selection methods effectively reduce the number of model features, they often cause information loss caused by merely selecting or discarding features, which limits classifier performance. To address this issue, we present Rore, an algorithm based on a feature-dimensionality reduction strategy. By mapping the original features to a latent space, Rore retains all relevant feature information while using fewer representations of the latent features. This approach significantly preserves the original information and overcomes the information loss problem associated with previous feature selection. Through extensive experimental validation and analysis, Rore demonstrated excellent performance on an antioxidant protein dataset, achieving an accuracy of 95.88% and MCC of 91.78%, using vectors including only 15 features. The Rore algorithm is available online at http://112.124.26.17:8021/Rore .

Insights into Women's health: Exploring the vaginal microbiome, quorum sensing dynamics, and therapeutic potential of quorum sensing quenchers

The vaginal microbiome is an important aspect of women's health that changes dynamically with various stages of the woman's life. Just like the gut microbiome, the vaginal microbiome can also be affected by pathologies that dramatically change the typical composition of native vaginal microorganisms. However, the mechanism as to how both vaginal endemic and gut endemic opportunistic microbes can express pathogenicity in vaginal polymicrobial biofilms is poorly understood. Quorum sensing is the cellular density-dependent bacterial and fungal communication process in which chemical signaling molecules, known as autoinducers, activate expression for genes responsible for virulence and pathogenicity, such as biofilm formation and virulence factor production. Quorum sensing inhibition, or quorum quenching, has been explored as a potential therapeutic route for both bacterial and fungal infections. By applying these quorum quenchers, one can reduce biofilm formation of opportunistic vaginal microbes and combine them with antibiotics for a synergistic effect. This review aims to display the relationship between the vaginal and gut microbiome, the role of quorum sensing in polymicrobial biofilm formation which cause pathology in the vaginal microbiome, and how quorum quenchers can be utilized to attenuate the severity of bacterial and fungal infections.

DeepForest-HTP: A novel deep forest approach for predicting antihypertensive peptides

Hypertension is a major preventable risk factor for cardiovascular disease, affecting over 1.5 billion adults worldwide. Antihypertensive peptides (AHTPs) have gained attention as a natural therapeutic option with minimal side effects. This study proposes a Deep Forest-based machine learning framework for AHTP prediction, leveraging a multi-granularity cascade structure to enhance classification accuracy. We integrated data from BIOPEP-UWM and three previously used datasets, totaling 2000 peptide sequences, and introduced novel feature extraction methods to build a comprehensive dataset for model training. This study represents the first application of Deep Forest for AHTP identification, demonstrating substantial classification performance advantages over traditional methods (e.g., SVM, CNN, and XGBoost) as well as recent mainstream prediction models (Ensemble-AHTPpred, CNN-SVM Ensemble, and mAHTPred). Requiring no complex manual feature engineering, the model adapts flexibly to various data needs, offering a novel perspective for efficient AHTP prediction and promising utility in hypertension management. On the benchmark dataset, the model achieved high accuracy, sensitivity, and AUC, providing a robust tool for identifying safe and effective AHTPs. However, future efforts should incorporate larger and more diverse independent validation datasets to further improve the model and enhance its generalizability. Additionally, the model's predictive accuracy relies on known AHTP targets and sequence features, potentially limiting its ability to detect AHTPs with uncharacterized or atypical properties.

A metagenomic catalogue of the ruminant gut archaeome

While the ruminant gut archaeome regulates the gut microbiota and hydrogen balance, it is also a major producer of the greenhouse gas methane. However, ruminant gut archaeome diversity within the gastrointestinal tract (GIT) of ruminant animals worldwide remains largely underexplored. Here, we construct a catalogue of 998 unique archaeal genomes recovered from the GITs of ruminants, utilizing 2270 metagenomic samples across 10 different ruminant species. Most of the archaeal genomes (669/998 = 67.03%) belong to Methanobacteriaceae and Methanomethylophilaceae (198/998 = 19.84%). We recover 47/279 previously undescribed archaeal genomes at the strain level with completeness of >80% and contamination of <5%. We also investigate the archaeal gut biogeography across various ruminants and demonstrate that archaeal compositional similarities vary significantly by breed and gut location. The catalogue contains 42,691 protein clusters, and the clustering and methanogenic pathway analysis reveal strain- and host-specific dependencies among ruminant animals. We also find that archaea potentially carry antibiotic and metal resistance genes, mobile genetic elements, virulence factors, quorum sensors, and complex archaeal viromes. Overall, this catalogue is a substantial repository for ruminant archaeal recourses, providing potential for advancing our understanding of archaeal ecology and discovering strategies to regulate methane production in ruminants.

Nisin-relevant antimicrobial peptides: synthesis strategies and applications

Small pentacyclic peptides, represented by nisin, have been successfully utilized as preservatives in the food industry and have evolved into a paradigm for understanding the genetic structure, expression, and control of genes created by lantibiotics. Due to the ever-increasing antibiotic resistance, nisin-relevant antimicrobial peptides have received much attention, which calls for a summarization of their synthesis, modification and applications. In this review, we first provided a timeline of select highlights in nisin biosynthesis and engineering. Then, we outlined the current developments in nisin synthesis. We also provided an overview of the engineering, screening, and production of nisin-relevant antimicrobial peptides based on enzyme alteration, substrate modification, and sequence mining. Furthermore, an updated summary of applications of nisin-relevant antimicrobial peptides has been developed for food applications. Finally, this study offers insights into emerging technologies, limitations and the future development of nisin-relevant antimicrobial peptides for pathogen inhibition, food preservatives, and improved health.

Massive expansion of the pig gut virome based on global metagenomic mining

The pig gut virome plays a vital role in the gut microbial ecosystem of pigs. However, a comprehensive understanding of their diversity and a reference database for the virome are currently lacking. To address this gap, we established a Pig Virome Database (PVD) that comprised of 5,566,804 viral contig sequences from 4650 publicly available gut metagenomic samples using a pipeline designated "metav". By clustering sequences, we identified 48,299 viral operational taxonomic units (vOTUs) genomes of at least medium quality, of which 92.83% of which were not found in existing major databases. The majority of vOTUs were identified as Caudoviricetes (72.21%). The PVD database contained a total of 2,362,631 protein-coding genes across the above medium-quality vOTUs genomes that can be used to explore the functional potential of the pig gut virome. These findings highlight the extensive diversity of viruses in the pig gut and provide a pivotal reference dataset for forthcoming research concerning the pig gut virome.

Prediction of cell-type-specific cohesin-mediated chromatin loops based on chromatin state

Chromatin loop is of crucial importance for the regulation of gene transcription. Cohesin is a type of chromatin-associated protein that mediates the interaction of chromatin through the loop extrusion. Cohesin-mediated chromatin interactions have strong cell-type specificity, posing a challenge for predicting chromatin loops. Existing computational methods perform poorly in predicting cell-type-specific chromatin loops. To address this issue, we propose a random forest model to predict cell-type-specific cohesin-mediated chromatin loops based on chromatin states identified by ChromHMM and the occupancy of related factors. Our results show that chromatin state is responsible for cell-type-specificity of loops. Using only chromatin states as features, the model achieved high accuracy in predicting cell-type-specific loops between two cell types and can be applied to different cell types. Furthermore, when chromatin states are combined with the occurrence frequency of CTCF, RAD21, YY1, and H3K27ac ChIP-seq peaks, more accurate prediction can be achieved. Our feature extraction method provides novel insights into predicting cell-type-specific chromatin loops and reveals the relationship between chromatin state and chromatin loop formation.

Multi-omic analysis tools for microbial metabolites prediction

How to resolve the metabolic dark matter of microorganisms has long been a challenging problem in discovering active molecules. Diverse omics tools have been developed to guide the discovery and characterization of various microbial metabolites, which make it gradually possible to predict the overall metabolites for individual strains. The combinations of multi-omic analysis tools effectively compensates for the shortcomings of current studies that focus only on single omics or a broad class of metabolites. In this review, we systematically update, categorize and sort out different analysis tools for microbial metabolites prediction in the last five years to appeal for the multi-omic combination on the understanding of the metabolic nature of microbes. First, we provide the general survey on different updated prediction databases, webservers, or software that based on genomics, transcriptomics, proteomics, and metabolomics, respectively. Then, we discuss the essentiality on the integration of multi-omics data to predict metabolites of different microbial strains and communities, as well as stressing the combination of other techniques, such as systems biology methods and data-driven algorithms. Finally, we identify key challenges and trends in developing multi-omic analysis tools for more comprehensive prediction on diverse microbial metabolites that contribute to human health and disease treatment.

Quorum sensing bacteria improve microbial networks stability and complexity in wastewater treatment plants

Quorum-sensing bacteria (QSB) are crucial factors for microbial communication, yet their ecological role in wastewater treatment plants (WWTPs) remains unclear. Here, we developed a method to identify QSB by comparing 16S rRNA gene sequences. QSB in 388 activated sludge samples collected from 130 WWTPs across China primarily were identified as rare taxa and conditionally rare taxa. A co-occurrence network shared by all sludge communities revealed that QSB exhibited higher average clustering coefficient (0.46) than non-QSB (0.15). Individual sludge networks demonstrated that quorum sensing microbiomes were positively correlated with network robustness and network complexity, including average clustering coefficient and link density. We confirmed that QSB keystones and QSB nodes have a positive impact on network complexity by influencing network modularity through a structural equation model. Meanwhile, QSB communities directly contributed to maintaining network robustness (r = 0.29, P < 0.05). Hence, QSB play an important role in promoting network complexity and stability. Furthermore, QSB communities were positively associated with the functional composition of activated sludge communities (r = 0.33, P < 0.01), especially the denitrification capacity (r = 0.45, P < 0.001). Overall, we elucidated the ecological significance of QSB and provided support for QS-based regulation of activated sludge microbial communities.

Bibliometric analysis and visualization of quorum sensing research over the last two decade

Background

Quorum sensing (QS) research stands as a pivotal and multifaceted domain within microbiology, holding profound implications across various scientific disciplines. This bibliometric analysis seeks to offer an extensive overview of QS research, covering the period from 2004 to 2023. It aims to elucidate the hotspots, trends, and the evolving dynamics within this research domain.

Methods

We conducted an exhaustive review of the literature, employing meticulous data curation from the Science Citation Index Extension (SCI-E) within the Web of Science (WOS) database. Subsequently, our survey delves into evolving publication trends, the constellation of influential authors and institutions, key journals shaping the discourse, global collaborative networks, and thematic hotspots that define the QS research field.

Results

The findings demonstrate a consistent and growing interest in QS research throughout the years, encompassing a substantial dataset of 4,849 analyzed articles. Journals such as Frontiers in Microbiology have emerged as significant contributor to the QS literature, highlighting the increasing recognition of QS's importance across various research fields. Influential research in the realm of QS often centers on microbial communication, biofilm formation, and the development of QS inhibitors. Notably, leading countries engaged in QS research include the United States, China, and India. Moreover, the analysis identifies research focal points spanning diverse domains, including pharmacological properties, genetics and metabolic pathways, as well as physiological and signal transduction mechanisms, reaffirming the multidisciplinary character of QS research.

Conclusion

This bibliometric exploration provides a panoramic overview of the current state of QS research. The data portrays a consistent trend of expansion and advancement within this domain, signaling numerous prospects for forthcoming research and development. Scholars and stakeholders engaged in the QS field can harness these findings to navigate the evolving terrain with precision and speed, thereby enhancing our comprehension and utilization of QS in various scientific and clinical domains.

Constructions of quorum sensing signaling network for activated sludge microbial community

In wastewater treatment systems, the interactions among various microbes based on chemical signals, namely quorum sensing (QS), play critical roles in influencing microbial structure and function. However, it is challenging to understand the QS-controlled behaviors and the underlying mechanisms in complex microbial communities. In this study, we constructed a QS signaling network, providing insights into the intra- and interspecies interactions of activated sludge microbial communities based on diverse QS signal molecules. Our research underscores the role of diffusible signal factors in both intra- and interspecies communication among activated sludge microorganisms, and signal molecules commonly considered to mediate intraspecies communication may also participate in interspecies communication. QS signaling molecules play an important role as communal resources among the entire microbial group. The communication network within the microbial community is highly redundant, significantly contributing to the stability of natural microbial systems. This work contributes to the establishment of QS signaling network for activated sludge microbial communities, which may complement metabolic exchanges in explaining activated sludge microbial community structure and may help with a variety of future applications, such as making the dynamics and resilience of highly complex ecosystems more predictable.

Targeting microbial quorum sensing: the next frontier to hinder bacterial driven gastrointestinal infections

Bacteria synchronize social behaviors via a cell-cell communication and interaction mechanism termed as quorum sensing (QS). QS has been extensively studied in monocultures and proved to be intensively involved in bacterial virulence and infection. Despite the role QS plays in pathogens during laboratory engineered infections has been proved, the potential functions of QS related to pathogenesis in context of microbial consortia remain poorly understood. In this review, we summarize the basic molecular mechanisms of QS, primarily focusing on pathogenic microbes driving gastrointestinal (GI) infections. We further discuss how GI pathogens disequilibrate the homeostasis of the indigenous microbial consortia, rebuild a realm dominated by pathogens, and interact with host under worsening infectious conditions via pathogen-biased QS signaling. Additionally, we present recent applications and main challenges of manipulating QS network in microbial consortia with the goal of better understanding GI bacterial sociality and facilitating novel therapies targeting bacterial infections.

Bacterial quorum sensing orchestrates longitudinal interactions to shape microbiota assembly

BACKGROUND

The mechanism of microbiota assembly is one of the main problems in microbiome research, which is also the primary theoretical basis for precise manipulation of microbial communities. Bacterial quorum sensing (QS), as the most common means for bacteria to exchange information and interactions, is characterized by universality, specificity, and regulatory power, which therefore may influence the assembly processes of human microbiota. However, the regulating role of QS in microbiota assembly is rarely reported. In this study, we developed an optimized in vitro oral biofilm microbiota assembling (OBMA) model to simulate the time-series assembly of oral biofilm microbiota (OBM), by which to excavate the QS network and its regulating power in the process.

RESULTS

By using the optimized OBMA model, we were able to restore the assembly process of OBM and generate time-series OBM metagenomes of each day. We discovered a total of 2291 QS protein homologues related to 21 QS pathways. Most of these pathways were newly reported and sequentially enriched during OBM assembling. These QS pathways formed a comprehensive longitudinal QS network that included successively enriched QS hubs, such as Streptococcus, Veillonella-Megasphaera group, and Prevotella-Fusobacteria group, for information delivery. Bidirectional cross-talk among the QS hubs was found to play critical role in the directional turnover of microbiota structure, which in turn, influenced the assembly process. Subsequent QS-interfering experiments accurately predicted and experimentally verified the directional shaping power of the longitudinal QS network in the assembly process. As a result, the QS-interfered OBM exhibited delayed and fragile maturity with prolonged membership of Streptococcus and impeded membership of Prevotella and Fusobacterium.

CONCLUSION

Our results revealed an unprecedented longitudinal QS network during OBM assembly and experimentally verified its power in predicting and manipulating the assembling process. Our work provides a new perspective to uncover underlying mechanism in natural complex microbiota assembling and a theoretical basis for ultimately precisely manipulating human microbiota through intervention in the QS network. Video Abstract.

The regulatory functions of oxylipins in fungi: A review

Quorum sensing (QS) is a communication mechanism between microorganisms originally found in bacteria. In recent years, an important QS mechanism has been discovered in the field of fungi, namely, the lipoxygenase compound oxylipin of arachidonic acid acts as a QS molecule in life cycle control, particularly in the sexual and asexual development of fungi. However, the role of oxylipins in mediating eukaryotic communication has not been previously described. In this paper, we review the regulatory role of oxylipins and the underlying mechanisms and discuss the potential for application in major fungi. The role of oxylipin as a fungal quorum-sensing molecule is the main focus of the review. Besides, the quorum regulation of fungal morphological transformation, biofilm formation, virulence factors, secondary metabolism, infection, symbiosis, and other physiological behaviors are discussed. Moreover, future prospectives and applications are elaborated as well.

Diffusible signal factors (DSFs) bind and repress VirF, the leading virulence activator of Shigella flexneri

Shigella, the aetiological agent of human bacillary dysentery, controls the expression of its virulence determinants through an environmentally stimulated cascade of transcriptional activators. VirF is the leading activator and is essential for proper virulence expression. In this work, we report on in vitro and in vivo experiments showing that two autoinducers of the DSF family, XcDSF and BDSF interact with the jelly roll module of VirF causing its inhibition and affecting the expression of the entire virulence system of Shigella, including its ability to invade epithelial cells. We propose a molecular model explaining how the binding of XcDSF and BDSF causes inhibition of VirF by preventing its dimerization. Overall, our experimental results suggest that XcDSF and BDSF may contribute to "colonisation resistance" in the human gut or, alternatively, may be exploited for the fine-tuning of Shigella virulence expression as the bacterium migrates from the lumen to approach the intestinal mucosa. Our findings also stress how a detailed understanding of the interaction of DSF ligands with VirF may contribute to the rational development of innovative antivirulence drugs to treat shigellosis.

Zooming into Gut Dysbiosis in Parkinson's Disease: New Insights from Functional Mapping

Gut dysbiosis has been involved in the pathogenesis and progression of Parkinson's disease (PD), but the mechanisms through which gut microbiota (GM) exerts its influences deserve further study. Recently, we proposed a two-hit mouse model of PD in which ceftriaxone (CFX)-induced dysbiosis amplifies the neurodegenerative phenotype generated by striatal 6-hydroxydopamine (6-OHDA) injection in mice. Low GM diversity and the depletion of key gut colonizers and butyrate producers were the main signatures of GM alteration in this model. Here, we used the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt2) to unravel candidate pathways of cell-to-cell communication associated with dual-hit mice and potentially involved in PD progression. We focused our analysis on short-chain fatty acids (SCFAs) metabolism and quorum sensing (QS) signaling. Based on linear discriminant analysis, combined with the effect size results, we found increased functions linked to pyruvate utilization and a depletion of acetate and butyrate production in 6-OHDA+CFX mice. The specific arrangement of QS signaling as a possible result of the disrupted GM structure was also observed. With this exploratory study, we suggested a scenario in which SCFAs metabolism and QS signaling might represent the effectors of gut dysbiosis potentially involved in the designation of the functional outcomes that contribute to the exacerbation of the neurodegenerative phenotype in the dual-hit animal model of PD.

QSP: An open sequence database for quorum sensing related gene analysis with an automatic annotation pipeline

Quorum sensing (QS) has attracted great attention due to its important role in the bacterial interactions and its relevance to water management. With the development of high-throughput sequencing technology, a specific database for QS-related sequence annotation is urgently needed. Here, Hidden Markov Model (HMM) profiles for 38 types of QS-related proteins were built using a total of 4024 collected seed sequences. Based on both homolog search and keywords confirmation against the non-redundant database, we established a QS-related protein (QSP) database, that includes 809,721 protein sequences and 186,133 nucleotide sequences, downloaded available at: https://github.com/chunxiao-dcx/QSP. The entries were classified into 38 types and 315 subtypes among 91 bacterial phyla. Furthermore, an automatic annotation pipeline, named QSAP, was developed for rapid annotation, classification and abundance quantification of QSP-like sequences from sequencing data. This pipeline provided the two homolog alignment strategies offered by Diamond (Blastp) or HMMER (Hmmscan), as well as a data cleansing function for a subset or union set of the hits. The pipeline was tested using 14 metagenomic samples from various water environments, including activated sludge, deep-sea sediments, estuary water, and reservoir water. The QSAP pipeline is freely available for academic use in the code repository at: https://github.com/chunxiao-dcx/QSAP. The establishment of this database and pipeline, provides a useful tool for QS-related sequence annotation in a wide range of projects, and will increase our understanding of QS communication in aquatic environments.

Computational tools for exploring peptide-membrane interactions in gram-positive bacteria

The vital cellular functions in Gram-positive bacteria are controlled by signaling molecules known as quorum sensing peptides (QSPs), considered promising therapeutic interventions for bacterial infections. In the bacterial system QSPs bind to membrane-coupled receptors, which then auto-phosphorylate and activate intracellular response regulators. These response regulators induce target gene expression in bacteria. One of the most reliable trends in drug discovery research for virulence-associated molecular targets is the use of peptide drugs or new functionalities. In this perspective, computational methods act as auxiliary aids for biologists, where methodologies based on machine learning and in silico analysis are developed as suitable tools for target peptide identification. Therefore, the development of quick and reliable computational resources to identify or predict these QSPs along with their receptors and inhibitors is receiving considerable attention. The databases such as Quorumpeps and Quorum Sensing of Human Gut Microbes (QSHGM) provide a detailed overview of the structures and functions of QSPs. The tools and algorithms such as QSPpred, QSPred-FL, iQSP, EnsembleQS and PEPred-Suite have been used for the generic prediction of QSPs and feature representation. The availability of compiled key resources for utilizing peptide features based on amino acid composition, positional preferences, and motifs as well as structural and physicochemical properties, including biofilm inhibitory peptides, can aid in elucidating the QSP and membrane receptor interactions in infectious Gram-positive pathogens. Herein, we present a comprehensive survey of diverse computational approaches that are suitable for detecting QSPs and QS interference molecules. This review highlights the utility of these methods for developing potential biomarkers against infectious Gram-positive pathogens.

Synthetic bacterial therapies for intestinal diseases based on quorum- sensing circuits

Bacterial therapy has become a key strategy against intestinal infectious diseases in recent years. Moreover, regulating the gut microbiota through traditional fecal microbiota transplantation and supplementation of probiotics faces controllability, efficacy, and safety challenges. The infiltration and emergence of synthetic biology and microbiome provide an operational and safe treatment platform for live bacterial biotherapies. Synthetic bacterial therapy can artificially manipulate bacteria to produce and deliver therapeutic drug molecules. This method has the advantages of solid controllability, low toxicity, strong therapeutic effects, and easy operation. As an essential tool for dynamic regulation in synthetic biology, quorum sensing (QS) has been widely used for designing complex genetic circuits to control the behavior of bacterial populations and achieve predefined goals. Therefore, QS-based synthetic bacterial therapy might become a new direction for the treatment of diseases. The pre-programmed QS genetic circuit can achieve a controllable production of therapeutic drugs on particular ecological niches by sensing specific signals released from the digestive system in pathological conditions, thereby realizing the integration of diagnosis and treatment. Based on this as well as the modular idea of synthetic biology, QS-based synthetic bacterial therapies are divided into an environmental signal sensing module (senses gut disease physiological signals), a therapeutic molecule producing module (plays a therapeutic role against diseases), and a population behavior regulating module (QS system). This review article summarized the structure and function of these three modules and discussed the rational design of QS gene circuits as a novel intervention strategy for intestinal diseases. Moreover, the application prospects of QS-based synthetic bacterial therapy were summarized. Finally, the challenges faced by these methods were analyzed to make the targeted recommendations for developing a successful therapeutic strategy for intestinal diseases.

Quorum sensing in human gut and food microbiomes: Significance and potential for therapeutic targeting

Human gut and food microbiomes interact during digestion. The outcome of these interactions influences the taxonomical composition and functional capacity of the resident human gut microbiome, with potential consequential impacts on health and disease. Microbe-microbe interactions between the resident and introduced microbiomes, which likely influence host colonisation, are orchestrated by environmental conditions, elements of the food matrix, host-associated factors as well as social cues from other microorganisms. Quorum sensing is one example of a social cue that allows bacterial communities to regulate genetic expression based on their respective population density and has emerged as an attractive target for therapeutic intervention. By interfering with bacterial quorum sensing, for instance, enzymatic degradation of signalling molecules (quorum quenching) or the application of quorum sensing inhibitory compounds, it may be possible to modulate the microbial composition of communities of interest without incurring negative effects associated with traditional antimicrobial approaches. In this review, we summarise and critically discuss the literature relating to quorum sensing from the perspective of the interactions between the food and human gut microbiome, providing a general overview of the current understanding of the prevalence and influence of quorum sensing in this context, and assessing the potential for therapeutic targeting of quorum sensing mechanisms.

Molecular regulation of conditioning film formation and quorum quenching in sulfate reducing bacteria

Sensing surface topography, an upsurge of signaling biomolecules, and upholding cellular homeostasis are the rate-limiting spatio-temporal events in microbial attachment and biofilm formation. Initially, a set of highly specialized proteins, viz. conditioning protein, directs the irreversible attachment of the microbes. Later signaling molecules, viz. autoinducer, take over the cellular communication phenomenon, resulting in a mature microbial biofilm. The mandatory release of conditioning proteins and autoinducers corroborated the existence of two independent mechanisms operating sequentially for biofilm development. However, both these mechanisms are significantly affected by the availability of the cofactor, e.g., Copper (Cu). Generally, the Cu concentration beyond threshold levels is detrimental to the anaerobes except for a few species of sulfate-reducing bacteria (SRB). Remarkably SRB has developed intricate ways to resist and thrive in the presence of Cu by activating numerous genes responsible for modifying the presence of more toxic Cu(I) to Cu(II) within the periplasm, followed by their export through the outer membrane. Therefore, the determinants of Cu toxicity, sequestration, and transportation are reconnoitered for their contribution towards microbial adaptations and biofilm formation. The mechanistic details revealing Cu as a quorum quencher (QQ) are provided in addition to the three pathways involved in the dissolution of cellular communications. This review articulates the Machine Learning based data curing and data processing for designing novel anti-biofilm peptides and for an in-depth understanding of QQ mechanisms. A pioneering data set has been mined and presented on the functional properties of the QQ homolog in Oleidesulfovibrio alaskensis G20 and residues regulating the multicopper oxidase properties in SRB.

Pharmacological hypothesis: A recombinant probiotic for taming bacterial β-glucuronidase in drug-induced enteropathy

Advances in pharmacomicrobiomics have shed light on the pathophysiology of drug‐induced enteropathy associated with the therapeutic use of certain non‐steroidal anti‐inflammatory drugs, anticancer chemotherapies and immunosuppressants. The toxicity pathway results from the post‐glucuronidation release and digestive accumulation of an aglycone generated in the context of intestinal dysbiosis characterized by the expansion of β‐glucuronidase‐expressing bacteria. The active aglycone could trigger direct or indirect inflammatory signaling on the gut epithelium. Therefore, taming bacterial β‐glucuronidase (GUS) activity is a druggable target for preventing drug‐induced enteropathy. In face of the limitations of antibiotic strategies that can worsen intestinal dysbiosis and impair immune functions, we hereby propose the use of a recombinant probiotic capable of mimicking repressive conditions of GUS through an inducible plasmid vector.

Strategies to prevent, curb and eliminate biofilm formation based on the characteristics of various periods in one biofilm life cycle

Biofilms are colonies of bacteria embedded inside a complicated self-generating intercellular. The formation and scatter of a biofilm is an extremely complex and progressive process in constant cycles. Once formed, it can protect the inside bacteria to exist and reproduce under hostile conditions by establishing tolerance and resistance to antibiotics as well as immunological responses. In this article, we reviewed a series of innovative studies focused on inhibiting the development of biofilm and summarized a range of corresponding therapeutic methods for biological evolving stages of biofilm. Traditionally, there are four stages in the biofilm formation, while we systematize the therapeutic strategies into three main periods precisely:(i) period of preventing biofilm formation: interfering the colony effect, mass transport, chemical bonds and signaling pathway of plankton in the initial adhesion stage; (ii) period of curbing biofilm formation:targeting several pivotal molecules, for instance, polysaccharides, proteins, and extracellular DNA (eDNA) via polysaccharide hydrolases, proteases, and DNases respectively in the second stage before developing into irreversible biofilm; (iii) period of eliminating biofilm formation: applying novel multifunctional composite drugs or nanoparticle materials cooperated with ultrasonic (US), photodynamic, photothermal and even immune therapy, such as adaptive immune activated by stimulated dendritic cells (DCs), neutrophils and even immunological memory aroused by plasmocytes. The multitargeted or combinational therapies aim to prevent it from developing to the stage of maturation and dispersion and eliminate biofilms and planktonic bacteria simultaneously.