Multiplexed Identification of Bacterial Biofilm Infections Based on Machine-Learning-Aided Lanthanide Encoding

Metabolism-triggered sensor array aided by machine learning for rapid identification of pathogens

Chemical-nose strategy has achieved certain success in the discrimination and identification of pathogens. However, this strategy usually relies on non-specific interactions, which are prone to be significantly disturbed by the change of environment thus limiting its practical usefulness. Herein, we present a novel chemical-nose sensing approach leveraging the difference in the dynamic metabolic variation during peptidoglycan metabolism among different species for rapid pathogen discrimination. Pathogens were first tethered with clickable handles through metabolic labeling at two different acidities (pH = 5 and 7) for 20 and 60 min, respectively, followed by click reaction with fluorescence up-conversion nanoparticles to generate a four-dimensional signal output. This discriminative multi-dimensional signal allowed eight types of model bacteria to be successfully classified within the training set into strains, genera, and Gram phenotypes. As the difference in signals of the four sensing channels reflects the difference in the amount/activity of enzymes involved in metabolic labeling, this strategy has good anti-interference capability, which enables precise pathogen identification within 2 h with 100% accuracy in spiked urinary samples and allows classification of unknown species out of the training set into the right phenotype. The robustness of this approach holds significant promise for its widespread application in pathogen identification and surveillance.

Dissolving microneedle system containing Ag nanoparticle-decorated silk fibroin microspheres and antibiotics for synergistic therapy of bacterial biofilm infection

Most cases of delayed wound healing are associated with bacterial biofilm infections due to high antibiotic resistance. To improve patient compliance and recovery rates, it is critical to develop minimally invasive and efficient methods to eliminate bacterial biofilms as an alternative to clinical debridement techniques. Herein, we develop a dissolving microneedle system containing Ag nanoparticles (AgNPs)-decorated silk fibroin microspheres (SFM-AgNPs) and antibiotics for synergistic treatment of bacterial biofilm infection. Silk fibroin microspheres (SFM) are controllably prepared in an incompatible system formed by a mixture of protein and carbohydrate solutions by using a mild all-aqueous phase method and serve as biological templates for the synthesis of AgNPs. The SFM-AgNPs exert dose- and time-dependent broad-spectrum antibacterial effects by inducing bacterial adhesion. The combination of SFM-AgNPs with antibiotics breaks the limitation of the antibacterial spectrum and achieves better efficacy with reduced antibiotic dosage. Using hyaluronic acid (HA) as the soluble matrix, the microneedle system containing SFM-AgNPs and anti-Gram-positive coccus drug (Mupirocin) inserts into the bacterial biofilms with sufficient strength, thereby effectively delivering the antibacterial agents and realizing good antibiofilm effect on Staphylococcus aureus-infected wounds. This work demonstrates the great potential for the development of novel therapeutic systems for eradicating bacterial biofilm infections.

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are among the most prevalent infectious diseases worldwide, with a notable increase in treatment costs due to the emergence of drug-resistant pathogens. Current diagnostic strategies for UTIs, such as urine culture and flow cytometry, require time-consuming protocols and expensive equipment. We present here a machine learning-assisted colorimetric sensor array based on recognition of ligand-functionalized Fe single-atom nanozymes (SANs) for the identification of microorganisms at the order, genus, and species levels. Colorimetric sensor arrays are built from the SAN Fe1-NC functionalized with four types of recognition ligands, generating unique microbial identification fingerprints. By integrating the colorimetric sensor arrays with a trained computational classification model, the platform can identify more than 10 microorganisms in UTI urine samples within 1 h. Diagnostic accuracy of up to 97% was achieved in 60 UTI clinical samples, holding great potential for translation into clinical practice applications.

Dual-Emission Single Sensing Element-Assembled Fluorescent Sensor Arrays for the Rapid Discrimination of Multiple Surfactants in Environments

Surfactants are considered as typical emerging pollutants, their extensive use of in disinfectants has hugely threatened the ecosystem and human health, particularly during the pandemic of coronavirus disease-19 (COVID-19), whereas the rapid discrimination of multiple surfactants in environments is still a great challenge. Herein, we designed a fluorescent sensor array based on luminescent metal-organic frameworks (UiO-66-NH2@Au NCs) for the specific discrimination of six surfactants (AOS, SDS, SDSO, MES, SDBS, and Tween-20). Wherein, UiO-66-NH2@Au NCs were fabricated by integrating UiO-66-NH2 (2-aminoterephthalic acid-anchored-MOFs based on zirconium ions) with gold nanoclusters (Au NCs), which exhibited a dual-emission features, showing good luminescence. Interestingly, due to the interactions of surfactants and UiO-66-NH2@Au NCs, the surfactants can differentially regulate the fluorescence property of UiO-66-NH2@Au NCs, producing diverse fluorescent "fingerprints", which were further identified by pattern recognition methods. The proposed fluorescence sensor array achieved 100% accuracy in identifying various surfactants and multicomponent mixtures, with the detection limit in the range of 0.0032 to 0.0315 mM for six pollutants, which was successfully employed in the discrimination of surfactants in real environmental waters. More importantly, our findings provided a new avenue in rapid detection of surfactants, rendering a promising technique for environmental monitoring against trace multicontaminants.

Strategies to Promote the Journey of Nanoparticles Against Biofilm-Associated Infections

Biofilm-associated infections are one of the most challenging healthcare threats for humans, accounting for 80% of bacterial infections, leading to persistent and chronic infections. The conventional antibiotics still face their dilemma of poor therapeutic effects due to the high tolerance and resistance led by bacterial biofilm barriers. Nanotechnology-based antimicrobials, nanoparticles (NPs), are paid attention extensively and considered as promising alternative. This review focuses on the whole journey of NPs against biofilm-associated infections, and to clarify it clearly, the journey is divided into four processes in sequence as 1) Targeting biofilms, 2) Penetrating biofilm barrier, 3) Attaching to bacterial cells, and 4) Translocating through bacterial cell envelope. Through outlining the compositions and properties of biofilms and bacteria cells, recent advances and present the strategies of each process are comprehensively discussed to combat biofilm-associated infections, as well as the combined strategies against these infections with drug resistance, aiming to guide the rational design and facilitate wide application of NPs in biofilm-associated infections.

Explainable Deep Learning-Assisted Self-Calibrating Colorimetric Patches for In Situ Sweat Analysis

Sweat has emerged as a compelling analyte for noninvasive biosensing technology because it contains a wealth of important biomarkers in hormones, organic biomacromolecules, and various ionic mixtures. These components offer valuable insights and can reflect an individual's physiological conditions. Here, we introduced an explainable deep learning (DL)-assisted wearable self-calibrating colorimetric biosensing analysis platform to efficiently and precisely detect the biomarker's concentration in sweat. Specifically, we have integrated the advantages of the colorimetric sensing method, adsorbing-swelling hydrogel, and explainable DL algorithms to develop an enzyme/indicator-immobilized colorimetric patch, which has reliable colorimetric sensing ability and excellent adsorbing-swelling function. A total of 5625 colorimetric images were collected as the analysis data set and assessed two DL algorithms and seven machine learning (ML) algorithms. Zn2+, glucose, and Ca2+ in human sweats could be facilely classified and quantified with 100% accuracy via the convolutional neural network (CNN) model, and the testing results of actual sweats via the DL-assisted colorimetric approach are 91.7-97.2% matching with the classical UV-vis spectrum. Class activation mapping (CAM) was utilized to visualize the inner working mechanism of CNN operation, which contributes to verify and explicate the design rationality of the noninvasive biosensing technology. An "end-to-end" model was established to ascertain the black box of the DL algorithm, promoted software design or principium optimization, and contributed facile indicators for health monitoring, disease prevention, and clinical diagnosis.

Cutting-Edge Research in Nanoscience and Nanotechnology: Celebrating the 130th Anniversary of Wuhan University

Thanks to the fast-paced progress of microscopic theories and nanotechnologies, a tremendous world of fundamental science and applications has opened up at the nanoscale. Ranging from quantum physics to chemical and biological mechanisms and from device functionality to materials engineering, nanoresearch has become an essential part of various fields. As one of the top universities in China, Wuhan University (WHU) aims to promote cutting-edge nanoresearch in multiple disciplines by leveraging comprehensive academic programs established throughout 130 years of history. As visible in prestigious scientific journals such as ACS Nano, WHU has made impactful advancements in various frontiers, including nanophotonics, functional nanomaterials and devices, biomedical nanomaterials, nanochemistry, and environmental science. In light of these contributions, WHU will be committed to serving talents and scientists wholeheartedly, fully supporting international collaborations and continuously driving innovative research.

Overview of the effects and mechanisms of NO and its donors on biofilms

Microbial biofilm is undoubtedly a challenging problem in the food industry. It is closely associated with human health and life, being difficult to remove and antibiotic resistance. Therefore, an alternate method to solve these problems is needed. Nitric oxide (NO) as an antimicrobial agent, has shown great potential to disrupt biofilms. However, the extremely short half-life of NO in vivo (2 s) has facilitated the development of relatively more stable NO donors. Recent studies reported that NO could permeate biofilms, causing damage to cellular biomacromolecules, inducing biofilm dispersion by quorum sensing (QS) pathway and reducing intracellular bis-(3'-5')-cyclic dimeric guanosine monophosphate (c-di-GMP) levels, and significantly improving the bactericidal effect without drug resistance. In this review, biofilm hazards and formation processes are presented, and the characteristics and inhibitory effects of NO donors are carefully discussed, with an emphasis on the possible mechanisms of NO resistance to biofilms and some advanced approaches concerning the remediation of NO donor deficiencies. Moreover, the future perspectives, challenges, and limitations of NO donors were summarized comprehensively. On the whole, this review aims to provide the application prospects of NO and its donors in the food industry and to make reliable choices based on these available research results.

A review on machine learning-powered fluorescent and colorimetric sensor arrays for bacteria identification

Biosensors have been widely used for bacteria determination with great success. However, the "lock-and-key" methodology used by biosensors to identify bacteria has a significant limitation: it can only detect one species of bacteria. In recent years, optical (fluorescent and colorimetric) sensor arrays are gradually gaining attention from researchers as a new type of biosensor. They can acquire multiple features of a target simultaneously, form a feature pattern, and determine the bacteria species with the help of pattern recognition/machine learning algorithms. Previous reviews in this area have focused on the interaction between the sensor array and bacteria or the materials used to make the sensors. This review, on the other hand, will provide researchers with a better understanding of the field by discussing fluorescent and colorimetric sensor arrays based on the mechanism of optical signal generation. These sensor arrays will be compared based on the identified species. Finally, we will discuss the limitations of these sensor arrays and explore possible solutions.

Consolidated knowledge-guided computational pipeline for therapeutic intervention against bacterial biofilms - a review

Biofilm-associated bacterial infections attributed to multifactorial antimicrobial resistance have caused worldwide challenges in formulating successful treatment strategies. In search of accelerated yet cost-effective therapeutics, several researchers have opted for bioinformatics-based protocols to systemize targeted therapies against biofilm-producing strains. The present review investigated the up-to-date computational databases and servers dedicated to anti-biofilm research to design/screen novel biofilm inhibitors (antimicrobial peptides/phytocompounds/synthetic compounds) and predict their biofilm-inhibition efficacy. Scrutinizing the contemporary in silico methods, a consolidated approach has been highlighted, referred to as a knowledge-guided computational pipeline for biofilm-targeted therapy. The proposed pipeline has amalgamated prominently employed methodologies in genomics, transcriptomics, interactomics and proteomics to identify potential target proteins and their complementary anti-biofilm compounds for effective functional inhibition of biofilm-linked pathways. This review can pave the way for new portals to formulate successful therapeutic interventions against biofilm-producing pathogens.

Advancing understanding of microbial biofilms through machine learning-powered studies

Microbial biofilms are prevalent in various environments and pose significant challenges to food safety and public health. The biofilms formed by pathogens can cause food spoilage, foodborne illness, and infectious diseases, which are difficult to treat due to their enhanced antimicrobial resistance. While the composition and development of biofilms have been widely studied, their profound impact on food, the food industry, and public health has not been sufficiently recapitulated. This review aims to provide a comprehensive overview of microbial biofilms in the food industry and their implication on public health. It highlights the existence of biofilms along the food-producing chains and the underlying mechanisms of biofilm-associated diseases. Furthermore, this review thoroughly summarizes the enhanced understanding of microbial biofilms achieved through machine learning approaches in biofilm research. By consolidating existing knowledge, this review intends to facilitate developing effective strategies to combat biofilm-associated infections in both the food industry and public health.

Spatiotemporally Responsive Hydrogel Dressing with Self-Adaptive Antibacterial Activity and Cell Compatibility for Wound Sealing and Healing

Adhesive hydrogels containing quaternary ammonium salt (QAS) moieties have shown attractive advantages in treatment for acute wounds, attributed to their high performances in wound sealing and sterilization. However, the introduction of QAS commonly leads to high cytotoxicity and adhesive deterioration. Herein, aimed to solve these two issues, a self-adaptive dressing with delicate spatiotemporal responsiveness is developed by employing cellulose sulfate (CS) as dynamic layers to coat QAS-based hydrogel. In detail, due to the acid environment of wound in the early stages of healing, the CS coating will quickly detach to expose the active QAS groups for maximum disinfectant efficacy; meanwhile, as the wound gradually heals and recovers to a neutral pH, the CS will remain stable to keep QAS screened, realizing a high cell growth-promoting activity for epithelium regeneration. Additionally, attributed to the synergy of temporary hydrophobicity by CS and slow water absorption kinetics of the hydrogel, the resultant dressing possesses outstanding wound sealing and hemostasis performance. At last, this work anticipates this approach to intelligent wound dressings based on dynamic and responsive intermolecular interaction can also be applied to a wide range of self-adaptive biomedical materials employing different chemistries for applications in medical therapy and health monitoring.

Nonstoichiometric Nanocubes with a Controllable Morphology and Persistent Luminescence for Autofluorescence-Free Biosensing

Persistent luminescence nanoparticles (PLNPs) have shown special advantages in areas such as bioimaging, cancer therapy, stress sensing, and photo-biocatalysis. However, the lack of methods for controllable synthesis of PLNPs with uniform morphologies and strong persistent luminescence has seriously hindered the applications of PLNPs. Herein, we reported that modifying the electronic structures of zinc gallogermanate (ZGGO) PLNPs by nonstoichiometric reactions can produce highly uniform nanocubes with controllable size and persistent luminescence. By nonstoichiometric increase of the Ge/Ga ratio in ZGGO, the ZGGO PLNPs were transformed from a mixture of nanocubes and small nanospheres into highly symmetrical and uniform large nanocubes, accompanied by the enhancement of persistent luminescence intensity by about 3.7 times. Moreover, we found that ZGGO PLNPs were responsive to reactive oxygen species (ROS), that is, the persistent luminescence of ZGGO can be quenched by ROS. Autofluorescence-free serum ROS detection was achieved with the developed PLNPs. Further, a biosensing assay for glucose oxidase (GOx) was designed based on the responsiveness of ZGGO PLNPs to H2O2. This study may pave a new way for better control of PLNPs' size, morphology, and persistent luminescence, and it can further promote the applications of PLNPs in areas ranging from theranostics to solar energy utilization.

Biofilm in sino-nasal infectious diseases: the role nasal cytology in the diagnostic work up and therapeutic implications

BACKGROUD

Biofilm formation has been recently recognised as one of the most important etiopathological mechanisms underlying chronic rhinosinusitis (CRS) and its recalcitrance. In this context, nasal cytology (NC) has become an integral part of diagnostic work up of patients suffering from sino-nasal diseases, since it is an easy-to-apply, reproducible and non-invasive diagnostic tool that allows to assess both the nasal inflammatory infiltrate and the presence of biofilms on nasal mucosal surface, further orienting the therapeutic choices in case of infectious diseases for eradicating infections and biofilms. Nevertheless, biofilms are typically resistant to common antibiotic treatments and may trigger or maintain chronic inflammation. Hence, the importance of correctly detecting the presence of biofilm and identifying new effective treatments.

PURPOSE

The aim of this brief review is to better clarify the role of biofilm in the pathogenesis and recurrence of sino-nasal disorders and to highlight the role of nasal cytology (NC) in the rhino-allergologic diagnostic path and in the evaluation of the effectiveness of new treatments.

Thermoresponsive Hydrogel-Enabled Thermostatic Photothermal Therapy for Enhanced Healing of Bacteria-Infected Wounds

Photothermal therapy (PTT) has emerged as an attractive technique for the treatment of bacterial infections. However, the uncontrolled heat generation in conventional PTT inevitably causes thermal damages to healthy tissues and/or organs. It is thus essential to develop a smart and universal strategy to regulate the photothermal equilibrium temperature to a preset safe threshold. Herein, a thermoresponsive hydrogel-enabled thermostatic PTT system for enhanced healing of bacteria-infected wounds is reported. In this system, the near-infrared (NIR)-triggered heat generation by photothermal nanomaterials is spontaneously transferred to a thermoresponsive hydrogel with a lower critical solution temperature (LCST), leading to its rapid phase transition by forming considerable light-scattering centers to block NIR penetration. Such a dynamic and reversible process automatically regulates the photothermal equilibrium temperature to the phase-transition point of the LCST-type hydrogel. In contrast to temperature-uncontrolled conventional PTT with severe thermal damages, the thermoresponsive hydrogel-enabled thermostatic PTT provides effective protection on healthy tissues and/or organs, which remarkably accelerates wound healing by efficient bacterial eradication. This study establishes a smart, simple and universal PTT platform, holding great promise in the safe and efficient treatment of bacterial skin infections.

Biofilms: Formation, Research Models, Potential Targets, and Methods for Prevention and Treatment

Due to the continuous rise in biofilm-related infections, biofilms seriously threaten human health. The formation of biofilms makes conventional antibiotics ineffective and dampens immune clearance. Therefore, it is important to understand the mechanisms of biofilm formation and develop novel strategies to treat biofilms more effectively. This review article begins with an introduction to biofilm formation in various clinical scenarios and their corresponding therapy. Established biofilm models used in research are then summarized. The potential targets which may assist in the development of new strategies for combating biofilms are further discussed. The novel technologies developed recently for the prevention and treatment of biofilms including antimicrobial surface coatings, physical removal of biofilms, development of new antimicrobial molecules, and delivery of antimicrobial agents are subsequently presented. Finally, directions for future studies are pointed out.

A Dual‐Encoded Bead‐Based Immunoassay with Tunable Detection Range for COVID‐19 Serum Evaluation

Serological assay for coronavirus 2019 (COVID‐19) patients including asymptomatic cases can inform on disease progression and prognosis. A detection method taking into account multiplex, high sensitivity, and a wider detection range will help to identify and treat COVID‐19. Here we integrated color‐size dual‐encoded beads and rolling circle amplification (RCA) into a bead‐based fluorescence immunoassay implemented in a size sorting chip to achieve high‐throughput and sensitive detection. We used the assay for quantifying COVID‐19 antibodies against spike S1, nucleocapsid, the receptor binding domain antigens. It also detected inflammatory biomarkers including interleukin‐6, interleukin‐1β, procalcitonin, C‐reactive protein whose concentrations range from pg mL⁻¹ to μg mL⁻¹. Use of different size beads integrating with RCA results in a tunable detection range. The assay can be readily modified to simultaneously measure more COVID‐19 serological molecules differing by orders of magnitude.

Biofilm Microenvironment-Mediated MoS2 Nanoplatform with Its Photothermal/Photodynamic Synergistic Antibacterial Molecular Mechanism and Wound Healing Study

Drug-resistant bacterial infections pose a serious threat to human public health. Biofilm formation is one of the main factors contributing to the development of bacterial resistance, characterized by a hypoxic and microacidic microenvironment. Traditional antibiotic treatments have been ineffective against multidrug-resistant (MDR) bacteria. Novel monotherapies have had little success. On the basis of the photothermal effect, molybdenum disulfide (MoS₂) nanoparticles were used to link quaternized polyethylenimine (QPEI), dihydroporphyrin e6 (Ce6), and Panax notoginseng saponins (PNS) in a zeolitic imidazolate framework-8 (ZIF-8). A multifunctional nanoplatform (MQCP@ZIF-8) was constructed with dual response to pH and near-infrared light (NIR), which resulted in synergistic photothermal and photodynamic antibacterial effects. The nanoplatform exhibited a photothermal conversion efficiency of 56%. It inhibited MDR Escherichia coli (E. coli) and MDR Staphylococcus aureus (S. aureus) by more than 95% and effectively promoted wound healing in mice infected with MDR S. aureus. The nanoplatform induced the death of MDR bacteria by promoting biofilm ablation, disrupting bacterial cell membranes and intracellular DNA, and interfering with intracellular material and energy metabolism. In this study, a multifunctional nanoplatform with good antibacterial effect was developed. The molecular mechanisms of MDR bacteria were also elucidated for possible clinical application.

Simultaneous Optical Detection of Multiple Bacterial Species Using Nanometer-Scaled Metal-Organic Hybrids

This paper describes a simple strategy to identify bacteria using the optical properties of the nanohybrid structures (NHs) of polymer-coated metal nanoparticles (NPs). NHs, in which many small NPs are encapsulated in polyaniline particles, are useful optical labels because they produce strong scattered light. The light-scattering characteristics of NHs are strongly dependent on the constituent metal elements of NPs. Gold NHs (AuNHs), silver NHs (AgNHs), and copper NHs (CuNHs) produce white, reddish, and bluish scattered light, respectively. Moreover, unlike NPs, the color of the scattered light does not change even when NHs are aggregated. Introducing an antibody into NHs induces antigen-specific binding to cells, enabling the identification of bacteria based on light scattering. Multiple bacterial species adsorbed on the slide can be identified within a single field of view under a dark field microscope based on the color of the scattered light. Therefore, it is a useful development for safety risk assessments at manufacturing sites, such as those for foods, beverages, and drugs, and environmental surveys that require rapid detection of multiple bacteria.

Photoluminescent inorganic nanoprobe-based pathogen detection

Pathogens are serious threats to human health, and traditional detection techniques suffer from various limitations. The unique optical properties of photoluminescent inorganic nanomaterials, such as high photoluminescence quantum yields, good photostability, and tunable spectrum, make them ideal tools for the detection of pathogens with high specificity and sensitivity. In this review, the design strategies, working mechanisms, and applications of photoluminescent inorganic nanomaterial-based probes in pathogen detection are introduced. In particular, the design and construction of stimuli-responsive nanoprobes and their potential in these fields are highlighted.