Evaluation of phage-based decontamination in respiratory intensive care unit environments using ddPCR and 16S rRNA targeted sequencing techniques.

Background: Klebsiella pneumoniae is a major cause of hospital-acquired infections (HAIs), primarily spread through environmental contamination in hospitals. The effectiveness of current chemical disinfectants is waning due to emerging resistance, which poses environmental hazards and fosters new resistance in pathogens. Developing environmentally friendly and effective disinfectants against multidrug-resistant organisms is increasingly important. Methods: This study developed a bacteriophage cocktail targeting two common carbapenem-resistant Klebsiella pneumoniae (CRKP) strains, ST11 KL47 and ST11 KL64. The cocktail was used as an adjunctive disinfectant in a hospital's respiratory intensive care unit (RICU) via ultrasonic nebulization. Digital PCR was used to quantify CRKP levels post-intervention. The microbial community composition was analyzed via 16S rRNA sequencing to assess the intervention's impact on overall diversity. Results: The phage cocktail significantly reduced CRKP levels within the first 24 hours post-treatment. While a slight increase in pathogen levels was observed after 24 hours, they remained significantly lower than those treated with conventional disinfectants. 16S rRNA sequencing showed a decrease in the target pathogens' relative abundance, while overall species diversity remained stable, confirming that phages selectively target CRKP without disrupting ecological balance. Discussion: The findings highlight the efficacy and safety of phage-based biocleaners as a sustainable alternative to conventional disinfectants. Phages selectively reduce multidrug-resistant pathogens while preserving microbial diversity, making them a promising tool for infection control.

Neurological complications caused by SARS-CoV-2.

SUMMARYSARS-CoV-2 can not only cause respiratory symptoms but also lead to neurological complications. Research has shown that more than 30% of SARS-CoV-2 patients present neurologic symptoms during COVID-19 (A. Pezzini and A. Padovani, Nat Rev Neurol 16:636-644, 2020, https://doi.org/10.1038/s41582-020-0398-3). Increasing evidence suggests that SARS-CoV-2 can invade both the central nervous system (CNS) (M.S. Xydakis, M.W. Albers, E.H. Holbrook, et al. Lancet Neurol 20: 753-761, 2021 https://doi.org/10.1016/S1474-4422(21)00182-4 ) and the peripheral nervous system (PNS) (M.N. Soares, M. Eggelbusch, E. Naddaf, et al. J Cachexia Sarcopenia Muscle 13:11-22, 2022, https://doi.org/10.1002/jcsm.12896), resulting in a variety of neurological disorders. This review summarized the CNS complications caused by SARS-CoV-2 infection, including encephalopathy, neurodegenerative diseases, and delirium. Additionally, some PNS disorders such as skeletal muscle damage and inflammation, anosmia, smell or taste impairment, myasthenia gravis, Guillain-Barré syndrome, ICU-acquired weakness, and post-acute sequelae of COVID-19 were described. Furthermore, the mechanisms underlying SARS-CoV-2-induced neurological disorders were also discussed, including entering the brain through retrograde neuronal or hematogenous routes, disrupting the normal function of the CNS through cytokine storms, inducing cerebral ischemia or hypoxia, thus leading to neurological complications. Moreover, an overview of long-COVID-19 symptoms is provided, along with some recommendations for care and therapeutic approaches of COVID-19 patients experiencing neurological complications.

One-Tube Nested PCR Coupled with CRISPR-Cas12a for Ultrasensitive Nucleic Acid Testing.

Nucleic acid testing with high sensitivity and specificity is of great importance for accurate disease diagnostics. Here, we developed an in situ one-tube nucleic acid testing assay. In this assay, the target nucleic acid is captured using magnetic silica beads, avoiding an elution step, followed directly by the polymerase chain reaction (PCR) and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas12a detection. This assay achieved visual readout and a sensitivity of 120 copies/mL for detecting SARS-CoV-2. More importantly, the assay demonstrated over 95% sensitivity and 100% specificity compared to the gold standard real-time quantitative PCR (RT-qPCR) test by using 75 SARS-CoV-2 clinical samples. By integrating nested PCR and Cas12a, this all-in-one nucleic acid testing approach enables ultrasensitive, highly specific, and cost-effective diagnosis at community clinics and township hospitals.

Advances in the development of phage-mediated cyanobacterial cell lysis.

Cyanobacteria, the only oxygenic photoautotrophs among prokaryotes, are developing as both carbon building blocks and energetic self-supported chassis for the generation of various bioproducts. However, one of the challenges to optimize it as a more sustainable platform is how to release intracellular bioproducts for an easier downstream biorefinery process. To date, the major method used for cyanobacterial cell lysis is based on mechanical force, which is energy-intensive and economically unsustainable. Phage-mediated bacterial cell lysis is species-specific and highly efficient and can be conducted under mild conditions; therefore, it has been intensively studied as a bacterial cell lysis weapon. In contrast to heterotrophic bacteria, biological cell lysis studies in cyanobacteria are lagging behind. In this study, we reviewed cyanobacterial cell envelope features that could affect cell strength and elicited a thorough presentation of the necessary phage lysin components for efficient cell lysis. We then summarized all bioengineering manipulated pipelines for lysin component optimization and further revealed the challenges for each intent-oriented application in cyanobacterial cell lysis. In addition to applied biotechnology usage, the significance of phage-mediated cyanobacterial cell lysis could also advance sophisticated biochemical studies and promote biocontrol of toxic cyanobacteria blooms.

vB_CacS-HV1 as a Novel Pahexavirus Bacteriophage with Lytic and Anti-Biofilm Potential against Cutibacterium acnes.

Acne vulgaris is a prevalent chronic inflammatory skin disease, most common in adolescence and often persisting into adulthood, leading to severe physical and psychological impacts. The primary etiological factor is Cutibacterium acnes infection. The overuse of antibiotics for acne treatment over recent decades has led to the emergence of antibiotic-resistant Cutibacterium acnes strains. In this study, we isolated and characterized a novel bacteriophage, vB_CacS-HV1, from saliva samples. The average nucleotide identity analysis indicated that vB_CacS-HV1 is a new species within the Pahexavirus genus, enhancing our understanding of this underexplored group. vB_CacS-HV1 demonstrates favorable stability, lacks potentially harmful genetic elements (virulence factors, antibiotic resistance genes, transposons, and integrases), and exhibits potent lytic and anti-biofilm activities against Cutibacterium acnes at low concentrations. These advantages highlight vB_CacS-HV1's potential as a promising antibacterial agent that could possibly be complementary to antibiotics or other treatments for acne therapy.

Efficient Broad-Spectrum Cyanophage Function Module Mining.

Cyanobacterial harmful algal blooms (CyanoHABs) cause health and environmental effects worldwide. Cyanophage is a virus that exclusively infects cyanobacteria. Using cyanophages to control blooms is the latest biological control method. However, little research on the genomics of cyanophages and the presence of numerous proteins with unidentified functions in cyanophage genomes pose challenges for their practical application and comprehensive investigation. We selected the broad-spectrum and efficient cyanophage YongM for our study. On the one hand, through rational analysis, we analyze essential genes, establish the minimal cyanophage genome and single essential gene modules, and examine the impact of essential modules on growth. Additionally, we conducted ultraviolet mutagenesis on YongM to generate more efficient cyanophages' critical modules through random mutagenesis. Then, we sequenced and analyzed the functionality of the mutational gene modules. These findings highlight several gene modules that contribute to a deeper understanding of the functional components within cyanophage genomes.

CRISPR/Cas12a coupled with loop-mediated isothermal amplification and lateral flow assay for SARS-CoV-2 detection.

Point-of-care testing (POCT) is rapid, exhibits highly sensitive performance, can facilitate home self-testing and avoids cross-contamination. Herein, we developed a biosensor that combines Si-OH magnetic bead (MB)-based fast RNA extraction, reverse transcription-loop-mediated isothermal amplification (RT-LAMP), CRISPR-Cas12a, and lateral flow assay (LFA) for rapid detection of SARS-CoV-2 RNA within 1.5 h. In the presence of the SARS-CoV-2 LAMP amplicon, the trans-cleavage activity of Cas12a was activated to cleave the probe, separating streptavidin from the AuNPs-digoxin (Dig) antibody, resulting in the inability of the test line to capture the AuNPs-Dig antibody. The method can distinguish SARS-CoV-2 from other RNA viruses, with a limit-of-detection (LOD) of 6.2 × 102 copies per mL. Therefore, LAMP-CRISPR-LFA has high specificity and sensitivity and is convenient to develop into commercial assay kits, which could have a broad prospect for practical application.

Cyanobacteria-cyanophage interactions between freshwater and marine ecosystems based on large-scale cyanophage genomic analysis.

The disparities in harmful algal blooms dynamics are largely attributed to variations in cyanobacteria populations within aquatic ecosystems. However, cyanobacteria-cyanophage interactions and their role in shaping cyanobacterial populations has been previously underappreciated. To address this knowledge gap, we isolated and sequenced 42 cyanophages from diverse water sources in China, with the majority (n = 35) originating from freshwater sources. We designated these sequences as the "Novel Cyanophage Genome sequence Collection" (NCGC). NCGC displayed notable genetic variations, with 95 % (40/42) of the sequences representing previously unidentified taxonomic ranks. By integrating NCGC with public data of cyanophages and cyanobacteria, we found evidence for more frequent historical cyanobacteria-cyanophage interactions in freshwater ecosystems. This was evidenced by a higher prevalence of prophage integrase-related genes in freshwater cyanophages (37.97 %) than marine cyanophages (7.42 %). In addition, freshwater cyanophages could infect a broader range of cyanobacteria orders (n = 4) than marine ones (n = 0). Correspondingly, freshwater cyanobacteria harbored more defense systems per million base pairs in their genomes, indicating more frequent phage infections. Evolutionary and cyanophage epidemiological studies suggest that interactions between cyanobacteria and cyanophages in freshwater and marine ecosystems are interconnected, and that brackish water can act as a transitional zone for freshwater and marine cyanophages. In conclusion, our research significantly expands the genetic information database of cyanophage, offering a wider selection of cyanophages to control harmful cyanobacterial blooms. Additionally, we represent a pioneering large-scale and comprehensive analysis of cyanobacteria and cyanophage sequencing data, and it provides theoretical guidance for the application of cyanophages in different environments.

Mining the Biosynthetic Landscape of Lactic Acid Bacteria Unearths a New Family of RiPPs Assembled by a Novel Type of ThiF-like Adenylyltransferases.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are chemically diverse natural products of ribosomal origin. These peptides, which frequently act as signals or antimicrobials, are biosynthesized by conserved enzymatic machinery, making genome mining a powerful strategy for unearthing previously uncharacterized members of their class. Herein, we investigate the untapped biosynthetic potential of Lactobacillales (i.e., lactic acid bacteria), an order of Gram-positive bacteria closely associated with human life, including pathogenic species and industrially relevant fermenters of dairy products. Through genome mining methods, we systematically explored the distribution and diversity of ThiF-like adenylyltransferase-utilizing RiPP systems in lactic acid bacteria and identified a number of unprecedented biosynthetic gene clusters. In one of these clusters, we found a previously undescribed group of macrocyclic imide biosynthetic pathways containing multiple transporters that may be involved in a potential quorum sensing (QS) system. Through in vitro assays, we determined that one such adenylyltransferase specifically catalyzes the intracyclization of its precursor peptide through macrocyclic imide formation. Incubating the enzyme with various primary amines revealed that it could effectively amidate the C-terminus of the precursor peptide. This new transformation adds to the growing list of Nature's peptide macrocyclization strategies and expands the impressive catalytic repertoire of the adenylyltransferase family. The diverse RiPP systems identified herein represent a vast, unexploited landscape for the discovery of a novel class of natural products and QS systems.

Cold atmospheric plasma can effectively disinfect SARS-CoV-2 in the wastewater.

COVID-19 is currently pandemic and the detection of SARS-CoV-2 variants in wastewater is causing widespread concern. Herein, cold atmospheric plasma (CAP) is proposed as a novel wastewater disinfection technology that effectively inactivates SARS-CoV-2 transcription- and replication-competent virus-like particles, coronavirus GX_P2V, pseudotyped SARS-CoV-2 variants, and porcine epidemic diarrhoea virus in a large volume of water within 180 s (inhibition rate > 99%). Further, CAP disinfection did not adversely affect the viability of various human cell lines. It is identified that CAP produced peroxynitrite (ONOO-), ozone (O3), superoxide anion radicals (O2 -), and hydrogen peroxide (H2O2) as the major active substances for coronavirus disinfection. Investigation of the mechanism showed that active substances not only reacted with the coronavirus spike protein and affected its infectivity, but also destroyed the nucleocapsid protein and genome, thus affecting virus replication. This method provides an efficient and environmentally friendly strategy for the elimination of SARS-CoV-2 and other coronaviruses from wastewater.

ViroISDC: a method for calling integration sites of hepatitis B virus based on feature encoding.

BACKGROUND: Hepatitis B virus (HBV) integrates into human chromosomes and can lead to genomic instability and hepatocarcinogenesis. Current tools for HBV integration site detection lack accuracy and stability. RESULTS: This study proposes a deep learning-based method, named ViroISDC, for detecting integration sites. ViroISDC generates corresponding grammar rules and encodes the characteristics of the language data to predict integration sites accurately. Compared with Lumpy, Pindel, Seeksv, and SurVirus, ViroISDC exhibits better overall performance and is less sensitive to sequencing depth and integration sequence length, displaying good reliability, stability, and generality. Further downstream analysis of integrated sites detected by ViroISDC reveals the integration patterns and features of HBV. It is observed that HBV integration exhibits specific chromosomal preferences and tends to integrate into cancerous tissue. Moreover, HBV integration frequency was higher in males than females, and high-frequency integration sites were more likely to be present on hepatocarcinogenesis- and anti-cancer-related genes, validating the reliability of the ViroISDC. CONCLUSIONS: ViroISDC pipeline exhibits superior precision, stability, and reliability across various datasets when compared to similar software. It is invaluable in exploring HBV infection in the human body, holding significant implications for the diagnosis, treatment, and prognosis assessment of HCC.

Rapid and highly sensitive colorimetric LAMP assay and integrated device for visual detection of monkeypox virus.

BACKGROUND: The monkeypox virus (MPXV) is a linear double-stranded DNA virus with a large genome that causes tens of thousands of infections and hundreds of deaths in at least 40 countries and regions worldwide. Therefore, timely and accurate diagnostic testing could be an important measure to prevent the ongoing spread of MPXV and widespread epidemics. RESULTS: Here, we designed multiple sets of primers for the target region of MPXV for loop-mediated isothermal amplification (LAMP) detection and identified the optimal primer set. Then, the specificity in fluorescent LAMP detection was verified using the plasmids containing the target gene, pseudovirus and other DNA/RNA viruses. We also evaluated the sensitivity of the colorimetric LAMP detection system using the plasmid and pseudovirus samples, respectively. Besides, we used monkeypox pseudovirus to simulate real samples for detection. Subsequent to the establishment and introduction of a magnetic beads (MBs)-based nucleic acid extraction technique, an integrated device was developed, characterized by rapidity, high sensitivity, and remarkable specificity. This portable system demonstrated a visual detection limit of 137 copies/mL, achieving sample-to-answer detection within 1 h. SIGNIFICANCE: The device has the advantages of integration, simplicity, miniaturization, and visualization, which help promote the realization of accurate, rapid, portable, and low-cost testing. Meanwhile, this platform could facilitate efficient, cost-effective and easy-operable point-of-care testing (POCT) in diverse resource-limited settings in addition to the laboratory.

A benchmark for evaluation of structure-based online tools for antibody-antigen binding affinity.

The prediction of binding affinity changes caused by missense mutations can elucidate antigen-antibody interactions. A few accessible structure-based online computational tools have been proposed. However, selecting suitable software for particular research is challenging, especially research on the SARS-CoV-2 spike protein with antibodies. Therefore, benchmarking of the mutation-diverse SARS-CoV-2 datasets is critical. Here, we collected the datasets including 1216 variants about the changes in binding affinity of antigens from 22 complexes for SARS-CoV-2 S proteins and 22 monoclonal antibodies as well as applied them to evaluate the performance of seven binding affinity prediction tools. The tested tools' Pearson correlations between predicted and measured changes in binding affinity were between -0.158 and 0.657, while accuracy in classification tasks on predicting increasing or decreasing affinity ranged from 0.444 to 0.834. These tools performed relatively better on predicting single mutations, especially at epitope sites, whereas poor performance on extremely decreasing affinity. The tested tools were relatively insensitive to the experimental techniques used to obtain structures of complexes. In summary, we constructed a list of datasets and evaluated a range of structure-based online prediction tools that will explicate relevant processes of antigen-antibody interactions and enhance the computational design of therapeutic monoclonal antibodies.

A Metagenomic Investigation of Potential Health Risks and Element Cycling Functions of Bacteria and Viruses in Wastewater Treatment Plants.

The concentration of viruses in sewage sludge is significantly higher (10-1000-fold) than that found in natural environments, posing a potential risk for human and animal health. However, the composition of these viruses and their role in the transfer of pathogenic factors, as well as their role in the carbon, nitrogen, and phosphorus cycles remain poorly understood. In this study, we employed a shotgun metagenomic approach to investigate the pathogenic bacteria and viral composition and function in two wastewater treatment plants located on a campus. Our analysis revealed the presence of 1334 amplicon sequence variants (ASVs) across six sludge samples, with 242 ASVs (41.22% of total reads) identified as pathogenic bacteria. Arcobacter was found to be the most dominant pathogen accounting for 6.79% of total reads. The virome analysis identified 613 viral genera with Aorunvirus being the most abundant genus at 41.85%. Approximately 0.66% of these viruses were associated with human and animal diseases. More than 60% of the virome consisted of lytic phages. Host prediction analysis revealed that the phages primarily infected Lactobacillus (37.11%), Streptococcus (21.11%), and Staphylococcus (7.11%). Furthermore, our investigation revealed an abundance of auxiliary metabolic genes (AMGs) involved in carbon, nitrogen, and phosphorus cycling within the virome. We also detected a total of 113 antibiotic resistance genes (ARGs), covering major classes of antibiotics across all samples analyzed. Additionally, our findings indicated the presence of virulence factors including the clpP gene accounting for approximately 4.78%, along with toxin genes such as the RecT gene representing approximately 73.48% of all detected virulence factors and toxin genes among all samples analyzed. This study expands our understanding regarding both pathogenic bacteria and viruses present within sewage sludge while providing valuable insights into their ecological functions.

Predicting Natural Evolution in the RBD Region of the Spike Glycoprotein of SARS-CoV-2 by Machine Learning.

Machine learning (ML) is a key focus in predicting protein mutations and aiding directed evolution. Research on potential virus variants is crucial for vaccine development. In this study, the machine learning software PyPEF was employed to conduct mutation analysis within the receptor-binding domain (RBD) of the Spike glycoprotein of SARS-CoV-2. Over 48,960,000 variants were predicted. Eight prospective variants that could surface in the future underwent modeling and molecular dynamics simulations. The study forecasts that the latest variant, ISOY2P5O1, may potentially emerge around 17 November 2023, with an approximate window of uncertainty of ±22 days. The ISOY8P5O2 variant displayed an increased binding capacity in the dry assay, with a total predicted binding energy of -110.306 kcal/mol. This represents an 8.25% enhancement in total binding energy compared to the original SARS-CoV-2 strain discovered in Wuhan (-101.892 kcal/mol). Reverse research confirmed the structural significance of mutation sites using ML models, particularly in the context of protein folding. The study validated regression methods (SVR, RF, and PLS) with different data structures. This study investigates the effectiveness of the "ML-Guided Design Correctly Predicts Combinatorial Effects Strategy" compared to the "ML-Guided Design Correctly Predicts Natural Evolution Prediction Strategy". To enhance machine learning, we created a timestamping algorithm and two auxiliary programs using advanced techniques to rapidly process extensive data, surpassing batch sequencing capabilities. This study not only advances machine learning in guiding protein evolution but also holds potential for forecasting future viruses and vaccine development.

Characterization, taxonomic classification, and genomic analysis of two newly isolated bacteriophages with potential to infect Escherichia coli.

Escherichia coli is a pathogenic bacterium that is widely distributed and can lead to serious illnesses in both humans and animals. As there is rising incidence of multidrug resistance among these bacteria, it has become imperative to discover alternative therapies beyond antibiotics to effectively treat such infections. Bacteriophage (phage) therapy has the potential to treat infections caused by E. coli, as phages contain enzymes that can cause lysis or destruction of bacterial cells. Simultaneously, the easy accessibility and cost-effectiveness of next-generation sequencing technologies have led to the accumulation of a vast amount of phage sequence data. Here, phages IME177 and IME267 were isolated from sewage water of a hospital in China. Modern phylogenetic approaches and key findings from the genomic analysis revealed that phages IME177 and IME267 are classified as members of the Kayfunavirus genus, Autographiviridae family, and a newly proposed Suseptimavirus genus under subfamily Gordonclarkvirinae, respectively. Further, the Kuravirus genus reshaped into three different genera: Kuravirus, Nieuwekanaalvirus, and Suspeptimavirus, which are classified together under a higher taxonomic rank (subfamily) named Gordonclarkvirinae. No genes related to virulence were detected in the genomes of the phages IME177 and IME267. Both phages exhibited a high degree of resilience to a wide range of conditions, including pH, temperature, exposure to chloroform, and UV radiation. Phages IME177 and IME267 are promising biological agents that can infect E. coli, making them suitable candidates for use in phage therapies.IMPORTANCEBiological and taxonomic characterization of phages is essential for facilitating the development of effective strategies for phage therapy and disease control. Escherichia coli phages are incredibly diverse, and their isolation and classification help us understand the scope and nature of this diversity. By identifying new phages and grouping them into families, we can better understand the genetic and structural variations between phages and how they affect their infectivity and interactions with bacteria. Overall, the isolation and classification of E. coli phages have broad implications for both basic and applied research, clinical practice, and public health.

Cepharanthine analogs mining and genomes of Stephania accelerate anti-coronavirus drug discovery.

Cepharanthine is a secondary metabolite isolated from Stephania. It has been reported that it has anti-conronaviruses activities including severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Here, we assemble three Stephania genomes (S. japonica, S. yunnanensis, and S. cepharantha), propose the cepharanthine biosynthetic pathway, and assess the antiviral potential of compounds involved in the pathway. Among the three genomes, S. japonica has a near telomere-to-telomere assembly with one remaining gap, and S. cepharantha and S. yunnanensis have chromosome-level assemblies. Following by biosynthetic gene mining and metabolomics analysis, we identify seven cepharanthine analogs that have broad-spectrum anti-coronavirus activities, including SARS-CoV-2, Guangxi pangolin-CoV (GX_P2V), swine acute diarrhoea syndrome coronavirus (SADS-CoV), and porcine epidemic diarrhea virus (PEDV). We also show that two other genera, Nelumbo and Thalictrum, can produce cepharanthine analogs, and thus have the potential for antiviral compound discovery. Results generated from this study could accelerate broad-spectrum anti-coronavirus drug discovery.

Characterization of phage evolution and phage resistance in drug-resistant Stenotrophomonas maltophilia.

Phage therapy has become a viable antimicrobial treatment as an alternative to antibiotic treatment, with an increase in antibiotic resistance. Phage resistance is a major limitation in the therapeutic application of phages, and the lack of understanding of the dynamic changes between bacteria and phages constrains our response strategies to phage resistance. In this study, we investigated the changing trends of mutual resistance between Stenotrophomonas maltophilia (S. maltophilia) and its lytic phage, BUCT603. Our results revealed that S. maltophilia resisted phage infection through mutations in the cell membrane proteins, while the evolved phage re-infected the resistant strain primarily through mutations in structure-related proteins. Compared with the wild-type strain (SMA118), the evolved phage-resistant strain (R118-2) showed reduced virulence, weakened biofilm formation ability, and reduced resistance to aminoglycosides. In addition, the evolved phage BUCT603B1 in combination with kanamycin could inhibit the development of phage-resistant S. maltophilia in vitro and significantly improve the survival rate of S. maltophilia-infected mice. Altogether, these results suggest that in vitro characterization of bacteria-phage co-evolutionary relationships is a useful research tool to optimize phages for the treatment of drug-resistant bacterial infections.IMPORTANCEPhage therapy is a promising approach to treat infections caused by drug-resistant Stenotrophomonas maltophilia (S. maltophilia). However, the rapid development of phage resistance has hindered the therapeutic application of phages. In vitro evolutionary studies of bacteria-phage co-cultures can elucidate the mechanism of resistance development between phage and its host. In this study, we investigated the resistance trends between S. maltophilia and its phage and found that inhibition of phage adsorption is the primary strategy by which bacteria resist phage infection in vitro, while phages can re-infect bacterial cells by identifying other adsorption receptors. Although the final bacterial mutants were no longer infected by phages, they incurred a fitness cost that resulted in a significant reduction in virulence. In addition, the combination treatment with phage and aminoglycoside antibiotics could prevent the development of phage resistance in S. maltophilia in vitro. These findings contribute to increasing the understanding of the co-evolutionary relationships between phages and S. maltophilia.

Advances in anti-EV-A71 drug development research.

BACKGROUND: Enterovirus A71 (EV-A71) is capable of causing hand, foot and mouth disease (HFMD), which may lead to neurological sequelae and even death. As EV-A71 is resistant to environmental changes and mutates easily, there is still a lack of effective treatments or globally available vaccines. AIM OF REVIEW: For more than 50 years since the HFMD epidemic, related drug research has been conducted. Progress in this area can promote the further application of existing potential drugs and develop more efficient and safe antiviral drugs, and provide useful reference for protecting the younger generation and maintaining public health security. KEY SCIENTIFIC CONCEPTS OF REVIEW: At present, researchers have identified hundreds of EV-A71 inhibitors based on screening repurposed drugs, targeted structural design, and rational modification of previously effective drugs as the main development strategies. This review systematically introduces the current potential drugs to inhibit EV-A71 infection, including viral inhibitors targeting key sites such as the viral capsid, RNA-dependent RNA polymerase (RdRp), 2C protein, internal ribosome entry site (IRES), 3C proteinase (3Cpro), and 2A proteinase (2Apro), starting from each stage of the viral life cycle. Meanwhile, the progress of host-targeting antiviral drugs and their development are summarized in terms of regulating host immunity, inhibiting autophagy or apoptosis, and regulating the cellular redox environment. In addition, the current clinical methods for the prevention and treatment of HFMD are summarized and discussed with the aim of providing support and recommendations for the treatment of enterovirus infections including EV-A71.