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332200.9980Combined analysis of metagenomic data revealed consistent changes of gut microbiome structure and function in inflammatory bowel disease. AIMS: To reveal the consistency and discrepancy in the gut microbial structure and function in inflammatory bowel disease (IBD) patients from different regions. METHODS AND RESULTS: Gut microbes, antibiotic resistance genes (ARGs) and virulence factors genes (VFGs) were analysed using metagenome data from three cohorts. The abundance of Escherichia coli extensively increased in IBD patients, whereas Subdoligranulum unclassified decreased dramatically in IBD patients from three countries. Escherichia coli showed a positive correlation with multiple ARGs and VFGs in cohorts from China and the United States, including multidrug-related resistance genes and Capsule and LOS-related virulence factors genes. Escherichia coli biofilm synthesis pathways significantly enriched in IBD patients from three different regions. Notably, Subdoligranulum unclassified and Eubacterium hallii were negatively related to ARGs and VFGs. CONCLUSIONS: Consistent changes of microbiome structure and function were observed in IBD patients from three different regions. As pathogenic bacteria, E. coli may accelerate IBD progression through encapsulation in biofilms by upregulating antibiotic resistance in Crohn's disease patients. Subdoligranulum unclassified and E. hallii may be beneficial for IBD patients and could serve as potential probiotics for IBD treatment. SIGNIFICANCE AND IMPACT OF THE STUDY: This work dispels worries about the regional differences in gut microbial changes in IBD patients and provides useful guidance for more rational microbiome-based therapies.202134008889
510010.9980DeepPBI-KG: a deep learning method for the prediction of phage-bacteria interactions based on key genes. Phages, the natural predators of bacteria, were discovered more than 100 years ago. However, increasing antimicrobial resistance rates have revitalized phage research. Methods that are more time-consuming and efficient than wet-laboratory experiments are needed to help screen phages quickly for therapeutic use. Traditional computational methods usually ignore the fact that phage-bacteria interactions are achieved by key genes and proteins. Methods for intraspecific prediction are rare since almost all existing methods consider only interactions at the species and genus levels. Moreover, most strains in existing databases contain only partial genome information because whole-genome information for species is difficult to obtain. Here, we propose a new approach for interaction prediction by constructing new features from key genes and proteins via the application of K-means sampling to select high-quality negative samples for prediction. Finally, we develop DeepPBI-KG, a corresponding prediction tool based on feature selection and a deep neural network. The results show that the average area under the curve for prediction reached 0.93 for each strain, and the overall AUC and area under the precision-recall curve reached 0.89 and 0.92, respectively, on the independent test set; these values are greater than those of other existing prediction tools. The forward and reverse validation results indicate that key genes and key proteins regulate and influence the interaction, which supports the reliability of the model. In addition, intraspecific prediction experiments based on Klebsiella pneumoniae data demonstrate the potential applicability of DeepPBI-KG for intraspecific prediction. In summary, the feature engineering and interaction prediction approaches proposed in this study can effectively improve the robustness and stability of interaction prediction, can achieve high generalizability, and may provide new directions and insights for rapid phage screening for therapy.202439344712
878920.9980Herbivore Oral Secreted Bacteria Trigger Distinct Defense Responses in Preferred and Non-Preferred Host Plants. Insect symbiotic bacteria affect host physiology and mediate plant-insect interactions, yet there are few clear examples of symbiotic bacteria regulating defense responses in different host plants. We hypothesized that plants would induce distinct defense responses to herbivore- associated bacteria. We evaluated whether preferred hosts (horsenettle) or non-preferred hosts (tomato) respond similarly to oral secretions (OS) from the false potato beetle (FPB, Leptinotarsa juncta), and whether the induced defense triggered by OS was due to the presence of symbiotic bacteria in OS. Both horsenettle and tomato damaged by antibiotic (AB) treated larvae showed higher polyphenol oxidase (PPO) activity than those damaged by non-AB treated larvae. In addition, application of OS from AB treated larvae induced higher PPO activity compared with OS from non-AB treated larvae or water treatment. False potato beetles harbor bacteria that may provide abundant cues that can be recognized by plants and thus mediate corresponding defense responses. Among all tested bacterial isolates, the genera Pantoea, Acinetobacter, Enterobacter, and Serratia were found to suppress PPO activity in tomato, while only Pantoea sp. among these four isolates was observed to suppress PPO activity in horsenettle. The distinct PPO suppression caused by symbiotic bacteria in different plants was similar to the pattern of induced defense-related gene expression. Pantoea inoculated FPB suppressed JA-responsive genes and triggered a SA-responsive gene in both tomato and horsenettle. However, Enterobacter inoculated FPB eliminated JA-regulated gene expression and elevated SA-regulated gene expression in tomato, but did not show evident effects on the expression levels of horsenettle defense-related genes. These results indicate that suppression of plant defenses by the bacteria found in the oral secretions of herbivores may be a more widespread phenomenon than previously indicated.201627294415
883830.9979Dual RNA-seq analysis reveals the interaction between multidrug-resistant Klebsiella pneumoniae and host in a mouse model of pneumonia. BACKGROUND: Multidrug-resistant Klebsiella pneumoniae (MDR-KP) poses a significant global health threat, associated with high morbidity and mortality rates among hospitalized patients. The interaction between MDR-KP and its host is highly complex, and few studies have investigated these interactions from both the pathogen and host perspectives. Here, we explored these interactions in a mouse model of pneumonia using dual RNA-seq analysis. METHODS: PCR identification and antimicrobial susceptibility test were employed to screen for MDR-KP strains. A mouse model of pneumonia was established through aerosolized intratracheal inoculation with high-dose or low-dose bacteria. Bacterial loads, pathological changes, inflammatory cytokine expression, and immune cell infiltration were assessed post-challenge. Dual RNA-seq analysis was conducted on lung tissues following infection. RESULTS: NY13307 was identified as an MDR-KP strain with minimal virulence factor genes and broad-spectrum drug resistance. High-dose bacteria induced more severe pulmonary pathological changes, a significant increase in bacterial load, and notably elevated secretion of inflammatory cytokines compared to low-dose bacteria. Alveolar macrophages and resident interstitial macrophages were identified as the primary sources of these cytokines. Further RNA-seq analysis revealed that, compared to the low-dose group, the high-dose group significantly upregulated hypoxia and pro-inflammatory cytokine-related genes in the host, and siderophore-related genes in the bacteria. Correlation analysis demonstrated a significant association between siderophore-related genes and clusters of genes related to pro-inflammatory cytokines and hypoxia. CONCLUSIONS: In this mouse model of bacterial pneumonia, excessive siderophore expression may trigger the activation of hypoxia signaling pathways and the release of pro-inflammatory cytokines, ultimately reducing survival rates.202540702458
464240.9979Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection. BACKGROUND: The abundance and diversity of antibiotic resistance genes (ARGs) in the human respiratory microbiome remain poorly characterized. In the context of influenza virus infection, interactions between the virus, the host, and resident bacteria with pathogenic potential are known to complicate and worsen disease, resulting in coinfection and increased morbidity and mortality of infected individuals. When pathogenic bacteria acquire antibiotic resistance, they are more difficult to treat and of global health concern. Characterization of ARG expression in the upper respiratory tract could help better understand the role antibiotic resistance plays in the pathogenesis of influenza-associated bacterial secondary infection. RESULTS: Thirty-seven individuals participating in the Household Influenza Transmission Study (HITS) in Managua, Nicaragua, were selected for this study. We performed metatranscriptomics and 16S rRNA gene sequencing analyses on nasal and throat swab samples, and host transcriptome profiling on blood samples. Individuals clustered into two groups based on their microbial gene expression profiles, with several microbial pathways enriched with genes differentially expressed between groups. We also analyzed antibiotic resistance gene expression and determined that approximately 25% of the sequence reads that corresponded to antibiotic resistance genes mapped to Streptococcus pneumoniae and Staphylococcus aureus. Following construction of an integrated network of ARG expression with host gene co-expression, we identified several host key regulators involved in the host response to influenza virus and bacterial infections, and host gene pathways associated with specific antibiotic resistance genes. CONCLUSIONS: This study indicates the host response to influenza infection could indirectly affect antibiotic resistance gene expression in the respiratory tract by impacting the microbial community structure and overall microbial gene expression. Interactions between the host systemic responses to influenza infection and antibiotic resistance gene expression highlight the importance of viral-bacterial co-infection in acute respiratory infections like influenza. Video abstract.202032178738
770350.9979The impact of antibiotic exposure on antibiotic resistance gene dynamics in the gut microbiota of inflammatory bowel disease patients. BACKGROUND: While antibiotics are commonly used to treat inflammatory bowel disease (IBD), their widespread application can disturb the gut microbiota and foster the emergence and spread of antibiotic resistance. However, the dynamic changes to the human gut microbiota and direction of resistance gene transmission under antibiotic effects have not been clearly elucidated. METHODS: Based on the Human Microbiome Project, a total of 90 fecal samples were collected from 30 IBD patients before, during and after antibiotic treatment. Through the analysis workflow of metagenomics, we described the dynamic process of changes in bacterial communities and resistance genes pre-treatment, during and post-treatment. We explored potential consistent relationships between gut microbiota and resistance genes, and established gene transmission networks among species before and after antibiotic use. RESULTS: Exposure to antibiotics can induce alterations in the composition of the gut microbiota in IBD patients, particularly a reduction in probiotics, which gradually recovers to a new steady state after cessation of antibiotics. Network analyses revealed intra-phylum transfers of resistance genes, predominantly between taxonomically close organisms. Specific resistance genes showed increased prevalence and inter-species mobility after antibiotic cessation. CONCLUSION: This study demonstrates that antibiotics shape the gut resistome through selective enrichment and promotion of horizontal gene transfer. The findings provide insights into ecological processes governing resistance gene dynamics and dissemination upon antibiotic perturbation of the microbiota. Optimizing antibiotic usage may help limit unintended consequences like increased resistance in gut bacteria during IBD management.202438694799
629060.9978Transcriptomic profiling of ceftriaxone-tolerant phenotypes of Neisseria gonorrhoeae reveals downregulation of ribosomal genes - a pilot study. Antibiotic tolerance is associated with failure of antibiotic treatment and accelerates the development of antimicrobial resistance. The molecular mechanisms underlying antimicrobial tolerance remain poorly understood. Tolerant bacteria can slow metabolism by extending the lag phase without altering antimicrobial susceptibility. We recently induced ceftriaxone (CRO) tolerance in the Neisseria gonorrhoeae reference strain WHO P. In the current study, we characterized the transcriptomic profiles of these CRO-tolerant phenotypes. To induce tolerance, WHO P strains were grown under 3-h intermittent CRO exposure (10× the MIC), followed by overnight growth in gonococcal (GC) broth for seven consecutive days, with cultures maintained in sextuplicate. Two control cultures were maintained without CRO exposure. The tolerance and CRO susceptibility of the isolates were assessed using a modified tolerance disc (TD) test. Total RNA was isolated from tolerant isolates (n = 12) and control (n = 3) strains, followed by Ribo depletion, Illumina Library preparation, and sequencing. Transcriptomic analysis revealed no differentially expressed genes after 1 day of CRO exposure. However, after 3 days of CRO exposure, 13 genes were found to be significantly downregulated, including tRNA-Ser (C7S06_RS03100) and tRNA-Leu (C7S06_RS04945) and ribosomal RNA genes (16S and 23S rRNA). Following 7 days of exposure, 51 genes were differentially expressed, with most downregulated, such as SecB (Protein-export chaperone SecB) and tRNA-Ser (C7S06_RS01850) and the 16S and 23S ribosomal RNA genes. The development of CRO-tolerance in N. gonorrhoeae was associated with the downregulation of various ribosomal genes and associated genes, reflecting a potential mechanism for bacterial survival under antibiotic stress. IMPORTANCE: Antibiotic tolerance allows some bacteria to survive antibiotic treatment, contributing to treatment failure and creating conditions that promote resistance. In this study, we showed that Neisseria gonorrhoeae, the bacteria that causes gonorrhea, can become tolerant to ceftriaxone-the last-line treatment used. By repeatedly exposing the bacteria to high doses of ceftriaxone, we observed the development of tolerance over several days. Using transcriptomic analysis, we found that tolerant bacteria consistently reduced the activity of genes involved in protein synthesis, including ribosomal RNAs and transfer RNAs. This suggests that N. gonorrhoeae may survive antibiotic stress by entering a low-metabolic state that makes the antibiotic less effective. These findings highlight a survival mechanism that does not rely on genetic resistance. Understanding this tolerance response is vital for improving current treatment approaches and could inform the development of new strategies to prevent antibiotic failure in gonorrhea and other infections.202540622217
654470.9978A rapid approach with machine learning for quantifying the relative burden of antimicrobial resistance in natural aquatic environments. The massive use and discharge of antibiotics have led to increasing concerns about antimicrobial resistance (AMR) in natural aquatic environments. Since the dose-response mechanisms of pathogens with AMR have not yet been fully understood, and the antibiotic resistance genes and bacteria-related data collection via field sampling and laboratory testing is time-consuming and expensive, designing a rapid approach to quantify the burden of AMR in the natural aquatic environment has become a challenge. To cope with such a challenge, a new approach involving an integrated machine-learning framework was developed by investigating the associations between the relative burden of AMR and easily accessible variables (i.e., relevant environmental variables and adjacent land-use patterns). The results, based on a real-world case analysis, demonstrate that the quantification speed has been reduced from 3-7 days, which is typical for traditional measurement procedures with field sampling and laboratory testing, to approximately 0.5 hours using the new approach. Moreover, all five metrics for AMR relative burden quantification exceed the threshold level of 85%, with F1-score surpassing 0.92. Compared to logistic regression, decision trees, and basic random forest, the adaptive random forest model within the framework significantly improves quantification accuracy without sacrificing model interpretability. Two environmental variables, dissolved oxygen and resistivity, along with the proportion of green areas were identified as three key feature variables for the rapid quantification. This study contributes to the enrichment of burden analyses and management practices for rapid quantification of the relative burden of AMR without dose-response information.202439047454
960380.9978Resistance signatures manifested in early drug response across cancer types and species. Aim: Growing evidence points to non-genetic mechanisms underlying long-term resistance to cancer therapies. These mechanisms involve pre-existing or therapy-induced transcriptional cell states that confer resistance. However, the relationship between early transcriptional responses to treatment and the eventual emergence of resistant states remains poorly understood. Furthermore, it is unclear whether such early resistance-associated transcriptional responses are evolutionarily conserved. In this study, we examine the similarity between early transcriptional responses and long-term resistant states, assess their clinical relevance, and explore their evolutionary conservation across species. Methods: We integrated datasets on early drug responses and long-term resistance from multiple cancer cell lines, bacteria, and yeast to identify early transcriptional changes predictive of long-term resistance and assess their evolutionary conservation. Using genome-wide CRISPR-Cas9 knockout screens, we evaluated the impact of genes associated with resistant transcriptional states on drug sensitivity. Clinical datasets were analyzed to explore the prognostic value of the identified resistance-associated gene signatures. Results: We found that transcriptional states observed in drug-naive cells and shortly after treatment overlapped with those seen in fully resistant populations. Some of these shared features appear to be evolutionarily conserved. Knockout of genes marking resistant states sensitized ovarian cancer cells to Prexasertib. Moreover, early resistance gene signatures effectively distinguished therapy responders from non-responders in multiple clinical cancer trials and differentiated premalignant breast lesions that progressed to malignancy from those that remained benign. Conclusion: Early cellular transcriptional responses to therapy exhibit key similarities to fully resistant states across different drugs, cancer types, and species. Gene signatures defining these early resistance states have prognostic value in clinical settings.202541019980
841290.9978Transcriptomic profiling analysis of tilapia (Oreochromis niloticus) following Streptococcus agalactiae challenge. Innate immune system is the primary defense mechanism against pathogen infection in teleost, which are living in pathogen-rich aquatic environment. It has been long hypothesized that the disease resistance in teleost are strongly correlated to the activities of innate immune genes. Tilapia is an important economical fish around the world, especially in China, where the production accounts for nearly half of the global production. Recently, S. agalactiae has become one of the most serious bacterial diseases in southern China, resulted in high cumulative mortality and economic loss to tilapia industry. Therefore, we sought here to characterize the expression profiles of tilapia against S. agalactiae infection at whole transcriptome level by RNA-seq technology. A total of 2822 genes were revealed significantly expressed in tilapia spleen with a general trend of induction. Notably, most of the genes were rapidly the most induced at the early timepoint. The significantly changed genes highlighted the function of pathogen attachment and recognition, antioxidant/apoptosis, cytoskeletal rearrangement, and immune activation. Collectively, the induced expression patterns suggested the strong ability of tilapia to rapidly recognize the invasive bacteria, and activation of downstream immune signaling pathways to clear the bacteria and prevent the tissue damage and bacteria triggered cell apoptosis. Our results heighted important roles of novel candidate genes which were often missed in previous tilapia studies. Further studies are needed to characterize the molecular relationships between key immune genes and disease resistance, and to identify the candidate genes for molecular-assistant selection of disease-resistant broodstock and evaluation of disease prevention and treatment measures.201728111359
2541100.9978Increased antibiotic resistance in preterm neonates under early antibiotic use. The standard use of antibiotics in newborns to empirically treat early-onset sepsis can adversely affect the neonatal gut microbiome, with potential long-term health impacts. Research into the escalating issue of antimicrobial resistance in preterm infants and antibiotic practices in neonatal intensive care units is limited. A deeper understanding of the effects of early antibiotic intervention on antibiotic resistance in preterm infants is crucial. This retrospective study employed metagenomic sequencing to evaluate antibiotic resistance genes (ARGs) in the meconium and subsequent stool samples of preterm infants enrolled in the Routine Early Antibiotic Use in Symptomatic Preterm Neonates study. Microbial metagenomics was conducted using a subset of fecal samples from 30 preterm infants for taxonomic profiling and ARG identification. All preterm infants exhibited ARGs, with 175 unique ARGs identified, predominantly associated with beta-lactam, tetracycline, and aminoglycoside resistance. Notably, 23% of ARGs was found in preterm infants without direct or intrapartum antibiotic exposure. Post-natal antibiotic exposure increases beta-lactam/tetracycline resistance while altering mechanisms that aid bacteria in withstanding antibiotic pressure. Microbial profiling revealed 774 bacterial species, with antibiotic-naive infants showing higher alpha diversity (P = 0.005) in their microbiota and resistome compared with treated infants, suggesting a more complex ecosystem. High ARG prevalence in preterm infants was observed irrespective of direct antibiotic exposure and intensifies with age. Prolonged membrane ruptures and maternal antibiotic use during gestation and delivery are linked to alterations in the preterm infant resistome and microbiome, which are pivotal in shaping the ARG profiles in the neonatal gut.This study is registered with ClinicalTrials.gov as NCT02784821. IMPORTANCE: A high burden of antibiotic resistance in preterm infants poses significant challenges to neonatal health. The presence of antibiotic resistance genes, along with alterations in signaling, energy production, and metabolic mechanisms, complicates treatment strategies for preterm infants, heightening the risk of ineffective therapy and exacerbating outcomes for these vulnerable neonates. Despite not receiving direct antibiotic treatment, preterm infants exhibit a concerning prevalence of antibiotic-resistant bacteria. This underscores the complex interplay of broader influences, including maternal antibiotic exposure during and beyond pregnancy and gestational complications like prolonged membrane ruptures. Urgent action, including cautious antibiotic practices and enhanced antenatal care, is imperative to protect neonatal health and counter the escalating threat of antimicrobial resistance in this vulnerable population.202439373498
8985110.9978High Wolbachia density correlates with cost of infection for insecticide resistant Culex pipiens mosquitoes. In the mosquito Culex pipiens, insecticide resistance genes alter many life-history traits and incur a fitness cost. Resistance to organophosphate insecticides involves two loci, with each locus coding for a different mechanism of resistance (degradation vs. insensitivity to insecticides). The density of intracellular Wolbachia bacteria has been found to be higher in resistant mosquitoes, regardless of the mechanism involved. To discriminate between costs of resistance due to resistance genes from those associated with elevated Wolbachia densities, we compared strains of mosquito sharing the same genetic background but differing in their resistance alleles and Wolbachia infection status. Life-history traits measured included strength of insecticide resistance, larval mortality, adult female size, fecundity, predation avoidance, mating competition, and strength of cytoplasmic incompatibility (CI). We found that: (1) when Wolbachia are removed, insecticide resistance genes still affect some life-history traits; (2) Wolbachia are capable of modifying the cost of resistance; (3) the cost of Wolbachia infections increases with their density; (4) different interactions occurred depending on the resistance alleles involved; and (5) high densities of Wolbachia do not increase the strength of CI or maternal transmission efficiency relative to low Wolbachia densities. Insecticide resistance genes generated variation in the costs of Wolbachia infections and provided an interesting opportunity to study how these costs evolve, a process generally operating when Wolbachia colonizes a new host.200616610322
6291120.9978Adaptive Resistance of Staphylococcus aureus to Cefquinome Sulfate in an In Vitro Pharmacokinetic Model with Transcriptomic Insights. Cefquinome sulfate has a strong killing effect against Staphylococcus aureus (S. aureus), but bacterial resistance has become increasingly widespread. Experiments were conducted to investigate the pattern of adaptive resistance of S. aureus to cefquinome sulfate under different dosage regimens by using pharmacokinetic-pharmacodynamics (PK-PD) modeling, and the adaptive-resistant bacteria in different states were screened and subjected to transcriptomic sequencing. The results showed that the minimum inhibitory concentration of Staphylococcus aureus under the action of cefquinome sulfate was 0.5 μg/mL, the anti-mutation concentration was 1.6 μg/mL, and the mutation selection window range was 0.5~1.6 μg/mL. In the in vitro pharmacokinetic model to simulate different dosing regimens in the animal body, there are certain rules for the emergence of adaptive drug-resistant bacteria: the intensity of bacterial resistance gradually increased with culture time, and the order of emergence was tolerant bacteria (TO) followed by persistent bacteria (PE) and finally resistant bacteria (RE). The sequence reflected the evolution of adaptive drug resistance. Transcriptome Gene Ontology (GO) analysis revealed that differentially expressed genes were involved in cellular respiration, energy derivation by oxidation of organic compounds, and oxidation-reduction processes. The differentially expressed genes identified functioned in the synthesis of cell membranes, cytoplasm, and intracellular parts. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis found that 65 genes were differentially expressed after cefquinome sulfate treatment, of which 35 genes were significantly upregulated and 30 genes were significantly downregulated. Five genes, sdhB, sdhA, pdhA, lpdA, and sucC, may be involved in network regulation. This study revealed the cross-regulation of multiple metabolic pathway networks and the targets of network regulation of S. aureus to produce adaptive drug resistance. The results will provide guidance for clinical drug use in animals infected with S. aureus.202540005696
7676130.9978The intestinal microbial community and function of Riptortus pedestris at different developmental stages and its effects on development. INTRODUCTION: Riptortus pedestris is a destructive pest that threatens multiple leguminous crops in China. The intestinal microbiota plays a crucial role in the growth and reproduction of host insects. However, the composition and function of the gut microbiota at different developmental stages remain unclear. METHODS: Here, metagenomic sequencing was performed to clarify the gut microbial diversity and function in 2nd-, 3rd-, 4th-, and 5th- instar nymphs (2 N-5 N) and female adults (FAs) of R. pedestris and the effects of vital gut bacteria on development was detected. The gut bacteria have the stage specificity, indicating their function in the development of R. pedestris. RESULTS: Enterococcus and Caballerronia were the predominant bacteria present during the development of the 2 N-FAs. In addition, the microbial abundances in the 3 N and 4 N guts were significantly greater than those in the others guts. Furthermore, 5 N harbored the abundant microbiota Burkholderia-Paraburkholderia-Caballeronia. The metabolic pathways were significantly enriched from 2 N to FAs. Carbohydrate metabolism, including glycoside hydrolases (GHs) and glycosyl transferases (GTs), occurs throughout the entire developmental stage. Many antibiotic resistance genes (ARGs) were detected from 2 N to FAs. The bacteria from Pseudomonadota and Bacillota presented a broad spectrum of antibiotic resistance. Excitingly, Burkholderia bacteria eliminated by antibiotic treatment were unable to molt normally, and their lifespan was shortened in nymphs, indicating that the gut microbiota had a significant effect on nymph development. CONCLUSION: In summary, our results, for the first time, systematically illustrate the abundance and function across the gut microbiota from the different developmental stages of R. pedestris and demonstrate that the genera Burkholderia are crucial during the development of R. pedestris. This study provides the basis for stinkbug management strategies that focus on the pivotal gut microbiota.202539935633
9008140.9978Dissolvable alginate hydrogel-based biofilm microreactors for antibiotic susceptibility assays. Biofilms are found in many infections in the forms of surface-adhering aggregates on medical devices, small clumps in tissues, or even in synovial fluid. Although antibiotic resistance genes are studied and monitored in the clinic, the structural and phenotypic changes that take place in biofilms can also lead to significant changes in how bacteria respond to antibiotics. Therefore, it is important to better understand the relationship between biofilm phenotypes and resistance and develop approaches that are compatible with clinical testing. Current methods for studying antimicrobial susceptibility are mostly planktonic or planar biofilm reactors. In this work, we develop a new type of biofilm reactor-three-dimensional (3D) microreactors-to recreate biofilms in a microenvironment that better mimics those in vivo where bacteria tend to form surface-independent biofilms in living tissues. The microreactors are formed on microplates, treated with antibiotics of 1000 times of the corresponding minimal inhibitory concentrations (1000 × MIC), and monitored spectroscopically with a microplate reader in a high-throughput manner. The hydrogels are dissolvable on demand without the need for manual scraping, thus enabling measurements of phenotypic changes. Bacteria inside the biofilm microreactors are found to survive exposure to 1000 × MIC of antibiotics, and subsequent comparison with plating results reveals no antibiotic resistance-associated phenotypes. The presented microreactor offers an attractive platform to study the tolerance and antibiotic resistance of surface-independent biofilms such as those found in tissues.202336691521
8986150.9978Gene expression in Lucilia sericata (Diptera: Calliphoridae) larvae exposed to Pseudomonas aeruginosa and Acinetobacter baumannii identifies shared and microbe-specific induction of immune genes. Antibiotic resistance is a continuing challenge in medicine. There are various strategies for expanding antibiotic therapeutic repertoires, including the use of blow flies. Their larvae exhibit strong antibiotic and antibiofilm properties that alter microbiome communities. One species, Lucilia sericata, is used to treat problematic wounds due to its debridement capabilities and its excretions and secretions that kill some pathogenic bacteria. There is much to be learned about how L. sericata interacts with microbiomes at the molecular level. To address this deficiency, gene expression was assessed after feeding exposure (1 h or 4 h) to two clinically problematic pathogens: Pseudomonas aeruginosa and Acinetobacter baumannii. The results identified immunity-related genes that were differentially expressed when exposed to these pathogens, as well as non-immune genes possibly involved in gut responses to bacterial infection. There was a greater response to P. aeruginosa that increased over time, while few genes responded to A. baumannii exposure, and expression was not time-dependent. The response to feeding on pathogens indicates a few common responses and features distinct to each pathogen, which is useful in improving the wound debridement therapy and helps to develop biomimetic alternatives.202234613655
8400160.9978Transferring knowledge of bacterial protein interaction networks to predict pathogen targeted human genes and immune signaling pathways: a case study on M. tuberculosis. BACKGROUND: Bacterial invasive infection and host immune response is fundamental to the understanding of pathogen pathogenesis and the discovery of effective therapeutic drugs. However, there are very few experimental studies on the signaling cross-talks between bacteria and human host to date. METHODS: In this work, taking M. tuberculosis H37Rv (MTB) that is co-evolving with its human host as an example, we propose a general computational framework that exploits the known bacterial pathogen protein interaction networks in STRING database to predict pathogen-host protein interactions and their signaling cross-talks. In this framework, significant interlogs are derived from the known pathogen protein interaction networks to train a predictive l(2)-regularized logistic regression model. RESULTS: The computational results show that the proposed method achieves excellent performance of cross validation as well as low predicted positive rates on the less significant interlogs and non-interlogs, indicating a low risk of false discovery. We further conduct gene ontology (GO) and pathway enrichment analyses of the predicted pathogen-host protein interaction networks, which potentially provides insights into the machinery that M. tuberculosis H37Rv targets human genes and signaling pathways. In addition, we analyse the pathogen-host protein interactions related to drug resistance, inhibition of which potentially provides an alternative solution to M. tuberculosis H37Rv drug resistance. CONCLUSIONS: The proposed machine learning framework has been verified effective for predicting bacteria-host protein interactions via known bacterial protein interaction networks. For a vast majority of bacterial pathogens that lacks experimental studies of bacteria-host protein interactions, this framework is supposed to achieve a general-purpose applicability. The predicted protein interaction networks between M. tuberculosis H37Rv and Homo sapiens, provided in the Additional files, promise to gain applications in the two fields: (1) providing an alternative solution to drug resistance; (2) revealing the patterns that M. tuberculosis H37Rv genes target human immune signaling pathways.201829954330
3160170.9978Impact of antibiotics on off-target infant gut microbiota and resistance genes in cohort studies. BACKGROUND: Young children are frequently exposed to antibiotics, with the potential for collateral consequences to the gut microbiome. The impact of antibiotic exposures to off-target microbes (i.e., bacteria not targeted by treatment) and antibiotic resistance genes (ARGs) is poorly understood. METHODS: We used metagenomic sequencing data from paired stool samples collected prior to antibiotic exposure and at 1 year from over 200 infants and a difference-in-differences approach to assess the relationship between subsequent exposures and the abundance or compositional diversity of microbes and ARGs while adjusting for covariates. RESULTS: By 1 year, the abundance of multiple species and ARGs differed by antibiotic exposure. Compared to infants never exposed to antibiotics, Bacteroides vulgatus relative abundance increased by 1.72% (95% CI: 0.19, 3.24) while Bacteroides fragilis decreased by 1.56% (95% CI: -4.32, 1.21). Bifidobacterium species also exhibited opposing trends. ARGs associated with exposure included class A beta-lactamase gene CfxA6. Among infants attending day care, Escherichia coli and ARG abundance were both positively associated with antibiotic use. CONCLUSION: Novel findings, including the importance of day care attendance, were identified through considering microbiome data at baseline and post-intervention. Thus, our study design and approach have important implications for future studies evaluating the unintended impacts of antibiotics. IMPACT: The impact of antibiotic exposure to off-target microbes and antibiotic resistance genes in the gut is poorly defined. We quantified these impacts in two cohort studies using a difference-in-differences approach. Novel to microbiome studies, we used pre/post-antibiotic data to emulate a randomized controlled trial. Compared to infants unexposed to antibiotics between baseline and 1 year, the relative abundance of multiple off-target species and antibiotic resistance genes was altered. Infants who attended day care and were exposed to antibiotics within the first year had a higher abundance of Escherichia coli and antibiotic resistance genes; a novel finding warranting further investigation.202235568730
3758180.9978The effects of hormones on sex differences in infection: from genes to behavior. Males of many species are more susceptible than females to infections caused by parasites, fungi, bacteria, and viruses. One proximate cause of sex differences in infection is differences in endocrine-immune interactions. Specifically, males may be more susceptible to infection than females because sex steroids, specifically androgens in males and estrogens in females, modulate several aspects of host immunity. It is, however, becoming increasingly more apparent that in addition to affecting host immunity, sex steroid hormones alter genes and behaviors that influence susceptibility and resistance to infection. Thus, males may be more susceptible to infection than females not only because androgens reduce immunocompetence, but because sex steroid hormones affect disease resistance genes and behaviors that make males more susceptible to infection. Consideration of the cumulative effects of sex steroid hormones on susceptibility to infection may serve to clarify current discrepancies in the literature and offer alternative hypotheses to the view that sex steroid hormones only alter susceptibility to infection via changes in host immune function.200010940438
8954190.9978Effect of biofilm formation by antimicrobial-resistant gram-negative bacteria in cold storage on survival in dairy processing lines. Antimicrobial-resistant gram-negative bacteria in dairy products can transfer antimicrobial resistance to gut microbiota in humans and can adversely impact the product quality. In this study, we aimed to investigate their distribution in dairy processing lines and evaluate biofilm formation and heat tolerance under dairy processing line-like conditions. Additionally, we compared the relative expression of general and heat stress-related genes as well as spoilage-related gene between biofilm and planktonic cells under consecutive stresses, similar to those in dairy processing lines. Most species of gram-negative bacteria isolated from five different dairy processing plants were resistant to one or more antimicrobials. Biofilm formation by the bacteria at 5 °C increased with the increase in exposure time. Moreover, cells in biofilms remained viable under heat treatment, whereas all planktonic cells of the selected strains died. The expression of heat-shock-related genes significantly increased with heat treatment in the biofilms but mostly decreased in the planktonic cells. Thus, biofilm formation under raw milk storage conditions may improve the tolerance of antimicrobial-resistant gram-negative bacteria to pasteurization, thereby increasing their persistence in dairy processing lines and products. Furthermore, the difference in response to heat stress between biofilm and planktonic cells may be attributed to the differential expression of heat stress-related genes. Therefore, this study contributes to the understanding of how gram-negative bacteria persist under consecutive stresses in dairy processing procedures and the potential mechanism underlying heat tolerance in biofilms.202336436412