Frontiers in Cellular and Infection Microbiology最新文献

The issue of antimicrobial resistance (AMR) in pathogenic microorganisms has emerged as a global public health crisis, posing a significant threat to the modern healthcare system. The advent of Artificial Intelligence (AI) and Machine Learning (ML) technologies has brought about revolutionary changes in this field. These advanced computational methods are capable of processing and analyzing large-scale biomedical data, thereby uncovering complex patterns and mechanisms behind the development of resistance. AI technologies are increasingly applied to predict the resistance of pathogens to various antibiotics based on gene content and genomic composition. This article reviews the latest advancements in AI and ML for predicting antimicrobial resistance in pathogenic microorganisms. We begin with an overview of the biological foundations of microbial resistance and its epidemiological research. Subsequently, we highlight the main AI and ML models used in resistance prediction, including but not limited to Support Vector Machines, Random Forests, and Deep Learning networks. Furthermore, we explore the major challenges in the field, such as data availability, model interpretability, and cross-species resistance prediction. Finally, we discuss new perspectives and solutions for research into microbial resistance through algorithm optimization, dataset expansion, and interdisciplinary collaboration. With the continuous advancement of AI technology, we will have the most powerful weapon in the fight against pathogenic microbial resistance in the future.

Introduction: Candida auris is an emerging pathogen that represents a worldwide health problem due to its global expansion, multidrug resistance, and difficult laboratory identification. Among the risk factors for colonization/infection by C. auris, a stay in an intensive care unit (ICU) stands out. This prospective multicenter study aimed to monitor the trend of the local epidemiology of Candida spp. and unveil the prevalence of C. auris.

Methods: From 2020 to 2022, axillar/inguinal swabs were collected from adult patients at three points: upon admission (D1) and on the fifth (D5) and eighth (D8) days of their ICU stay. We employed culture-based screening methods combined with molecular techniques to identify Candida spp. down to the species level. Specific screening for Candida auris was conducted using a real-time PCR assay in combination with an improved selective culture medium, mannitol salt agar auris (MSAA). To validate the effectiveness of MSAA, a collection of reference C. auris strains representing the four major geographical clades was used.

Results: We enrolled 675 patients, and 355 Candida isolates were retrieved from the 988 swab samples collected. From those, 185/355 (52.1%) were identified as C. albicans and 170/355 (47.9%) as non-albicans Candida (NAC). MSAA medium showed a specificity of 94.8%, albeit C. auris was not detected in this cohort. The dynamics of Candida spp. colonization by ICU were significant at the three collection points. Upon admission, C. albicans was associated with the Beatriz Ângelo Hospital ICU (p=0.003) and C. tropicalis with the general Hospital Professor Doutor Fernando Fonseca (FFH) ICU (p=0.006). C. parapsilosis and C. lusitaniae were associated with FFH ICUs, with the general ICU at D5 (p=0.047) and surgical ICU at D8 (p=0.012). The dynamics of NAC colonization by ICU were significantly different at D1 (p=0.011), D5 (p=0.047), and D8 (p=0.012).

Conclusion: We developed and implemented a screening protocol for C. auris while uncovering the colonization patterns of Candida in the ICU. Our findings contribute to the optimization of overall patient management, ensuring that ICU protocols are resilient and adaptive to emerging fungal threats.

Enzymes play a significant role in mediating inflammatory and immune responses in periodontitis. Effective diagnosis, timely treatment, and continuous management of periodontal enzymes are essential to prevent undesirable consequences; however, this remains a significant challenge. Nanoparticles (NPs) have attracted significant attention in biomedicine because of their advantageous nanosized effects. NPs are conjugated with specific enzyme substrates at responsive sites that are triggered by periodontitis enzyme biomarkers, leading to functional or characteristic changes. In contrast, NPs with enzyme-mimetic activities exhibit catalytic activity, effectively destroying pathogenic biofilms and modulating the immune response in periodontitis. The unique properties of enzyme-targeting NPs have enabled the development of biosensors and fluorescent probes capable of identifying enzyme biomarkers associated with periodontitis. Enzyme-responsive and enzyme-mimetic NPs both exert therapeutic applications in the treatment of periodontitis. In this review, we provide a comprehensive overview of the enzymes associated with periodontitis, the mechanisms of enzyme-responsive and enzyme-mimetic NPs, recent advancements in the use of NPs for detecting these enzymes, and the therapeutic applications of NPs in targeting or mimicking enzyme functions. We also discuss the challenges and prospects of using NPs in the diagnosis and treatment of periodontitis.

Aerobic respiration is the key driver of Vibrio cholerae proliferation and infection. Our previous transcriptome results suggested that degS knockout downregulates a few genes involved in NADH and ATP synthesis in the aerobic respiratory pathway. In this study, non-targeted metabolomics results showed that the differential metabolites affected by degS knockout were associated with aerobic respiration. Further results suggested that the key products of aerobic respiration, NADH and ATP, were reduced upon degS deletion and were not dependent on the classical σ^E pathway. The two-component system response factor aerobic respiration control A (ArcA) is involved in regulating NADH and ATP levels. qRT-PCR demonstrated that DegS negatively regulates the transcription of the arcA gene, which negatively regulates the expression of isocitrate dehydrogenase (ICDH), a key rate-limiting enzyme of the tricarboxylic acid cycle. NADH and ATP levels were partially restored with the knockout of the arcA gene in the ΔdegS strain, while levels were partially restored with overexpression of ICDH in the ΔdegS strain. In a growth experiment, compared to the ΔdegS strain, the growth rates of ΔdegSΔarcA and ΔdegS-overexpressed icdh strains (ΔdegS+icdh) were partially restored during the logarithmic growth period. Colonization of the intestines of suckling mice showed a significant reduction in the colonizing ability of the ΔdegS strain, similar colonizing ability of the ΔdegS::degS strain and the wild-type strain, and a partial recovery of the colonizing ability of the ΔdegS+icdh strain. Overall, these findings suggest that the DegS protease regulates the expression of ICDH through ArcA, thereby affecting the NADH and ATP levels of V. cholerae and its growth and intestinal colonization ability.

Objectives: Recent studies have increasingly demonstrated that a multiplatform water environment combined with lard gavage is an effective method for establishing a mouse model of diarrhea. However, the interactions between intestinal microorganisms and diarrhea, as well as the relationships among energy metabolism, fluid balance, and gastrointestinal function in this model, remain poorly understood.

Methods: Building on previous research, this study aimed to optimiz and replicate a multiplatform water environment combined with a lard gavage model. Male Kunming mice, free of specific pathogens, were randomly divided into four groups: a normal control group (ZC), a standing group (ZL), a standing combined with lard group (ZLZ), and a standing combined with internal and external wet conditions group (ZLZS). The mice in the ZL, ZLZ, and ZLZS groups were subjected to 4 hours of daily standing in a custom-designed multiplatform water environment. Starting on day 8, mice in the ZLZ and ZLZS groups were gavaged with lard (0.4 mL per session, twice daily) for 7 consecutive days, while those in the ZLZS group were additionally exposed to a wet litter environment (50 g/100 mL). The ZC and ZL groups received equal volumes of sterile water via gavage. The microbiota in the small intestine, as well as serum levels of cAMP, cGMP, VIP, Gas, and D-xylose, were analyzed.

Results: Compared with the ZLZ group, the ZLZS group showed significantly lower serum levels of cAMP/cGMP (p<0.01) and Gas (p<0.01). D-xylose levels were lower in the ZL, ZLZ, and ZLZS groups compared to the ZC group, while VIP levels were significantly higher in the ZL and ZLZS groups (p<0.01). Moverover, Corynebacterium, Empedobacter, and Pseudochrobactrum were identified as characteristic bacterial genera in the ZLZS group. The mechanism by which the small intestinal microbiota induces diarrhea was linked to the biosynthesis of secondary bile acids.

Conclusion: A multiplatform water environment combined with lard gavage can effectively induce diarrhea, and the addition of an external wet environment exacerbates this condition by affecting small intestinal contents microbiota and other functions.

Introduction: Intraamniotic infection is crucial in preterm prelabor rupture of membranes(PPROM), a clinical condition resulting from the invasion of vaginal opportunistic microbes into the amniotic cavity. Although previous studies have suggested potential associations between infection and PPROM, the role of vaginalopportunistic bacteria in PPROM has received limited attention.

Methods: This study aimed to confirm the vaginal bacterial etiology of PPROM. We investigated vaginal microbiotas using automatic analysis of vaginal discharge, microbiological tests, and 16s rRNA genehigh-throughput sequencing.

Results: The research findings revealed that the proportion of parabasal epitheliocytes, leukocytes, toxic leukocytes, and bacteria with diameters smaller than 1.5 um was significantly higher in the PPROM group than that in the normal full-term labor (TL) group. The top three vaginal opportunistic bacterial isolates in all participants were 9.47% Escherichia coli, 5.99% Streptococcus agalactiae, and 3.57% Enterococcus faecalis. The bacterial resistance differed, but all the isolates were sensitive to nitrofurantoin. Compared with the vaginal microbiota dysbiosis (VMD) TL (C) group, the VMD PPROM (P) group demonstrated more operational taxonomic units, a high richness of bacterial taxa, and a different beta-diversity index. Indicator species analysis revealed that Lactobacillus jensenii, Lactobacillus crispatus, and Veillonellaceae bacterium DNF00626 were strongly associated with the C group. Unlike the C group, the indicator bacteria in the P group were Enterococcus faecalis, Escherichia coli, and Streptococcus agalactiae.

Discussion: These findings provide solidevidence that an abnormal vaginal microbiome is a very crucial risk factorclosely related to PPROM. There were no unique bacteria in the vaginalmicrobiota of the PPROM group; however, the relative abundance of bacteria inthe abnormal vaginal flora of PPROM pregnancies differed. Antibiotics should bereasonably selected based on drug sensitivity testing. The findings presented in this paper enhance our understanding of Streptococcus agalactiae, Enterococcus faecalis, and Escherichia coli vaginal bacterial etiology of PPROM in Western China.

Endometriosis (EMT) has a significant impact on women's physical and mental health. In this study, high-throughput sequencing technology was employed to detect differences in gut microbiota between EMT patients and healthy individuals (CTL). Additionally, Spearman correlation analysis was utilized to analyze the correlation between different bacterial genera and EMT biomarkers (CA125 and CA199). The results demonstrated that at the phylum level, the relative abundances of Proteobacteria and Desulfobacterota_G_459546 in the EMT group were significantly higher than those in the CTL group, while the relative abundances of Bacteroidota and Firmicutes_A in the EMT group were significantly lower than those in the CTL group. At the genus level, the relative abundances of Burkholderiales and Sphingomonadales in the EMT group were significantly higher than those in the CTL group, while the relative abundances of Bacteroidales and Roseburia in the EMT group were significantly lower than those in the CTL group. The correlation analysis results show that CA125 and CA199 are significantly positively correlated with Burkholderiales and Sphingomonadales, and significantly negatively correlated with Bacteroidales, Oscillospirales, and Roseburia. The PICRUSt2 results show that the relative abundance in the cell motility and xenobiotics biodegradation and metabolism pathways in the EMT group was higher than that in the CTL group, while the relative abundance in the translation, replication and repair, folding, sorting and degradation, metabolism of terpenoids and polyketides and metabolism of cofactors and vitamins pathways in the EMT group was lower than that in the CTL group. In brief, there is a close correlation between the imbalance of gut microbiota and the onset of EMT. The intestinal microbiota has great significance broad prospects for the prevention, diagnosis and treatment of EMT.

Introduction: The homeostasis of the microbiome in lower respiratory tract is crucial in sustaining normal physiological functions of the lung. Different pulmonary diseases display varying degrees of microbiome imbalance; however, the specific variability and clinical significance of their microbiomes remain largely unexplored.

Methods: In this study, we delineated the pathogen spectrum and commensal microorganisms in the lower respiratory tract of various pulmonary diseases using metagenomic sequencing. We analyzed the disparities and commonalities of the microbial features and examined their correlation with disease characteristics.

Results: We observed distinct pathogen profiles and a diversity in lower airway microbiome in patients diagnosed with cancer, interstitial lung disease, bronchiectasis, common pneumonia, Nontuberculous mycobacteria (NTM) pneumonia, and severe pneumonia.

Discussion: This study illustrates the utility of Metagenomic Next-generation Sequencing (mNGS) in identifying pathogens and analyzing the lower respiratory microbiome, which is important for understanding the microbiological aspect of pulmonary diseases and essential for their early and precise diagnosis.

Leptospirosis is an emerging illness presenting a broad range of clinical manifestations, ranging from asymptomatic or mild cases to severe and fatal outcomes. Early detection is crucial for effective treatment; however, similar clinical presentations in various febrile illnesses or co-infections, along with challenges in laboratory diagnostics, can lead to misdiagnosis and severe consequences. Identifying clinical predictors for severe forms of the disease is essential in mitigating complications and reducing mortality. Consequently, we conducted a retrospective case-control study to identify clinical markers indicative of severe disease in leptospirosis patients from the Transcarpathian region. The study focused on patients admitted with clinically suspected leptospirosis, involving a total of 51 diagnosed cases, with 13 resulting in severe outcomes and death. Categorical variables were analyzed using χ², revealing a mean patient age of 50 years, predominantly male (n = 36, 70.5%). Oliguria emerged as a significant independent factor associated with mortality (odds ratio [OR], 13.5; 95% confidence interval [CI], 2.56-71.12; p = 0.001). Additionally, our analysis uncovered a noteworthy increase in leptospirosis notification rates in Transcarpathian compared to Ukraine, with 150 cases out of the total 433 in Ukraine. The highest notification rates were observed in Mukachevo District and Perechyn District. These findings highlight the importance of early recognition of key clinical markers, such as oliguria, which are critical for predicting severe outcomes in leptospirosis patients. The higher notification rates in Transcarpathian regions also underscore the need for enhanced surveillance, targeted public health interventions, and timely treatment to reduce mortality in endemic areas.

Background: The symbiotic gut microbiota is pivotal for human health, with its composition linked to various diseases and metabolic disorders. Despite its significance, there remains a gap in systematically evaluating how host phenotypes, such as gender, age, and body mass index (BMI), influence gut microbiota.

Methodology/principal findings: We conducted an analysis of the gut microbiota of 185 Chinese adults based on whole-metagenome shotgun sequencing of fecal samples. Our investigation focused on assessing the effects of gender, age, and BMI on gut microbiota across three levels: diversity, gene/phylogenetic composition, and functional composition. Our findings suggest that these phenotypes have a minor impact on shaping the gut microbiome compared to enterotypes, they do not correlate significantly within- or between-sample diversity. We identified a substantial number of phenotype-associated genes and metagenomic linkage groups (MLGs), indicating variations in gut microflora composition. Specifically, we observed a decline in beneficial Firmicutes microbes, such as Eubacterium, Roseburia, Faecalibacterium and Ruminococcus spp., in both older individuals and those with higher BMI, while potentially harmful microbes like Erysipelotrichaceae, Subdoligranulum and Streptococcus spp. increased with age. Additionally, Blautia and Dorea spp. were found to increase with BMI, aligning with prior research. Surprisingly, individuals who were older or overweight exhibited a lack of Bacteroidetes, a dominant phylum in the human gut microbiota that includes opportunistic pathogens, while certain species of the well-known probiotics Bifidobacterium were enriched in these groups, suggesting a complex interplay of these bacteria warranting further investigation. Regarding gender, several gender-associated MLGs from Bacteroides, Parabacteroides, Clostridium and Akkermansia were enriched in females. Functional analysis revealed a multitude of phenotype-associated KEGG orthologs (KOs).

Conclusions/significance: Our study underscores the influence of gender, age, and BMI on gut metagenomes, affecting both phylogenetic and functional composition. However, further investigation is needed to elucidate the precise roles of these bacteria, including both pathogens and probiotics.