MicrobiologyOpen最新文献

Coagulase-negative staphylococci (CNS) and Mammaliicoccus species recently reclassified from the Staphylococcus sciuri group, are increasingly recognized as opportunistic pathogens in dairy animals and humans. This study investigated phylogenetic diversity and antimicrobial resistance in raw caprine milk from Sudan by integrating conventional bacteriological methods, molecular sequencing, and antimicrobial susceptibility testing. Raw goat milk samples were cultured, and presumptive CNS isolates were identified using phenotypic tests (novobiocin, oxidase, urease, and carbohydrate fermentation) following the standard Staphylococcus identification flow chart. PCR amplification of the elongation factor Tu (tuf) gene and the methicillin-resistance gene (mecA) enabled molecular confirmation and assessment of antimicrobial resistance. Sequenced tuf amplicons (~370 bp) were analyzed by BLAST and aligned in MEGA 12 for maximum-likelihood phylogenetic reconstruction. Staphylococcus simulans and Mammaliicoccus lentus were isolated in this study; antimicrobial susceptibility testing revealed that S. simulans, but not M. lentus, was methicillin-resistant and carried the mecA gene. Partial tuf gene sequencing confirmed 99.6%–99.7% identity with reference strains of the respective species. Phylogenetic analysis revealed that the isolated S. simulans formed a distinct branch within the global clusters. Meanwhile, M. lentus was found to be closely related to the global strains, showing only minor divergence. This study reports the presence of S. simulans and M. lentus in caprine milk from Sudan using both phenotypic and genotypic identification methods. This underscores the importance of integrating traditional laboratory methods with molecular techniques for precise species identification. The identification of methicillin-resistant S. simulans highlights the need for ongoing monitoring of CNS in raw milk.

Antibiotic-resistant bacteria represent a major global challenge as increasing infections become recalcitrant to standard treatments. A lack of novel therapeutics entering the market in the past 30 years further exacerbates this issue and highlights the importance of identifying and validating novel antibiotic targets. In this study, we explored prospective therapeutic targets by examining two metabolites in the lysine biosynthesis pathway, meso-diaminopimelate (DAP) and lysine, within the critically listed pathogen Pseudomonas aeruginosa. These metabolites are involved in bacterial cell wall and protein synthesis; therefore, enzymes present in this pathway represent potential targets for novel therapeutics. To elucidate the validity of these targets, we generated for the first time, gene deletion mutants of the P. aeruginosa DHDPR- and DAPDC-encoding genes using a two-step allelic exchange method. Both the mutants resulted in a lethal phenotype that could be rescued by supplementation with meso-DAP and/or lysine. We subsequently characterized the mutants' pathogenicity in a Galleria mellonella infection model. The DHDPR mutant was unable to provide a lethal infection in this model. Given the importance of these metabolites to membrane and cell wall synthesis, we investigated membrane permeability utilizing a fluorescent probe assay and transmission electron microscopy. Due to their increased membrane permeability, these mutants exhibited greater sensitivity to antibiotics commonly used against Pseudomonas infections. Overall, this study highlights that targeting the lysine biosynthesis pathway could enhance bacterial susceptibility to existing antibiotics, supporting its development as an adjuvant strategy to potentiate current treatments and extend their clinical utility.

Aptamers, short nucleic acid sequences with high specificity and affinity for their targets, are promising candidates for diagnostic applications due to their ability to detect a wide range of pathogens. We present a fluorescent bioimaging approach for detecting Pseudomonas aeruginosa, based on aptamer F23. Conjugated with fluorescent dye, its detection efficacy was evaluated on 15 Gram-negative and -positive bacteria, including fixed and live cells, as homogeneous and heterogeneous populations. We developed an automated, open-access software for quantifying microscopy images. Its high sensitivity enables accurate quantification of bacteria labeled with aptamers. For example, it successfully detected 1122 P. aeruginosa cells labeled with aptamer F23 out of a total of 1123 P. aeruginosa cells in a single image. With 200,000 analyzed bacteria, we demonstrated that the aptamer effectively detects various reference and clinical strains of P. aeruginosa, while failing to detect Gram-positive Staphylococcus aureus, Staphylococcus haemolyticus, Staphylococcus epidermidis, and Corynebacterium striatum, as well as Gram-negative Klebsiella pneumoniae, Acinetobacter baumannii, and Escherichia coli. This aptamer is therefore a promising tool to distinguish P. aeruginosa from different strains of the skin microbiota. However, our quantitative method also revealed partial labeling to other bacterial cells, highlighting the issue of refining aptamer selection to improve selectivity.

Mycobacterium tuberculosis (Mtb), the etiological agent of tuberculosis, is one of the most challenging pathogens due to its complex physiology, diverse clinical manifestations, and growing multidrug resistance. The global rise of drug-resistant Mtb strains has prompted the search for innovative genetic and molecular strategies to accelerate drug discovery and vaccine development. Progress in Mtb research has long been hindered by its slow replication rate and impermeable cell envelope, which limit the efficacy of genetic manipulation. This review outlines methodological advances that have transformed the study of Mtb pathogenesis and drug resistance mechanisms. Traditional homologous recombination–based approaches, including allelic exchange and specialized transduction, laid the groundwork for targeted mutagenesis but were limited by low efficiency. The advent of phage-derived recombineering systems, such as the Che9c RecET, has substantially improved the precision and throughput of genetic modification. Hybrid systems such as ORBIT, which combines oligonucleotide-mediated recombineering with Bxb1 integrase, have further enabled rapid and versatile genome engineering across mycobacterial species. Parallel developments in conditional gene expression systems (e.g., the use of TetR/Pip-based promoters) have facilitated the functional analysis of essential genes and the validation of novel drug targets. The advent of CRISPR–Cas technologies has represented a paradigm shift, by enabling programmable, high-fidelity gene regulation and functional genomics even in slow-growing mycobacteria. Together, these genetic innovations are transforming Mtb research by accelerating drug discovery and vaccine design, and shedding light on host–pathogen interactions.

Multi-Locus Sequence Typing (MLST) is a key method for allocation of Sequence Types (STs) for bacterial isolates. Traditionally, this is performed by the Sanger sequencing method, which can be highly time-consuming and laborious. In this study, we present NanoMLST, a high-throughput MLST workflow using multiplex PCR, Oxford Nanopore Technologies Next-Generation Sequencing, and the Krocus program for typing ESKAPE + E pathogens (Enterococcus faecium [E. faecium], Staphylococcus aureus, Klebsiella pneumoniae [K. pneumoniae], Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli). Bacterial isolates were obtained from the Hospital Universitario La Paz's Microbiology Department and the Centro Nacional de Microbiología. Primers that can be multiplexed in a single PCR reaction were designed for the seven housekeeping genes for each species. DNA was extracted from single colonies by heating at 95°C for 10 min, mechanical lysis at 4.20 m/s for 2 min, and then by the MagCore extraction system. Multiplex PCRs were then performed with the respective primer mixes for each species, and libraries were prepared for sequencing by ONT Flongle cells. The Krocus program was then used to determine the STs from the raw FastQ reads. STs for 221 isolates were obtained through this workflow with an average time of 12 h per 24 isolates. In line with local data, the K. pneumoniae and E. faecium isolates were relatively oligoclonal, while the rest were polyclonal. STs from representative isolates showed 100% concordance between Sanger sequencing and the proposed workflow. NanoMLST offers a fast, cheaper, and less labor-intensive alternative for large-scale MLST applications targeting clinically important pathogens.

Fungal plant biomass conversion (FPBC) is of great importance to the global carbon cycle and has been increasingly applied for the production of biofuel and biochemicals from lignocellulose. However, the comprehensive understanding of relevant molecular mechanisms in different fungi remains challenging. Here, we comparatively analyzed the transcriptome, proteome and metabolome profile of four ascomycetes and one basidiomycete fungi during their growth on two common agricultural feedstocks (soybean hulls and corn stover). We revealed strong time-, substrate- and species-specific responses at multi-omics levels for the tested fungi, highlighting species-specific carbon utilization approaches and evolutionary adaptation to environmental niches. Notably, a remarkable expressional diversity of lignocellulose degrading enzymes, sugar transporter and metabolic genes, as well as industrially relevant metabolites were identified across different fungi and cultivation conditions. The findings improves our understanding of complex molecular networks underlying FPBC and fungal ecological roles, offering novel insights that can guide future genetic engineering of fungi for valorization of agriculture waste into value-added bioproducts.

Candida albicans is a fungal commensal of humans that often causes mucosal infections in otherwise healthy individuals and also serious infections in immunocompromised patients. The capacity of this fungus to colonize and cause disease relies on its ability to grow within the host, adapting to various nutrient restrictions and physicochemical conditions. The presence of alternative carbon sources, such as the lactate produced by the local microbiota, influences C. albicans antifungal drug resistance and immune evasion. In this study, we used genome-wide transcriptomic analysis to investigate the effect of lactate exposure upon metabolic rewiring. We provide evidence that C. albicans cells respond to growth in the presence of lactate at pH 5 by regulating genes encoding micronutrient transporters, notably iron transporters. More specifically, lactate triggers the downregulation of genes on the reductive iron uptake pathway, inferring a diminished requirement for high-affinity iron uptake. This is supported by the observation that lactate promotes the intracellular accumulation of iron by C. albicans cells. Lactate even enhances the growth of iron-transport defective C. albicans cells under iron-limited conditions. Lactate is known to activate protein kinase A (PKA) signaling. However, lactate-induced iron assimilation is PKA-independent. This study provides new insights into the role of lactate in iron homeostasis—two important factors that promote C. albicans virulence in the mammalian host, where nutritional immunity is a key antimicrobial strategy.

Bloodstream infection (BSI) is a severe and often fatal condition, and a major cause of mortality in patients with hematological malignancies due to underlying conditions and anticancer therapy-induced immunodeficiency. Rapid identification of the causative pathogens is essential as BSI results in worsened prognosis, extended hospitalization, delays or dose reductions in therapy, and may progress to sepsis and septic shock if untreated. Shotgun metagenomics is a culture-independent technique capable of detecting a wide range of fungal, viral, and bacterial organisms along with their antimicrobial resistance genes. Several studies showed that shotgun metagenomics enables the diagnosis of BSI, specifically in cases where conventional methods/culture-dependent techniques fail to identify the causative pathogens. However, evaluation of the accuracy of the applied bioinformatics pipelines remains incomplete. This study aimed to compare and optimize four commonly used bioinformatics pipelines (BLAST, Kraken, Metaphlan, RTG Core) for shotgun metagenomics by assessing their accuracy in identifying pathogens in blood samples from patients with hematological malignancies and suspected BSI, with blood culture serving as the reference standard. Our work shows that the selection of bioinformatics pipelines for diagnosing BSI strongly affects the precision of the findings, and an optimized BLAST pipeline was superior to the alternatives, as it was the only method that accurately identified the causative pathogens.

Patients in intensive care units, especially those immunocompromised, are prone to opportunistic infections, such as respiratory and urinary tract infections. Extended antibiotic use disrupts the production of microbiome-derived metabolites, including those involved in colonization resistance to Pseudomonas aeruginosa, which is known for its multidrug resistance. Hence, prior antibiotic treatment has been shown to increase susceptibility to P. aeruginosa infection, but the role of microbiota-derived metabolic cues in this context is still elusive. This study investigates how tryptophan metabolites from the indigenous microbiota affect P. aeruginosa virulence. In vitro tests on motility, biofilm production, and pigment quantification (pyocyanin and pyoverdine) were performed on P. aeruginosa strains (PAO1, PA103, PA14) and clinical isolates. Additionally, gene expression related to virulence was analyzed, and the effects of tryptophan metabolites on experimental lung infection in mice were evaluated. Indole, indoleacetic acid (IAA), and indoleacrylic acid (IA) reduced motility and pigment production. IAA and indole promoted biofilm formation, with indole having a stronger effect. Clinical isolates showed significant phenotypic diversity, and IAA was more effective at inhibiting virulence traits than indole or IA. Mice infected with bacteria grown in the presence of IAA had lower lethality and fewer polymorphonuclear leukocyte influx compared to the control group. This suggests that tryptophan metabolites, especially IAA, can modulate P. aeruginosa virulence and may help control infection progression.

Detecting pathogens in environmental samples using molecular-based technologies can be challenging, particularly in low biomass environments or where pathogens represent a low percentage of the community. Multiple displacement amplification (MDA) is a whole genome amplification (WGA) method that has been developed for low biomass samples. However, there is a lack of information on how MDA could improve PCR and sequence-based detection and genomic characterization of pathogens in challenging environmental samples. In this study, MDA was evaluated on low template samples of the Salmonella LT2 isolate, a foodborne and waterborne environmental pathogen. MDA was also evaluated on a variety of low template mixed-microbial mock, environmental communities containing a range of Salmonella genome percentages to simulate different levels of Salmonella in the environment. Using MDA starting inputs of 1.8 × 10⁴–1.8 × 10¹ Salmonella LT2 genome copies, > 99% of the Salmonella genome was recovered following MDA at > 16X depth of coverage from as few as 500,000 merged, 250 bp paired-end reads. For the mock microbial communities, moderately high levels of genome abundance distortion were evident following MDA across all communities when compared to the expected compositions, which could not be attributed to either genome size or GC content alone. Overall, MDA may provide a useful method for increasing Salmonella detection sensitivity in low target environmental samples where downstream selective targeted applications such as real-time PCR or targeted amplicon sequencing are used, but MDA may not be appropriate for identification and detection of Salmonella when using untargeted, metagenomic sequencing.