Microbiology spectrum最新文献

Silicosis is an irreversible and progressive form of pulmonary fibrosis resulting from inhalation of silica particles, representing a persistent global health concern. Although the gut microbiota has been implicated in chronic lung diseases, its role in silicosis remains largely unexplored. Here, we performed 16S ribosomal RNA (rRNA) gene sequencing on fecal samples from 78 silicosis patients (27 stage I, 24 stage II, 27 stage III) and 30 matched healthy controls (HCs), and further conducted untargeted fecal metabolomics profiling in stage I patients, the critical point for microbial dysbiosis. Silicosis patients exhibited significantly altered beta diversity compared with HCs. At the phylum level, a progressive increase in Proteobacteria and a decline in Bacteroidota were observed. Notably, Pantoea, Kluyvera, and unclassified Pasteurellaceae were significantly enriched in stage I patients, with persistent alterations across later stages, suggesting stage I as a key turning point of microbial dysbiosis. Metabolomic analysis of stage I patients revealed distinct profiles enriched in tyrosine, histidine, purine metabolism, and arginine biosynthesis pathways. Correlation analysis identified strong associations between specific taxa and metabolites, and combined microbial-metabolite signatures such as Lactobacillus with N-succinyl-2-amino-6-ketopimelate (N-Succinyl-AKP) achieved an area under the curve (AUC) of 0.84 in distinguishing stage I patients from HCs.IMPORTANCEThis study systematically characterizes gut microbial changes across different stages of silicosis and integrates microbiome-metabolome data specifically in early-stage patients. We demonstrate that stage I is a critical point for gut microbiome alterations and identify microbe-metabolite signatures with diagnostic potential. These findings highlight the gut microbiome-metabolome combination as a promising source of non-invasive biomarkers for the early detection of silicosis.

There is a need for new therapies to treat drug-resistant nontuberculous mycobacteria (NTM) disease. Bacteriophages (phages), which are viruses that infect and kill bacteria, are actively being explored as an alternative approach for treating mycobacterial diseases. Several compassionate-use cases of phage therapy for drug-resistant NTM infections exhibit favorable outcomes. To further the development of phage therapy, it is important to recognize and avoid conditions that negatively impact phage activity during phage production, storage, formulation, or treatment. Conversely, there is a need to inactivate free phages in certain preclinical phage therapy experiments. In this study, we investigated three mycobacteriophages BPsΔ33HTH-HRM10, Muddy, and ZoeJΔ45 from compassionate-use NTM treatment cases for their sensitivity to a variety of conditions that included temperature, acid pH, detergents, mucus, and phage inactivating buffers. Several conditions resulted in dramatic and rapid reductions in the level of active phage, while others had no effect. We also observed different sensitivities between the phages. The results provide valuable information to support further investigation and development of these phages as therapeutics.IMPORTANCEBacteriophages (phages) offer a promising alternative therapy for treating drug-resistant mycobacterial infections. For the successful implementation of phage therapy, it is important to recognize conditions that inactivate the phages. Here, we studied three mycobacteriophages from recent compassionate-use phage therapy cases for their sensitivity to a range of conditions that may be encountered in production, storage, formulation, or treatment. The results demonstrate sensitivity to some conditions and tolerance to others, and they additionally reveal phage-specific differences in sensitivities, highlighting the need for direct evaluation of individual therapeutic phages during development.

Staphylococcus aureus exhibits remarkable tolerance to antibiotic stress, facilitated by a complex network of cellular responses and metabolism controlled by numerous gene expression patterns that can be rapidly remodeled. This tolerance can lead to treatment failure and the emergence of antibiotic resistance. However, the expression patterns of these genes caused by metabolic alterations driving antibiotic tolerance remain poorly understood. Our objective was to identify the core metabolic genes involved in the development of tolerance. Using proteomic analysis and gene complementation assays, we found that seven tolerant isolates shared similar protein expression profiles and mechanisms for tolerance. Seven metabolic genes, including NWMN_0676-0677, opuCB, gltD, adhE, clpP, and rarA, were confirmed as major contributors to tolerance. Notably, these genes were linked to elevated intracellular reactive oxygen species (ROS) levels in drug-tolerant strains. Treatment with ROS scavengers increased the sensitivity of these strains to antibiotics. These results demonstrate that changes in the expression of metabolic genes play a crucial role in the development of drug tolerance, and the regulation of ROS metabolism may be central to the broader metabolic alterations in drug-tolerant bacteria.

Importance: S. aureus poses a major public health threat due to its remarkable ability to develop antibiotic tolerance, often leading to treatment failure and resistance emergence. This study provides critical insights into the underlying metabolic mechanisms. Proteomic analysis revealed that different genetic mutations in tolerant isolates converged on similar gene expression changes, which directly impacted the tolerance phenotype. Notably, the tolerant strains exhibited elevated intracellular reactive oxygen species (ROS) levels, and ROS scavenger treatment increased their antibiotic susceptibility. These findings demonstrate that shifts in core metabolic gene expression are pivotal for S. aureus to withstand antibiotic stress, with ROS metabolism regulation being a central component of the broader metabolic adaptations conferring drug tolerance. Understanding these metabolic underpinnings is crucial for developing more effective treatments against persistent, tolerant S. aureus infections. The identified metabolic targets and ROS-modulating approaches offer promising strategies to combat escalating antibiotic resistance.

Endophytes play essential roles in protecting plants against abiotic stresses. However, whether and how they enhance waterlogging resilience in mulberry through changes in host-associated microbiota and metabolites remains unclear. Here, an endophytic bacterium strain HLG18, with plant growth promotion potential, was selected and identified as Pseudomonas koreensis HLG18. Genome analysis revealed that it possessed multiple genes involved in phytohormone biosynthesis, mineral dissolution, and stress adaptation. Greenhouse experiments consistently indicated that P. koreensis HLG18 significantly stimulated mulberry growth under waterlogging stress, accompanied by enhanced antioxidant enzyme activities and osmoprotectants. Amplicon sequencing revealed distinct endospheric microbiome profiles following HLG18 treatment, with notable changes in genera, such as Rhizorhapis, Bacillus, Caulobacter, and Rhodococcus. Meanwhile, soil potassium, phosphorus, and iron levels also differed. Correlation analyses indicated that the relative abundances of Rhizorhapis, Bacillus, Caulobacter, and Rhodococcus were significantly associated with soil properties and mulberry performance. Concurrently, metabolomic profiling revealed distinct metabolic signatures between treatments, including higher levels of stress-related metabolites (e.g., L-arginine, L-isoleucine) and differences in key metabolic pathways, such as tryptophan and purine metabolism. Overall, this study uncovers that P. koreensis HLG18 is linked to altered microenvironmental features and host metabolic patterns under waterlogging, providing new insights into endophyte-assisted plant stress adaptation.IMPORTANCEWaterlogging severely threatens the riparian zone of the Three Gorges Reservoir in China, causing extensive plant mortality and hindering restoration efforts. Mulberry is a promising candidate for ecological restoration, yet its growth is severely constrained under such conditions. Endophytes have emerged as key mediators of plant stress tolerance; however, their potential role in supporting mulberry adaptation to waterlogging in riparian zones remains largely unexplored. Our results show that the endophytic bacterium Pseudomonas koreensis HLG18 significantly promotes mulberry growth and enhances waterlogging tolerance. HLG18 inoculation is associated with distinct shifts in the host's endophytic microbiome, soil properties, and metabolite profiles, suggesting potential links to mulberry performance under waterlogging. Our findings highlight the potential of endophytes as bioinoculants to enhance mulberry waterlogging tolerance for ecological restoration in fragile riparian ecosystems and provide a valuable reference for harnessing beneficial microbial resources in sustainable agriculture under waterlogged conditions.

Metallo-β-lactamases (MBLs) hydrolyze a broad range of β-lactams, including carbapenems. VIM-28, an MBL identified in Pseudomonas aeruginosa, is an H224L/S228R variant of VIM-1 and H224L variant of VIM-4. Compared with VIM-26 (R228S), VIM-28 displayed decreased K_m (12.5 for VIM-28 vs 513 μM for VIM-26; 9.66 vs 150 μM) and increased k_cat/K_m(15.3 vs 1.81 μM^-1s^-1; 28.6 vs 5.89 μM^-1s^-1) for ampicillin and cephalothin, respectively. VIM-1, which has a His in position 224 and Ser in position 228, displayed intermediate kinetic values (K_m 215 and 77.0 μM; k_cat/K_m 2.63 and 8.61 μM^-1s^-1) for ampicillin and cephalothin, respectively, indicating that the presence of a positively charged residue at either position 224 or 228 enhanced substrate interactions. The combined L224H/R228S substitutions in VIM-1 increased the catalytic efficiency of the enzyme for ceftazidime by more than one order of magnitude. These kinetic trends were consistent with the minimum inhibitory concentration (MIC) data, with an eightfold increase in ceftazidime MIC for VIM-1-producing cells. Moreover, relative MIC assay showed that VIM-26 (R228S)-producing cells were more refractory to the addition of chelators than cells producing VIM-28, whereas VIM-4 (L224H)-producing cells showed reduced resistance, suggesting that the residues at positions 224 and 228 influence the metal-binding affinity of the enzyme. Differential scanning fluorimetry assay revealed that the R228S substitution increased the melting temperature of the enzyme, whereas the L224H substitution reduced its thermal stability. VIM-28 exhibited high catalytic efficiency for substrates other than ceftazidime, and the H224L substitution conferred higher zinc-binding affinity and thermal stability compared with VIM-4.IMPORTANCEβ-Lactam-resistant bacteria, especially carbapenem-resistant strains, pose a major global health threat, often through metallo-β-lactamases (MBLs). To anticipate resistance evolution, we characterized VIM-28, a variant of the widespread VIM-1/VIM-4-type enzymes, focusing on the roles of two variable L10 loop residues. Substitutions at positions 224 and 228 strongly affected substrate specificity, enzyme stability, and zinc affinity. Arg228 was important for carbapenem recognition, while combined substitutions at positions 224 and 228 could enhance activity toward ceftazidime. Notably, the R228S substitution improved zinc binding and thermal stability, supporting enzyme function under zinc-limited host conditions. These findings reveal mechanisms driving MBL diversity and highlight evolutionary strategies sustaining antibiotic resistance.

Searching publicly archived sequence data for emerging aquatic animal pathogens is a powerful but challenging approach for increasing our understanding of newly identified or poorly characterized organisms. However, searching for target sequences within the sequence read archive (SRA) database requires significant time, data storage, and computing power, limiting its accessibility. Utilizing a new database, Logan, we undertook a meta-analysis of SRA data sets to investigate the presence of an emerging virus, Macrobrachium rosenbergii golda virus (MrGV). MrGV was first characterized in M. rosenbergii larvae in 2020, associated with repeated mass mortalities in Bangladesh hatcheries. MrGV has since been detected in two separate reports from the Jiangsu Province of central, coastal China, and during a larval mortality event in India. Here, we discovered that MrGV is present in two additional provinces in southern China, Thailand, and India. We also found molecular evidence to confirm, as previously suspected, the circulation of the virus within Southern Asian populations of M. rosenbergii as far back as 2011, and that, based on relative abundance, MrGV is mostly associated with larvae. Overall, the identification of MrGV sequences in data sets that are largely unpublished within the scientific literature has provided novel insights into the pathogen's biology, including the prevalence of MrGV globally and the life stages of prawns that should be screened to prevent the spread of the virus. This work illustrates how mining public sequencing data, supported by databases like Logan and standardized metadata submissions, can support cost-effective epidemiological studies of pathogens and strengthen One Health approaches to global disease monitoring.IMPORTANCESearching for target sequences within the sequence read archive (SRA) database requires significant time, data storage, and computing power, limiting its accessibility. This study demonstrates how the Logan database, constructed from an SRA-wide genome assembly, can be utilized to rapidly and efficiently find target sequences within the SRA database, expanding the use of these publicly available data sets outside of their original intended purposes. Here, we searched for an emerging virus, Macrobrachium rosenbergii golda virus, in prawns to reveal insights into its geographic distribution, host range, and relative abundance, without the need for additional sampling. We demonstrate how, with careful application of this approach, alongside improvements in metadata quality and accessibility, sequencing data sets can be used to uncover critical insights into pathogen biology. This type of data mining could add otherwise unknown data to epidemiological studies of emerging, re-emerging, and rare pathogens globally, allowing the determination of the spread of agents within and between populations.