Microbiology Spectrum

Background: Microbiota dysbiosis of the skin has been implicated in ulcer formation. Individuals with diabetes remain at high risk for diabetic foot ulcers (DFUs) even after ulcer healing. Topical chlorhexidine gluconate (CHG) is a broad-spectrum antiseptic commonly used to reduce microbial burden. In a prior randomized clinical trial comparing daily CHG foot treatment with soap-and-water treatment, no statistically significant reduction in new DFUs was observed, prompting evaluation of whether CHG produced durable changes in the skin microbiota. Objective: To compare changes in foot skin microbiota (including bacterial bioburden, diversity, and community composition) associated with daily CHG versus soap-and-water use over one year in people with diabetes and prior foot complications. Methods: In a single-center, double-blind, placebo-controlled randomized trial, 87 participants were randomized to daily CHG wipes or soap-and-water wipes for 12 months. Foot swabs were collected at baseline, 3 and 12 months, and 4 weeks post-treatment. Bacterial bioburden was quantified. Microbiota composition was assessed using 16S rRNA and ITS amplicon sequencing. Key Results: CHG treatment significantly reduced bacterial bioburden, increased microbial diversity, and altered community composition, including sustained reductions in Staphylococcus abundance. Several microbiota changes persisted more than 4 weeks after treatment cessation. Soap-and-water treatment showed similar but smaller and largely nonsignificant trends. Conclusions: Daily CHG use durably modifies foot skin microbiota in high-risk individuals with diabetes. However, this alone may be insufficient to prevent new foot complications, highlighting the need for additional interventions. These findings have implications for long-term CHG use in populations at risk for staphylococcal infections.

BackgroundNumerous countries use the EXTEL HEMO-AUTO MC Quantitative Faecal Immunochemical Test (qFIT) to screen for faecal haemoglobin. We aimed to determine if bacterial 16S rRNA gene sequencing results (16S V1V2) from the leftover qFIT cassettes would be stable over time and comparable with larger volume faecal collection protocols. MethodsFour qFIT probe samples were taken from each of the sixteen fresh healthy volunteer stool samples and 16S results were compared after 0, 4, 7 and 14 days, to provide a baseline control and mimic postage and sample processing conditions in cancer screening programmes. qFIT results were then compared to those of standard laboratory processing of larger whole-stool samples. DNA was extracted from 100 NHS surplus qFIT samples from symptomatic patients reporting rectal bleeding and quantified to assess suitability for 16S sequencing. ResultsBacterial composition and diversity from healthy volunteer qFITs remained stable over 14 days with no differences compared to baseline (day 0) and larger stool control samples; at least 75% of the symptomatic qFITs yielded sufficient DNA for 16S sequencing. ConclusionqFIT samples were not significantly different to control samples and stable over 14 days, allowing them to be used for large-scale low-cost population-based intestinal microbiota studies. Clinical Trial RegistrationThe study was registered on clinicaltrials.gov (NCT06100549).

Recessive dystrophic epidermolysis bullosa (RDEB) is an inherited disorder characterized by recurrent wounds and frequent bacterial colonization. Clinically applicable methods that provide information on bacterial composition, viable burden, and spatial distribution are needed to support wound assessment and therapeutic evaluation. In this exploratory four-week longitudinal study, standard-of-care-treated wounds from five patients with RDEB were examined using autofluorescence imaging, quantitative and chromogenic culture, MALDI-TOF MS, 16S rRNA and staphylococcal tuf2 amplicon sequencing, and spatial Bactogram analysis. Sequencing showed that staphylococci dominated 22/23 communities, with Staphylococcus aureus being the most abundant staphylococcal species (21/23). Culture likewise identified S. aureus as the most frequent species in all 14 swab samples. Aerobic bacterial burden showed no association with open wound area and remained high in several contracting wounds. The Bactogram provided a spatial representation of viable bacterial growth and, when combined with chromogenic agar, reflected the predominance of S. aureus identified by sequencing, MALDI-TOF MS, and quantitative culture. Together, these complementary methods captured the dynamic nature of RDEB wounds through heterogeneous healing trajectories and longitudinal variation in bacterial burden, while consistently identifying a low-diversity, S. aureus-dominated microbiota. Bactogram spatial imprinting and autofluorescence imaging warrant further evaluation as minimally invasive tools for longitudinal EB assessment.

The microbiome serves important functions in human health, and postmortem, the microbial signatures of colonized organ tissue could be useful in helping to predict the manner of death in cases where this information is not known. We surveyed the microbiota (16S rRNA V4 amplicon sequencing) of 265 organ tissue samples including liver, blood, brain, heart, prostate, spleen and uterus from cadavers in Italy, Finland and the United States with confirmed manners of death comprising either accidental death, natural death, homicide, and suicide. Geographic locality (i.e. nationality) had a strong effect on observed microbial composition. Differing PERMANOVA results between unweighted and weighted UniFrac (nearly inverse results) suggest that specific bacteria may be associated with ethnicity and age, but that these differences are negligible when taking into account the relative abundance of bacterial taxa; weighted UniFrac measures suggest that although taxonomic composition may not vary significantly between different manners of death, PMI, or BMI categories, the relative abundance of specific taxa vary significantly. Various tissues exhibit differential associations with bacteria, and prostate and uterus were substantially different compared to other organs. For example, in Italian cadavers, the bacteria MLE1-12 permeated nearly all tissues, except the prostate and uterus. We identified specific bacterial ASVs as biomarkers of either natural or accidental death and suicide, but not for homicide. While the manner of death may have an impact on microbial associations, further investigation under more controlled conditions will be needed to validate whether these associations are predictive in forensic determinations.\n\nImportanceThe utilization of microbial data in the context of forensic investigations holds great promise for the field of forensic science. Identification of taxa that are associated with postmortem interval (PMI), specific manners of death (MOD), or other traits such as age, sex, ethnicity, and nationality may allow investigators to refine the circumstantial details surrounding the death of an individual. In this study we find nationality (geographic location of cadaver) to be a dominant predictor of cadaver microbiome composition. We also identify a number of cadaver-specific traits to be associated with microbial alpha- and beta diversity, as well as bacterial taxa that are differentially associated with these traits.

Challenges from infections caused by biofilms and antimicrobial resistance highlight the need for novel antimicrobials that work synergistically with antibiotics and minimize resistance risk. In this study we investigated the potential synergistic effect of HAMLET (human alpha-lactalbumin made lethal to tumor cells), a human milk protein-lipid complex and amoxicillin on microbial ecology using an ex-vivo oral biofilm model. HAMLET was chosen due to its multi-targeted antimicrobial mechanism, together with its synergistic effect with antibiotics on single species pathogens, and low risk of resistance development. The combination of HAMLET and amoxicillin significantly reduced biofilm viability, while each of them alone had little or no impact. Using a whole metagenomics approach, we found that the combination group promoted a most remarkable shift in overall microbial composition compared to the untreated samples. Up to 90% of the bacterial species in the combined treatment were Lactobacillus crispatus, a species with probiotic effects, whereas it was detected in minor fraction in untreated samples. Resistome analysis indicated no major shifts on alpha-diversity, while beta-diversity revealed distinct clustering patterns for each treatment group, signifying that each treatment group harbors a unique resistome. TEM beta-lactamase genes were detected in low proportions in all treated samples but absent in untreated samples. Our study highlights the potential of HAMLET to synergize with amoxicillin in an ex-vivo model of the oral microbiome and modulate the proportion of probiotic bacteria. The findings extend the knowledge on the synergistic effects of HAMLET and antibiotics from single-species studies to polymicrobial biofilms of human origin. ImportancePolymicrobial infections are challenging to treat and prevent, requiring the use of antibiotics that exhibit reduced efficacy due to biofilm formation. HAMLET has recently emerged as an antimicrobial agent that can synergize with antibiotics while limiting microbial resistance. We investigated the effects of HAMLET, alone and combined with low concentrations of amoxicillin, on ex vivo oral biofilms to simulate complex microbial interactions observed in the oral cavity. The combination of HAMLET and amoxicillin effectively targeted polymicrobial biofilms and led to an increase in Lactobacillus crispatus. The potency of this combination appears to be due to the synergistic effect of HAMLET and amoxicillin. These findings underscore the potential of combining antimicrobials with different modes of action for the development of more effective strategies for preventing and treating polymicrobial infections.

The gut microbiome is crucial for host health. Early childhood is a critical period for the development of a healthy gut microbiome, but it is particularly sensitive to external influences. Recent research has focused on using advanced techniques like shotgun metagenome sequencing to identify key microbial signatures and disruptions linked to disease. For accurate microbiome analysis, samples need to be collected and stored under specific conditions to preserve microbial integrity and composition, with -80{degrees}C storage considered the gold standard for stabilization. This study investigates the effect of domestic freezer storage on the microbial composition of stool samples from 20 children under 4 years with the use of shotgun metagenomic sequencing. Fresh stool samples were aliquoted into sterile tubes, with one aliquot stored at 4{degrees}C and analyzed within 24 hours, while others were frozen in domestic freezers (below -18{degrees}C) and analyzed after 1 week, 2 months, and 6 months. Assessments of contig assembly quality, microbial diversity, and antimicrobial resistance genes revealed no significant degradation or variation in microbial composition. ImportanceMost previous studies on sample storage have used amplicon sequencing, which limits relevance to metagenome sequencing, in which contig quality and functional gene detection are additional concerns. Moreover, the effects of domestic freezer storage for at-home stool collection on microbiome profiles, contig quality, and antimicrobial resistance gene profiles have not been tested previously. Our findings suggest that stool samples stored in domestic freezers for up to six months maintain the integrity of metagenomic data. These findings indicate that domestic freezer storage does not compromise the integrity or reproducibility of metagenomic data, offering a reliable and accessible alternative for temporary sample storage. This approach enhances the feasibility of large-scale at-home stool collection and citizen science projects, even those focused on the more easily perturbed early life microbiome. This advancement enables more inclusive research into the gut microbiome, enhancing our understanding of its role in human health.

The lack of preparedness for detecting the highly infectious SARS-CoV-2 pathogen, the pathogen responsible for the COVID-19 disease, has caused enormous harm to public health and the economy. It took [~]60 days for the first reverse transcription quantitative polymerase chain reaction (RT-qPCR) tests for SARS-CoV-2 infection developed by the United States Centers for Disease Control (CDC) to be made publicly available. It then took >270 days to deploy 800,000 of these tests at a time when the estimated actual testing needs required over 6 million tests per day. Testing was therefore limited to individuals with symptoms or in close contact with confirmed positive cases. Testing strategies deployed on a population scale at Day Zero i.e., at the time of the first reported case, would be of significant value. Next Generation Sequencing (NGS) has such Day Zero capabilities with the potential for broad and large-scale testing. However, it has limited detection sensitivity for low copy numbers of pathogens which may be present. Here we demonstrate that by using CRISPR-Cas9 to remove abundant sequences that do not contribute to pathogen detection, NGS detection sensitivity of COVID-19 is comparable to RT-qPCR. In addition, we show that this assay can be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single workflow using existing open-source analysis pipelines. This NGS workflow is pathogen agnostic, and therefore has the potential to transform how both large-scale pandemic response and focused clinical infectious disease testing are pursued in the future. SIGNIFICANCE STATEMENTThe lack of preparedness for detecting infectious pathogens has had a devastating effect on the global economy and society. Thus, a Day Zero testing strategy, that can be deployed at the first reported case and expanded to population scale, is required. Next generation sequencing enables Day Zero capabilities but is inadequate for detecting low levels of pathogen due to abundant sequences of little biological interest. By applying the CRISPR-Cas system to remove these sequences in vitro, we show sensitivity of pathogen detection equivalent to RT-qPCR. The workflow is pathogen agnostic, and enables detection of strain types, co-infections and human host response with a single workflow and open-source analysis tools. These results highlight the potential to transform future large-scale pandemic response.

Over the past two decades, advances in molecular biology have greatly expanded our understanding of microbiomes - the diverse assemblages of microorganisms that inhabit the human body as well as the world around us, and applications in microbiome science have become an active area of research. Differences in the diversity (i.e., richness) and composition of microbiomes has been found to be informative in varied areas of science, including human health, agronomy, and forensic science. Soil harbors microbiomes that vary based on many factors, including the geology of the soil (e.g., sand, silt, or clay), climate, and use of the soil. As a result, the microbiological composition of any two soil samples will never be exactly alike. This inherent variation between microbiomes of different locations has proven to be specific enough to be potentially useful in forensic investigations to associate a person or piece of evidence to a source site. In this study, a soil microbiome was extracted from the sock of a criminal suspect and compared to the microbiome of soil samples taken from locations traveled to by the suspect. The locations analyzed varied in their soil microbiome composition, and the microbiome profiled from the sock was found to be most similar to the location where the suspect was thought to have left the body of a murder victim. These results provide a case study illustrating that information contained in a soil microbiome may be applied to link evidence to the location where a crime took place, potentially serving as an investigative tool in law enforcement.

The number of patients suffering from Mycobacterium abscessus complex (MABC) pulmonary diseases is steadily increasing. MABC consists of three subspecies, and it is recommended that the three subspecies be distinguished because of their differing macrolide susceptibilities. Unfortunately, current methods are inefficient due to their high cost, complexity, and time requirements. The third-generation Bruker MALDI Biotyper (MBT) Sirius has the capability to detect phospholipids and glycolipids using negative-ion mode. Mycobacterial cell walls are rich in lipids, and if lipid structure diversity can serve as species-specific fingerprints, this method may provide an alternative for microbial identification. This study aimed to examine the accuracy of discriminating between the three MABC subspecies by lipid profiling. Our best model failed to differentiate the three subspecies. Even in the two-dimensional space of the most significant peaks, M. abscessus and M. massiliense could not be separated. The agreement rate between lipid fingerprint-based and WGS-based identification was, at most, 47.2% for negative-ion mode. Even after applying recent machine learning algorithms to detect variables and create predictive models, accuracy remained at 50%. Our results suggest that using lipid fingerprinting alone to differentiate the three MABC subspecies is currently inadequate. Further advancements and standardization of MALDI-TOF MS-based methods are necessary for the routine differentiation of MABC subspecies in clinical settings.

Fecal microbiota transplantation (FMT) is an effective therapy for recurrent Clostridioides difficile infection and is increasingly explored for other dysbiosis-related disorders. However, its implementation as a regulated therapeutic strategy still requires robust donor screening, biosafety frameworks, and standardized processing workflows. Here, we describe the establishment of the first fecal microbiota biobank in the south of Brazil and evaluate the incorporation of metagenomic sequencing as a complementary layer of donor safety assessment. A structured donor selection pipeline based on international guidelines was implemented, integrating clinical screening, biochemical and serological testing, and microbiological analyses. Of 100 screened candidates, only four donors met all eligibility criteria and were included in the biobank, highlighting the stringency of the selection process. Shotgun metagenomic sequencing revealed a diverse resistome across all donors, including a shared core set of resistance-related genes alongside marked interindividual variability. Dominant antibiotic resistance genes included tetracycline-associated determinants, as well as ermF, CfxA-type {beta}-lactamases, and aminoglycoside-modifying enzymes, each linked to specific gut taxa. Notably, the relatively high abundance of tetW and ermF in Bacteroides fragilis suggests that this dominant commensal species may act as a reservoir for tetracycline and multidrug resistance determinants within the intestinal microbiota. Rather than serving as exclusion criteria, such determinants highlight the importance of integrating functional genomic profiling into donor characterization. Overall, this study provides a framework for microbiota biobank implementation and supports the use of metagenomics as a complementary strategy to improve biosafety and functional assessment in FMT.

BackgroundDiagnostics for tuberculosis (TB) and treatment monitoring remains a challenge, particularly in less-resourced laboratories. Further, the comprehensive sputum microbiota of TB patients during treatment are less described, particularly using long-read sequencers. MethodsDNA from sputum samples collected from newly-diagnosed TB patients were sequenced with Oxford Nanopores MinION. MG-RAST and R packages (Phyloseq, /{beta} diversities, functional components, OTUs networks and ordination plots. Statistical significance of the generated data was determined using GraphPad. Results & conclusionAntibiotics reduced the abundance and functional subsystems of each samples microbiota from baseline until day 7, when persistent, tolerant, and resistant microbiota, including fungi, grew back again. Variations in microbiota abundance and diversity were patient-specific. Closer microbiome network relationships observed in baseline samples reduced until day 7, when it became closer again. Bacterial microbiota networks and spatial ordination relationships were closer than that of other kingdoms. Actinobacteria phylum and Mycobacterium were more affected by antibiotics than other phyla and genera. Parasites, viruses, and fungi were less affected by antibiotics than bacteria in a descending order. Resistance genes/mechanisms to important antibiotics, plasmids, transposons, insertion sequences, integrative conjugative elements were identified in few samples. MinION can be adopted clinically to monitor treatment and consequent dysbiosis, and identify both known and unknown pathogens and resistance genes to inform tailored treatment choices, specifically in TB. Author summaryTuberculosis (TB), one of the major killers of mankind, continually remains elusive as challenges with early diagnosis and treatment monitoring remain. Herein, we use a single portable sequencer from Oxford Nanopore, the minION, to diagnose TB and monitor its treatment with antibiotics using routine sputum samples. In addition, the presence of other pathogens, important commensals, antibiotic resistance genes, mobile genetic elements, and the effect of the antibiotic treatment on the sputum microbiota were determined from the same data. This makes the minION an important tool that can be used in clinical laboratories to obtain data that can inform live-saving decisions.

Innovation in sequencing techniques has enabled the identification of microbiome in low biomass sites. In this study, we sought to investigate the utility of 16S rRNA deep sequencing of whole blood in kidney transplant recipients and to assess a link between the gut microbiota and the blood microbiota. We recruited 63 kidney transplant recipients who provided 163 whole blood specimens over the first 140 days after transplantation. We profiled the blood microbiome using 16S rRNA gene sequencing of the V4-V5 hypervariable region and additionally evaluated the gut microbiota in a subset of kidney transplant recipients who had gut bacteria detected in the blood. We generated a median of 19,959 sequences per blood specimen and found that most whole blood microbiome profiles consisted of mitochondrial DNA. While we did not identify classically pathogenic bacteria in the blood such as Escherichia, Klebsiella, and Enterococcus, we identified 25 gut bacterial taxa at very low levels in the blood of 22 kidney transplant recipients. For 9 of these kidney transplant recipients the same bacterial taxa detected in the blood were also identified in the gut microbiota. Our study is one of the first to show the detection of gut bacterial DNA in the blood of kidney transplant patients.

Hospital-acquired infections driven by ESKAPEE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) are highly prevalent. Premise plumbing, sinks and drains, seeds these organisms into patient environments via aerosolization and subsequent surface contamination. We measured viable ESKAPEE pathogens and overall microbial communities in and around sinks in two high-burden hospitals in La Paz, Bolivia, using culture and 16S rDNA sequencing. In a prospective observational study (May-August 2025), we collected 233 surface swabs and 39 air samples across four sink-related surface categories and in room air. Samples were plated on selective media for ESKAPEE identification and quantified as colony-forming units (CFU) normalized to 100 cm2 or 6000 L. DNA was extracted, and the full 16S rDNA gene was sequenced on PacBio Revio, analyzed via DADA2/QIIME2 and R. We detected viable presumptive ESKAPEE pathogens in 74.7% surface swabs and 74.4% air samples. Sink basins were most contaminated (mean 31CFU/100 cm2, 95 % CI16-46); concentrations declined with distance from the drain. Klebsiella/Enterobacter spp. showed the highest mean concentration across samples; S. aureus was most frequently detected (54.4% of samples). Hospital-specific differences were evident in culture positivity (Hospital A 85% vs. Hospital B 66.9%) and community composition (PERMANOVA P = 0.001; sample location explained 21.9% vs. 11.7% of variation). 16S profiling confirmed elevated relative abundances of Klebsiella, Enterococcus, and Enterobacter in basins relative to distant surfaces and air. The hospitals studied had high levels of ESKAPEE pathogens, underscoring the need for control measures.

IntroductionThe COVID-19 pandemic demonstrated the need for comprehensive, cost-effective surveillance systems integrating multiple data streams. This study directly compares SARS-CoV-2 genomic data from wastewater-based surveillance (WBS) and clinical diagnostic testing (CDT) to evaluate lineage diversity, detection timing, and persistence patterns that could inform integrated surveillance strategies. MethodsWe analyzed SARS-CoV-2 genomic data from Alberta, Canada (July 2022 - March 2025), encompassing 13 municipal wastewater treatment plants covering 80% of the provincial population and clinical samples from provincial diagnostic testing. Clinical samples (n=28,610) and wastewater samples (n=1,685) were sequenced using a tiled amplicon approach. We compared lineage richness over time, lead time for first detection using collection dates and explored four additional wastewater metrics: abundance at first detection, peak abundance, time to peak abundance, and total time detected. The comparison grouped lineages into those found only in WBS and those that were seen in both WBS and CDT. ResultsOf the 2,586 unique lineages identified over the study period, 1,588 (61.1%) appeared exclusively in WBS, 42 (1.6%) only in CDT, and 956 (36.9%) in both systems. WBS consistently demonstrated higher monthly lineage richness (95-660 lineages) compared to CDT (23-160 lineages). While WBS detected lineages an average of almost 12 days earlier than CDT, the most frequent pattern showed CDT detection first by 8 days, indicating substantial variability. Lineages detected in both systems showed significantly higher initial relative abundance, peak relative abundance, longer persistence, and delayed time to peak compared to WBS-only lineages (all p<0.0001). ConclusionsWBS and CDT provide complementary surveillance capabilities with distinct strengths. Rather than relying on "first detection" as an early warning metric, integrated surveillance should prioritize concordance patterns and abundance metrics that indicate lineages with sustainable transmission potential. These findings support developing surveillance frameworks that strategically combine population-level WBS monitoring with case-linked CDT data for more effective public health response. KEY MESSAGESO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIWBS can detect SARS-CoV-2 and other pathogens at the population level and has been described as an early warning system, while CDT provides case-linked genomic data but may be biased towards symptomatic, high-risk or healthcare-seeking individuals. C_LIO_LIBoth surveillance methods were used during the COVID-19 pandemic, but it remains uncertain how to best integrate WBS and CDT genomics and which WBS metrics are most informative. C_LI What this study addsO_LIThis study provides the first direct comparison of SARS-CoV-2 genomic data from WBS and CDT processed by a single laboratory over nearly three years. C_LIO_LIWBS consistently captured greater lineage diversity than CDT, but "first detection" showed substantial variability, with lineages frequently detected in clinical samples before wastewater. C_LIO_LILineages identified in both surveillance systems showed distinct signatures: higher peak abundance and longer persistence, suggesting these concordance patterns are more reliable indicators than timing alone. C_LI How this study might affect research, practice or policyO_LIIntegrated surveillance frameworks should prioritize monitoring concordance between WBS and CDT, using abundance and persistence metrics to identify lineages with significant transmission potential. C_LIO_LIThe complementary strengths of these systems support their combined use for cost-effective surveillance with WBS monitoring population trends and CDT providing clinical context for targeted interventions. C_LI

Acinetobacter baumannii is a critical pathogen which can cause hospital-acquired infections, particularly urinary tract infections (UTIs). The antimicrobial resistance (AMR) of A. baumannii is rising which poses a significant challenge to clinical management. Nitroxoline, an old antibiotic for treating uncomplicated UTIs, has gained renewed interest as a potential therapeutic option. Here, we investigates the bactericidal activity of nitroxoline against 34 A. baumannii (17 carbapenem-resistant and 17 carbapenem-sensitive isolates) collected from UTI patients. Nitroxoline exhibited a biphasic bactericidal effect, characterized by enhanced efficacy up to an optimal bactericidal concentration (OBC), followed by declined activity at higher nitroxoline concentrations. The OBCs, minimum bactericidal concentration (MBC), minimum inhibitory concentration (MIC), and time-killing curves were evaluated to elucidate bactericidal activity. Raman deuterium stable isotope probing (Raman-DIP) was employed to validate nitroxolines bactericidal effect and its impact on bacterial metabolic activity and survival rates. These results demonstrate that nitroxoline exhibits excellent inhibitory and bactericidal activity against A. baumannii. While nitroxoline exhibits biphasic bactericidal activity with OBC50/90 values of 4/8 mg/L. Raman spectroscopy identified a decreased C-D ratio as nitroxoline concentration increased, indicating reduced metabolic activity. Notably, an inverse correlation (r = -0.7594, p <0.0001) was observed between bacterial survival and the ccratio at concentrations above the OBC. These findings underscore the necessity of optimizing dosing regimens to enhance nitroxolines therapeutic efficacy and alleviate AMR development. Raman-DIP emerges as a robust tool for assessing nitroxolines effects on bacterial metabolism and determining MIC, offering valuable insights for future clinical applications.

Hypermucoviscosity(HMV) is a phenotype that is commonly associated with hypervirulence in Klebsiella pneumoniae. The factors that contribute to the emergence of HMV subpopulations remain unclear. In this study, eight K. pneumoniae strains were recovered from an inpatient who were hospitalized for 20 days. Three of the isolates exhibited a non-HMV phenotype, which was concomitant with increased biofilm formation and higher siderophore secretion than the other five HMV isolates. All eight isolates were highly susceptible to serum killing, albeit HMV strains were remarkably more infective than non-HMV counterparts in a mouse model of infection. Whole genome sequencing(WGS) showed that the eight isolates belonged to the K57-ST412 lineage. Average nucleotide identity(ANI) analysis indicated that eight isolates share 99.96% to 99.99% similarity and were confirmed to be the same clone. Through comparative genomics analysis, 12 non-synonymous mutations were found among these isolates, seven of which in the non-HMV variants, including rmpA(R96G) and wbap (S435R), which are assumed to be associated with the non-HMV phenotype. The mutations manB(G440L), dmsB(R193W) and tkt(A643N) occurred in HMV isolates only. RNA-Seq and RT-qPCR revealed transcripts of genes involved in transporter activity, carbohydrate metabolism and energy metabolism, including cysK, paaF, vasD, celC and fruA, to be significantly dysregulated in the non-HMV strain K201060 compared to the HMV strain K201059, suggesting a participation in HMV phenotype development. This study suggests that co-occurrence of HMV and non-HMV phenotypes in the same clonal population may be mediated by mutational mechanisms as well as by certain genes involved in transport and central metabolism. ImportanceK. pneumoniae with a hypermucoviscosity(HMV) phenotype is a community-acquired pathogen that associated with increased invasiveness and pathogenicity, and underlying diseases are the most common comorbid risk factors inducing metastatic complications. HMV was earlier attributed to the overproduction of capsular polysaccharide, and more data point to the possibility of several causes contribute to this bacterial phenotype. Here, we describe a unique event in which the same clonal population showed both HMV and non-HMV characteristics. Studies have demonstrated that this process is influenced by mutational processes and genes related to transport and central metabolism. These finding provide fresh insight into the mechanisms between behind co-occurrence of HMV and non-HMV phenotypes in monoclonal populations as well as potentially being critical in developing strategies to control the further spread of HMV K. pneumoniae.

To evaluate the diagnostic performance of clinical shotgun metagenomic sequencing (SMg) for detecting medically relevant fungi and parasites compared with standard of care (SoC), and to define read-based thresholds for interpretation, we retrospectively analyzed 198 clinical samples from 187 patients across four university hospitals (2018-2022): blood (n=37), faeces (n=63), respiratory fluids (n=54), other biological fluids (n=24), and tissue biopsies (n=20). Total nucleic acids were sequenced ([&ge;]10 million reads per library) and processed with MetaMIC v2.2.1. Data were normalized as reads per million (RPM). Receiver operating characteristic analyses were used to derive optimal RPM thresholds by sample type. SoC identified microorganisms in 152/198 samples (76.8%). All 46 SoC-negative samples were also negative by SMg. At the genus level, SoC identified 187 taxa and SMg 175. Of these, 147 (78.6%) were detected by both methods, 40 (21.4%) by SoC only, and 28 (14.9%) by SMg only. The overall genus-level F1-score was 0.84. Quantification cycle (Cq) values (n=57) correlated inversely with RPM (p<0.001), and no false negatives occurred with Cq<28.6. Optimal thresholds were 0.06 RPM for faeces (AUC 0.89), 0.07 for respiratory fluids (AUC 0.93; sensitivity 88.9%, specificity 90.7%), 0.09 for blood (AUC 0.99), 0.19 for other fluids (AUC 0.94), and 0.57 for biopsies (AUC 0.89). A global threshold of 0.06 RPM yielded an AUC of 0.92 (sensitivity 88.9%, specificity 88.5%). A pragmatic uniform 0.1 RPM threshold maintained performance, while sample-type specific thresholds further improved accuracy, supporting standardized implementation of clinical metagenomics for fungal and parasitic diagnostics.

BackgroundThe accurate and timely identification of bacterial pathogens in low-diversity samples is critical for clinical diagnostics, yet traditional culture-based methods often fail due to prior antibiotic exposure or fastidious growth requirements. While 16S rRNA gene sequencing provides a culture-independent alternative, traditional Sanger sequencing cannot resolve polymicrobial infections, and short-read sequencing platforms are often limited by long turnaround time and high associated costs. Oxford Nanopore Technologies (ONT) offers a promising solution through rapid turnaround times and lower costs; however, its clinical adoption is hindered by a lack of standardized, validated protocols and large-scale comparative data. MethodsWe developed a rapid, cost-effective 16S rRNA diagnostic workflow using ONT and benchmarked its performance against an Illumina Next-Generation Sequencing (NGS) workflow. The pipeline utilizes an in vitro diagnostic (IVD) certified amplification protocol targeting the V3-V4 region with DNA-free reagents to minimize contamination in low-biomass specimens. We first verified the detection limits using dilution series of pure and mixed bacterial cultures. Subsequently, the workflow was prospectively applied to 101 clinical samples, with results evaluated retrospectively against Illumina data and subjected to rigorous clinical review to determine infection plausibility. ResultsComparative analysis revealed high concordance between NGS platforms across the clinical cohort, achieving a weighted species overlap of 93.5 {+/-} 7.6% and a Cohens kappa of 0.81 {+/-} 0.04 upon clinical review. While Illumina demonstrated slightly higher sensitivity at the lowest microbial concentrations in dilution series experiments, ONT generated sequences with comparable average accuracy (99.9 {+/-} 0.39% for ONT, 99.8 {+/-} 0.42% for Illumina). Crucially, the ONT workflow was significantly more efficient, requiring approximately 50 hours less total processing time and proving more cost-effective for small-batch, on-demand diagnostics than the Illumina workflow. ConclusionsThis study offers strong supporting evidence for the integration of 16S nanopore sequencing into routine infectious disease diagnostics. Our findings demonstrate that 16S nanopore sequencing is a feasible, time-efficient, and high-resolution alternative to established NGS methods, particularly suited for rapid, decentralized clinical implementation for diagnostic sequencing of low-diversity samples.

BackgroundEarly diagnosis of pathogenic bacteria is crucial for the treatment of community-acquired pneumonia (CAP), but conventional diagnostics are limited by sampling difficulties. Oral microbiota has also been explored as a noninvasive biomarker of lung diseases, but its role in CAP has been neglected. We aimed to investigate whether the oral bacteria can be novel non-invasive biomarkers for CAP. MethodsOral swab samples were collected from 29 patients with CAP and 26 healthy volunteers and characterized based on clinical parameters and 16S rRNA profiling of oral bacteria. A predict functional profiling was performed for the functional and metabolic changes in oral microbial communities. ResultsOral microbial of patients with CAP had a lower diversity than healthy group. And the dominant bacteria were Streptococcus, Prevotella and Neisseria in CAP. Higher abundance of Prevotella (particularly Prevotella_melaninogenica), Veillonella and Campylobacter, and lower abundance of Neisseria and Fusobacterium were detected in CAP group. Analysis of the functional potential of oral microbiota demonstrated that the pathway involving infectious disease was overrepresented in the CAP groups relative to that in the healthy controls. ConclusionsOral microbial dysbiosis was found in patients with CAP, supporting the use of this non-invasive specimen for biomarkers of CAP. HighlightsO_LIOral microbial diversity was significantly lower in community-acquired pneumonia (CAP) patients than healthy controls. C_LIO_LIGenera Neisseria and Fusobacterium were decreased, while genera Prevotella, Veillonella and Campylobacter were increased in CAP versus healthy controls. C_LIO_LIOral microbiota-based biomarkers can serve as a promising non-invasive tool for the detection of CAP. C_LI

Chemical disinfectants and water-wash methods are widely employed in sanitizing broiler chicken barns. Previous studies showed that chemical disinfectants affect environmental microbial composition and antibiotic resistance genes (ARGs). However, little is known regarding how barn disinfection treatments impact the chicken gut resistome and microbial functionality. The current study compared the effects of chemical disinfection and water-wash method on the gut microbiome and resistome of commercial broilers using a crossover experimental design after 2 production cycles at 7 barns. Shotgun metagenomic sequencing performed on cecal contents collected at day 7 and 30 also allowed evaluation of age-associated characteristics of microbiome. Age of the chickens had the largest effects on the resistome, with younger birds having increased relative abundance of total ARGs (P<0.05) and differences in resistance mechanism, however, functional and resistome differences were also identified by barn sanitation practice. At day 7, chickens in chemically-disinfected barns had decreased functional capacity related to amino acid synthesis compared to the water-wash group. Additionally, genes related to stringent response were enriched in chickens raised under chemically-disinfected condition (FDR-P<0.05), suggesting selection for stress resistance. Consistently, lower abundance of genetic pathways encoding amino acid biosynthesis associated with cecal Helicobacter pullorum was observed in the disinfection group at day 30 compared to the water-wash group, with the same pattern in short-chain fatty acid biosynthesis (FDR-P<0.05). Overall, while the use of disinfectants in barn sanitation slightly affected the relative abundance of some ARGs in the gut, age had a dominant effect on the microbial functionality and resistome. ImportanceThis is the first study to evaluate the effect of sanitation practices on microbial functional capacity and resistome of chickens in a commercial setting. It is also amongst the biggest metagenomics studies on the gut microbiome of broiler chickens. It provides new insights into the changes in resistance profiles with age that agree with other studies examining maturation of the microbiome in other species. Finally, the current study provides valuable insights for informing industry sanitation practices and future studies on broiler gut microbiome and resistome.