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The prevalence of many chronic diseases has increased over the last decades. It has been postulated that dysbiosis driven by environmental factors such as antibiotic use is shifting the microbiome in ways that increase inflammation and the onset of chronic disease. Dysbiosis can be defined through the loss or gain of bacteria that either promote health or disease, respectively. Here we use multiple independent datasets to determine the nature of dysbiosis for a cluster of chronic diseases that includes urinary stone disease (USD), obesity, diabetes, cardiovascular disease, and kidney disease, which often exist as co-morbidities. For all disease states, individuals exhibited a statistically significant association with antibiotics in the last year compared to healthy counterparts. There was also a statistically significant association between antibiotic use and gut microbiota composition. Furthermore, each disease state was associated with a loss of microbial diversity in the gut. Three genera, Bacteroides, Prevotella , and Ruminococcus , were the most common dysbiotic taxa in terms of being enriched or depleted in disease populations and was driven in part by the diversity of operational taxonomic units (OTUs) within these genera. Results of the cross-sectional analysis suggest that antibiotic-driven loss of microbial diversity may increase the risk for chronic disease. However, longitudinal studies are needed to confirm the causative effect of diversity loss for chronic disease risk.

The prevalence of urinary stone disease (USD) is rapidly rising. However, the factors driving this increase are unknown. Recent microbiome studies suggest that dysbiosis may in part contribute to the increasing prevalence. The objective of the current study was to determine the nature and location of dysbiosis associated with USD. We conducted microbiome analysis from the gastrointestinal and urinary tracts, along with a metabolomic analysis of the urinary metabolome, from subjects with an active episode of USD or no history of the disease. Higher rates of antibiotic use among USD patients along with integrated microbiome and metabolomic results support the hypothesis that USD is associated with an antibiotic-driven shift in the microbiome from one that protects against USD to one that promotes the disease. Specifically, our study implicates urinary tract Lactobacillus and Enterobacteriaceae in protective and pathogenic roles for USD, respectively, which conventional, culture-based methods of bacterial analysis from urine and kidney stones would not necessarily detect. Results suggest that antibiotics produce a long-term shift in the microbiome that may increase the risk for USD, with the urinary tract microbiome holding more relevance for USD than the gut microbiome.

Antimicrobial coatings for medical implants are critical in preventing device failures and infections. Antibiotics are often used as prophylactic or coatings but fail to prevent biofilm formation and drive antibiotic resistance. Herein, the antibacterial and antibiofilm activities of different polyhydroxy fullerene-based metal nanoparticle coatings on polyurethane discs were quantified after exposure to Escherichia coli . Gold-silver nanoparticles (GSNP) exhibited superior antibacterial activity compared to other silver-containing nanoparticles. GSNPs were evaluated against Escherichia coli , Enterococcus faecalis , Enterobacter hormaechei , Klebsiella oxytoca , Staphylococcus aureus and Staphylococcus epidermidis isolated from ureteral stents and inflatable penile prostheses and achieved 100% reduction of all tested urologic pathogens at physiological relevant bacterial loads ( p  < 0.0001). GSNPs inactivate bacteria by reactive oxygen species production with the estimated minimum inhibitory concentrations slightly higher for Gram-positive than Gram-negative bacteria with highest observed for S. epidermidis at 2.23 µg/mL. Safety studies with fibroblasts demonstrate that GSNPs at estimated minimum inhibitory concentrations have minimal effect (< 20%) on cell viability. Further, the GSNPs were able to reduce bacteria by six logs more than commercial nanoparticles. GSNPs represent a promising strategy for preventing biofilm formation on medical devices and implants due to their broad antibacterial activity and low toxicity.

Clinical studies of the urinary tract microbiome, termed urobiome, suggest a direct, antibiotic-dependent, impact of the urobiome on kidney physiology. However, evidence for kidney bacteria comes from indirect sources or infected tissue. Further, it is unclear how antibiotics impact kidney bacteria. Here we show direct evidence for the presence of bacteria in the kidneys, with microniches in nephrons. In murine kidneys, administration of cefazolin, a commonly used perioperative antibiotic, led to a loss of uroprotective Lactobacillus spp . and proliferation of Enterobacteriaceae (which includes many known uropathogens). This effect was dependent on treatment duration, with recovery post treatment. Uroprotective L. crispatus and a strain of stone-associated E. coli differentially influenced calcium oxalate (CaOx) crystallization through the incorporation of CaOx inhibitors or promoters, respectively. In humans, microbial signatures were identified in the kidney, with unique niches between the glomeruli and tubules, established through RNA sequencing analysis and direct imaging of two independent populations. Collectively, findings support the hypothesis that the kidneys harbor a stable and antibiotic-responsive microbiota that can influence CaOx lithogenesis. The presence of unique, age-dependent microbial signatures in the glomeruli and tubuli carry implications for non-infectious kidney diseases. Here, the authors provide evidence that the renal microbiome can be disrupted by antibiotics, leading to differential effects on anti-lithogenic taxa like Lactobacillus and pro-lithogenic bacteria such as Enterobacteriaceae .

Microbiome studies in low-biomass environments face challenges due to contamination. However, even after implementing strict contamination prevention, control, and analysis measures, the impact of residual contamination on the validity of statistical outcomes in such studies remains a topic of ongoing discussion. Our analyses reveal that key drivers of microbiome study outcomes are group dissimilarity and the number of unique taxa, while contamination has minimal impact on statistical outcomes, primarily limited to the number of differentially abundant taxa detected. A common approach to contamination control involves removing taxa based on published contaminant lists. However, our analysis shows that these lists are highly inconsistent across studies, limiting reliability. Instead, our results support the use of internal negative controls as the most robust means of identifying and mitigating contamination. Collectively, data show that low-biomass microbiome studies have reduced power to detect differences between groups. However, when differences are observed, they are unlikely to be contamination-driven. By prioritizing validated protocols that prevent, assess, and eliminate contaminants through the use of internal negative controls, researchers can minimize the impact of contamination and improve the reliability of results.

Studies focused on the microbiome broadly support the hypothesis that the microbiome influences the onset of chronic diseases such as urinary stone disease. However, it is unclear what environmental factors shape the microbiome in ways that increase the risk for chronic disease. To determine whether functionally relevant questions associated with the urinary or gut microbiome and urinary stone disease (USD) can be answered from metagenome-wide association studies (MWAS), we performed the most comprehensive meta-analysis of published clinical MWAS in USD to date, using publicly available data published prior to April 2021. Six relevant studies met inclusion criteria. For alpha-diversity, significant differences were noted between USD status, stone composition, sample type, study location, age, diet, and sex. For beta-diversity, significant differences were noted by USD status, stone composition, sample type, study location, antibiotic use (30 days and 12 months before sampling), sex, hypertension, water intake, body habitus, and age. Prevotella and Lactobacillus in the gut and urinary tract, respectively, were associated with healthy individuals, while Enterobacteriaceae was associated with USD in the urine and stones. Paradoxically, other Prevotella strains were also strongly associated with USD in the gut microbiome. When data were analyzed together, USD status, stone composition, age group, and study location were the predominant factors associated with microbiome composition. Meta-analysis showed significant microbiome differences based on USD status, stone composition, age group or study location. However, analyses were limited by a lack of public data from published studies, metadata collected, and differing study protocols. Results highlight the need for field-specific standardization of experimental protocols in terms of sample collection procedures and the anatomical niches to assess, as well as in defining clinically relevant metadata and subphenotypes such as stone composition. IMPORTANCE Studies focused on the microbiome broadly support the hypothesis that the microbiome influences the onset of chronic diseases such as urinary stone disease. However, it is unclear what environmental factors shape the microbiome in ways that increase the risk for chronic disease. In addition, it is unclear how differences in study methodology can impact the results of clinical metagenome-wide association studies. In the current meta-analysis, we show that age, stone composition, and study location are the predominant factors that associate with the microbiome and USD status. Furthermore, we reveal differences in results based on specific analytical protocols, which impacts the interpretation of any microbiome study.

Inherited and germ-line de novo copy number variants (CNVs) are increasingly found to be correlated with human developmental and cancerous phenotypes. Several models for template switching during replication have been proposed to explain the generation of these gross chromosomal rearrangements. We proposed a model of template switching (ODIRA—origin dependent inverted repeat amplification) in which simultaneous ligation of the leading and lagging strands at diverging replication forks could generate segmental inverted triplications through an extrachromosomal inverted circular intermediate. Here, we created a genetic assay using split- ura3 cassettes to trap the proposed inverted intermediate. However, instead of recovering circular inverted intermediates, we found inverted linear chromosomal fragments ending in native telomeres—suggesting that a template switch had occurred at the centromere-proximal fork of a replication bubble. As telomeric inverted hairpin fragments can also be created through double strand breaks we tested whether replication errors or repair of double stranded DNA breaks were the most likely initiating event. The results from CRISPR/Cas9 cleavage experiments and growth in the replication inhibitor hydroxyurea indicate that it is a replication error, not a double stranded break that creates the inverted junctions. Since inverted amplicons of the SUL1 gene occur during long-term growth in sulfate-limited chemostats, we sequenced evolved populations to look for evidence of linear intermediates formed by an error in replication. All of the data are compatible with a two-step version of the ODIRA model in which sequential template switching at short inverted repeats between the leading and lagging strands at a replication fork, followed by integration via homologous recombination, generates inverted interstitial triplications.

As sequencing technologies have advanced, the amount of information regarding the composition of bacterial communities from various environments (for example, skin or soil) has grown exponentially. To date, most work has focused on cataloging taxa present in samples and determining whether the distribution of taxa shifts with exogenous covariates. However, important questions regarding how taxa interact with each other and their environment remain open thus preventing in-depth ecological understanding of microbiomes. Time-series data from 16S rDNA amplicon sequencing are becoming more common within microbial ecology, but methods to infer ecological interactions from these longitudinal data are limited. We address this gap by presenting a method of analysis using Poisson regression fit with an elastic-net penalty that (1) takes advantage of the fact that the data are time series; (2) constrains estimates to allow for the possibility of many more interactions than data; and (3) is scalable enough to handle data consisting of thousands of taxa. We test the method on gut microbiome data from white-throated woodrats ( Neotoma albigula ) that were fed varying amounts of the plant secondary compound oxalate over a period of 22 days to estimate interactions between OTUs and their environment.

Oxalate, a compound produced by many edible plants and as a terminal metabolite in the liver of mammals, is a toxin that has a detrimental role to human health. Humans and other mammals do possess enzymatic systems to degrade oxalate. Moreover, numerous oxalate-degrading bacteria reside in the mammalian gut and, thus, provide an important function for hosts. The current review focuses on the environmental factors that influence the efficacy of probiotic oxalate-degrading bacteria, relative to oxalate metabolism. We describe the mechanism of oxalate catabolism and its consumption by obligate and facultative anaerobic oxalate-degrading bacteria, in both in vitro and in vivo environments. We also explore the environmental variables that impact oxalate degradation. Studies on single species degrade oxalate have not shown a strong impact on oxalate metabolism, especially in high oxalate conditions such as consumption of foods high in oxalate (such as coffee and chocolate for humans or halogeton in animal feed). Considering effective variables which enhance oxalate degradation could be used in application of effective probiotic as a therapeutic tool in individuals with hyperoxaluria. This study indicates probiotics can be considered a good source of naturally occurring oxalate degrading agent in human colon.

Decades of research have made clear that host-associated microbiomes touch all facets of health. However, effective therapies that target the microbiome have been elusive given its inherent complexity. Here, we experimentally examined diet-microbe-host interactions through a complex systems framework, centered on dietary oxalate. Using multiple, independent molecular, rodent, and in vitro experimental models, we found that microbiome composition influenced multiple oxalate-microbe-host interfaces. Importantly, the administration of the oxalate-degrading specialist, Oxalobacter formigenes, was only effective against a poor oxalate-degrading microbiota background and gives critical new insights into why clinical intervention trials with this species exhibit variable outcomes. Data suggest that, while heterogeneity in the microbiome impacts multiple diet-host-microbe interfaces, metabolic redundancy among diverse microorganisms in specific diet-microbe axes is a critical variable that may impact the efficacy of bacteriotherapies, which can help guide patient and probiotic selection criteria in probiotic clinical trials.