Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences.

Acquisition of the intestinal microbiota begins at birth, and a stable microbial community develops from a succession of key organisms. Disruption of the microbiota during maturation by low-dose antibiotic exposure can alter host metabolism and adiposity. We now show that low-dose penicillin (LDP), delivered from birth, induces metabolic alterations and affects ileal expression of genes involved in immunity. LDP that is limited to early life transiently perturbs the microbiota, which is sufficient to induce sustained effects on body composition, indicating that microbiota interactions in infancy may be critical determinants of long-term host metabolic effects. In addition, LDP enhances the effect of high-fat diet induced obesity. The growth promotion phenotype is transferrable to germ-free hosts by LDP-selected microbiota, showing that the altered microbiota, not antibiotics per se, play a causal role. These studies characterize important variables in early-life microbe-host metabolic interaction and identify several taxa consistently linked with metabolic alterations. PAPERCLIP:

SpaceANOVA: Spatial Co-occurrence Analysis of Cell Types in Multiplex Imaging Data Using Point Process and Functional ANOVA.

Multiplex imaging platforms have enabled the identification of the spatial organization of different types of cells in complex tissue or the tumor microenvironment. Exploring the potential variations in the spatial co-occurrence or colocalization of different cell types across distinct tissue or disease classes can provide significant pathological insights, paving the way for intervention strategies. However, the existing methods in this context either rely on stringent statistical assumptions or suffer from a lack of generalizability. We present a highly powerful method to study differential spatial co-occurrence of cell types across multiple tissue or disease groups, based on the theories of the Poisson point process and functional analysis of variance. Notably, the method accommodates multiple images per subject and addresses the problem of missing tissue regions, commonly encountered due to data-collection complexities. We demonstrate the superior statistical power and robustness of the method in comparison with existing approaches through realistic simulation studies. Furthermore, we apply the method to three real data sets on different diseases collected using different imaging platforms. In particular, one of these data sets reveals novel insights into the spatial characteristics of various types of colorectal adenoma.

Prolonged Antibiotic Exposure during Adolescence Dysregulates Liver Metabolism and Promotes Adiposity in Mice.

Antibiotic administration during early life has been shown to have lasting effects on the gut microbiota, which have been linked to sustained alterations in liver metabolism and adiposity. Recent investigations have discerned that the gut microbiota continues to develop toward an adult-like profile during adolescence. However, the impact of antibiotic exposure during adolescence on metabolism and adiposity is unclear. Herein, a retrospective analysis of Medicaid claims data was performed, which indicated that tetracycline class antibiotics are commonly prescribed for the systemic treatment of adolescent acne. The purpose of this was to discern the impact of a prolonged tetracycline antibiotic exposure during adolescence on the gut microbiota, liver metabolism, and adiposity. Male C57BL/6T specific pathogen-free mice were administered a tetracycline antibiotic during the pubertal/postpubertal adolescent growth phase. Groups were euthanized at different time points to assess immediate and sustained antibiotic treatment effects. Antibiotic exposure during adolescence caused lasting genera-level shifts in the intestinal bacteriome and persistent dysregulation of metabolic pathways in the liver. Dysregulated hepatic metabolism was linked to sustained disruption of the intestinal farnesoid X receptor-fibroblast growth factor 15 axis, a gut-liver endocrine axis that supports metabolic homeostasis. Antibiotic exposure during adolescence increased subcutaneous, visceral, and marrow adiposity, which intriguingly manifested following antibiotic therapy. This preclinical work highlights that prolonged antibiotic courses for the clinical treatment of adolescent acne may have unintended deleterious effects on liver metabolism and adiposity.

The adolescent and young adult microbiome and its association with substance use: a scoping review.

AIMS: The microbiome is a critical factor in health throughout human development. The aims of this scoping review are to (i) elucidate the differences between the youth (post-natal day 21-65 for rodents, 2-7 years for non-human primates, and 10-25 years for humans) microbiome with other life stages and (ii) identify youth-specific microbial changes associated with substance use. METHODS: Peer-reviewed studies published up to May 2023 were identified in PubMed and SCOPUS and included gut and oral microbiome studies from rodents, non-human primates, and humans (N = 1733). Twenty-six articles were determined eligible based on inclusion criteria (aim 1: n = 19, aim 2: n = 7). RESULTS: The adolescent and young adult oral and gut microbiomes are distinct compared to other life stages, within both non-human and human models. While there is limited research in this area, the microbiome appears to be vulnerable to substance use exposure earlier in life, including substances commonly initiated and escalated during adolescence and young adulthood (i.e. alcohol, cannabis, and tobacco). CONCLUSIONS: Studies across the lifespan indicate that adolescence and young adulthood are distinct periods of development, where the microbiome is sensitive to exposures, including substance use. There is a need for more studies focused on the adolescent and young adult microbiome and substance use, as well as focused on the oral microbiome during this developmental period. Understanding the gut and oral microbiome during adolescence and young adulthood may provide insight into the pathophysiology of substance use disorders.

Longitudinal gut microbiome analyses and blooms of pathogenic strains during lupus disease flares.

OBJECTIVE: Whereas genetic susceptibility for systemic lupus erythematosus (SLE) has been well explored, the triggers for clinical disease flares remain elusive. To investigate relationships between microbiota community resilience and disease activity, we performed the first longitudinal analyses of lupus gut-microbiota communities. METHODS: In an observational study, taxononomic analyses, including multivariate analysis of ß-diversity, assessed time-dependent alterations in faecal communities from patients and healthy controls. From gut blooms, strains were isolated, with genomes and associated glycans analysed. RESULTS: Multivariate analyses documented that, unlike healthy controls, significant temporal community-wide ecological microbiota instability was common in SLE patients, and transient intestinal growth spikes of several pathogenic species were documented. Expansions of only the anaerobic commensal, Ruminococcus (blautia) gnavus (RG) occurred at times of high-disease activity, and were detected in almost half of patients during lupus nephritis (LN) disease flares. Whole genome sequence analysis of RG strains isolated during these flares documented 34 genes postulated to aid adaptation and expansion within a host with an inflammatory condition. Yet, the most specific feature of strains found during lupus flares was the common expression of a novel type of cell membrane-associated lipoglycan. These lipoglycans share conserved structural features documented by mass spectroscopy, and highly immunogenic repetitive antigenic-determinants, recognised by high-level serum IgG2 antibodies, that spontaneously arose, concurrent with RG blooms and lupus flares. CONCLUSIONS: Our findings rationalise how blooms of the RG pathobiont may be common drivers of clinical flares of often remitting-relapsing lupus disease, and highlight the potential pathogenic properties of specific strains isolated from active LN patients.

Antibiotic prophylaxis dysregulates dental implant placement surgery-induced osteoimmune wound healing and attenuates the alveolar bone-implant interface in mice.

AIM: Antimicrobial-induced shifts in commensal oral microbiota can dysregulate helper T-cell oral immunity to affect osteoclast-osteoblast actions in alveolar bone. Antibiotic prophylaxis is commonly performed with dental implant placement surgery to prevent post-surgical complications. However, antibiotic prophylaxis effects on osteoimmune processes supporting dental implant osseointegration are unknown. The aim of the study was to discern the impact of antibiotic prophylaxis on dental implant placement surgery-induced osteoimmune wound healing and osseointegration. MATERIALS AND METHODS: We performed SHAM or dental implant placement surgery in mice. Groups were administered prophylactic antibiotics (amoxicillin or clindamycin) or vehicle. Gingival bacteriome was assessed via 16S sequencing. Helper T-cell oral immunity was evaluated by flow cytometry. Osteoclasts and osteoblasts were assessed via histomorphometry. Implant osseointegration was evaluated by micro-computed tomography. RESULTS: Dental implant placement surgery up-regulated TH 1, TH 2 and TREG cells in cervical lymph nodes (CLNs), which infers helper T-cell oral immunity contributes to dental implant placement osseous wound healing. Prophylactic antibiotics with dental implant placement surgery caused a bacterial dysbiosis, suppressed TH 1, TH 2 and TREG cells in CLNs, reduced osteoclasts and osteoblasts lining peri-implant alveolar bone, and attenuated the alveolar bone-implant interface. CONCLUSIONS: Antibiotic prophylaxis dysregulates dental implant placement surgery-induced osteoimmune wound healing and attenuates the alveolar bone-implant interface in mice.

Antimicrobial-induced oral dysbiosis exacerbates naturally occurring alveolar bone loss.

Periodontitis-mediated alveolar bone loss is caused by dysbiotic shifts in the commensal oral microbiota that upregulate proinflammatory osteoimmune responses. The study purpose was to determine whether antimicrobial-induced disruption of the commensal microbiota has deleterious effects on alveolar bone. We administered an antibiotic cocktail, minocycline, or vehicle-control to sex-matched C57BL/6T mice from age 6- to 12 weeks. Antibiotic cocktail and minocycline had catabolic effects on alveolar bone in specific-pathogen-free (SPF) mice. We then administered minocycline or vehicle-control to male mice reared under SPF and germ-free conditions, and we subjected minocycline-treated SPF mice to chlorhexidine oral antiseptic rinses. Alveolar bone loss was greater in vehicle-treated SPF versus germ-free mice, demonstrating that the commensal microbiota drives naturally occurring alveolar bone loss. Minocycline- versus vehicle-treated germ-free mice had similar alveolar bone loss outcomes, implying that antimicrobial-driven alveolar bone loss is microbiota dependent. Minocycline induced phylum-level shifts in the oral bacteriome and exacerbated naturally occurring alveolar bone loss in SPF mice. Chlorhexidine further disrupted the oral bacteriome and worsened alveolar bone loss in minocycline-treated SPF mice, validating that antimicrobial-induced oral dysbiosis has deleterious effects on alveolar bone. Minocycline enhanced osteoclast size and interface with alveolar bone in SPF mice. Neutrophils and plasmacytoid dendritic cells were upregulated in cervical lymph nodes of minocycline-treated SPF mice. Paralleling the upregulated proinflammatory innate immune cells, minocycline therapy increased TH 1 and TH 17 cells that have known pro-osteoclastic actions in the alveolar bone. This report reveals that antimicrobial perturbation of the commensal microbiota induces a proinflammatory oral dysbiotic state that exacerbates naturally occurring alveolar bone loss.

A phylogenetic approach for weighting genetic sequences.

BACKGROUND: Many important applications in bioinformatics, including sequence alignment and protein family profiling, employ sequence weighting schemes to mitigate the effects of non-independence of homologous sequences and under- or over-representation of certain taxa in a dataset. These schemes aim to assign high weights to sequences that are 'novel' compared to the others in the same dataset, and low weights to sequences that are over-represented. RESULTS: We formalise this principle by rigorously defining the evolutionary 'novelty' of a sequence within an alignment. This results in new sequence weights that we call 'phylogenetic novelty scores'. These scores have various desirable properties, and we showcase their use by considering, as an example application, the inference of character frequencies at an alignment column-important, for example, in protein family profiling. We give computationally efficient algorithms for calculating our scores and, using simulations, show that they are versatile and can improve the accuracy of character frequency estimation compared to existing sequence weighting schemes. CONCLUSIONS: Our phylogenetic novelty scores can be useful when an evolutionarily meaningful system for adjusting for uneven taxon sampling is desired. They have numerous possible applications, including estimation of evolutionary conservation scores and sequence logos, identification of targets in conservation biology, and improving and measuring sequence alignment accuracy.

A simple approximation to bias in the genetic effect estimates when multiple disease states share a clinical diagnosis.

Case-control genome-wide association studies (CC-GWAS) might provide valuable clues to the underlying pathophysiologic mechanisms of complex diseases, such as neurodegenerative disease and cancer. A commonly overlooked complication is that multiple distinct disease states might present with the same set of symptoms and hence share a clinical diagnosis. These disease states can only be distinguished based on a biomarker evaluation that might not be feasible in the whole set of cases in the large number of samples that are typically needed for CC-GWAS. Instead, the biomarkers are measured on a subset of cases. Or an external reliability study estimates the frequencies of the disease states of interest within the clinically diagnosed set of cases. These frequencies often vary by the genetic and/or nongenetic variables. We derive a simple approximation that relates the genetic effect estimates obtained in a traditional logistic regression model with the clinical diagnosis as the outcome variable to the genetic effect estimates in the relationship to the true disease state of interest. We performed simulation studies to assess the accuracy of the approximation that we have derived. We next applied the derived approximation to the analysis of the genetic basis of the innate immune system of Alzheimer's disease.

A simple approximation to the bias of gene-environment interactions in case-control studies with silent disease.

One of the most important research areas in case-control Genome-Wide Association Studies is to determine how the effect of a genotype varies across the environment or to measure the gene-environment interaction (G × E). We consider the scenario when some of the "healthy" controls actually have the disease and when the frequency of these latent cases varies by the environmental variable of interest. In this scenario, performing logistic regression with the clinically diagnosed disease status as an outcome variable and will result in biased estimates of G × E interaction. Here, we derive a general theoretical approximation to the bias in the estimates of the G × E interaction and show, through extensive simulation, that this approximation is accurate in finite samples. Moreover, we apply this approximation to evaluate the bias in the effect estimates of the genetic variants related to mitochondrial proteins a large-scale prostate cancer study.

Antibiotic Perturbation of Gut Microbiota Dysregulates Osteoimmune Cross Talk in Postpubertal Skeletal Development.

Commensal gut microbiota-host immune responses are experimentally delineated via gnotobiotic animal models or alternatively by antibiotic perturbation of gut microbiota. Osteoimmunology investigations in germ-free mice, revealing that gut microbiota immunomodulatory actions critically regulate physiologic skeletal development, highlight that antibiotic perturbation of gut microbiota may dysregulate normal osteoimmunological processes. We investigated the impact of antibiotic disruption of gut microbiota on osteoimmune response effects in postpubertal skeletal development. Sex-matched C57BL/6T mice were administered broad-spectrum antibiotics or vehicle-control from the age of 6 to 12 weeks. Antibiotic alterations in gut bacterial composition and skeletal morphology were sex dependent. Antibiotics did not influence osteoblastogenesis or endochondral bone formation, but notably enhanced osteoclastogenesis. Unchanged Tnf or Ccl3 expression in marrow and elevated tumor necrosis factor-α and chemokine (C-C motif) ligand 3 in serum indicated that the pro-osteoclastic effects of the antibiotics are driven by increased systemic inflammation. Antibiotic-induced broad changes in adaptive and innate immune cells in mesenteric lymph nodes and spleen demonstrated that the perturbation of gut microbiota drives a state of dysbiotic hyperimmune response at secondary lymphoid tissues draining local gut and systemic circulation. Antibiotics up-regulated the myeloid-derived suppressor cells, immature myeloid progenitor cells known for immunosuppressive properties in pathophysiologic inflammatory conditions. Myeloid-derived suppressor cell-mediated immunosuppression can be antigen specific. Therefore, antibiotic-induced broad suppression of major histocompatibility complex class II antigen presentation genes in bone marrow discerns that antibiotic perturbation of gut microbiota dysregulates critical osteoimmune cross talk.

Lupus nephritis is linked to disease-activity associated expansions and immunity to a gut commensal.

BACKGROUND/PURPOSE: To search for a transmissible agent involved in lupus pathogenesis, we investigated the faecal microbiota of patients with systemic lupus erythematosus (SLE) for candidate pathobiont(s) and evaluated them for special relationships with host immunity. METHODS: In a cross-sectional discovery cohort, matched blood and faecal samples from 61 female patients with SLE were obtained. Faecal 16 S rRNA analyses were performed, and sera profiled for antibacterial and autoantibody responses, with findings validated in two independent lupus cohorts. RESULTS: Compared with controls, the microbiome in patients with SLE showed decreased species richness diversity, with reductions in taxonomic complexity most pronounced in those with high SLE disease activity index (SLEDAI). Notably, patients with SLE had an overall 5-fold greater representation of Ruminococcus gnavus (RG) of the Lachnospiraceae family, and individual communities also displayed reciprocal contractions of a species with putative protective properties. Gut RG abundance correlated with serum antibodies to only 1/8 RG strains tested. Anti-RG antibodies correlated directly with SLEDAI score and antinative DNA levels, but inversely with C3 and C4. These antibodies were primarily against antigen(s) in an RG strain-restricted pool of cell wall lipoglycans. Novel structural features of these purified lipoglycans were characterised by mass spectrometry and NMR. Highest levels of serum anti-RG strain-restricted antibodies were detected in those with active nephritis (including Class III and IV) in the discovery cohort, with findings validated in two independent cohorts. CONCLUSION: These findings suggest a novel paradigm in which specific strains of a gut commensal may contribute to the immune pathogenesis of lupus nephritis.

Longitudinal changes during pregnancy in gut microbiota and methylmercury biomarkers, and reversal of microbe-exposure correlations.

OBJECTIVE: Gut microorganisms contribute to the metabolism of environmental toxicants, including methylmercury (MeHg). Our main objective was to investigate whether associations between biomarkers for prenatal MeHg exposure and maternal gut microbiota differed between early and late gestation. METHODS: Maternal blood and stool samples were collected during early (8.3-17 weeks, n=28) and late (27-36 weeks, n=24) gestation. Total mercury and MeHg concentrations were quantified in biomarkers, and inorganic mercury was estimated by subtraction. The diversity and structure of the gut microbiota were investigated using 16S rRNA gene profiling (n = 52). Biomarkers were dichotomized, and diversity patterns were compared between high/low mercury concentrations. Spearman's correlation was used to assess bivariate associations between MeHg biomarkers (stool, blood, and meconium), and 23 gut microbial taxa (genus or family level, >1% average relative abundance). RESULTS: Within-person and between-person diversity patterns in gut microbiota differed between early/late gestation. The overall composition of the microbiome differed between high/low MeHg concentrations (in blood and stool) during early gestation, but not late gestation. Ten (of 23) taxa were significantly correlated with MeHg biomarkers (increasing or decreasing); however, associations differed, depending on whether the sample was collected during early or late gestation. A total of 43% of associations (69/161) reversed the direction of correlation between early/late gestation. CONCLUSIONS: The time point at which a maternal fecal sample is collected may yield different associations between gut microorganisms and MeHg biomarkers, which may be due in part to remodeling of maternal microbiota during pregnancy. Our results suggest the effectiveness of dietary interventions to reduce prenatal MeHg exposure may differ between early and late gestation.

Human oral microbiome and prospective risk for pancreatic cancer: a population-based nested case-control study.

OBJECTIVE: A history of periodontal disease and the presence of circulating antibodies to selected oral pathogens have been associated with increased risk of pancreatic cancer; however, direct relationships of oral microbes with pancreatic cancer have not been evaluated in prospective studies. We examine the relationship of oral microbiota with subsequent risk of pancreatic cancer in a large nested case-control study. DESIGN: We selected 361 incident adenocarcinoma of pancreas and 371 matched controls from two prospective cohort studies, the American Cancer Society Cancer Prevention Study II and the National Cancer Institute Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. From pre-diagnostic oral wash samples, we characterised the composition of the oral microbiota using bacterial 16S ribosomal RNA (16S rRNA) gene sequencing. The associations between oral microbiota and risk of pancreatic cancer, controlling for the random effect of cohorts and other covariates, were examined using traditional and L1-penalised least absolute shrinkage and selection operator logistic regression. RESULTS: Carriage of oral pathogens, Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans, were associated with higher risk of pancreatic cancer (adjusted OR for presence vs absence=1.60 and 95% CI 1.15 to 2.22; OR=2.20 and 95% CI 1.16 to 4.18, respectively). Phylum Fusobacteria and its genus Leptotrichia were associated with decreased pancreatic cancer risk (OR per per cent increase of relative abundance=0.94 and 95% CI 0.89 to 0.99; OR=0.87 and 95% CI 0.79 to 0.95, respectively). Risks related to these phylotypes remained after exclusion of cases that developed within 2 years of sample collection, reducing the likelihood of reverse causation in this prospective study. CONCLUSIONS: This study provides supportive evidence that oral microbiota may play a role in the aetiology of pancreatic cancer.

A general framework for association analysis of microbial communities on a taxonomic tree.

Motivation: : Association analysis of microbiome composition with disease-related outcomes provides invaluable knowledge towards understanding the roles of microbes in the underlying disease mechanisms. Proper analysis of sparse compositional microbiome data is challenging. Existing methods rely on strong assumptions on the data structure and fail to pinpoint the associated microbial communities. Results: : We develop a general framework to: (i) perform robust association tests for the microbial community that exhibits arbitrary inter-taxa dependencies; (ii) localize lineages on the taxonomic tree that are associated with covariates (e.g. disease status); and (iii) assess the overall association of the whole microbial community with the covariates. Unlike existing methods for microbiome association analysis, our framework does not make any distributional assumptions on the microbiome data; it allows for the adjustment of confounding variables and accommodates excessive zero observations; and it incorporates taxonomic information. We perform extensive simulation studies under a wide-range of scenarios to evaluate the new methods and demonstrate substantial power gain over existing methods. The advantages of the proposed framework are further demonstrated with real datasets from two microbiome studies. The relevant R package miLineage is publicly available. Availability and Implementation: : miLineage package, manual and tutorial are available at https://medschool.vanderbilt.edu/tang-lab/software/miLineage . Contact: z.tang@vanderbilt.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Antibiotics in early life alter the murine colonic microbiome and adiposity.

Antibiotics administered in low doses have been widely used as growth promoters in the agricultural industry since the 1950s, yet the mechanisms for this effect are unclear. Because antimicrobial agents of different classes and varying activity are effective across several vertebrate species, we proposed that such subtherapeutic administration alters the population structure of the gut microbiome as well as its metabolic capabilities. We generated a model of adiposity by giving subtherapeutic antibiotic therapy to young mice and evaluated changes in the composition and capabilities of the gut microbiome. Administration of subtherapeutic antibiotic therapy increased adiposity in young mice and increased hormone levels related to metabolism. We observed substantial taxonomic changes in the microbiome, changes in copies of key genes involved in the metabolism of carbohydrates to short-chain fatty acids, increases in colonic short-chain fatty acid levels, and alterations in the regulation of hepatic metabolism of lipids and cholesterol. In this model, we demonstrate the alteration of early-life murine metabolic homeostasis through antibiotic manipulation.

Multivariate Welch t-test on distances.

MOTIVATION: Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method, however, suffers from loss of power and type I error inflation in the presence of heteroscedasticity and sample size imbalances. RESULTS: We develop a solution in the form of a distance-based Welch t-test, [Formula: see text], for two sample potentially unbalanced and heteroscedastic data. We demonstrate empirically the desirable type I error and power characteristics of the new test. We compare the performance of PERMANOVA and [Formula: see text] in reanalysis of two existing microbiome datasets, where the methodology has originated. AVAILABILITY AND IMPLEMENTATION: The source code for methods and analysis of this article is available at https://github.com/alekseyenko/Tw2 Further guidance on application of these methods can be obtained from the author. CONTACT: alekseye@musc.edu.

PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances.

MOTIVATION: Recent advances in sequencing technology have made it possible to obtain high-throughput data on the composition of microbial communities and to study the effects of dysbiosis on the human host. Analysis of pairwise intersample distances quantifies the association between the microbiome diversity and covariates of interest (e.g. environmental factors, clinical outcomes, treatment groups). In the design of these analyses, multiple choices for distance metrics are available. Most distance-based methods, however, use a single distance and are underpowered if the distance is poorly chosen. In addition, distance-based tests cannot flexibly handle confounding variables, which can result in excessive false-positive findings. RESULTS: We derive presence-weighted UniFrac to complement the existing UniFrac distances for more powerful detection of the variation in species richness. We develop PERMANOVA-S, a new distance-based method that tests the association of microbiome composition with any covariates of interest. PERMANOVA-S improves the commonly-used Permutation Multivariate Analysis of Variance (PERMANOVA) test by allowing flexible confounder adjustments and ensembling multiple distances. We conducted extensive simulation studies to evaluate the performance of different distances under various patterns of association. Our simulation studies demonstrate that the power of the test relies on how well the selected distance captures the nature of the association. The PERMANOVA-S unified test combines multiple distances and achieves good power regardless of the patterns of the underlying association. We demonstrate the usefulness of our approach by reanalyzing several real microbiome datasets. AVAILABILITY AND IMPLEMENTATION: miProfile software is freely available at https://medschool.vanderbilt.edu/tang-lab/software/miProfile CONTACT: z.tang@vanderbilt.edu or g.chen@vanderbilt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The RAG2 C terminus suppresses genomic instability and lymphomagenesis.

Misrepair of DNA double-strand breaks produced by the V(D)J recombinase (the RAG1/RAG2 proteins) at immunoglobulin (Ig) and T cell receptor (Tcr) loci has been implicated in pathogenesis of lymphoid malignancies in humans and in mice. Defects in DNA damage response factors such as ataxia telangiectasia mutated (ATM) protein and combined deficiencies in classical non-homologous end joining and p53 predispose to RAG-initiated genomic rearrangements and lymphomagenesis. Although we showed previously that RAG1/RAG2 shepherd the broken DNA ends to classical non-homologous end joining for proper repair, roles for the RAG proteins in preserving genomic stability remain poorly defined. Here we show that the RAG2 carboxy (C) terminus, although dispensable for recombination, is critical for maintaining genomic stability. Thymocytes from 'core' Rag2 homozygotes (Rag2(c/c) mice) show dramatic disruption of Tcrα/δ locus integrity. Furthermore, all Rag2(c/c) p53(-/-) mice, unlike Rag1(c/c) p53(-/-) and p53(-/-) animals, rapidly develop thymic lymphomas bearing complex chromosomal translocations, amplifications and deletions involving the Tcrα/δ and Igh loci. We also find these features in lymphomas from Atm(-/-) mice. We show that, like ATM-deficiency, core RAG2 severely destabilizes the RAG post-cleavage complex. These results reveal a novel genome guardian role for RAG2 and suggest that similar 'end release/end persistence' mechanisms underlie genomic instability and lymphomagenesis in Rag2(c/c) p53(-/-) and Atm(-/-) mice.

Cutaneous microbiome effects of fluticasone propionate cream and adjunctive bleach baths in childhood atopic dermatitis.

BACKGROUND: Patients with atopic dermatitis (AD) are prone to skin infections, with microbes such as Staphylococcus aureus suspected of contributing to pathogenesis. Bleach baths might improve AD by reducing skin microbial burden. OBJECTIVE: We sought to characterize the microbiota of lesional and nonlesional skin in young children with AD and control subjects and compare changes after treatment with a topical corticosteroid (TCS) alone or TCS + dilute bleach bath. METHODS: In a randomized, placebo-controlled, single-blinded clinical trial in 21 children with AD and 14 healthy children, lesional and nonlesional AD skin was examined at baseline and after 4-week treatment with TCS alone or TCS plus bleach bath. Microbial DNA was extracted for quantitative polymerase chain reaction of predominant genera and 16S rRNA sequencing. RESULTS: At baseline, densities of total bacteria and Staphylococcus, including Staphylococcus aureus, were significantly higher at the worst AD lesional site than nonlesional (P = .001) or control (P < .001) skin; bacterial communities on lesional and nonlesional AD skin significantly differed from each other (P = .04) and from control (P < .001). After TCS + bleach bath or TCS alone, bacterial compositions on lesional skin normalized (P < .0001), resembling nonlesional skin, with microbial diversity restored to control skin levels. LIMITATIONS: The 4-week time period and/or the twice-weekly baths may not have been sufficient for additional impact on the cutaneous microbiome. More detailed sequencing may allow better characterization of the distinguishing taxa with bleach bath treatment. CONCLUSIONS: Treatment with a TCS cream suffices to normalize the cutaneous microbiota on lesional AD; after treatment, bacterial communities on lesional skin resemble nonlesional skin but remain distinct from control.