Smoking-induced subgingival dysbiosis precedes clinical signs of periodontal disease.

Smoking accelerates periodontal disease and alters the subgingival microbiome. However, the relationship between smoking-associated subgingival dysbiosis and progression of periodontal disease is not well understood. Here, we sampled 233 subgingival sites longitudinally from 8 smokers and 9 non-smokers over 6-12 months, analyzing 804 subgingival plaque samples using 16 rRNA sequencing. At equal probing depths, the microbial richness and diversity of the subgingival microbiome was higher in smokers compared to non-smokers, but these differences decreased as probing depths increased. The overall subgingival microbiome of smokers differed significantly from non-smokers at equal probing depths, which was characterized by colonization of novel minority microbes and a shift in abundant members of the microbiome to resemble periodontally diseased communities enriched with pathogenic bacteria. Temporal analysis showed that microbiome in shallow sites were less stable than deeper sites, but temporal stability of the microbiome was not significantly affected by smoking status or scaling and root planing. We identified 7 taxa-Olsenella sp., Streptococcus cristatus, Streptococcus pneumoniae, Streptococcus parasanguinis, Prevotella sp., Alloprevotella sp., and a Bacteroidales sp. that were significantly associated with progression of periodontal disease. Taken together, these results suggest that subgingival dysbiosis in smokers precedes clinical signs of periodontal disease, and support the hypothesis that smoking accelerates subgingival dysbiosis to facilitate periodontal disease progression.

Microbiome Resilience despite a Profound Loss of Minority Microbiota following Clindamycin Challenge in Humanized Gnotobiotic Mice.

Antibiotics are known to induce gut dysbiosis and increase the risk of antibiotic resistance. While antibiotic exposure is a known risk factor leading to compromised colonization resistance against enteric pathogens such as Clostridioides difficile, the extent and consequences of antibiotic perturbation on the human gut microbiome remain poorly understood. Human studies on impacts of antibiotics are complicated by the tremendous variability of gut microbiome among individuals, even between identical twins. Furthermore, antibiotic challenge experiments cannot be replicated in human subjects for a given gut microbiome. Here, we transplanted feces from three unrelated human donors into groups of identical germfree (GF) Swiss-Webster mice, and examined the temporal responses of the transplanted microbiome to oral clindamycin challenge in gnotobiotic isolators over 7 weeks. Analysis of 177 longitudinal fecal samples revealed that 59% to 81% of human microbiota established a stable configuration rapidly and stably in GF mice. Microbiome responses to clindamycin challenge was highly reproducible and microbiome-dependent. A short course of clindamycin was sufficient to induce a profound loss (∼one third) of the microbiota by disproportionally eliminating minority members of the transplanted microbiota. However, it was inadequate to disrupt the global microbial community structure or function, which rebounded rapidly to resemble its pre-treatment state after clindamycin discontinuation. Furthermore, the response of individual microbes was community-dependent. Taken together, these results suggest that the overall gut microbiome structure is resilient to antibiotic perturbation, the functional consequences of which warrant further investigation. IMPORTANCE Antibiotics cause imbalance of gut microbiota, which in turn increase our susceptibility to gastrointestinal infections. However, how antibiotics disrupt gut bacterial communities is not well understood, and exposing healthy volunteers to unnecessary antibiotics for research purposes carries clinical and ethical concerns. In this study, we used genetically identical mice transplanted with the same human gut microbiota to control for both genetic and environmental variables. We found that a short course of oral clindamycin was sufficient to eliminate one third of the gut bacteria by disproportionally eliminating minority members of the transplanted microbiota, but it was inadequate to disrupt the overall microbial community structure and function, which rebounded rapidly to its pre-treatment state. These results suggest that gut microbiome is highly resilient to antibiotic challenge and degradation of the human gut ecosystem may require repeated or prolonged antibiotic exposure.

Stability of healthy subgingival microbiome across space and time.

The subgingival microbiome is one of the most stable microbial ecosystems in the human body. Alterations in the subgingival microbiome have been associated with periodontal disease, but their variations over time and between different subgingival sites in periodontally healthy individuals have not been well described. We performed extensive, longitudinal sampling of the subgingival microbiome from five periodontally healthy individuals to define baseline spatial and temporal variations. A total of 251 subgingival samples from 5 subjects were collected over 6-12 months and deep sequenced. The overall microbial diversity and composition differed significantly between individuals. Within each individual, we observed considerable differences in microbiome composition between different subgingival sites. However, for a given site, the microbiome was remarkably stable over time, and this stability was associated with increased microbial diversity but was inversely correlated with the enrichment of putative periodontal pathogens. In contrast to microbiome composition, the predicted functional metagenome was similar across space and time, suggesting that periodontal health is associated with shared gene functions encoded by different microbiome consortia that are individualized. To our knowledge, this is one of the most detailed longitudinal analysis of the healthy subgingival microbiome to date that examined the longitudinal variability of different subgingival sites within individuals. These results suggest that a single measurement of the healthy subgingival microbiome at a given site can provide long term information of the microbial composition and functional potential, but sampling of each site is necessary to define the composition and community structure at individual subgingival sites.

Upper versus lower airway microbiome and metagenome in children with cystic fibrosis and their correlation with lung inflammation.

OBJECTIVE: Airways of children with cystic fibrosis (CF) harbor complex polymicrobial communities which correlates with pulmonary disease progression and use of antibiotics. Throat swabs are widely used in young CF children as a surrogate to detect potentially pathogenic microorganisms in lower airways. However, the relationship between upper and lower airway microbial communities remains poorly understood. This study aims to determine (1) to what extent oropharyngeal microbiome resembles the lung microbiome in CF children and (2) if lung microbiome composition correlates with airway inflammation. METHOD: Throat swabs and bronchoalveolar lavage (BAL) were obtained concurrently from 21 CF children and 26 disease controls. Oropharyngeal and lung microbiota were analyzed using 16S rRNA deep sequencing and correlated with neutrophil counts in BAL and antibiotic exposure. RESULTS: Oropharyngeal microbial communities clustered separately from lung communities and had higher microbial diversity (p < 0.001). CF microbiome differed significantly from non-CF controls, with a higher abundance of Proteobacteria in both upper and lower CF airways. Neutrophil count in the BAL correlated negatively with the diversity but not richness of the lung microbiome. In CF children, microbial genes involved in bacterial motility proteins, two-component system, flagella assembly, and secretion system were enriched in both oropharyngeal and lung microbiome, whereas genes associated with synthesis and metabolism of nucleic acids and protein dominated the non-CF controls. CONCLUSIONS: This study identified a unique microbial profile with altered microbial diversity and metabolic functions in CF airways which is significantly affected by airway inflammation. These results highlight the limitations of using throat swabs as a surrogate to study lower airway microbiome and metagenome in CF children.

SVIP regulates Z variant alpha-1 antitrypsin retro-translocation by inhibiting ubiquitin ligase gp78.

Alpha-1 antitrypsin deficiency (AATD) is an inherited disorder characterized by early-onset emphysema and liver disease. The most common disease-causing mutation is a single amino acid substitution (Glu/Lys) at amino acid 342 of the mature protein, resulting in disruption of the 290-342 salt bridge (an electrophoretic abnormality defining the mutation [Z allele, or ZAAT]), protein misfolding, polymerization, and accumulation in the endoplasmic reticulum of hepatocytes and monocytes. The Z allele causes a toxic gain of function, and the E3 ubiquitin ligase gp78 promotes degradation and increased solubility of endogenous ZAAT. We hypothesized that the accumulation of ZAAT is influenced by modulation of gp78 E3 ligase and SVIP (small VCP-interacting protein) interaction with p97/VCP in ZAAT-expressing hepatocytes. We showed that the SVIP inhibitory effect on ERAD due to overexpression causes the accumulation of ZAAT in a human Z hepatocyte-like cell line (AT01). Overexpression of gp78, as well as SVIP suppression, induces gp78-VCP/p97 interaction in AT01 cells. This interaction leads to retro-translocation of ZAAT and reduction of the SVIP inhibitory role in ERAD. In this context, overexpression of gp78 or SVIP suppression may eliminate the toxic gain of function associated with polymerization of ZAAT, thus providing a potential new therapeutic approach to the treatment of AATD.

Transcription factor Bcl11b sustains iNKT1 and iNKT2 cell programs, restricts iNKT17 cell program, and governs iNKT cell survival.

Invariant natural killer T (iNKT) cells are innate-like T cells that recognize glycolipid antigens and play critical roles in regulation of immune responses. Based on expression of the transcription factors (TFs) Tbet, Plzf, and Rorγt, iNKT cells have been classified in effector subsets that emerge in the thymus, namely, iNKT1, iNKT2, and iNKT17. Deficiency in the TF Bcl11b in double-positive (DP) thymocytes has been shown to cause absence of iNKT cells in the thymus and periphery due to defective self glycolipid processing and presentation by DP thymocytes and undefined intrinsic alterations in iNKT precursors. We used a model of cre-mediated postselection deletion of Bcl11b in iNKT cells to determine its intrinsic role in these cells. We found that Bcl11b is expressed equivalently in all three effector iNKT subsets, and its removal caused a reduction in the numbers of iNKT1 and iNKT2 cells, but not in the numbers of iNKT17 cells. Additionally, we show that Bcl11b sustains subset-specific cytokine production by iNKT1 and iNKT2 cells and restricts expression of iNKT17 genes in iNKT1 and iNKT2 subsets, overall restraining the iNKT17 program in iNKT cells. The total numbers of iNKT cells were reduced in the absence of Bcl11b both in the thymus and periphery, associated with the decrease in iNKT1 and iNKT2 cell numbers and decrease in survival, related to changes in survival/apoptosis genes. Thus, these results extend our understanding of the role of Bcl11b in iNKT cells beyond their selection and demonstrate that Bcl11b is a key regulator of iNKT effector subsets, their function, identity, and survival.

Dysbiosis and alterations in predicted functions of the subgingival microbiome in chronic periodontitis.

Chronic periodontitis is an inflammatory disease of the periodontium affecting nearly 65 million adults in the United States. Changes in subgingival microbiota have long been associated with chronic periodontitis. Recent culture-independent molecular studies have revealed the immense richness and complexity of oral microbial communities. However, data sets across studies have not been directly compared, and whether the observed microbial variations are consistent across different studies is not known. Here, we used 16S rRNA sequencing to survey the subgingival microbiota in 25 subjects with chronic periodontal disease and 25 healthy controls and compared our data sets with those of three previously reported microbiome studies. Consistent with data from previous studies, our results demonstrate a significantly altered microbial community structure with decreased heterogeneity in periodontal disease. Comparison with data from three previously reported studies revealed that subgingival microbiota clustered by study. However, differences between periodontal health and disease were larger than the technical variations across studies. Using a prediction score and applying five different distance metrics, we observed two predominant clusters. One cluster was driven by Fusobacterium and Porphyromonas and was associated with clinically apparent periodontitis, and the second cluster was dominated by Rothia and Streptococcus in the majority of healthy sites. The predicted functional capabilities of the periodontitis microbiome were significantly altered. Genes involved in bacterial motility, energy metabolism, and lipopolysaccharide biosynthesis were overrepresented in periodontal disease, whereas genes associated with transporters, the phosphotransferase system, transcription factors, amino acid biosynthesis, and glycolysis/gluconeogenesis were enriched in healthy controls. These results demonstrate significant alterations in microbial composition and function in periodontitis and suggest genes and metabolic pathways associated with periodontal disease.

Deep sequencing analysis of HCV NS3 resistance-associated variants and mutation linkage in liver transplant recipients.

Viral variants with decreased susceptibility to HCV protease inhibitors (PIs) occur naturally and preexist at low levels within HCV populations. In patients failing PI monotherapy, single and double mutants conferring intermediate to high-level resistance to PIs have been selected in vivo. The abundance, temporal dynamics and linkage of naturally occurring resistance-associated variants (RAVs), however, have not been characterized in detail. Here, using high-density pyrosequencing, we analyzed HCV NS3 gene segments from 20 subjects with chronic HCV infection, including 12 subjects before and after liver transplantation. Bioinformatics analysis revealed that Q80 substitution was a dominant variant in 40% of the subjects, whereas other RAVs circulate at low levels within quasispecies populations. Low frequency mutation linkage was detectable by Illumina paired-end sequencing in as low as 0.5% of the mock populations constructed from in vitro RNA transcripts but were uncommon in vivo. We show that naturally occurring RAVs are common and can persist long term following liver transplant at low levels not readily detectable by conventional sequencing. Our results indicate that mutation linkage at low levels could be identified using the Illumina paired-end approach. The methods described here should facilitate the analysis of low frequency HCV drug resistance, mutation linkage and evolution, which may inform future therapeutic strategies in patients undergoing direct acting antiviral therapies.

Identification and characterization of endoplasmic reticulum-associated degradation proteins differentially affected by endoplasmic reticulum stress.

The disposal of misfolded proteins from the lumen of the endoplasmic reticulum (ER) is one of the quality control mechanisms present in the protein secretory pathway. Through ER-associated degradation, misfolded substrates are targeted to the cytosol where they are degraded by the proteasome. We have identified four maize (Zea mays) Der1-like genes (Zm Derlins) that encode homologs of Der1p, a yeast (Saccharomyces cerevisiae) protein implicated in ER-associated degradation. Zm Derlins are capable of functionally complementing a yeast Der1 deletion mutant. Such complementation indicates that the Der1p function is conserved among species. Zm Derlin genes are expressed at low levels throughout the plant, but appear prevalent in tissues with high activity of secretory protein accumulation, including developing endosperm cells. Expression of three of the four Zm Derlin genes increases during ER stress, with Zm Derlin1-1 showing the strongest induction. Subcellular fractionation experiments localized Zm Derlin proteins to the membrane fraction of microsomes. In maize endosperm, Zm Derlin proteins were found primarily associated with ER-derived protein bodies regardless of the presence of an ER stress response.

Coordinated genetic regulation of growth and lignin revealed by quantitative trait locus analysis of cDNA microarray data in an interspecific backcross of eucalyptus.

Phenotypic, genotypic, and transcript level (microarray) data from an interspecific backcross population of Eucalyptus grandis and Eucalyptus globulus were integrated to dissect the genetic and metabolic network underlying growth variation. Transcript abundance, measured for 2,608 genes in the differentiating xylem of a 91 (E. grandis x E. globulus) x E. grandis backcross progeny was correlated with diameter variation, revealing coordinated down-regulation of genes encoding enzymes of the lignin biosynthesis and associated methylation pathways in fast growing individuals. Lignin analysis of wood samples confirmed the content and quality predicted by the transcript levels measured on the microarrays. Quantitative trait locus (QTL) analysis of transcript levels of lignin-related genes showed that their mRNA abundance is regulated by two genetic loci, demonstrating coordinated genetic control over lignin biosynthesis. These two loci colocalize with QTLs for growth, suggesting that the same genomic regions are regulating growth, and lignin content and composition in the progeny. Genetic mapping of the lignin genes revealed that most of the key biosynthetic genes do not colocalize with growth and transcript level QTLs, with the exception of the locus encoding the enzyme S-adenosylmethionine synthase. This study illustrates the power of integrating quantitative analysis of gene expression data and genetic map information to discover genetic and metabolic networks regulating complex biological traits. (Sequence data for this article have been deposited with the EMBL/GenBank data libraries under accession numbers CB 967505 to CB 968059; CD 667988 to CD 670002; CD 670004; CD 670097; CD 670101 to CD 670112; and CD 670114 to CD 670137.)