(Yan et. al)
Figure 4c. Distribution of bacterial genera. Box plots for individual genera segregated by controls, early-stage (T1/T2) oral cancer and late-stage (T3/T4) cancer (*p<0.05).
Yan, K., Auger, S., Diaz, A., Naman, J., Vemulapalli, R., Hasina, R., Izumchenko, E., Shogan, B. and Agrawal, N. (2023), Microbial Changes Associated With Oral Cavity Cancer Progression. Otolaryngol Head Neck Surg. https://doi.org/10.1002/ohn.211
Objective: To examine the oral microbiome in the context of oral cavity squamous cell carcinoma.
Study Design: Basic science research.
Setting: Academic medical center.
Methods: Oral swabs were collected from patients presenting to the operating room for management of oral cavity squamous cell carcinoma and from age- and sex-matched control patients receiving surgery for unrelated benign conditions. 16S ribosomal RNA (rRNA) sequencing was performed on genetic material obtained from swabs. A bacterial rRNA gene library was created and sequence reads were sorted into taxonomic units.
Results: Thirty-one control patients (17 males) and 35 cancer patients (21 males) were enrolled. Ages ranged from 23 to 89 (median 63) for control patients and 35 to 86 (median 66) for cancer patients. Sixty-one percent of control patients and 63% of cancer patients were smokers. 16S analyses demonstrated a significant decrease in Streptococcus genera in oral cancer patients (34.11% vs 21.74% of the population, p = .04). Increases in Fusobacterium, Peptostreptococcus, Parvimonas, and Neisseria were also found. The abundance of these bacteria correlated with tumor T-stage.
Conclusion: 16S rRNA sequencing demonstrated changes in bacterial populations in oral cavity cancer and its progression compared to noncancer controls. We found increases in bacteria genera that correspond with tumor stage—Fusobacteria, Peptostreptococcus, Parvimonas, Neisseria, and Treponema. These data suggest that oral cancer creates an environment to facilitate foreign bacterial growth, rather than implicating a specific bacterial species in carcinogenesis. These bacteria can be employed as a potential marker for tumor progression or interrogated to better characterize the tumor microenvironment.
(Fahrenfeld et. al)
A.S. Deshpande, N.L. Fahrenfeld, Influence of DNA from non-viable sources on the riverine water and biofilm microbiome, resistome, mobilome, and resistance gene host assignments, Journal of Hazardous Materials, Volume 446,
2023, 130743, ISSN 0304-3894,
Abstract: Shotgun metagenomic studies have revealed the diversity, relative abundance, and hosts of antibiotic resistance genes (ARGs) across environmental matrices. There is motivation to combine this method with viability-based techniques to better define ARG hazard. The objectives of this study were to evaluate the performance of different methods for extracellular DNA (eDNA) and putative “non-viable” cell DNA separation to understand the influence on ARG-host assignments. Paired water and biofilm samples were collected along a land use gradient. To study putative “viable-cell” DNA, samples were treated with propidium monoazide (i.e., PMA-DNA). To study eDNA, intracellular and extracellular DNA were separated. qPCR revealed differences in total 16S rRNA gene copies in water for filter vs. centrifuge-concentrated samples, but otherwise there were no differences in gene copy concentrations between DNA fractions. Next, metagenomic sequencing was performed on PMA-DNA and total DNA extracts revealing significant differences between the two for bacterial community structure and ARG profiles. Putative viable taxa containing pathogenic ARG hosts were identified in biofilm and water. Removing PMA-bound DNA improved N50 and assembly mapping compared to total DNA extracts. This study demonstrates the impact of different sample preparation methods on informing the hazard potential associated with riverine ARGs in water and biofilm.
Keywords: Propidium monoazide; ARG; Metagenomics; eDNA
A.S. Deshpande, N.L. Fahrenfeld. Abundance, diversity, and host assignment of total, intracellular, and extracellular antibiotic resistance genes in riverbed sediments. Water Research. Volume 217, 2022. 118363, ISSN 0043-1354,
Abstract: Human health risk assessment for environmental antibiotic resistant microbes requires not only quantifying the abundance of antibiotic resistance genes (ARGs) in environmental matrices, but also understanding their hosts and genetic context. Further, differentiating ARGs in intracellular and extracellular DNA (iDNA and eDNA) fractions may help refine our understanding of ARG transferability. The objectives of this study were to understand the (O1) abundance and diversity of extracellular, intracellular, and total ARGs along a land use gradient and (O2) impact of bioinformatics pipeline on the assignment of putative hosts for the ARGs observed in the different DNA fractions. Sediment samples were collected along a land use gradient in the Raritan River, New Jersey, USA. DNA was extracted to separate eDNA and iDNA and qPCR was performed for select ARGs and the 16S rRNA gene. Shotgun metagenomic sequencing was performed on DNA extracts for the different DNA fractions. ARG hosts were assigned via two different bioinformatic pipelines: network analysis of raw reads versus assembly. Results of the two pipelines were compared to evaluate their performance in terms of number and diversity of linkages and accuracy of in silico matrix spike host assignments. No differences were observed in the 16S rRNA gene normalized sul1 concentrations between the DNA fractions. The overall microbial community structure was more similar for iDNA and total DNA compared to eDNA and generally clustered by sampling site. ARGs associated with mobile genetic elements increased in iDNA for the downstream sites. Regarding host assignment, the raw reads pipeline via network analysis identified 247 ARG hosts as compared to 53 hosts identified by assembly pipeline. Other comparisons between the pipelines were made including ARG assignment to taxa containing waterborne pathogens and practical considerations regarding processing time.
Keywords: ARG; sul1; Metagenomic sequencing; Assembly; Network analysis; eDNA; iDNA
Longoria, C. R., Guers, J. J., & Campbell, S. C. (2022). The Interplay between Cardiovascular Disease, Exercise, and the Gut Microbiome. Reviews in Cardiovascular Medicine, 23(11), 365.
Cardiovascular disease (CVD) is the leading cause of death worldwide, with physical inactivity being a known contributor to the global rates of CVD incidence. The gut microbiota has been associated with many diseases including CVD and other comorbidities such at type 2 diabetes and obesity. Researchers have begun to examine the gut microbiome as a predictor of early disease states by detecting disruptions, or dysbiosis, in the microbiota. Evidence is lacking to investigate the potential link between the gut microbiota, exercise, and CVD risk and development. Research supports that diets with whole food have reduced instances of CVD and associated diseases, increased abundances of beneficial gut bacteria, and altered gut-derived metabolite production. Further, exercise and lifestyle changes to increase physical activity demonstrate improved health outcomes related to CVD risk and comorbidities and gut microbial diversity. It is difficult to study an outcome such as CVD when including multiple factors; however, it is evident that exercise, lifestyle, and the gut microbiota contribute to improved health in their own ways. This review will highlight current research findings and what potential treatments of CVD may be generated by manipulation of the gut microbiota and/or exercise.
Keywords: gut microbiota; inflammation; endothelial function; prebiotics; probiotics; metabolites; trimethylamine N-oxide (TMAO)
Figure 3. Heat map showing strain-level BLAST results from 19 in silico mutated sequences (in triplicate) vs % identity. The number of rRNA operons in each strain, the number of strains for each bacterial species and the total number of rRNA operons for each bacterial species in the database are indicated.
Lee J Kerkhof, Pierce A Roth, Samir V Deshpande, R Cory Bernhards, Alvin T Liem, Jessica M Hill, Max M Häggblom, Nicole S Webster, Olufunmilola Ibironke, Seda Mirzoyan, James J Polashock, Raymond F Sullivan, A ribosomal operon database and MegaBLAST settings for strain-level resolution of microbiomes, FEMS Microbes, Volume 3, 2022, xtac002, https://doi.org/10.1093/femsmc/xtac002
Abstract: Current methods to characterize microbial communities generally employ sequencing of the 16S rRNA gene (<500 bp) with high accuracy (∼99%) but limited phylogenetic resolution. However, long-read sequencing now allows for the profiling of near-full-length ribosomal operons (16S-ITS-23S rRNA genes) on platforms such as the Oxford Nanopore MinION. Here, we describe an rRNA operon database with >300 ,000 entries, representing >10 ,000 prokaryotic species and ∼ 150, 000 strains. Additionally, BLAST parameters were identified for strain-level resolution using in silico mutated, mock rRNA operon sequences (70–95% identity) from four bacterial phyla and two members of the Euryarchaeota, mimicking MinION reads. MegaBLAST settings were determined that required <3 s per read on a Mac Mini with strain-level resolution for sequences with >84% identity. These settings were tested on rRNA operon libraries from the human respiratory tract, farm/forest soils and marine sponges ( n = 1, 322, 818 reads for all sample sets). Most rRNA operon reads in this data set yielded best BLAST hits (95 ± 8%). However, only 38–82% of library reads were compatible with strain-level resolution, reflecting the dominance of human/biomedical-associated prokaryotic entries in the database. Since the MinION and the Mac Mini are both portable, this study demonstrates the possibility of rapid strain-level microbiome analysis in the field.
Figure 2. Fecal Lcn-2 level is a sensitive biological indicator for gut dysbiosis and intestinal inflammation in multiple sclerosis
Yadav SK, Ito N, Mindur JE, Kumar H, Youssef M, Suresh S, Kulkarni R, Rosario Y, Balashov KE, Dhib-Jalbut S and Ito K (2022) Fecal Lcn-2 level is a sensitive biological indicator for gut dysbiosis and intestinal inflammation in multiple sclerosis. Front. Immunol. 13:1015372.
Abstract: Multiple Sclerosis (MS) has been reported to be associated with intestinal inflammation and gut dysbiosis. To elucidate the underlying biology of MS-linked gut inflammation, we investigated gut infiltration of immune cells during the development of spontaneous experimental autoimmune encephalomyelitis (EAE) in humanized transgenic (Tg) mice expressing HLA-DR2a and human T cell receptor (TCR) specific for myelin basic protein peptide (MBP87-99)/HLA-DR2a complexes. Strikingly, we noted the simultaneous development of EAE and colitis, suggesting a link between autoimmune diseases of the central nervous system (CNS) and intestinal inflammation. Examination of the colon in these mice revealed the infiltration of MBP-specific Th17 cells as well as recruitment of neutrophils. Furthermore, we observed that fecal Lipocalin-2 (Lcn-2), a biomarker of intestinal inflammation, was significantly elevated and predominantly produced by the gut-infiltrating neutrophils. We then extended our findings to MS patients and demonstrate that their fecal Lcn-2 levels are significantly elevated compared to healthy donors (HDs). The elevation of fecal Lcn-2 levels correlated with reduced bacterial diversity and increased levels of other intestinal inflammation markers including neutrophil elastase and calprotectin. Of interest, bacteria thought to be beneficial for inflammatory bowel disease (IBD) such as Anaerobutyricum, Blautia, and Roseburia, were reduced in fecal Lcn-2-high MS patients. We also observed a decreasing trend in serum acetate (a short-chain fatty acid) levels in MS Lcn-2-high patients compared to HDs. Furthermore, a decrease in the relative abundance of Blautia massiliensis was significantly associated with a reduction of acetate in the serum of MS patients. This study suggests that gut infiltration of Th17 cells and recruitment of neutrophils are associated with the development of gut dysbiosis and intestinal inflammation, and that fecal Lcn-2 level is a sensitive biological indicator for gut dysbiosis in multiple sclerosis.
Figure 4. Small intestinal microbiota signature is associated with the local expansion of the γδ IEL compartment.
a Morphometric analysis of the number of GFP+ γδ T cells in untreated WT-S, IFNAR KO-S or F2 WT mice. b Principal coordinates analysis of 16S rRNA sequencing of SI luminal microbiota from WT-S, IFNAR KO-S and F2 WT mice. Bray Curtis distance was applied. c Seven ASVs in the SI were enriched in the mice with γδ IEL hyperproliferative phenotype. d and e Associations between the 7 ASVs in the SI enriched by the mice with γδ IEL hyperproliferative phenotype. Statistical analysis: a: one-way ANOVA with Tukey’s post hoc test; c: MaAsLin2 was applied to explore the differential ASVs in SI samples between mice with (IFNAR KO-S and F2 WT) and without the γδ IEL hyperproliferative phenotype (WT-S). BH-adjusted p values < 0.05 considered as significant. Boxes show the medians and the interquartile ranges (IQRs), the whiskers denote the lowest and highest values that were within 1.5 times the IQR from the first and third quartiles, and outliers are shown as individual points; d: Random Forest model with leave-one-out cross-validation was applied to use the ASVs abundance in the intestine to regress the intestinal γδ IEL cell number or e: to classify intestinal segments based on the γδ IEL hyperproliferative phenotype. Pearson correlation was used to compare the predicted and measured values. *P<0.05, **P<0.01, *** P<0.001.
Jia L, Wu G, Alonso S, Zhao C, Lemenze A, Lam YY, Zhao L, Edelblum KL. A transmissible γδ intraepithelial lymphocyte hyperproliferative phenotype is associated with the intestinal microbiota and confers protection against acute infection. Mucosal Immunol. 2022 Apr;15(4):772-782. doi: 10.1038/s41385-022-00522-x. Epub 2022 May 19. PMID: 35589986; PMCID: PMC9262869.
Abstract: Intraepithelial lymphocytes expressing the gamma delta T cell receptor (gamma delta IELs) serve as a first line of defense against luminal microbes. Although the presence of an intact microbiota is dispensable for gamma delta IEL development, several microbial factors contribute to the maintenance of this sentinel population. However, whether specific commensals influence population of the gamma delta IEL compartment under homeostatic conditions has yet to be determined. We identified a novel gamma delta IEL hyperproliferative phenotype that is characterized by expansion of multiple Vgamma subsets. Horizontal transfer of this hyperproliferative phenotype to mice harboring a phenotypically normal gamma delta IEL compartment was prevented following antibiotic treatment, thus demonstrating that the microbiota is both necessary and sufficient for the observed increase in gamma delta IELs. Further, we identified two guilds of small intestinal or fecal bacteria represented by 12 amplicon sequence variants (ASV) that are strongly associated with gamma delta IEL expansion. Using intravital microscopy, we find that hyperproliferative gamma delta IELs also exhibit increased migratory behavior leading to enhanced protection against bacterial infection. These findings reveal that transfer of a specific group of commensals can regulate gamma delta IEL homeostasis and immune surveillance, which may provide a novel means to reinforce the epithelial barrier.
(Bassel et. al)
Graphical Abstract [see abstract below for more information]
Bassel Ghaddar, Antara Biswas, Chris Harris, M. Bishr Omary, Darren R. Carpizo, Martin J. Blaser, Subhajyoti De.
Tumor microbiome links cellular programs and immunity in pancreatic cancer, Cancer Cell, Volume 40, Issue 10, 2022, Pages 1240-1253.e5, ISSN 1535-6108, https://doi.org/10.1016/j.ccell.2022.09.009.
Microorganisms are detected in multiple cancer types, including in putatively sterile organs, but the contexts in which they influence oncogenesis or anti-tumor responses in humans remain unclear. We recently developed single-cell analysis of host-microbiome interactions (SAHMI), a computational pipeline to recover and denoise microbial signals from single-cell sequencing of host tissues. Here we use SAHMI to interrogate tumor-microbiome interactions in two human pancreatic cancer cohorts. We identify somatic-cell-associated bacteria in a subset of tumors and their near absence in nonmalignant tissues. These bacteria predominantly pair with tumor cells, and their presence is associated with cell-type-specific gene expression and pathway activities, including cell motility and immune signaling. Modeling results indicate that tumor-infiltrating lymphocytes closely resemble T cells from infected tissue. Finally, using multiple independent datasets, a signature of cell-associated bacteria predicts clinical prognosis. Tumor-microbiome crosstalk may modulate tumorigenesis in pancreatic cancer with implications for clinical management.
Keywords: cancer genomics; microbiome; immunity; oncogenesis; cancer biology; gene expression; single cell sequencing