Among the laboratory and bioinformatic processing steps for human microbiome studies, a lack of consistency in DNA extraction methodologies is hindering the ability to compare results between studies ...and sometimes leading to errant conclusions. The purpose of this article is to highlight the issues related to DNA extraction methods and to suggest minimum standard requirements that should be followed to ensure consistency and reproducibility.
In order for human microbiome studies to translate into actionable outcomes for health, meta-analysis of reproducible data from population-scale cohorts is needed. Achieving sufficient ...reproducibility in microbiome research has proven challenging. We report a baseline investigation of variability in taxonomic profiling for the Microbiome Quality Control (MBQC) project baseline study (MBQC-base). Blinded specimen sets from human stool, chemostats, and artificial microbial communities were sequenced by 15 laboratories and analyzed using nine bioinformatics protocols. Variability depended most on biospecimen type and origin, followed by DNA extraction, sample handling environment, and bioinformatics. Analysis of artificial community specimens revealed differences in extraction efficiency and bioinformatic classification. These results may guide researchers in experimental design choices for gut microbiome studies.
Background
Little is known about the microbiota and upper gastrointestinal tumors. Esophageal squamous cell carcinoma (ESCC) and gastric cardia adenocarcinoma (GCA) occur in adjacent organs, co‐occur ...geographically, and share many risk factors despite being of different tissue types.
Methods
This study characterized the microbial communities of paired tumor and nontumor samples from 67 patients with ESCC and 36 patients with GCA in Henan, China. DNA was extracted with the MoBio PowerSoil kit. The V4 region of the 16S ribosomal RNA gene was sequenced with MiniSeq and was processed with Quantitative Insights Into Microbial Ecology 1. The linear discriminant analysis effect size method was used to identify differentially abundant microbes, the Wilcoxon rank‐sum test was used to test α diversity differences, and permutational multivariate analysis of variance was used to test for differences in β diversity.
Results
The microbial environments of ESCC and GCA tissues were all composed primarily of Firmicutes, Bacteroidetes, and Proteobacteria. ESCC tumor tissues contained more Fusobacterium (3.2% vs 1.3%) and less Streptococcus (12.0% vs 30.2%) than nontumor tissues. GCA nontumor tissues had a greater abundance of Helicobacter (60.5% vs 11.8%), which may have been linked to the lower α diversity (58.0 vs 102.5; P = .0012) in comparison with tumor tissues. A comparison of ESCC and GCA nontumor tissues showed that the microbial composition (P = .0040) and the α diversity (87.0 vs 58.0; P = .00052) were significantly different. No significant differences were detected for α diversity within ESCC and GCA tumor tissues.
Conclusions
This study showed differences in the microbial compositions of paired ESCC and GCA tumor and nontumor tissues and differences by organ site. Large‐scale, prospective cohort studies are needed to confirm these findings.
This is the first study to investigate the microbial composition of esophageal squamous cell carcinoma tumor and nontumor tissues through 16S ribosomal RNA gene sequencing and the differences between esophageal squamous cell carcinoma and gastric cardia adenocarcinoma tissues. The levels of Fusobacterium increase in esophageal squamous cell carcinoma tumor tissues, and there is a large decrease in the relative levels of Helicobacter in gastric cardia adenocarcinoma tumor tissues in comparison with nontumor tissues.
Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a ...meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10
). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.
Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. ...Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect associations that are reproducible and significant after correction for multiple testing.
Genetics and the microbiota Although it is well known that race and ethnicity are poor proxies for genetic ancestry, these factors may be somewhat correlated. ...host genetics may marginally ...contribute to racial/ethnic differences in gastrointestinal microbial composition and functionality. Periodontal disease may be attributable to complex and difficult-to-measure differences in socioeconomic and other social factors occurring over the life course that contribute to a lack of health care access and utilization. ...oral health metrics and their associated oral microbiota may be proxies for these complex exposures. ...the annual National Health and Nutrition Examination Survey (NHANES) ascertains the health and nutritional status of children and adults via questionnaires and biospecimen collection in a nationally representative sample of approximately 5000 individuals 13. Because of their oversampling of targeted groups of individuals, NHANES has become an invaluable resource for reliably estimating various US exposures, including those pertaining to social determinants of health. ...study populations like those represented in NHANES are particularly suitable for future collection of oral and fecal samples to characterize the gastrointestinal microbiota of a representative portion of the US population.
Colorectal adenomas are precancerous lesions of colorectal cancer (CRC) that offer a means of viewing the events key to early CRC development. A number of studies have investigated the changes and ...roles of gut microbiota in adenoma and carcinoma development, highlighting its impact on carcinogenesis. However, there has been less of a focus on the gut metabolome, which mediates interactions between the host and gut microbes. Here, we investigated metabolomic profiles of stool samples from patients with advanced adenoma (
= 102), matched controls (
= 102), and patients with CRC (
= 36). We found that several classes of bioactive lipids, including polyunsaturated fatty acids, secondary bile acids, and sphingolipids, were elevated in the adenoma patients compared to the controls. Most such metabolites showed directionally consistent changes in the CRC patients, suggesting that those changes may represent early events of carcinogenesis. We also examined gut microbiome-metabolome associations using gut microbiota profiles in these patients. We found remarkably strong overall associations between the microbiome and metabolome data and catalogued a list of robustly correlated pairs of bacterial taxa and metabolomic features which included signatures of adenoma. Our findings highlight the importance of gut metabolites, and potentially their interplay with gut microbes, in the early events of CRC pathogenesis.
Colorectal adenomas are precursors of CRC. Recently, the gut microbiota, i.e., the collection of microbes residing in our gut, has been recognized as a key player in CRC development. There have been a number of gut microbiota profiling studies for colorectal adenoma and CRC; however, fewer studies have considered the gut metabolome, which serves as the chemical interface between the host and gut microbiota. Here, we conducted a gut metabolome profiling study of colorectal adenoma and CRC and analyzed the metabolomic profiles together with paired microbiota composition profiles. We found several chemical signatures of colorectal adenoma that were associated with some gut microbes and potentially indicative of future CRC. This study highlights potential early-driver metabolites in CRC pathogenesis and guides further targeted experiments and thus provides an important stepping stone toward developing better CRC prevention strategies.
Aims/hypothesis
The gut microbiome is hypothesised to be related to insulin resistance and other metabolic variables. However, data from population-based studies are limited. We investigated ...associations between serologic measures of metabolic health and the gut microbiome in the Northern Finland Birth Cohort 1966 (NFBC1966) and the TwinsUK cohort.
Methods
Among 506 individuals from the NFBC1966 with available faecal microbiome (16S rRNA gene sequence) data, we estimated associations between gut microbiome diversity metrics and serologic levels of HOMA for insulin resistance (HOMA-IR), HbA
1c
and C-reactive protein (CRP) using multivariable linear regression models adjusted for sex, smoking status and BMI. Associations between gut microbiome diversity measures and HOMA-IR and CRP were replicated in 1140 adult participants from TwinsUK, with available faecal microbiome (16S rRNA gene sequence) data. For both cohorts, we used general linear models with a quasi-Poisson distribution and Microbiome Regression-based Kernel Association Test (MiRKAT) to estimate associations of metabolic variables with alpha- and beta diversity metrics, respectively, and generalised additive models for location scale and shape (GAMLSS) fitted with the zero-inflated beta distribution to identify taxa associated with the metabolic markers.
Results
In NFBC1966, alpha diversity was lower in individuals with higher HOMA-IR with a mean of 74.4 (95% CI 70.7, 78.3) amplicon sequence variants (ASVs) for the first quartile of HOMA-IR and 66.6 (95% CI 62.9, 70.4) for the fourth quartile of HOMA-IR. Alpha diversity was also lower with higher HbA
1c
(number of ASVs and Shannon’s diversity,
p
< 0.001 and
p
= 0.003, respectively) and higher CRP (number of ASVs,
p
= 0.025), even after adjustment for BMI and other potential confounders. In TwinsUK, alpha diversity measures were also lower among participants with higher measures of HOMA-IR and CRP. When considering beta diversity measures, we found that microbial community profiles were associated with HOMA-IR in NFBC1966 and TwinsUK, using multivariate MiRKAT models, with binomial deviance dissimilarity
p
values of <0.001. In GAMLSS models, the relative abundances of individual genera
Prevotella
and
Blautia
were associated with HOMA-IR in both cohorts.
Conclusions/interpretation
Overall, higher levels of HOMA-IR, CRP and HbA
1c
were associated with lower microbiome diversity in both the NFBC1966 and TwinsUK cohorts, even after adjustment for BMI and other variables. These results from two distinct population-based cohorts provide evidence for an association between metabolic variables and gut microbial diversity. Further experimental and mechanistic insights are now needed to provide understanding of the potential causal mechanisms that may link the gut microbiota with metabolic health.
Graphical abstract
Despite widespread popularity and possible health effects, the prevalence and distribution of coffee consumption in US adults are poorly characterized.
We sought to estimate usual daily coffee ...intakes from all coffee-containing beverages, including decaffeinated and regular coffee, among US adults according to demographic, socioeconomic, and health-related factors.
Dietary intake data from ≤2 nonconsecutive 24-h dietary recalls and a food-frequency questionnaire administered during the NHANES 2003-2006 were used to estimate the person-specific probability of consuming coffee on a particular day and the usual amount consumed on consumption days. Trends in population mean coffee consumption over time were evaluated by using multiple linear regression and 1-d 24-h recall data from NHANES 2003-2012. Analyses were weighted to be representative of the US adult population aged ≥20 y.
An estimated 154 million adults, or 75% of the US population, aged ≥20 y reported drinking coffee; 49% reported drinking coffee daily. Prevalence did not vary by sex, education, income, or self-reported general health (all P ≥ 0.05) but did vary by age, race/ethnicity, smoking status, and alcohol drinking (all P < 0.05). Among coffee drinkers, the mean ± SE usual intake was 14.1 ± 0.5 fluid ounces/d (417 ± 15 mL/d). Mean usual intakes were higher in men than women, in older age groups than in those aged 20 to <30 y, in non-Hispanic whites than in non-Hispanic blacks or Hispanic/other races, in smokers than in never smokers, and in daily alcohol consumers than in nonconsumers (all P < 0.05). Population mean coffee consumption was stable from 2003 to 2012 (P-trend = 0.09).
Coffee is widely consumed in the United States, with usual intakes varying by lifestyle and demographic factors, most notably by age. Longitudinal studies are needed to determine whether observed differences by age reflect birth cohort effects or changes in drinking patterns over the lifetime.
Previous studies suggested associations between the oral microbiome and lung cancer, but studies were predominantly cross-sectional and underpowered.
Using a case-cohort design, 1306 incident lung ...cancer cases were identified in the Agricultural Health Study; National Institutes of Health-AARP Diet and Health Study; and Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Referent subcohorts were randomly selected by strata of age, sex, and smoking history. DNA was extracted from oral wash specimens using the DSP DNA Virus Pathogen kit, the 16S rRNA gene V4 region was amplified and sequenced, and bioinformatics were conducted using QIIME 2. Hazard ratios and 95% confidence intervals were calculated using weighted Cox proportional hazards models.
Higher alpha diversity was associated with lower lung cancer risk (Shannon index hazard ratio = 0.90, 95% confidence interval = 0.84 to 0.96). Specific principal component vectors of the microbial communities were also statistically significantly associated with lung cancer risk. After multiple testing adjustment, greater relative abundance of 3 genera and presence of 1 genus were associated with greater lung cancer risk, whereas presence of 3 genera were associated with lower risk. For example, every SD increase in Streptococcus abundance was associated with 1.14 times the risk of lung cancer (95% confidence interval = 1.06 to 1.22). Associations were strongest among squamous cell carcinoma cases and former smokers.
Multiple oral microbial measures were prospectively associated with lung cancer risk in 3 US cohort studies, with associations varying by smoking history and histologic subtype. The oral microbiome may offer new opportunities for lung cancer prevention.
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