Adjusting microbiome profiles for differences in microbial load by spike-in bacteria

Accurate prediction of absolute prokaryotic abundance from DNA concentration

Quantification of the absolute microbial abundance in a human stool sample is crucial for a comprehensive understanding of the microbial ecosystem, but this information is lost upon metagenomic sequencing. While several methods exist to measure absolute microbial abundance, they are technically challenging and costly, presenting an opportunity for machine learning. Here, we observe a strong correlation between DNA concentration and the absolute number of 16S ribosomal RNA copies as measured by digital droplet PCR in clinical stool samples from individuals undergoing hematopoietic cell transplantation (BMT CTN 1801). Based on this correlation and additional measurements, we trained an accurate yet simple machine learning model for the prediction of absolute prokaryotic load, which showed exceptional prediction accuracy on an external cohort that includes people living with Parkinson's disease and healthy controls. We propose that, with further validation, this model has the potential to enable accurate absolute abundance estimation based on readily available sample measurements.

Targeting the Gut Microbiota's Role in Host Energy Absorption With Precision Nutrition Interventions for the Prevention and Treatment of Obesity

The field of precision nutrition aims to develop dietary approaches based on individual biological factors such as genomics or the gut microbiota. The gut microbiota, which is the highly individualized and complex community of microbes residing in the colon, is a key contributor to human physiology. Although gut microbes play multiple roles in the metabolism of nutrients, their role in modulating the absorption of dietary energy from foods that escape digestion in the small intestine has the potential to variably affect energy balance and, thus, body weight. The fate of this energy, and its subsequent impact on body weight, is well described in rodents and is emerging in humans. This narrative review is focused on recent clinical evidence of the role of the gut microbiota in human energy balance, specifically its impact on energy available to the human host. Despite recent progress, remaining gaps in knowledge present opportunities for developing and implementing strategies to understand causal microbial mechanisms related to energy balance. We propose that implementing rigorous microbiota-focused measurements in the context of innovative clinical trial designs will elucidate integrated diet-host-gut microbiota mechanisms. These mechanisms are primed to be targets for precision nutrition interventions to optimize energy balance to achieve desired weight outcomes. Given the magnitude and impact of the obesity epidemic, implementing these interventions within comprehensive weight management paradigms has the potential to be of public health significance.

Tracking Different States of Spiked Environmental DNA Using Multiplex Digital PCR Assays

The study of microbial communities based on the total environmental DNA (eDNA) is influenced by the presence of different eDNA states, i.e., intracellular (iDNA) and extracellular DNA (exDNA), and the choice of the DNA extraction method. Although the use of spike-and-recovery controls facilitates the diagnosis of such issues, appropriate experimental setups simultaneously accounting for the different eDNA states and their bacterial origins are missing. Here, we used two single-gene deletion mutants of both Escherichia coli and Bacillus subtilis to trace exDNA and iDNA spike-ins of each selected model organism within environmental samples. Unique primer/probe sets were developed for each strain, allowing their absolute quantification using multiplex digital PCR assays. The proposed spike-and-recovery controls were successfully applied to various environments including soil, sediment, sludge and compost. While the percent recovery of spiked iDNA differed significantly between E. coli and B. subtilis, results were similar for both model organisms in the case of spiked exDNA, emphasising that the fate of DNA molecules in the environment is similar irrespective of their bacterial origin. Hence, future studies may benefit from the proposed approach to better understand methodological ambiguities related to the eDNA extraction in general as well as the separation of the different eDNA states.

In vivo manipulation of human gut Bacteroides fitness by abiotic oligosaccharides

Synthetic glycans (SGs) containing glycosidic linkages and structures not identified in nature offer a means for deliberately altering microbial community properties. Here pools of SG oligosaccharides were generated via polymerization of monosaccharides and screened for their ability to increase saccharolytic Bacteroides in ex vivo cultures of human fecal samples. A lead SG preparation was orally administered to gnotobiotic mice harboring a consortium of 56 cultured, phylogenetically diverse human gut bacteria and fed a Western diet. The abundances of 3 of 15 Bacteroides strains increased, most prominently B. intestinalis. Underlying mechanisms were characterized by analyzing in vivo expression of the carbohydrate utilization machinery, using retrievable microscopic paramagnetic particles with bound SG oligosaccharides and assaying SG degradation by individual purified B. intestinalis glycoside hydrolases. The results reveal that SGs can selectively co-opt carbohydrate utilization machinery in different human gut Bacteroides and demonstrate a means for identifying artificial carbohydrate structures for targeted bacterial manipulation.

Microbiota of Healthy Dental Pulp Under the Omics Loupe

This study aims to contribute to the understanding of the dental pulp microbiome through metataxonomic analysis of pulp tissues from clinically healthy impacted third molars in 17 patients. Samples from coronal pulp, outer radicular dentin, and negative controls were included. Each sample was spiked with a known bacterial standard. Sequencing of the 16S rRNA V3-V4 region revealed similarity in bacterial taxonomic profiles. The bacterial DNA was detected in all pulp samples, primarily originating from reagent contaminants. Although some oral taxa appeared more abundant in pulp than in dentin or controls, contaminant species overwhelmingly dominated. Most of the extracted DNA was of human origin, rather than bacterial. Our findings question the concept of a core microbiome in healthy pulp and highlight the critical need for rigorous controls in pulpal microbiome studies.

Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies

Background

The intestinal microbiota contributes to the colonization resistance of the gut towards bacterial pathogens. Antibiotic treatment often negatively affects the microbiome composition, rendering the host more susceptible for infections. However, a correct interpretation of such a perturbation requires quantitative microbiome profiling to reflect accurately the direction and magnitude of compositional changes within a microbiota. Standard 16S rRNA gene amplicon sequencing of microbiota samples offers compositional data in relative, but not absolute abundancies, and the presence of multiple copies of 16S rRNA genes in bacterial genomes introduces bias into compositional data. We explored whether improved sequencing data analysis influences the significance of the effect exerted by antibiotics on the faecal microbiota of young pigs using two veterinary antibiotics. Calculation of absolute abundances, either by flow cytometry-based bacterial cell counts or by spike-in of synthetic 16S rRNA genes, was employed and 16S rRNA gene copy numbers (GCN) were corrected.

Results

Cell number determination exhibited large interindividual variability in two pig studies, using either tylosin or tulathromycin. Following tylosin application, flow cytometry-based cell counting revealed decreased absolute abundances of five families and ten genera. These results were not detectable by standard 16S analysis based on relative abundances. Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. In another experimental setting with tulathromycin treatment, bacterial abundance quantification by flow cytometry and by a spike-in method yielded similar results only on the phylum level. Even though the spike-in method identified the decrease of four genera, analysis by fluorescence-activated cell sorting (FACS) uncovered eight significantly reduced genera, such as Prevotella and Paraprevotella upon antibiotic treatment. In contrast, analysis of relative abundances only showed a decrease of Faecalibacterium and Rikenellaceae RC9 gut group and, thus, a much less detailed antibiotic effect.

Conclusion

Flow cytometry is a laborious method, but identified a higher number of significant microbiome changes in comparison to common compositional data analysis and even revealed to be superior to a spike-in method. Calculation of absolute abundances and GCN correction are valuable methods that should be standards in microbiome analyses in veterinary as well as human medicine.

The relict plant Tetraena mongolica plantations increase the nutrition and microbial diversity in desert soil

Introduction

Tetraena mongolica was established in the West Ordos Region of northwest China approximately 140 million years ago. It plays an irreplaceable role in maintaining local ecosystem stability.

Methods

This study aimed to evaluate the effects of planting T. mongolica on soil nutrition and microbial communities by comparing the root zone soil (Rz_soil) and bare soil (B_soil) across three different plant communitie.

Results

The results showed that T. mongolica decreased soil pH and Na+ while increasing available potassium, soil organic matter, organic carbon, total nitrogen, and potassium. T. mongolica significantly improved the diversity indices (Sobs and Ace), as well as the richness index (Chao), of bacterial and fungal communities across three plant communities. Meanwhile, the relative abundances of Rubrobacter and norank_c_Actinobacteria in the bacterial communities declined significantly in the Rz_soil compared with the B_soil across all three plant communities. In contrast, the relative abundances of Fusarium and Penicillium were higher, whereas those of Monosporascus and Darksidea were lower in Rz_soil than in B_soil in the two plant communities. T. mongolica decreased the soil bacterial co-occurrence networks while increasing the soil fungal co-occurrence networks.

Discussion

These results provide a new perspective to understand the role of T. Mongolica in the desert ecosystems.

The translocator protein 18 kDa (TSPO) ligand etifoxine in an animal model of anxiety: Line- and sex-dependent effects on emotionality, stress reactivity, spine density, oxytocin receptors, steroids, and microbiome composition

The treatment of stress-related disorders such as anxiety and depression is still challenging. One potential therapeutical option are neurosteroids. Their synthesis is promoted by ligands of the mitochondrial translocator protein 18 kDa (TSPO). We tested the TSPO ligand etifoxine (ETX) in a rat model of hyper-anxiety and depression-like behavior, i.e., in female and male HAB (high anxiety-related behavior) rats, as well as in respective low anxiety (LAB) and non-selected control (NAB) rats for behavioral, molecular, cellular, and physiological parameters. Daily acute i.p. treatment with ETX or vehicle over 5 or 9 days revealed that ETX was most effective in female HAB rats; it reduced anxiety levels (5 days) and OXT-R binding brain site-specifically (5 and 9 days), and increased spine density (5 days). The behavioral ETX effect exclusively found in female HABs was accompanied by increased 3β5α-THDOC levels, without any effect in female LABs and NABs and on other neurosteroids. In males of all breeding lines, ETX changed a total of 10 out of 23 brain steroids. Passive stress-coping during 10-min forced swimming was not affected by 9-day treatment with ETX, the resulting stress-induced plasma corticosterone levels were higher in ETX-treated NAB rats of both sexes compared with their VEH-treated groups. The fecal bacterial composition was similar but beta diversity differed between HABs and LABs and from NABs independent of sex; ETX treatment had no effect. Therefore, we propose considering the aspect of sex in treatment strategies for anxiety disorders. This is particularly important to establish better treatment regimens for women.

Absolute quantification of the living skin microbiome overcomes relic-DNA bias and reveals specific patterns across volunteers

BACKGROUND

As the first line of defense against external pathogens, the skin and its resident microbiota are responsible for protection and eubiosis. Innovations in DNA sequencing have significantly increased our knowledge of the skin microbiome. However, current characterizations do not discriminate between DNA from live cells and remnant DNA from dead organisms (relic DNA), resulting in a combined readout of all microorganisms that were and are currently present on the skin rather than the actual living population of the microbiome. Additionally, most methods lack the capability for absolute quantification of the microbial load on the skin, complicating the extrapolation of clinically relevant information.

RESULTS

Here, we integrated relic-DNA depletion with shotgun metagenomics and bacterial load determination to quantify live bacterial cell abundances across different skin sites. Though we discovered up to 90% of microbial DNA from the skin to be relic DNA, we saw no significant effect of this on the relative abundances of taxa determined by shotgun sequencing. Relic-DNA depletion prior to sequencing strengthened underlying patterns between microbiomes across volunteers and reduced intraindividual similarity. We determined the absolute abundance and the fraction of population alive for several common skin taxa across body sites and found taxa-specific differential abundance of live bacteria across regions to be different from estimates generated by total DNA (live + dead) sequencing.

CONCLUSIONS

Our results reveal the significant bias relic DNA has on the quantification of low biomass samples like the skin. The reduced intraindividual similarity across samples following relic-DNA depletion highlights the bias introduced by traditional (total DNA) sequencing in diversity comparisons across samples. The divergent levels of cell viability measured across different skin sites, along with the inconsistencies in taxa differential abundance determined by total vs live cell DNA sequencing, suggest an important hypothesis for certain sites being susceptible to pathogen infection. Overall, our study demonstrates a characterization of the skin microbiome that overcomes relic-DNA bias to provide a baseline for live microbiota that will further improve mechanistic studies of infection, disease progression, and the design of therapies for the skin. Video Abstract.

Sinomonas gamaensis NEAU-HV1 remodels the IAA14-ARF7/19 interaction to promote plant growth

Sinomonas species typically reside in soils or the rhizosphere and can promote plant growth. Sinomonas enrichment in rhizospheric soils is positively correlated with increases in plant biomass. However, the growth promotion mechanisms regulated by Sinomonas remain unclear. By using soil systems, we studied the growth-promoting effects of Sinomonas gamaensis NEAU-HV1 on various plants. Through a combination of phenotypic analyses and microscopic observations, the effects of NEAU-HV1 on root development were evaluated. We subsequently conducted molecular and genetic experiments to reveal the mechanism promoting lateral root (LR) development. We demonstrated that NEAU-HV1 significantly promoted the growth of lettuce, wheat, maize, peanut and Arabidopsis. This effect was associated with multiple beneficial traits, including phosphate solubilization, indole-3-acetic acid and 1-aminocyclopropane-1-carboxylic acid deaminase production and survival ability in the rhizosphere and within the inner tissue of roots. In addition, NEAU-HV1 could secrete metabolites to promote LR development by affecting auxin transport and signaling. Importantly, we found that the influence of auxin signaling may be attributed to the remodeling interaction between SOLITARY-ROOT (SLR)/IAA14 and ARF7/19, occurring independently of the auxin receptor TIR1/AFB2. Our results indicate that NEAU-HV1-induced LR formation is dependent on direct remodeling interactions between transcription factors, providing novel insights into plant-microbe interactions.

Development of a quantitative metagenomic approach to establish quantitative limits and its application to viruses

Quantitative metagenomic methods are maturing but continue to lack clearly-defined analytical limits. Here, we developed a computational tool, QuantMeta, to determine the absolute abundance of targets in metagenomes spiked with synthetic DNA standards. The tool establishes (i) entropy-based detection thresholds to confidently determine the presence of targets, and (ii) an approach to identify and correct read mapping or assembly errors and thus improve the quantification accuracy. Together this allows for an approach to confidently quantify absolute abundance of targets, be they microbial populations, genes, contigs, or metagenome-assembled genomes. We applied the approach to quantify single- and double-stranded DNA viruses in wastewater viral metagenomes, including pathogens and bacteriophages. Concentrations of total DNA viruses in wastewater influent and effluent were >108 copies/ml using QuantMeta. Human-associated DNA viruses were detected and quantifiable with QuantMeta thresholds, including polyomavirus, papillomavirus, and crAss-like phages, at concentrations similar to previous reports that utilized quantitative polymerase chain reaction (PCR)-based assays. Our results highlight the higher detection thresholds of quantitative metagenomics (approximately 500 copies/μl) as compared to PCR-based quantification (approximately 10 copies/μl) despite a sequencing depth of 200 million reads per sample. The QuantMeta approach, applicable to both viral and cellular metagenomes, advances quantitative metagenomics by improving the accuracy of measured target absolute abundances.

Theabrownin remodels the circadian rhythm disorder of intestinal microbiota induced by a high-fat diet to alleviate obesity in mice

The intestinal microbiota undergoes diurnal compositional and functional oscillations within a day, which affect the metabolic homeostasis of the host and exacerbate the occurrence of obesity. TB has the effect of reducing body weight and lipid accumulation, but the mechanism of improving obesity caused by a high-fat diet based on the circadian rhythm of intestinal microorganisms has not been clarified. In this study, we used multi-omics and imaging approaches to investigate the mechanism of TB in alleviating obesity in mice based on the circadian rhythm of gut microbiota. The results showed that TB could significantly regulate the levels and rhythmic expression of serum lipid indicators (TG, TC, LDL) and serum hormones (MT, FT3, LEP, CORT). The number of intestinal microbiota colonizing the colonic epithelium underwent daily fluctuations. TB remodeled the rhythmic oscillation of gut microbes (i.e., Lachnospiraceae_NK4A136_group, Alistipes, etc.), including the number, composition, abundance and rhythmic expression of the biogeographic localization of microbes. TB notably reduced the levels of 16 bile acids (TCA, THDCA, TCDA, GHDCA, T-α-MCA, etc.) and restored the balance of bile acid metabolism. It was found that TB may mitigate high-fat diet-induced obesity in mice by reshaping the circadian rhythm of the gut microbiome and regulating bile acid metabolism.

Diverse vaginal microbiota in healthy Japanese women: a combined relative and quantitative analyses

Introduction

This cross-sectional study aimed to characterize the viable vaginal microbiota and identify host factors influencing this microbiota by employing a combination of relative and quantitative analyses.

Methods

Twenty-four vaginal fluid samples were collected from healthy adult Japanese women for analysis. Vaginal fluid pH was measured using a portable pH meter. DNA was extracted from the vaginal fluid, and the 16S ribosomal RNA gene sequences in the V3-V4 regions were analyzed to identify bacterial species. Additionally, the vaginal fluid was cultured on four types of selective agar plates. The predominant species in the growing colonies were identified using colony polymerase chain reaction, and the colonies were counted.

Results

The vaginal microbiota was classified into four categories based on the characterization of the dominant bacterial population: Lactobacillus crispatus, Lactobacillus iners, Lactobacillus gasseri, and a diversity group. The predominant bacterial species were consistent across methods; however, the levels of the viable population varied significantly. Body mass index had a significant influence on the total number of viable bacteria and vaginal pH, while age only affected vaginal pH.

Conclusions

Our findings indicate that the vaginal microbiome of healthy Japanese women is not only highly diverse but also affected by host factors such as BMI and age.

Oral Lactoferrin-Responsive Formulation Anchoring around Inflammatory Bowel Region for IBD Therapy

Oral formulation is the ideal treatment method for inflammatory bowel disease (IBD) therapy, but the mucosal damage and diarrhea symptoms impede the drug retention around the inflammatory region, severely limiting IBD therapeutic efficacy. To address this, an oral astaxanthin (Ast) precise delivery formulation is developed with the selective Ast anchoring around the inflammatory region by the novel lactoferrin (LF)-responsive flocculation. This formulation also heightens the apparent solubility of Ast with the minimized edible safety risks for the edible raw materials. For in vivo IBD therapy, the precise delivery formulation exhibits remarkable outcomes, including a significant increase in colon length and a 100% survival rate. Furthermore, it is verified that the mechanism of treatment is primarily attributed to the improved immunoregulation, epithelial repair, and gut microbiota remodeling after the LF-responsive flocculation. This effective inflammatory-responsive delivery design is instructive and valuable to develop more precise delivery systems for IBD therapy.

The quest for environmental analytical microbiology: absolute quantitative microbiome using cellular internal standards

BACKGROUND

High-throughput sequencing has revolutionized environmental microbiome research, providing both quantitative and qualitative insights into nucleic acid targets in the environment. The resulting microbial composition (community structure) data are essential for environmental analytical microbiology, enabling characterization of community dynamics and assessing microbial pollutants for the development of intervention strategies. However, the relative abundances derived from sequencing impede comparisons across samples and studies.

RESULTS

This review systematically summarizes various absolute quantification (AQ) methods and their applications to obtain the absolute abundance of microbial cells and genetic elements. By critically comparing the strengths and limitations of AQ methods, we advocate the use of cellular internal standard-based high-throughput sequencing as an appropriate AQ approach for studying environmental microbiome originated from samples of complex matrices and high heterogeneity. To minimize ambiguity and facilitate cross-study comparisons, we outline essential reporting elements for technical considerations, and provide a checklist as a reference for environmental microbiome research.

CONCLUSIONS

In summary, we propose absolute microbiome quantification using cellular internal standards for environmental analytical microbiology, and we anticipate that this approach will greatly benefit future studies. Video Abstract.

Challenge of validation in whole-cell spike-in amplicon sequencing to comprehensively quantify food lactic acid bacteriota

Lactic acid bacteria (LAB) shape diverse communities in fermented foods. Developing comprehensive quantification methods for community structure will revolutionize our understanding of food LAB microbiome. For this purpose, 16S rRNA gene amplicon-based quantification, using spiked exogenous bacterial cells as an internal standard, shows potential for comprehensiveness and accuracy. We validated cell spike-in amplicon sequencing for quantifying LAB communities in food. Low efficiency of LAB DNA extraction underscores the importance of compensating for DNA loss by spiking internal standard cells. Quantitative equations generated using 15 selected LAB mock species showed positive relationships between the ratio of MiSeq read counts and the expected 16S rRNA gene copy numbers, with coefficients of determination (R2) ≥ 0.6823. The fold differences between observed and expected 16S copy numbers were within the range of 1/3 to 3-fold. Our validation highlights that accurate preparation of the LAB mock community is crucial for cell spike-in amplicon sequencing accuracy.

Characterization of liver, adipose, and fecal microbiome in obese patients with MASLD: links with disease severity and metabolic dysfunction parameters

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses a range of histological findings from the generally benign simple steatosis to steatohepatitis (MASH) which can progress to fibrosis and cirrhosis. Several factors, including the microbiome, may contribute to disease progression.

RESULTS

Here, we demonstrate links between the presence and abundance of specific bacteria in the adipose and liver tissues, inflammatory genes, immune cell responses, and disease severity. Overall, in MASLD patients, we observed a generalized obesity-induced translocation of gut bacteria to hepatic and adipose tissues. We identified microbial patterns unique to more severely diseased tissues. Specifically, Enterococcus, Granulicatella, and Morganellaceae abundance is positively correlated with immune cell counts and inflammatory gene expression levels, and both genera are significantly enriched in MASH patients. Brevibacterium is enriched in adipose tissues of patients with liver fibrosis.

CONCLUSION

Together, these results provide further insight into the microbial factors that may be driving disease severity. Video Abstract.

Fecal microbial load is a major determinant of gut microbiome variation and a confounder for disease associations

The microbiota in individual habitats differ in both relative composition and absolute abundance. While sequencing approaches determine the relative abundances of taxa and genes, they do not provide information on their absolute abundances. Here, we developed a machine-learning approach to predict fecal microbial loads (microbial cells per gram) solely from relative abundance data. Applying our prediction model to a large-scale metagenomic dataset (n = 34,539), we demonstrated that microbial load is the major determinant of gut microbiome variation and is associated with numerous host factors, including age, diet, and medication. We further found that for several diseases, changes in microbial load, rather than the disease condition itself, more strongly explained alterations in patients' gut microbiome. Adjusting for this effect substantially reduced the statistical significance of the majority of disease-associated species. Our analysis reveals that the fecal microbial load is a major confounder in microbiome studies, highlighting its importance for understanding microbiome variation in health and disease.

Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization

Absolute bacterial biomass estimation in the human gut is crucial for understanding microbiome dynamics and host-microbe interactions. Current methods for quantifying bacterial biomass in stool, such as flow cytometry, qPCR, or spike-ins (i.e., adding cells or DNA from an organism not normally found in a sample), can be labor-intensive, costly, and confounded by factors like water content, DNA extraction efficiency, PCR inhibitors, and other technical challenges that add bias and noise. We propose a simple, cost-effective approach that circumvents some of these technical challenges: directly estimating bacterial biomass from metagenomes using bacterial-to-host (B:H) read ratios. We compare B:H ratios to the standard methods outlined above, demonstrating that B:H ratios are useful proxies for bacterial biomass in stool and possibly in other host-associated substrates. We show how B:H ratios can be used to track antibiotic treatment response and recovery in both mice and humans, which showed 403-fold and 45-fold reductions in bacterial biomass during antibiotic treatment, respectively. Our results indicate that host and bacterial metagenomic DNA fractions in human stool fluctuate longitudinally around a stable mean in healthy individuals, and the average host read fraction varies across healthy individuals by < 8-9 fold. B:H ratios offer a convenient alternative to other absolute biomass quantification methods, without the need for additional measurements, experimental design considerations, or machine learning algorithms, enabling retrospective absolute biomass estimates from existing stool metagenomic data.

Synthetic DNA spike-in standards for cross-domain absolute quantification of microbiomes by rRNA gene amplicon sequencing

Microbiome studies using high-throughput sequencing are increasingly incorporating absolute quantitative approaches to overcome the inherent limitations of relative abundances. In this study, we have designed and experimentally validated a set of 12 unique synthetic rRNA operons, which we refer to as rDNA-mimics, to serve as spike-in standards for quantitative profiling of fungal/eukaryotic and bacterial microbiomes. The rDNA-mimics consist of conserved sequence regions from natural rRNA genes to act as binding sites for common universal PCR primers, and bioinformatically designed variable regions that allow their robust identification in any microbiome sample. All constructs cover multiple rRNA operon regions commonly targeted in fungal/eukaryotic microbiome studies (SSU-V9, ITS1, ITS2, and LSU-D1D2) and two of them also include an artificial segment of the bacterial 16S rRNA gene (SSU-V4) for cross-domain application. We validated the quantitative performance of the rDNA-mimics using defined mock communities and representative environmental samples. In particular, we show that rDNA-mimics added to extracted DNA or directly to the samples prior to DNA extraction precisely reflects the total amount of fungal and/or bacterial rRNA genes in the samples. We demonstrate that this allows accurate estimation of differences in microbial loads between samples, thereby confirming that the rDNA-mimics are suitable for absolute quantitative analyses of differential microbial abundances.

Effects of intergenerational transmission of small intestinal bacteria cultured from stunted Bangladeshi children with enteropathy

Environmental enteric dysfunction (EED), a small intestinal disorder found at a high prevalence in stunted children, is associated with gut mucosal barrier disruption and decreased absorptive capacity due to reduced intact small intestinal villi1-4. To test the hypothesis that intergenerational transmission of a perturbed small intestinal microbiota contributes to undernutrition by inducing EED5, we characterized two consortia of bacterial strains cultured from duodenal aspirates from stunted Bangladeshi children with EED - one of which induced local and systemic inflammation in gnotobiotic female mice. Offspring of dams that received this inflammatory consortium exhibited immunologic changes along their gut that phenocopied features of EED in children. Single nucleus plus bulk RNA-sequencing revealed alterations in inter-cellular signaling pathways related to intestinal epithelial cell renewal, barrier integrity and immune function while analyses of cerebral cortex disclosed alterations in glial- and endothelial-neuronal signaling pathways that regulate neural growth/axonal guidance, angiogenesis and inflammation. Analysis of ultrasonic vocalization calls in gnotobiotic P5-P9 pups indicated increased arousal and perturbed neurodevelopment in the offspring of dams harboring the inflammation-inducing consortium. Cohousing experiments and follow-up screening of candidate disease-promoting bacterial isolates identified a strain typically found in the oral microbiota (Campylobacter concisus) as a contributor to enteropathy. Given that fetal growth was also impaired in the dams with the consortium that induced enteropathy, this preclinical model allows the effects of the human small intestinal microbiota on both pre- and postnatal development to be ascertained, setting the stage for identification of small intestinal microbiota-targeted therapeutics for (intergenerational) undernutrition.

Multi-factor analysis of the quality of cellar mud of Luzhou-flavor liquor in Yibin production area

The aim of this study was to conduct a thorough scientific investigation into the similarities and differences in the quality of the cellars of different Luzhou-flavor liquor wineries in Yibin production area and the reasons for them. This study analyzed cellar mud samples from five wineries in Yibin production area. The analysis of volatile flavor compounds was carried out using headspace solid-phase microextraction and gas chromatography-mass spectrometry. The bacterial and archaeal community structures and their correlations were analyzed by high-throughput sequencing. The study indicates that the Distillery A had the highest levels of ammonium nitrogen and effective phosphorus, Distillery F had the highest humus levels, and Distillery I had the highest pH levels. The community structure of the principal bacterial and archaeal communities in the five subterranean clays exhibited similarity, and all samples were dominated by Firmicutes as the primary bacterial group. However, there was variation in bacterial abundance. The cellar mud also has obvious regional differences, and there are three genera of differentially dominant archaea in the archaea. In summary, significant differences were observed in the physicochemical indexes of bacterial and archaeal abundance across all five samples. These differences led to variations in both the content and composition of volatile constituents.

Harnessing human microbiomes for disease prediction

The human microbiome has been increasingly recognized as having potential use for disease prediction. Predicting the risk, progression, and severity of diseases holds promise to transform clinical practice, empower patient decisions, and reduce the burden of various common diseases, as has been demonstrated for cardiovascular disease or breast cancer. Combining multiple modifiable and non-modifiable risk factors, including high-dimensional genomic data, has been traditionally favored, but few studies have incorporated the human microbiome into models for predicting the prospective risk of disease. Here, we review research into the use of the human microbiome for disease prediction with a particular focus on prospective studies as well as the modulation and engineering of the microbiome as a therapeutic strategy.

Multiple Sclerosis and Clostridium perfringens Epsilon Toxin: Is There a Relationship?

Recent research has suggested a link between multiple sclerosis and the gut microbiota. This prospective pilot study aimed to investigate the composition of the gut microbiota in MS patients, the presence of Clostridium perfringens epsilon toxin in the serum of MS patients, and the influence of disease-modifying drugs (DMDs) on epsilon toxin levels and on the microbiota. Epsilon toxin levels in blood were investigated by two methods, a qualitative ELISA and a highly sensitive quantitative ELISA. Neither epsilon toxin nor antibodies against it were detected in the analyzed serum samples. 16S ribosomal RNA sequencing was applied to obtain insights into the composition of the gut microbiota of MS patients. No significant differences in the quantity, diversity, and the relative abundance of fecal microbiota were observed in the gut microbiota of MS patients receiving various DMDs, including teriflunomide, natalizumab, ocrelizumab, and fingolimod, or no therapy. The present study did not provide evidence supporting the hypothesis of a causal relationship between Clostridium perfringens epsilon toxin and multiple sclerosis.

A new spike-in-based method for quantitative metabarcoding of soil fungi and bacteria

Metabarcoding is a powerful tool to characterize biodiversity in biological samples. The interpretation of taxonomic profiles from metabarcoding data has been hindered by their compositional nature. Several strategies have been proposed to transform compositional data into quantitative data, but they have intrinsic limitations. Here, I propose a workflow based on bacterial and fungal cellular internal standards (spike-ins) for absolute quantification of the microbiota in soil samples. These standards were added to the samples before DNA extraction in amounts estimated after qPCRs, to target around 1-2% coverage in the sequencing run. In bacteria, proportions of spike-in reads in the sequencing run were very similar (< 2-fold change) to those predicted by the qPCR assessment, and for fungi they differed up to 40-fold. The low variation among replicates highlights the reproducibility of the method. Estimates based on multiple bacterial spike-ins were highly correlated (r = 0.99). Procrustes analysis evidenced significant biological effects on the community composition when normalizing compositional data. A protocol based on qPCR estimation of input amounts of cellular spikes is proposed as a cheap and reliable strategy for quantitative metabarcoding of biological samples.

Quantitative analysis of the effects of essential oil mouthrinses on clinical plaque microbiome: a parallel-group, randomized trial

BACKGROUND

The rich diversity of microorganisms in the oral cavity plays an important role in the maintenance of oral health and development of detrimental oral health conditions. Beyond commonly used qualitative microbiome metrics, such as relative proportions or diversity, both the species-level identification and quantification of bacteria are key to understanding clinical disease associations. This study reports the first-time application of an absolute quantitative microbiome analysis using spiked DNA standards and shotgun metagenome sequencing to assess the efficacy and safety of product intervention on dental plaque microbiome.

METHODS

In this parallel-group, randomized clinical trial, essential oil mouthrinses, including LISTERINE® Cool Mint Antiseptic (LCM), an alcohol-containing prototype mouthrinse (ACPM), and an alcohol-free prototype mouthrinse (AFPM), were compared against a hydroalcohol control rinse on clinical parameters and the oral microbiome of subjects with moderate gingivitis. To enable a sensitive and clinically meaningful measure of bacterial abundances, species were categorized according to their associations with oral conditions based on published literature and quantified using known amounts of spiked DNA standards.

RESULTS

Multivariate analysis showed that both LCM and ACPM shifted the dysbiotic microbiome composition of subjects with gingivitis to a healthier state after 4 weeks of twice-daily use, resembling the composition of subjects with clinically healthy oral conditions recruited for observational reference comparison at baseline. The essential oil-containing mouthrinses evaluated in this study showed statistically significant reductions in clinical gingivitis and plaque measurements when compared to the hydroalcohol control rinse after 6 weeks of use.

CONCLUSIONS

By establishing a novel quantitative method for microbiome analysis, this study sheds light on the mechanisms of LCM mouthrinse efficacy on oral microbial ecology, demonstrating that repeated usage non-selectively resets a gingivitis-like oral microbiome toward that of a healthy oral cavity.

TRIAL REGISTRATION

The trial was registered on ClinicalTrials.gov on 10/06/2021. The registration number is NCT04921371.

Prevotella copri and microbiota members mediate the beneficial effects of a therapeutic food for malnutrition

Microbiota-directed complementary food (MDCF) formulations have been designed to repair the gut communities of malnourished children. A randomized controlled trial demonstrated that one formulation, MDCF-2, improved weight gain in malnourished Bangladeshi children compared to a more calorically dense standard nutritional intervention. Metagenome-assembled genomes from study participants revealed a correlation between ponderal growth and expression of MDCF-2 glycan utilization pathways by Prevotella copri strains. To test this correlation, here we use gnotobiotic mice colonized with defined consortia of age- and ponderal growth-associated gut bacterial strains, with or without P. copri isolates closely matching the metagenome-assembled genomes. Combining gut metagenomics and metatranscriptomics with host single-nucleus RNA sequencing and gut metabolomic analyses, we identify a key role of P. copri in metabolizing MDCF-2 glycans and uncover its interactions with other microbes including Bifidobacterium infantis. P. copri-containing consortia mediated weight gain and modulated energy metabolism within intestinal epithelial cells. Our results reveal structure-function relationships between MDCF-2 and members of the gut microbiota of malnourished children with potential implications for future therapies.

Strain specific differences in vitamin D3 response: impact on gut homeostasis

Vitamin D3 regulates a variety of biological processes irrespective of its well-known importance for calcium metabolism. Epidemiological and animal studies indicate a role in immune regulation, intestinal barrier function and microbiome diversity. Here, we analyzed the impact of different vitamin D3- containing diets on C57BL/6 and BALB/c mice, with a particular focus on gut homeostasis and also investigated effects on immune cells in vitro. Weak regulatory effects were detected on murine T cells. By trend, the active vitamin D3 metabolite 1,25-dihydroxyvitamin D3 suppressed IFN, GM-CSF and IL-10 cytokine secretion in T cells of C57BL/6 but not BALB/c mice, respectively. Using different vitamin D3-fortified diets, we found a tissue-specific enrichment of mainly CD11b+ myeloid cells but not T cells in both mouse strains e.g. in spleen and Peyer's Patches. Mucin Reg3γ and Batf expression, as well as important proteins for gut homeostasis, were significantly suppressed in the small intestine of C57BL76 but not BALB/c mice fed with a high-vitamin D3 containing diet. Differences between both mouse stains were not completely explained by differences in vitamin D3 receptor expression which was strongly expressed in epithelial cells of both strains. Finally, we analyzed gut microbiome and again an impact of vitamin D3 was detected in C57BL76 but not BALB/c. Our data suggest strain-specific differences in vitamin D3 responsiveness under steady state conditions which may have important implications when choosing a murine disease model to study vitamin D3 effects.

A tripartite bacterial-fungal-plant symbiosis in the mycorrhiza-shaped microbiome drives plant growth and mycorrhization

BACKGROUND

Plant microbiomes play crucial roles in nutrient cycling and plant growth, and are shaped by a complex interplay between plants, microbes, and the environment. The role of bacteria as mediators of the 400-million-year-old partnership between the majority of land plants and, arbuscular mycorrhizal (AM) fungi is still poorly understood. Here, we test whether AM hyphae-associated bacteria influence the success of the AM symbiosis.

RESULTS

Using partitioned microcosms containing field soil, we discovered that AM hyphae and roots selectively assemble their own microbiome from the surrounding soil. In two independent experiments, we identified several bacterial genera, including Devosia, that are consistently enriched on AM hyphae. Subsequently, we isolated 144 pure bacterial isolates from a mycorrhiza-rich sample of extraradical hyphae and isolated Devosia sp. ZB163 as root and hyphal colonizer. We show that this AM-associated bacterium synergistically acts with mycorrhiza on the plant root to strongly promote plant growth, nitrogen uptake, and mycorrhization.

CONCLUSIONS

Our results highlight that AM fungi do not function in  isolation and that the plant-mycorrhiza symbiont can recruit beneficial bacteria that support the symbiosis. Video Abstract.

Bacteria and bacteriophage consortia are associated with protective intestinal metabolites in patients receiving stem cell transplantation

The microbiome is a predictor of clinical outcome in patients receiving allogeneic hematopoietic stem cell transplantation (allo-SCT). Microbiota-derived metabolites can modulate these outcomes. How bacteria, fungi and viruses contribute to the production of intestinal metabolites is still unclear. We combined amplicon sequencing, viral metagenomics and targeted metabolomics from stool samples of patients receiving allo-SCT (n = 78) and uncovered a microbiome signature of Lachnospiraceae and Oscillospiraceae and their associated bacteriophages, correlating with the production of immunomodulatory metabolites (IMMs). Moreover, we established the IMM risk index (IMM-RI), which was associated with improved survival and reduced relapse. A high abundance of short-chain fatty acid-biosynthesis pathways, specifically butyric acid via butyryl-coenzyme A (CoA):acetate CoA-transferase (BCoAT, which catalyzes EC 2.8.3.8) was detected in IMM-RI low-risk patients, and virome genome assembly identified two bacteriophages encoding BCoAT as an auxiliary metabolic gene. In conclusion, our study identifies a microbiome signature associated with protective IMMs and provides a rationale for considering metabolite-producing consortia and metabolite formulations as microbiome-based therapies.

A metagenomics method for the quantitative detection of bacterial pathogens causing hospital-associated and ventilator-associated pneumonia

IMPORTANCE

The management of ventilator-associated pneumonia and hospital-acquired pneumonia requires rapid and accurate quantitative detection of the infecting pathogen. To this end, we propose a metagenomic sequencing assay that includes the use of an internal sample processing control for the quantitative detection of 20 relevant bacterial species from bronchoalveolar lavage samples.

A quantitative sequencing method using synthetic internal standards including functional and phylogenetic marker genes

The method of spiking synthetic internal standard genes (ISGs) to samples for amplicon sequencing, generating sequences and converting absolute gene numbers from read counts has been used only for phylogenetic markers and has not been applied to functional markers. In this study, we developed ISGs, including gene sequences of the 16S rRNA, pmoA, encoding a subunit of particulate methane monooxygenase and amoA, encoding a subunit of ammonia monooxygenase. We added ISGs to the samples, amplified the target genes and performed amplicon sequencing. For the mock community, the copy numbers converted from read counts using ISGs were equivalent to those obtained by the quantitative real-time polymerase chain reaction (4.0 × 104 versus 4.1 × 104 and 3.0 × 103 versus 4.0 × 103 copies μL-DNA-1 for 16S rRNA and pmoA genes, respectively), but we also identified underestimation, possibly due to primer coverage (7.8 × 102 versus 3.7 × 103  μL-DNA-1 for amoA gene). We then applied this method to environmental samples and analysed phylogeny, functional diversity and absolute quantities. One Methylocystis population was most abundant in the sludge samples [16S rRNA gene (3.8 × 109 copies g-1 ) and the pmoA gene (2.3 × 109 copies g-1 )] and were potentially interrelated. This study demonstrates that ISG spiking is useful for evaluating sequencing data processing and quantifying functional markers.

Restrictive Versus Permissive Use of Broad-spectrum Antibiotics in Patients Receiving Allogeneic Stem Cell Transplantation and With Early Fever Due to Cytokine Release Syndrome: Evidence for Beneficial Microbiota Protection Without Increase in Infectious Complications

BACKGROUND

Intestinal microbiome contributes to the pathophysiology of acute gastrointestinal (GI) graft-versus-host disease (GvHD) and loss of microbiome diversity influences the outcome of patients after allogeneic stem cell transplantation (SCT). Systemic broad-spectrum antibiotics have been identified as a major cause of early intestinal dysbiosis.

METHODS

In 2017, our transplant unit at the university hospital in Regensburg changed the antibiotic strategy from a permissive way with initiation of antibiotics in all patients with neutropenic fever independent of the underlying cause and risk to a restrictive use in cases with high likelihood of cytokine release syndrome (eg, after anti-thymocyte globulin [ATG] therapy). We analyzed clinical data and microbiome parameters obtained 7 days after allogeneic SCT from 188 patients with ATG therapy transplanted in 2015/2016 (permissive cohort, n = 101) and 2918/2019 (restrictive cohort, n = 87).

RESULTS

Restrictive antibiotic treatment postponed the beginning of antibiotic administration from 1.4 ± 7.6 days prior to 1.7 ± 5.5 days after SCT (P = .01) and significantly reduced the duration of antibiotic administration by 5.8 days (P < .001) without increase in infectious complications. Furthermore, we observed beneficial effects of the restrictive strategy compared with the permissive way on microbiome diversity (urinary 3-indoxylsulfate, P = .01; Shannon and Simpson indices, P < .001) and species abundance 7 days post-transplant as well as a positive trend toward a reduced incidence of severe GI GvHD (P = .1).

CONCLUSIONS

Our data indicate that microbiota protection can be achieved by a more careful selection of neutropenic patients qualifying for antibiotic treatment during allogeneic SCT without increased risk of infectious complications.

Quantitative Amplicon Sequencing Is Necessary to Identify Differential Taxa and Correlated Taxa Where Population Sizes Differ

High-throughput, multiplexed-amplicon sequencing has become a core tool for understanding environmental microbiomes. As researchers have widely adopted sequencing, many open-source analysis pipelines have been developed to compare microbiomes using compositional analysis frameworks. However, there is increasing evidence that compositional analyses do not provide the information necessary to accurately interpret many community assembly processes. This is especially true when there are large gradients that drive distinct community assembly processes. Recently, sequencing has been combined with Q-PCR (among other sources of total quantitation) to generate "Quantitative Sequencing" (QSeq) data. QSeq more accurately estimates the true abundance of taxa, is a more reliable basis for inferring correlation, and, ultimately, can be more reliably related to environmental data to infer community assembly processes. In this paper, we use a combination of published data sets, synthesis, and empirical modeling to offer guidance for which contexts QSeq is advantageous. As little as 5% variation in total abundance among experimental groups resulted in more accurate inference by QSeq than compositional methods. Compositional methods for differential abundance and correlation unreliably detected patterns in abundance and covariance when there was greater than 20% variation in total abundance among experimental groups. Whether QSeq performs better for beta diversity analysis depends on the question being asked, and the analytic strategy (e.g., what distance metric is being used); for many questions and methods, QSeq and compositional analysis are equivalent for beta diversity analysis. QSeq is especially useful for taxon-specific analysis; QSeq transformation and analysis should be the default for answering taxon-specific questions of amplicon sequence data. Publicly available bioinformatics pipelines should incorporate support for QSeq transformation and analysis.

Depth-Dependent Distribution of Prokaryotes in Sediments of the Manganese Crust on Nazimov Guyots of the Magellan Seamounts

Deep ocean polymetallic nodules, rich in cobalt, nickel, and titanium which are commonly used in high-technology and biotechnology applications, are being eyed for green energy transition through deep-sea mining operations. Prokaryotic communities underneath polymetallic nodules could participate in deep-sea biogeochemical cycling, however, are not fully described. To address this gap, we collected sediment cores from Nazimov guyots, where polymetallic nodules exist, to explore the diversity and vertical distribution of prokaryotic communities. Our 16S rRNA amplicon sequencing data, quantitative PCR results, and phylogenetic beta diversity indices showed that prokaryotic diversity in the surficial layers (0-8 cm) was > 4-fold higher compared to deeper horizons (8-26 cm), while heterotrophs dominated in all sediment horizons. Proteobacteria was the most abundant taxon (32-82%) across all sediment depths, followed by Thaumarchaeota (4-37%), Firmicutes (2-18%), and Planctomycetes (1-6%). Depth was the key factor controlling prokaryotic distribution, while heavy metals (e.g., iron, copper, nickel, cobalt, zinc) can also influence significantly the downcore distribution of prokaryotic communities. Analyses of phylogenetic diversity showed that deterministic processes governing prokaryotic assembly in surficial layers, contrasting with stochastic influences in deep layers. This was further supported from the detection of a more complex prokaryotic co-occurrence network in the surficial layer which suggested more diverse prokaryotic communities existed in the surface vs. deeper sediments. This study expands current knowledge on the vertical distribution of benthic prokaryotic diversity in deep sea settings underneath polymetallic nodules, and the results reported might set a baseline for future mining decisions.

Overview of data preprocessing for machine learning applications in human microbiome research

Although metagenomic sequencing is now the preferred technique to study microbiome-host interactions, analyzing and interpreting microbiome sequencing data presents challenges primarily attributed to the statistical specificities of the data (e.g., sparse, over-dispersed, compositional, inter-variable dependency). This mini review explores preprocessing and transformation methods applied in recent human microbiome studies to address microbiome data analysis challenges. Our results indicate a limited adoption of transformation methods targeting the statistical characteristics of microbiome sequencing data. Instead, there is a prevalent usage of relative and normalization-based transformations that do not specifically account for the specific attributes of microbiome data. The information on preprocessing and transformations applied to the data before analysis was incomplete or missing in many publications, leading to reproducibility concerns, comparability issues, and questionable results. We hope this mini review will provide researchers and newcomers to the field of human microbiome research with an up-to-date point of reference for various data transformation tools and assist them in choosing the most suitable transformation method based on their research questions, objectives, and data characteristics.

Climate change drives loss of bacterial gut mutualists at the expense of host survival in wild meerkats

Climate change and climate-driven increases in infectious disease threaten wildlife populations globally. Gut microbial responses are predicted to either buffer or exacerbate the negative impacts of these twin pressures on host populations. However, examples that document how gut microbial communities respond to long-term shifts in climate and associated disease risk, and the consequences for host survival, are rare. Over the past two decades, wild meerkats inhabiting the Kalahari have experienced rapidly rising temperatures, which is linked to the spread of tuberculosis (TB). We show that over the same period, the faecal microbiota of this population has become enriched in Bacteroidia and impoverished in lactic acid bacteria (LAB), a group of bacteria including Lactococcus and Lactobacillus that are considered gut mutualists. These shifts occurred within individuals yet were compounded over generations, and were better explained by mean maximum temperatures than mean rainfall over the previous year. Enriched Bacteroidia were additionally associated with TB exposure and disease, the dry season and poorer body condition, factors that were all directly linked to reduced future survival. Lastly, abundances of LAB taxa were independently and positively linked to future survival, while enriched taxa did not predict survival. Together, these results point towards extreme temperatures driving an expansion of a disease-associated pathobiome and loss of beneficial taxa. Our study provides the first evidence from a longitudinally sampled population that climate change is restructuring wildlife gut microbiota, and that these changes may amplify the negative impacts of climate change through the loss of gut mutualists. While the plastic response of host-associated microbiotas is key for host adaptation under normal environmental fluctuations, extreme temperature increases might lead to a breakdown of coevolved host-mutualist relationships.

Inducible CRISPR-targeted "knockdown" of human gut Bacteroides in gnotobiotic mice discloses glycan utilization strategies

Understanding how members of the human gut microbiota prioritize nutrient resources is one component of a larger effort to decipher the mechanisms defining microbial community robustness and resiliency in health and disease. This knowledge is foundational for development of microbiota-directed therapeutics. To model how bacteria prioritize glycans in the gut, germfree mice were colonized with 13 human gut bacterial strains, including seven saccharolytic Bacteroidaceae species. Animals were fed a Western diet supplemented with pea fiber. After community assembly, an inducible CRISPR-based system was used to selectively and temporarily reduce the absolute abundance of Bacteroides thetaiotaomicron or B. cellulosilyticus by 10- to 60-fold. Each knockdown resulted in specific, reproducible increases in the abundances of other Bacteroidaceae and dynamic alterations in their expression of genes involved in glycan utilization. Emergence of these "alternate consumers" was associated with preservation of community saccharolytic activity. Using an inducible system for CRISPR base editing in vitro, we disrupted translation of transporters critical for utilizing dietary polysaccharides in Phocaeicola vulgatus, a B. cellulosilyticus knockdown-responsive taxon. In vitro and in vivo tests of the resulting P. vulgatus mutants allowed us to further characterize mechanisms associated with its increased fitness after knockdown. In principle, the approach described can be applied to study utilization of a range of nutrients and to preclinical efforts designed to develop therapeutic strategies for precision manipulation of microbial communities.

Long-term biodegradation of crude oil in high-arctic backshore sediments: The Baffin Island Oil Spill (BIOS) after nearly four decades

With an on-going disproportional warming of the Arctic Ocean and the reduction of the sea ice cover, the risk of an accidental oil spill from ships or future oil exploration is increasing. It is hence important to know how crude oil weathers in this environment and what factors affect oil biodegradation in the Arctic. However, this topic is currently poorly studied. In the 1980s, the Baffin Island Oil Spill (BIOS) project carried out a series of simulated oil spills in the backshore zone of beaches located on Baffin Island in the Canadian High Arctic. In this study two BIOS sites were re-visited, offering the unique opportunity to study the long-term weathering of crude oil under Arctic conditions. Here we show that residual oil remains present at these sites even after almost four decades since the original oiling. Oil at both BIOS sites appears to have attenuated very slowly with estimated loss rates of 1.8-2.7% per year. The presence of residual oil continues to significantly affect sediment microbial communities at the sites as manifested by a significantly decreased diversity, differences in the abundance of microorganisms and an enrichment of putative oil-degrading bacteria in oiled sediments. Reconstructed genomes of putative oil degraders suggest that only a subset is specifically adapted for growth under psychrothermic conditions, further reducing the time for biodegradation during the already short Arctic summers. Altogether, this study shows that crude oil spilled in the Arctic can persist and significantly affect the Arctic ecosystem for a long time, in the order of several decades.

Uterine Microbiome: Does the Sampling Technique Matter?

Studies have proven the significance of microbial communities in various parts of the human body for health. In recent years it has been discovered that the uterine cavity is not sterile, and endometrium has its own microbiome which appears to have an impact on female fertility and gynecological pathologies. Lactobacillus has shown to dominate the microbial profile in the uterus and is considered an indicator of a healthy uterine environment. Yet, many argue that the Lactobacillus dominance is due to vaginal contamination during the sampling process. To date there is no clearly defined healthy endometrial microbial profile, which is largely due to the fact that determining the microbial community from the endometrium is complicated, and there is currently no consensus on sampling methods for the endometrial microbiome. As a result, this restricts ability to replicate discoveries made in other cohorts. Here we aim to give an overview of the sampling methods used and discuss what impedes the endometrial microbiome studies as well as how to reach a consensus on the study design. This knowledge could be incorporated into the future research and the knowledge on endometrial microbiome could be included into the diagnostics and treatment of female reproductive health.

RSim: A reference-based normalization method via rank similarity

Microbiome sequencing data normalization is crucial for eliminating technical bias and ensuring accurate downstream analysis. However, this process can be challenging due to the high frequency of zero counts in microbiome data. We propose a novel reference-based normalization method called normalization via rank similarity (RSim) that corrects sample-specific biases, even in the presence of many zero counts. Unlike other normalization methods, RSim does not require additional assumptions or treatments for the high prevalence of zero counts. This makes it robust and minimizes potential bias resulting from procedures that address zero counts, such as pseudo-counts. Our numerical experiments demonstrate that RSim reduces false discoveries, improves detection power, and reveals true biological signals in downstream tasks such as PCoA plotting, association analysis, and differential abundance analysis.

Multimodal immune cell phenotyping in GI biopsies reveals microbiome-related T cell modulations in human GvHD

Acute graft-versus-host disease (aGvHD) is a significant complication after allogeneic hematopoietic stem cell transplantation (aHSCT), but major factors determining disease severity are not well defined yet. By combining multiplexed tissue imaging and single-cell RNA sequencing on gastrointestinal biopsies from aHSCT-treated individuals with fecal microbiome analysis, we link high microbiome diversity and the abundance of short-chain fatty acid-producing bacteria to the sustenance of suppressive regulatory T cells (Tregs). Furthermore, aGvHD severity strongly associates with the clonal expansion of mainly CD8 T cells, which we find distributed over anatomically distant regions of the gut, persistent over time, and inversely correlated with the presence of suppressive Tregs. Overall, our study highlights the pathophysiological importance of expanded CD8 T cell clones in the progression of aGvHD toward more severe clinical manifestations and strongly supports the further development of microbiome interventions as GvHD treatment via repopulation of the gut Treg niche to suppress inflammation.

Comparison of DNA extraction methods for 16S rRNA gene sequencing in the analysis of the human gut microbiome

The gut microbiome is widely analyzed using high-throughput sequencing, such as 16S rRNA gene amplicon sequencing and shotgun metagenomic sequencing (SMS). DNA extraction is known to have a large impact on the metagenomic analyses. The aim of this study was to compare DNA extraction protocols for 16S sequencing. In that context, four commonly used DNA extraction methods were compared for the analysis of the gut microbiota. Commercial versions were evaluated against modified protocols using a stool preprocessing device (SPD, bioMérieux) upstream DNA extraction. Stool samples from nine healthy volunteers and nine patients with a Clostridium difficile infection were extracted with all protocols and 16S sequenced. Protocols were ranked using wet- and dry-lab criteria, including quality controls of the extracted genomic DNA, alpha-diversity, accuracy using a mock community of known composition and repeatability across technical replicates. SPD improved overall efficiency of three of the four tested protocols compared with their commercial version, in terms of DNA extraction yield, sample alpha-diversity, and recovery of Gram-positive bacteria. The best overall performance was obtained for the S-DQ protocol, SPD combined with the DNeasy PowerLyser PowerSoil protocol from QIAGEN. Based on this evaluation, we strongly believe that the use of such stool preprocessing device improves both the standardization and the quality of the DNA extraction in the human gut microbiome studies.

EMBED: Essential MicroBiomE Dynamics, a dimensionality reduction approach for longitudinal microbiome studies

Dimensionality reduction offers unique insights into high-dimensional microbiome dynamics by leveraging collective abundance fluctuations of multiple bacteria driven by similar ecological perturbations. However, methods providing lower-dimensional representations of microbiome dynamics both at the community and individual taxa levels are not currently available. To that end, we present EMBED: Essential MicroBiomE Dynamics, a probabilistic nonlinear tensor factorization approach. Like normal mode analysis in structural biophysics, EMBED infers ecological normal modes (ECNs), which represent the unique orthogonal modes capturing the collective behavior of microbial communities. Using multiple real and synthetic datasets, we show that a very small number of ECNs can accurately approximate microbiome dynamics. Inferred ECNs reflect specific ecological behaviors, providing natural templates along which the dynamics of individual bacteria may be partitioned. Moreover, the multi-subject treatment in EMBED systematically identifies subject-specific and universal abundance dynamics that are not detected by traditional approaches. Collectively, these results highlight the utility of EMBED as a versatile dimensionality reduction tool for studies of microbiome dynamics.

A Refined, Controlled 16S rRNA Gene Sequencing Approach Reveals Limited Detection of Cerebrospinal Fluid Microbiota in Children with Bacterial Meningitis

Advances in both laboratory and computational components of high-throughput 16S amplicon sequencing (16S HTS) have markedly increased its sensitivity and specificity. Additionally, these refinements have better delineated the limits of sensitivity, and contributions of contamination to these limits, for 16S HTS that are particularly relevant for samples with low bacterial loads, such as human cerebrospinal fluid (CSF). The objectives of this work were to (i) optimize the performance of 16S HTS in CSF samples with low bacterial loads by defining and addressing potential sources of error, and (ii) perform refined 16S HTS on CSF samples from children diagnosed with bacterial meningitis and compare results with those from microbiological cultures. Several bench and computational approaches were taken to address potential sources of error for low bacterial load samples. We compared DNA yields and sequencing results after applying three different DNA extraction approaches to an artificially constructed mock-bacterial community. We also compared two postsequencing computational contaminant removal strategies, decontam R and full contaminant sequence removal. All three extraction techniques followed by decontam R yielded similar results for the mock community. We then applied these methods to 22 CSF samples from children diagnosed with meningitis, which has low bacterial loads relative to other clinical infection samples. The refined 16S HTS pipelines identified the cultured bacterial genus as the dominant organism for only 3 of these samples. We found that all three DNA extraction techniques followed by decontam R generated similar DNA yields for mock communities at the low bacterial loads representative of CSF samples. However, the limits of detection imposed by reagent contaminants and methodologic bias precluded the accurate detection of bacteria in CSF from children with culture-confirmed meningitis using these approaches, despite rigorous controls and sophisticated computational approaches. Although we did not find current DNA-based diagnostics to be useful for pediatric meningitis samples, the utility of these methods for CSF shunt infection remains undefined. Future advances in sample processing methods to minimize or eliminate contamination will be required to improve the sensitivity and specificity of these methods for pediatric meningitis. IMPORTANCE Advances in both laboratory and computational components of high-throughput 16S amplicon sequencing (16S HTS) have markedly increased its sensitivity and specificity. These refinements have better delineated the limits of sensitivity, and contributions of contamination to these limits, for 16S HTS that are particularly relevant for samples with low bacterial loads such as human cerebrospinal fluid (CSF). The objectives of this work were to (i) optimize the performance of 16S HTS in CSF samples by defining and addressing potential sources of error, and (ii) perform refined 16S HTS on CSF samples from children diagnosed with bacterial meningitis and compare results with those from microbiological cultures. We found that the limits of detection imposed by reagent contaminants and methodologic bias precluded the accurate detection of bacteria in CSF from children with culture-confirmed meningitis using these approaches, despite rigorous controls and sophisticated computational approaches.

Genome-wide mapping of gene-microbe interactions in the murine lung microbiota based on quantitative microbial profiling

BACKGROUND

Mammalian lungs comprise a complex microbial ecosystem that interacts with host physiology. Previous research demonstrates that the environment significantly contributes to bacterial community structure in the upper and lower respiratory tract. However, the influence of host genetics on the makeup of lung microbiota remains ambiguous, largely due to technical difficulties related to sampling, as well as challenges inherent to investigating low biomass communities. Thus, innovative approaches are warranted to clarify host-microbe interactions in the mammalian lung.

RESULTS

Here, we aimed to characterize host genomic regions associated with lung bacterial traits in an advanced intercross mouse line (AIL). By performing quantitative microbial profiling (QMP) using the highly precise method of droplet digital PCR (ddPCR), we refined 16S rRNA gene amplicon-based traits to identify and map candidate lung-resident taxa using a QTL mapping approach. In addition, the two abundant core taxa Lactobacillus and Pelomonas were chosen for independent microbial phenotyping using genus-specific primers. In total, this revealed seven significant loci involving eight bacterial traits. The narrow confidence intervals afforded by the AIL population allowed us to identify several promising candidate genes related to immune and inflammatory responses, cell apoptosis, DNA repair, and lung functioning and disease susceptibility. Interestingly, one genomic region associated with Lactobacillus abundance contains the well-known anti-inflammatory cytokine Il10, which we confirmed through the analysis of Il10 knockout mice.

CONCLUSIONS

Our study provides the first evidence for a role of host genetic variation contributing to variation in the lung microbiota. This was in large part made possible through the careful curation of 16S rRNA gene amplicon data and the incorporation of a QMP-based methods. This approach to evaluating the low biomass lung environment opens new avenues for advancing lung microbiome research using animal models.

Mock community as an in situ positive control for amplicon sequencing of microbiotas from the same ecosystem

Metataxonomy has become the standard for characterizing the diversity and composition of microbial communities associated with multicellular organisms and their environment. Currently available protocols for metataxonomy assume a uniform DNA extraction, amplification and sequencing efficiency for all sample types and taxa. It has been suggested that the addition of a mock community (MC) to biological samples before the DNA extraction step could aid identification of technical biases during processing and support direct comparisons of microbiota composition, but the impact of MC on diversity estimates of samples is unknown. Here, large and small aliquots of pulverized bovine fecal samples were extracted with no, low or high doses of MC, characterized using standard Illumina technology for metataxonomics, and analysed with custom bioinformatic pipelines. We demonstrated that sample diversity estimates were distorted only if MC dose was high compared to sample mass (i.e. when MC > 10% of sample reads). We also showed that MC was an informative in situ positive control, permitting an estimation of the sample 16S copy number, and detecting sample outliers. We tested this approach on a range of sample types from a terrestrial ecosystem, including rhizosphere soil, whole invertebrates, and wild vertebrate fecal samples, and discuss possible clinical applications.

The Effects of Phytase and Non-Starch Polysaccharide-Hydrolyzing Enzymes on Trace Element Deposition, Intestinal Morphology, and Cecal Microbiota of Growing-Finishing Pigs

This study investigated the effects of supplementing phytase and non-starch polysaccharide-degrading enzymes (NSPases) to corn-soybean meal-based diet on the growth performance, trace element deposition, and intestinal health of growing-finishing pigs. Fifty pigs were randomly assigned into the control (basal diet), phytase (basal diet + 100 g/t of phytase), β-mannanase (basal diet + 40 g/t of β-mannanase), β-glucanase (basal diet + 100 g/t of β-glucanase), and xylanase (basal diet + 100 g/t of xylanase) groups. The results show that the supplementation of phytase and NSPases had no impacts (p  >  0.05) on the growth performance of pigs. Compared with the control group, pigs fed with xylanase had higher (p < 0.05) Zn concentrations in the ileum and muscle and those fed with phytase had higher (p < 0.05) Zn concentrations in the ileum. Phytase and xylanase supplementation decreased (p < 0.05) fecal Zn concentrations in pigs compared with the control group (p < 0.05). In addition, phytase, β-mannanase, β-glucanase, and xylanase supplementation up-regulated (p < 0.05) the FPN1 expression, whereas xylanase up-regulated (p < 0.05) the Znt1 expression in the duodenum of pigs compared with the control group. Moreover, phytase, β-glucanase, and xylanase supplementation up-regulated (p < 0.05) the jejunal Znt1 expression compared with the control group. The intestinal morphology results show that the phytase, β-mannanase, and xylanase groups had increased villus heights (VHs), an increased villus height-crypt depth ratio (VH:CD), and decreased crypt depths (CDs) in the duodenum, whereas phytase, β-mannanase, β-glucanase, and xylanase groups had decreased VH and VH:CD, and increased CD in the jejunum compared with the control group (p < 0.05). Pigs fed with exogenous enzymes had decreased bacterial diversity in the cecum. The dietary supplementation of NSPases increased the relative abundance of Firmicutes and decreased spirochaetes (p < 0.05). Compared with the control group, dietary NSPase treatment decreased (p < 0.05) the opportunistic pathogens, such as Treponema_2 and Eubacterium_ruminantium. Moreover, the relative abundances of Lachnospiraceae_XPB1014 and Lachnospiraceae were enriched in the β-glucanase and β-mannanase groups (p < 0.05), respectively. In conclusion, phytase and xylanase supplementation may promote zinc deposition in pigs. Additionally, the supplementation of NSPases may improve the gut health of pigs by modulating the intestinal morphology and microbiota.

QMD: A new method to quantify microbial absolute abundance differences between groups

A new method, quantification of microbial absolute abundance differences (QMD), was proposed to estimate the microbial absolute abundance changes of each taxon under different conditions based on the microbial relative abundance. Compared with other methods, QMD displayed greater confidence in understanding microbiome dynamics between groups. We also provide QMD software to investigate common deviations and achieve a better understanding of microbiota changes under different conditions.