Analysis of composition of microbiomes: a novel method for studying microbial composition

MIDASim: a fast and simple simulator for realistic microbiome data

BACKGROUND

Advances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time.

METHODS

We develop MIDASim (MIcrobiome DAta Simulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, a generalized gamma distribution is used in place of the empirical distribution.

RESULTS

We demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PERMANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model.

CONCLUSIONS

MIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods, at both the presence-absence level and the relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets. Video Abstract.

Metatranscriptomics: A Tool for Clinical Metagenomics

In the field of bioinformatics, amplicon sequencing of 16S rRNA genes has long been used to investigate community membership and taxonomic abundance in microbiome studies. As we can observe, shotgun metagenomics has become the dominant method in this field. This is largely owing to advancements in sequencing technology, which now allow for random sequencing of the entire genetic content of a microbiome. Furthermore, this method allows profiling both genes and the microbiome's membership. Although these methods have provided extensive insights into various microbiomes, they solely assess the existence of organisms or genes, without determining their active role within the microbiome. Microbiome scholarship now includes metatranscriptomics to decipher how a community of microorganisms responds to changing environmental conditions over a period of time. Metagenomic studies identify the microbes that make up a community but metatranscriptomics explores the diversity of active genes within that community, understanding their expression profile and observing how these genes respond to changes in environmental conditions. This expert review article offers a critical examination of the computational metatranscriptomics tools for studying the transcriptomes of microbial communities. First, we unpack the reasons behind the need for community transcriptomics. Second, we explore the prospects and challenges of metatranscriptomic workflows, starting with isolation and sequencing of the RNA community, then moving on to bioinformatics approaches for quantifying RNA features, and statistical techniques for detecting differential expression in a community. Finally, we discuss strengths and shortcomings in relation to other microbiome analysis approaches, pipelines, use cases and limitations, and contextualize metatranscriptomics as a tool for clinical metagenomics.

Dietary Acculturation Is Associated With Altered Gut Microbiome, Circulating Metabolites, and Cardiovascular Disease Risk in US Hispanics and Latinos: Results From HCHS/SOL

BACKGROUND

Dietary acculturation, or adoption of dominant culture diet by migrant groups, influences human health. We aimed to examine dietary acculturation and its relationships with cardiovascular disease (CVD), gut microbiota, and blood metabolites among US Hispanic and Latino adults.

METHODS

In the HCHS/SOL (Hispanic Community Health Study/Study of Latinos), US exposure was defined by years in the United States (50 states and Washington, DC) and US nativity. A dietary acculturation pattern was derived from 14 172 participants with two 24-hour dietary recalls at baseline (2008-2011) using least absolute shrinkage and selection operator regression, with food groups as predictors of US exposure. We evaluated associations of dietary acculturation with incident CVD across ≈7 years of follow-up (n=211/14 172 cases/total) and gut microbiota (n=2349; visit 2, 2014 to 2017). Serum metabolites associated with both dietary acculturation-related gut microbiota (n=694) and incident CVD (n=108/5256 cases/total) were used as proxy measures to assess the association of diet-related gut microbiome with incident CVD.

RESULTS

We identified an empirical US-oriented dietary acculturation score that increased with US exposure. Higher dietary acculturation score was associated with higher risk of incident CVD (hazard ratio per SD, 1.33 [95% CI, 1.13-1.57]), adjusted for sociodemographic, lifestyle, and clinical factors. Sixty-nine microbial species (17 enriched from diverse species, 52 depleted mainly from fiber-utilizing Clostridia and Prevotella species) were associated with dietary acculturation, driven by lower intakes of whole grains, beans, and fruits and higher intakes of refined grains. Twenty-five metabolites, involved predominantly in fatty acid and glycerophospholipid metabolism (eg, branched-chain 14:0 dicarboxylic acid** and glycerophosphoethanolamine), were associated with both diet acculturation-related gut microbiota and incident CVD. Proxy association analysis based on these metabolites suggested a positive relationship between diet acculturation-related microbiome and risk of CVD (r=0.70, P<0.001).

CONCLUSIONS

Among US Hispanic and Latino adults, greater dietary acculturation was associated with elevated CVD risk, possibly through alterations in gut microbiota and related metabolites. Diet and microbiota-targeted interventions may offer opportunities to mitigate CVD burdens of dietary acculturation.

Dietary fiber monosaccharide content alters gut microbiome composition and fermentation

Members of the mammalian gut microbiota metabolize diverse complex carbohydrates that are not digested by the host, which are collectively labeled "dietary fiber." While the enzymes and transporters that each strain uses to establish a nutrient niche in the gut are often exquisitely specific, the relationship between carbohydrate structure and microbial ecology is imperfectly understood. The present study takes advantage of recent advances in complex carbohydrate structure determination to test the effects of fiber monosaccharide composition on microbial fermentation. Fifty-five fibers with varied monosaccharide composition were fermented by a pooled feline fecal inoculum in a modified MiniBioReactor array system over a period of 72 hours. The content of the monosaccharides glucose and xylose was significantly associated with the reduction of pH during fermentation, which was also predictable from the concentrations of the short-chain fatty acids lactic acid, propionic acid, and the signaling molecule indole-3-acetic acid. Microbiome diversity and composition were also predictable from monosaccharide content and SCFA concentration. In particular, the concentrations of lactic acid and propionic acid correlated with final alpha diversity and were significantly associated with the relative abundance of several of the genera, including Lactobacillus and Dubosiella. Our results suggest that monosaccharide composition offers a generalizable method to compare any dietary fiber of interest and uncover links between diet, gut microbiota, and metabolite production.

IMPORTANCE

The survival of a microbial species in the gut depends on the availability of the nutrients necessary for that species to survive. Carbohydrates in the form of non-host digestible fiber are of particular importance, and the set of genes possessed by each species for carbohydrate consumption can vary considerably. Here, differences in the monosaccharides that are the building blocks of fiber are considered for their impact on both the survival of different species of microbes and on the levels of microbial fermentation products produced. This work demonstrates that foods with similar monosaccharide content will have consistent effects on the survival of microbial species and on the production of microbial fermentation products.

Highly purified hypochlorous acid water facilitates glucose metabolism and memory formation in type 2 diabetic mice associated with altered-gut microbiota

Hypochlorous acid (HOCl) is an endogenous oxidant and chlorinating agent in mammals that is effective against a broad range of microorganisms. However, the effects of exogenous HOCl on biological processes have not been reported. In this study, the effects of highly purified slightly acidic hypochlorous acid water (HP-HAW) were investigated. After the safety of oral administration of HP-HAW was confirmed, the effects of HP-HAW on glucose homeostasis were assessed in mice. HP-HAW treatment significantly improved blood glucose levels in hyperglycemic condition. Based on the 16S rRNA sequencing, HP-HAW treatment significantly increased the diversity and changed the composition of gut microbiota by decreasing the abundance of genus Romboutsia in mice fed normal chow. In obese mice, HP-HAW administration tended to improve glucose tolerance. HP-HAW also attenuated memory impairments and changes N-methyl-d-aspartate (NMDA) receptor mRNA expression in obese mice. HP-HAW treatment suppressed Il-6 mRNA expression in the hippocampus in type 2 diabetic mice. Overall, these results support HP-HAW as a potential therapeutic agent to improve or prevent glucose tolerance and memory decline via gut microbiota alteration.

In-hospital areas with distinct maintenance and staff/patient traffic have specific microbiome profiles, functions, and resistomes

Hospitals are subject to strict microbial control. Stringent cleaning and confinement measures in hospitals lead to a decrease in microbial diversity, but an increase in resistance genes. Given the rise of antimicrobial resistances and healthcare-associated infections, understanding the hospital microbiome and its resistome is crucial. This study compared the microbiome and resistome at different levels of confinement (CL) within a single hospital. Using amplicon sequencing, shotgun metagenomics, and genome/plasmid reconstruction, we demonstrate that microbial composition differs in a stable way between the CLs and that the most restrictive confinement level CL1 had the lowest microbial but the highest functional diversity. This CL also exhibited a greater abundance of functions related to virulence, disease, defense, and stress response. Comparison of antibiotic resistance also showed differences among CLs in terms of the selection process and specific mechanisms for antimicrobial/antibiotic resistance. The resistances found in the samples of CL1 were mostly mediated via antibiotic efflux pumps and were mainly located on chromosomes, whereas in the other, less restrictive CL antibiotic resistances were more present on plasmids. This could be of particular importance for patient-related areas (CL2), as the potential spread of antibiotic resistances could be a major concern in this area. Our results show that there are differences in the microbiome and resistome even within a single hospital, reflecting room utilization and confinement. Since restrictive confinement selects for resistant microorganisms, strategies are required to deepen our understanding of dynamic processes of microbiome and resistome within hospital environments.

IMPORTANCE

Effective measures to combat antibiotic resistances and healthcare-associated infections are urgently needed, including optimization of microbial control. However, previous studies have indicated that stringent control can lead to an increase in the resistance capacities of microbiomes on surfaces. This study adds to previous knowledge by focusing on the conditions in a single hospital, resolving the microbiomes and their resistomes in three different confinement levels (CL): operating room, patient-related areas, and non-patient-related areas. We were able to identify stable key taxa; profiled the capacities of taxa, functions, and antimicrobial resistances (AMR); and reconstruct genomes and plasmids in each CL. Our results show that the most restrictive CL indeed had the highest functional diversity, but that resistances were mostly encoded on chromosomes, indicating a lower possibility of resistance spread. However, clever strategies are still required to strike a balance between microbial control and selective pressures in environments where patients need protection.

Effects of low-intensity pulsed ultrasound on the microorganisms of expressed prostatic secretion in patients with IIIB prostatitis

To detect and analyze the changes of microorganisms in expressed prostatic secretion (EPS) of patients with IIIB prostatitis before and after low-intensity pulsed ultrasound (LIPUS) treatment, and to explore the mechanism of LIPUS in the treatment of chronic prostatitis (CP). 25 patients (study power was estimated using a Dirichlet-multinomial approach and reached 96.5% at α = 0.05 using a sample size of 25) with IIIB prostatitis who were effective in LIPUS treatment were divided into two groups before and after LIPUS treatment. High throughput second-generation sequencing technique was used to detect and analyze the relative abundance of bacterial 16 s ribosomal variable regions in EPS before and after treatment. The data were analyzed by bioinformatics software and database, and differences with P < 0.05 were considered statistically significant. Beta diversity analysis showed that there was a significant difference between groups (P = 0.046). LEfSe detected four kinds of characteristic microorganisms in the EPS of patients with IIIB prostatitis before and after LIPUS treatment. After multiple comparisons among groups by DESeq2 method, six different microorganisms were found. LIPUS may improve patients' clinical symptoms by changing the flora structure of EPS, stabilizing and affecting resident bacteria or opportunistic pathogens.

Swine farm environmental microbiome: exploring microbial ecology and functionality across farms with high and low sanitary status

Introduction

Stringent regulations in pig farming, such as antibiotic control and the ban on certain additives and disinfectants, complicate disease control efforts. Despite the evolution of microbial communities inside the house environment, they maintain stability over the years, exhibiting characteristics specific to each type of production and, in some cases, unique to a particular company or farm production type. In addition, some infectious diseases are recurrent in specific farms, while other farms never present these diseases, suggesting a connection between the presence of these microorganisms in animals or their environment. Therefore, the aim of this study was to characterise environmental microbiomes of farms with high and low sanitary status, establishing the relationships between both, health status, environmental microbial ecology and its functionality.

Methods

For this purpose, 6 pig farms were environmentally sampled. Farms were affiliated with a production company that handle the majority of the pigs slaughtered in Spain. This study investigated the relationship among high health and low health status farms using high throughput 16S rRNA gene sequencing. In addition, to identify ecologically relevant functions and potential pathogens based on the 16S rRNA gene sequences obtained, functional Annotation with PROkaryotic TAXa (FAPROTAX) was performed.

Results and Discussion

This study reveals notable differences in microbial communities between farms with persistent health issues and those with good health outcomes, suggesting a need for protocols tailored to address specific challenges. The variation in microbial populations among farms underscores the need for specific and eco-friendly cleaning and disinfection protocols. These measures are key to enhancing the sustainability of livestock farming, ensuring safer products and boosting competitive edge in the market.

Soil pH amendment alters the abundance, diversity, and composition of microbial communities in two contrasting agricultural soils

Soil microorganisms are the most active participants in terrestrial ecosystems, and have key roles in biogeochemical cycles and ecosystem functions. Despite the extensive research on soil pH as a key predictor of microbial community and composition, a limitation of these studies lies in determining whether bacterial and/or fungal communities are directly or indirectly influenced by pH. We conducted a controlled laboratory experiment to investigate the effects of soil pH amendment (+/- 1-2 units) with six levels on soil microbial communities in two contrasting Chinese agricultural soils (pH 8.43 in Dezhou, located in the North China Plain, Shandong vs pH 6.17 in Wuxi, located in the Taihu Lake region, Jiangsu, east China). Results showed that the fungal diversity and composition were related to soil pH, but the effects were much lower than the effects of soil pH on bacterial community in two soils. The diversity and composition of bacterial communities were more closely associated with soil pH in Wuxi soils compared to Dezhou soils. The alpha diversity of bacterial communities peaked near in situ pH levels in both soils, displaying a quadratic fitting pattern. Redundancy analysis and variation partition analysis indicated that soil pH affected bacterial community and composition by directly imposing a physiological constraint on soil bacteria and indirectly altering soil characteristics (e.g., nutrient availability). The study also examined complete curves of taxa relative abundances at the phylum and family levels in response to soil pH, with most relationships conforming to a quadratic fitting pattern, indicating soil pH is a reliable predictor. Furthermore, soil pH amendment affected the transformation of nitrogen and the abundances of functional genes involved in the nitrogen cycle, and methane production and consumption. Overall, results from this study would enhance our comprehension of how soil microorganisms in contrasting farmlands will respond to soil pH changes, and would contribute to more effective soil management and conservation strategies.

IMPORTANCE

This study delves into the impact of soil pH on microbial communities, investigating whether pH directly or indirectly influences bacterial and fungal communities. The research involved two contrasting soils subjected to a 1-2 pH unit amendment. Results indicate bacterial community composition was shaped by soil pH through physiological constraints and nutrient limitations. We found that most taxa relative abundances at the phylum and family levels responded to pH with a quadratic fitting pattern, indicating that soil pH is a reliable predictor. Additionally, soil pH was found to significantly influence the predicted abundance of functional genes involved in the nitrogen cycle as well as in methane production and consumption processes. These insights can contribute to develop more effective soil management and conservation strategies.

Do fish gut microbiotas vary across spatial scales? A case study of Diplodus vulgaris in the Mediterranean Sea

BACKGROUND

Biogeography has been linked to differences in gut microbiota in several animals. However, the existence of such a relationship in fish is not clear yet. So far, it seems to depend on the fish species studied. However, most studies of fish gut microbiotas are based on single populations. In this study, we investigated the gut microbiota of fish from three wild populations of the two-banded sea bream Diplodus vulgaris (Geoffroy Saint-Hilaire, 1817) to determine whether its diversity, structure and potential functionality reflect the geographic origin of the fish, at large and small geographical scale. Additionally, we explored the host- and environmental-related factors explaining this relationship.

RESULTS

We showed that the taxonomy and potential functionality of the mucosa-associated gut microbiota of Diplodus vulgaris differ to varying degrees depending on the spatial scale considered. At large scale, we observed that both the taxonomical structure and the potential functionality of the fish microbiota differed significantly between populations. In contrast, the taxonomical diversity of the microbial community displayed a significant relationship with factors other than the geographic origin of the fish (i.e. sampling date). On the other hand, at small scale, the different composition and diversity of the microbiota differ according to the characteristics of the habitat occupied by the fish. Specifically, we identified the presence of Posidonia oceanica in the benthic habitat as predictor of both the microbiota composition and diversity. Lastly, we reported the enrichment of functions related to the metabolism of xenobiotics (i.e. drugs and 4-aminobenzoate) in a population and we indicated it as a potential target of future monitoring.

CONCLUSIONS

With this study, we confirmed the importance of investigating the gut microbiota of wild fish species using multiple populations, taking into account the different habitats occupied by the individuals. Furthermore, we underscored the use of the biodegradation potential of the gut microbiota as an alternative means of monitoring emerging contaminants in Mediterranean fish.

Establishment of the uterine microbiome following artificial insemination in virgin heifers

Introduction

The concept of a sterile uterus was challenged by recent studies that have described the microbiome of the virgin and pregnant uterus for species including humans and cattle. We designed two studies that tested whether the microbiome is introduced into the uterus when the virgin heifer is first inseminated and whether the origin of the microbiome is the vagina/cervix.

Methods

The uterine microbiome was measured immediately before and after an artificial insemination (AI; Study 1; n = 7 AI and n = 6 control) and 14 d after insemination (Study 2; n = 12 AI and n = 12 control) in AI and non-AI (control) Holstein heifers. A third study (Study 3; n = 5 Holstein heifers) that included additional negative controls was subsequently conducted to support the presence of a unique microbiome within the uterus despite the low microbial biomass and regardless of insemination. Traditional bacteriological culture was performed in addition to 16S rRNA gene sequencing on the same samples to determine whether there were viable organisms in addition to those detected based on DNA sequencing (16S rRNA gene sequence).

Results and discussion

Inseminating a heifer did not lead to a large change in the microbiome when assessed by traditional methods of bacterial culture or metataxonomic (16S rRNA gene) sequencing (results of Studies 1 and 2). Very few bacteria were cultured from the body or horn of the uterus regardless of whether an AI was or was not (negative control) performed. The cultured bacterial genera (e.g., Bacillus, Corynebacterium, Cutibacterium, Micrococcus, Staphylococcus, and Streptococcus) were typical of those found in the soil, environment, skin, mucous membranes, and urogenital tract of animals. Metataxonomic sequencing of 16S rRNA gene generated a large number of amplicon sequence variants (ASV), but these larger datasets that were based on DNA sequencing did not consistently demonstrate an effect of AI on the abundance of ASVs across all uterine locations compared with the external surface of the tract (e.g., perimetrium; positive control samples for environment contamination during slaughter and collection). Major genera identified by 16S rRNA gene sequencing overlapped with those identified with bacterial culture and included Cutibacterium, Staphylococcus, and Streptococcus.

Environmental and structural factors associated with bacterial diversity in household dust across the Arizona-Sonora border

We previously reported that asthma prevalence was higher in the United States (US) compared to Mexico (MX) (25.8% vs. 8.4%). This investigation assessed differences in microbial dust composition in relation to demographic and housing characteristics on both sides of the US-MX Border. Forty homes were recruited in the US and MX. Home visits collected floor dust and documented occupants' demographics, asthma prevalence, housing structure, and use characteristics. US households were more likely to have inhabitants who reported asthma when compared with MX households (30% vs. 5%) and had significantly different flooring types. The percentage of households on paved roads, with flushing toilets, with piped water and with air conditioning was higher in the US, while dust load was higher in MX. Significant differences exist between countries in the microbial composition of the floor dust. Dust from Mexican homes was enriched with Alishewanella, Paracoccus, Rheinheimera genera and Intrasporangiaceae family. A predictive metagenomics analysis identified 68 significantly differentially abundant functional pathways between US and MX. This study documented multiple structural, environmental, and demographic differences between homes in the US and MX that may contribute to significantly different microbial composition of dust observed in these two countries.

The effect of daily usage of Listerine Cool Mint mouthwash on the oropharyngeal microbiome: a substudy of the PReGo trial

Introduction. ListerineÒ is a bactericidal mouthwash widely used to prevent oral health problems such as dental plaque and gingivitis. However, whether it promotes or undermines a healthy oral microbiome is unclear.Hypothesis/Gap Statement. We hypothesized that the daily use of Listerine Cool Mint would have a significant impact on the oropharyngeal microbiome.Aim. We aimed to assess if daily usage of Listerine Cool Mint influenced the composition of the pharyngeal microbiome.Methodology. The current microbiome substudy is part of the Preventing Resistance in Gonorrhoea trial. This was a double-blind single-centre, crossover, randomized controlled trial of antibacterial versus placebo mouthwash to reduce the incidence of gonorrhoea/chlamydia/syphilis in men who have sex with men (MSM) taking HIV pre-exposure prophylaxis (PrEP). Fifty-nine MSM taking HIV PrEP were enrolled. In this crossover trial, participants received 3 months of daily Listerine followed by 3 months of placebo mouthwash or vice versa. Oropharyngeal swabs were taken at baseline and after 3 months use of each mouthwash. DNA was extracted for shotgun metagenomic sequencing (Illumina Inc.). Non-host reads were taxonomically classified with MiniKraken and Bracken. The alpha and beta diversity indices were compared between baseline and after each mouthwash use. Differentially abundant bacterial taxa were identified using ANOVA-like differential expression analysis.Results. Streptococcus was the most abundant genus in most samples (n = 103, 61.7 %) with a median relative abundance of 31.5% (IQR 20.6-44.8), followed by Prevotella [13.5% (IQR 4.8-22.6)] and Veillonella [10.0% (IQR 4.0-16.8)]. Compared to baseline, the composition of the oral microbiome at the genus level (beta diversity) was significantly different after 3 months of Listerine (P = 0.006, pseudo-F = 2.29) or placebo (P = 0.003, pseudo-F = 2.49, permutational multivariate analysis of variance) use. Fusobacterium nucleatum and Streptococcus anginosus were significantly more abundant after Listerine use compared to baseline.Conclusion. Listerine use was associated with an increased abundance of common oral opportunistic bacteria previously reported to be enriched in periodontal diseases, oesophageal and colorectal cancer, and systemic diseases. These findings suggest that the regular use of Listerine mouthwash should be carefully considered.

Milk and Lacticaseibacillus paracasei BL23 effects on intestinal responses in a murine model of colitis

Probiotic-containing fermented dairy foods have the potential to benefit human health, but the importance of the dairy matrix for efficacy remains unclear. We investigated the capacity of Lacticaseibacillus paracasei BL23 in phosphate-buffered saline (BL23-PBS), BL23-fermented milk (BL23-milk), and milk to modify intestinal and behavioral responses in a dextran sodium sulfate (DSS, 3% wt/vol) mouse model of colitis. Significant sex-dependent differences were found such that female mice exhibited more severe colitis, greater weight loss, and higher mortality rates. Sex differences were also found for ion transport ex vivo, colonic cytokine and tight junction gene expression, and fecal microbiota composition. Measurements of milk and BL23 effects showed BL23-PBS consumption improved weight recovery in females, whereas milk resulted in better body weight recovery in males. Occludin and Claudin-2 gene transcript levels indicated barrier function was impaired in males, but BL23-milk was still found to improve colonic ion transport in those mice. Proinflammatory and anti-inflammatory gene expression levels were increased in both male and female mice fed BL23, and to a more variable extent, milk, compared with controls. The female mouse fecal microbiota contained high proportions of Akkermansia (average of 18.1%) at baseline, and females exhibited more changes in gut microbiota composition following BL23 and milk intake. Male fecal microbiota harbored significantly more Parasutterella and less Blautia and Roseburia after DSS treatment, independent of BL23 or milk consumption. These findings show the complex interplay between dietary components and sex-dependent responses in mitigating inflammation in the digestive tract.NEW & NOTEWORTHY Sex-dependent responses to probiotic Lacticaseibacillus paracasei and milk and the potential of the dairy matrix to enhance probiotic protection against colitis in this context have not been previously explored. Female mice were more sensitive than males to colonic injury, and neither treatment effectively alleviated inflammation in both sexes. These sex-dependent responses may result from differences in the higher baseline proportions of Akkermansia in the gut microbiome of female mice.

Microbiome-driven alterations in metabolic pathways and impaired cognition in aged female TgF344-AD rats

Alzheimer's disease (AD) not only affects cognition and neuropathology, but several other facets capable of negatively impacting quality of life and potentially driving impairments, including altered gut microbiome (GMB) composition and metabolism. Aged (20 + mo) female TgF344-AD and wildtype rats were cognitively characterized on several tasks incorporating several cognitive domains, including task acquisition, object recognition memory, anxiety-like behaviors, and spatial navigation. Additionally, metabolic phenotyping, GMB sequencing throughout the intestinal tract (duodenum, jejunum, ileum, colon, and feces), neuropathological burden assessment and marker gene functional abundance predictions (PICRUSt2) were conducted. TgF344-AD rats demonstrated significant cognitive impairment in multiple domains, as well as regionally specific GMB dysbiosis. Relationships between peripheral factors were investigated using Canonical Correspondence Analysis (CCA), revealing correlations between GMB changes and both cognitive and metabolic factors. Moreover, communities of gut microbes contributing to essential metabolic pathways were significantly altered in TgF344-AD rats. These data indicate dysbiosis may affect cognitive outcomes in AD through alterations in metabolism-related enzymatic pathways that are necessary for proper brain function. Moreover, these changes were mostly observed in intestinal segments required for carbohydrate digestion, not fecal samples. These data support the targeting of intestinal and microbiome health for the treatment of AD.

A strategy for differential abundance analysis of sparse microbiome data with group-wise structured zeros

Comparing the abundance of microbial communities between different groups or obtained under different experimental conditions using count sequence data is a challenging task due to various issues such as inflated zero counts, overdispersion, and non-normality. Several methods and procedures based on counts, their transformation and compositionality have been proposed in the literature to detect differentially abundant species in datasets containing hundreds to thousands of microbial species. Despite efforts to address the large numbers of zeros present in microbiome datasets, even after careful data preprocessing, the performance of existing methods is impaired by the presence of inflated zero counts and group-wise structured zeros (i.e. all zero counts in a group). We propose and validate using extensive simulations an approach combining two differential abundance testing methods, namely DESeq2-ZINBWaVE and DESeq2, to address the issues of zero-inflation and group-wise structured zeros, respectively. This combined approach was subsequently successfully applied to two plant microbiome datasets that revealed a number of taxa as interesting candidates for further experimental validation.

A GLM-based zero-inflated generalized Poisson factor model for analyzing microbiome data

Motivation

High-throughput sequencing technology facilitates the quantitative analysis of microbial communities, improving the capacity to investigate the associations between the human microbiome and diseases. Our primary motivating application is to explore the association between gut microbes and obesity. The complex characteristics of microbiome data, including high dimensionality, zero inflation, and over-dispersion, pose new statistical challenges for downstream analysis.

Results

We propose a GLM-based zero-inflated generalized Poisson factor analysis (GZIGPFA) model to analyze microbiome data with complex characteristics. The GZIGPFA model is based on a zero-inflated generalized Poisson (ZIGP) distribution for modeling microbiome count data. A link function between the generalized Poisson rate and the probability of excess zeros is established within the generalized linear model (GLM) framework. The latent parameters of the GZIGPFA model constitute a low-rank matrix comprising a low-dimensional score matrix and a loading matrix. An alternating maximum likelihood algorithm is employed to estimate the unknown parameters, and cross-validation is utilized to determine the rank of the model in this study. The proposed GZIGPFA model demonstrates superior performance and advantages through comprehensive simulation studies and real data applications.

Association of maternal genetics with the gut microbiome and eucalypt diet selection in captive koalas

Background

Koalas, an Australian arboreal marsupial, depend on eucalypt tree leaves for their diet. They selectively consume only a few of the hundreds of available eucalypt species. Since the koala gut microbiome is essential for the digestion and detoxification of eucalypts, their individual differences in the gut microbiome may lead to variations in their eucalypt selection and eucalypt metabolic capacity. However, research focusing on the relationship between the gut microbiome and differences in food preferences is very limited. We aimed to determine whether individual and regional differences exist in the gut microbiome of koalas as well as the mechanism by which these differences influence eucalypt selection.

Methods

Foraging data were collected from six koalas and a total of 62 feces were collected from 15 koalas of two zoos in Japan. The mitochondrial phylogenetic analysis was conducted to estimate the mitochondrial maternal origin of each koala. In addition, the 16S-based gut microbiome of 15 koalas was analyzed to determine the composition and diversity of each koala's gut microbiome. We used these data to investigate the relationship among mitochondrial maternal origin, gut microbiome and eucalypt diet selection.

Results and Discussion

This research revealed that diversity and composition of the gut microbiome and that eucalypt diet selection of koalas differs among regions. We also revealed that the gut microbiome alpha diversity was correlated with foraging diversity in koalas. These individual and regional differences would result from vertical (maternal) transmission of the gut microbiome and represent an intraspecific variation in koala foraging strategies. Further, we demonstrated that certain gut bacteria were strongly correlated with both mitochondrial maternal origin and eucalypt foraging patterns. Bacteria found to be associated with mitochondrial maternal origin included bacteria involved in fiber digestion and degradation of secondary metabolites, such as the families Rikenellaceae and Synergistaceae. These bacteria may cause differences in metabolic capacity between individual and regional koalas and influence their eucalypt selection.

Conclusion

We showed that the characteristics (composition and diversity) of the gut microbiome and eucalypt diet selection of koalas differ by individuals and regional origins as we expected. In addition, some gut bacteria that could influence eucalypt foraging of koalas showed the relationships with both mitochondrial maternal origin and eucalypt foraging pattern. These differences in the gut microbiome between regional origins may make a difference in eucalypt selection. Given the importance of the gut microbiome to koalas foraging on eucalypts and their strong symbiotic relationship, future studies should focus on the symbiotic relationship and coevolution between koalas and the gut microbiome to understand individual and regional differences in eucalypt diet selection by koalas.

Microbiome analyses of poultry feeds: Part I. Comparison of five different DNA extraction methods

Given extensive variability in feed composition, the absence of a dedicated DNA extraction kit for poultry feed underscores the need for an optimized extraction technique for reliable downstream sequencing analyses. This study investigates the impact of five DNA extraction techniques: Qiagen QIAamp DNA Stool Mini Kit (Qiagen), modified Qiagen with Lysing Matrix B (MQ), modified Qiagen with celite purification (MQC), polyethylene glycol (PEG), and 1-Day Direct. Genomic DNA amplification and Illumina MiSeq sequencing were conducted. QIIME2-2021.4 facilitated data analysis, revealing significant diversity and compositional differences influenced by extraction methods. Qiagen exhibited lower evenness and richness compared to other methods. 1-Day Direct and PEG enhanced bacterial diversities by employing bead beating and lysozyme. Despite similar taxonomic resolution, the Qiagen kit provides a rapid, consistent method for assessing poultry feed microbiomes. Modified techniques (MQ and MQC) improve DNA purification, reducing bias in commercial poultry feed samples. PEG and 1-Day Direct methods were effective but may require standardization. Overall, this study underscores the importance of optimized extraction techniques in poultry feed analysis, with potential implications for future standardization of effective methods.

The rhizosphere microbiome and its influence on the accumulation of metabolites in Bletilla striata (Thunb.) Reichb. f

BACKGROUND

Bletilla striata (Thunb.) Reichb. f. (B. striata) is a perennial herbaceous plant in the Orchidaceae family known for its diverse pharmacological activities, such as promoting wound healing, hemostasis, anti-inflammatory effects, antioxidant properties, and immune regulation. Nevertheless, the microbe-plant-metabolite regulation patterns for B. striata remain largely undetermined, especially in the field of rhizosphere microbes. To elucidate the interrelationships between soil physics and chemistry and rhizosphere microbes and metabolites, a comprehensive approach combining metagenome analysis and targeted metabolomics was employed to investigate the rhizosphere soil and tubers from four provinces and eight production areas in China.

RESULTS

Our study reveals that the core rhizosphere microbiome of B. striata is predominantly comprised of Paraburkholderia, Methylibium, Bradyrhizobium, Chitinophaga, and Mycobacterium. These microbial species are recognized as potentially beneficial for plants health. Comprehensive analysis revealed a significant association between the accumulation of metabolites, such as militarine and polysaccharides in B. striata and the composition of rhizosphere microbes at the genus level. Furthermore, we found that the soil environment indirectly influenced the metabolite profile of B. striata by affecting the composition of rhizosphere microbes. Notably, our research identifies soil organic carbon as a primary driving factor influencing metabolite accumulation in B. striata.

CONCLUSION

Our fndings contribute to an enhanced understanding of the comprehensive regulatory mechanism involving microbe-plant-metabolite interactions. This research provides a theoretical basis for the cultivation of high-quality traditional Chinese medicine B. striata.

ADAPT: Analysis of Microbiome Differential Abundance by Pooling Tobit Models

Microbiome differential abundance analysis remains a challenging problem despite multiple methods proposed in the literature. The excessive zeros and compositionality of metagenomics data are two main challenges for differential abundance analysis. We propose a novel method called "analysis of differential abundance by pooling Tobit models" (ADAPT) to overcome these two challenges. ADAPT uniquely treats zero counts as left-censored observations to facilitate computation and enhance interpretation. ADAPT also encompasses a theoretically justified way of selecting non-differentially abundant microbiome taxa as a reference for hypothesis testing. We generate synthetic data using independent simulation frameworks to show that ADAPT has more consistent false discovery rate control and higher statistical power than competitors. We use ADAPT to analyze 16S rRNA sequencing of saliva samples and shotgun metagenomics sequencing of plaque samples collected from infants in the COHRA2 study. The results provide novel insights into the association between the oral microbiome and early childhood dental caries.

Nutraceutical blends predict enhanced health via microbiota reshaping improving cytokines and life quality: a Brazilian double-blind randomized trial

Nutraceutical interventions supporting microbiota and eliciting clinical improvements in metabolic diseases have grown significantly. Chronic stress, gut dysbiosis, and metainflammation have emerged as key factors intertwined with sleep disorders, consequently exacerbating the decline in quality of life. This study aimed to assess the effects of two nutraceutical formulations containing prebiotics (fructooligosaccharides (FOS), galactooligosaccharides (GOS), yeast β-glucans), minerals (Mg, Se, Zn), and the herbal medicine Silybum marianum L. Gaertn., Asteraceae (Milk thistle or Silymarin). These formulations, namely NSupple (without silymarin) and NSupple_Silybum (with silymarin) were tested over 180 days in overweight/obese volunteers from Brazil's southeastern region. We accessed fecal gut microbiota by partial 16S rRNA sequences; cytokines expression by CBA; anthropometrics, quality of life and sleep, as well as metabolic and hormonal parameters, at baseline (T0) and 180 days (T180) post-supplementation. Results demonstrated gut microbiota reshaping at phyla, genera, and species level post-supplementation. The Bacteroidetes phylum, Bacteroides, and Prevotella genera were positively modulated especially in the NSupple_Silybum group. Gut microbiota modulation was associated with improved sleep patterns, quality-of-life perception, cytokines expression, and anthropometric parameters post-supplementation. Our findings suggest that the nutraceutical blends positively enhance cardiometabolic and inflammatory markers. Particularly, NSupple_Silybum modulated microbiota composition, underscoring its potential significance in ameliorating metabolic dysregulation. Clinical trial registry number: NCT04810572. 23/03/2021.

The microbiome of the pregnant uterus in Holstein dairy heifers and cows assessed by bacterial culture and 16S ribosomal RNA gene sequencing

Introduction

The possibility that there is a resident and stable commensal microbiome within the pregnant uterus has been supported and refuted by a series of recent studies. One element of most of the initial studies was that they were based primarily on 16S rRNA gene sequencing from bacteria. To account for this limitation, the current study performed both bacterial culture and 16S rRNA gene sequencing in a side-by-side manner (e.g., same tissues isolated from the same animal).

Methods

The uteruses of 10 mid-pregnant (156 ± 5 d of gestation) Holstein heifers and cows were collected following slaughter. The external surface of the reproductive tract (positive control for contamination during tissue collection) as well as tissues within the pregnant uterus (placentome, inter-cotyledonary placenta, inter-caruncular endometrium, amnionic fluid, allantoic fluid, fetal abomasum content, and fetal meconium) were sampled for bacterial culture and 16S rRNA gene sequencing.

Results

There were 87 unique bacterial species cultured from the external surface of the pregnant reproductive tract (contamination control) and 12 bacterial species cultured from pregnancy tissues. Six out of 10 cattle (60%) exhibited bacterial growth in at least one location within the pregnant uterus. For the metataxonomic results (16S rRNA gene sequencing), a low targeted microbial biomass was identified. Analyses of the detected amplicon sequence variants (ASV) revealed that there were: (1) genera that were prevalent on both the external surface and within the pregnant uterus; (2) genera that were prevalent on the external surface but either not detected or had very low prevalence within the pregnant uterus; and (3) genera that were either not detected or had low prevalence on the external surface but found with relatively high prevalence within the pregnant uterus.

Conclusion

There are a small number of viable bacteria in the pregnant uterus. The 16S rRNA gene sequencing detected a microbial community within the pregnant uterus but with a low biomass. These results are consistent with recent studies of the pregnant bovine uterus and leave open the question of whether there is adequate microbial mass to significantly affect the biology of the normal healthy bovine pregnancy.

A taste of wilderness: supplementary feeding of red deer (Cervus elaphus) increases individual bacterial microbiota diversity but lowers abundance of important gut symbionts

The gut microbiome plays a crucial role in the health and well-being of animals. It is especially critical for ruminants that depend on this bacterial community for digesting their food. In this study, we investigated the effects of management conditions and supplemental feeding on the gut bacterial microbiota of red deer (Cervus elaphus) in the Bavarian Forest National Park, Germany. Fecal samples were collected from free-ranging deer, deer within winter enclosures, and deer in permanent enclosures. The samples were analyzed by high-throughput sequencing of the 16 S rRNA gene. The results showed that the gut bacterial microbiota differed in diversity, abundance, and heterogeneity within and between the various management groups. Free-ranging deer exhibited lower alpha diversity compared with deer in enclosures, probably because of the food supplementation available to the animals within the enclosures. Free-living individuals also showed the highest beta diversity, indicating greater variability in foraging grounds and plant species selection. Moreover, free-ranging deer had the lowest abundance of potentially pathogenic bacterial taxa, suggesting a healthier gut microbiome. Winter-gated deer, which spent some time in enclosures, exhibited intermediate characteristics between free-ranging and all-year-gated deer. These findings suggest that the winter enclosure management strategy, including supplementary feeding with processed plants and crops, has a significant impact on the gut microbiome composition of red deer. Overall, this study provides important insights into the effects of management conditions, particularly winter enclosure practices, on the gut microbiome of red deer. Understanding these effects is crucial for assessing the potential health implications of management strategies and highlights the value of microbiota investigations as health marker.

The gut microbiome, resistome, and mycobiome in preterm newborn infants and mouse pups: lack of lasting effects by antimicrobial therapy or probiotic prophylaxis

BACKGROUND

Enhancing our understanding of the underlying influences of medical interventions on the microbiome, resistome and mycobiome of preterm born infants holds significant potential for advancing infection prevention and treatment strategies. We conducted a prospective quasi-intervention study to better understand how antibiotics, and probiotics, and other medical factors influence the gut development of preterm infants. A controlled neonatal mice model was conducted in parallel, designed to closely reflect and predict exposures. Preterm infants and neonatal mice were stratified into four groups: antibiotics only, probiotics only, antibiotics followed by probiotics, and none of these interventions. Stool samples from both preterm infants and neonatal mice were collected at varying time points and analyzed by 16 S rRNA amplicon sequencing, ITS amplicon sequencing and whole genome shotgun sequencing.

RESULTS

The human infant microbiomes showed an unexpectedly high degree of heterogeneity. Little impact from medical exposure (antibiotics/probiotics) was observed on the strain patterns, however, Bifidobacterium bifidum was found more abundant after exposure to probiotics, regardless of prior antibiotic administration. Twenty-seven antibiotic resistant genes were identified in the resistome. High intra-variability was evident within the different treatment groups. Lastly, we found significant effects of antibiotics and probiotics on the mycobiome but not on the microbiome and resistome of preterm infants.

CONCLUSIONS

Although our analyses showed transient effects, these results provide positive motivation to continue the research on the effects of medical interventions on the microbiome, resistome and mycobiome of preterm infants.

Gut microbiota, blood metabolites, and left ventricular diastolic dysfunction in US Hispanics/Latinos

BACKGROUND

Left ventricular diastolic dysfunction (LVDD) is an important precursor of heart failure (HF), but little is known about its relationship with gut dysbiosis and microbial-related metabolites. By leveraging the multi-omics data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a study with population at high burden of LVDD, we aimed to characterize gut microbiota associated with LVDD and identify metabolite signatures of gut dysbiosis and incident LVDD.

RESULTS

We included up to 1996 Hispanic/Latino adults (mean age: 59.4 years; 67.1% female) with comprehensive echocardiography assessments, gut microbiome, and blood metabolome data. LVDD was defined through a composite criterion involving tissue Doppler assessment and left atrial volume index measurements. Among 1996 participants, 916 (45.9%) had prevalent LVDD, and 212 out of 594 participants without LVDD at baseline developed incident LVDD over a median 4.3 years of follow-up. Using multivariable-adjusted analysis of compositions of microbiomes (ANCOM-II) method, we identified 7 out of 512 dominant gut bacterial species (prevalence > 20%) associated with prevalent LVDD (FDR-q < 0.1), with inverse associations being found for Intestinimonas_massiliensis, Clostridium_phoceensis, and Bacteroide_coprocola and positive associations for Gardnerella_vaginali, Acidaminococcus_fermentans, Pseudomonas_aeruginosa, and Necropsobacter_massiliensis. Using multivariable adjusted linear regression, 220 out of 669 circulating metabolites with detection rate > 75% were associated with the identified LVDD-related bacterial species (FDR-q < 0.1), with the majority being linked to Intestinimonas_massiliensis, Clostridium_phoceensis, and Acidaminococcus_fermentans. Furthermore, 46 of these bacteria-associated metabolites, mostly glycerophospholipids, secondary bile acids, and amino acids, were associated with prevalent LVDD (FDR-q < 0.1), 21 of which were associated with incident LVDD (relative risk ranging from 0.81 [p = 0.001, for guanidinoacetate] to 1.25 [p = 9 × 10-5, for 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)]). The inclusion of these 21 bacterial-related metabolites significantly improved the prediction of incident LVDD compared with a traditional risk factor model (the area under the receiver operating characteristic curve [AUC] = 0.73 vs 0.70, p = 0.001). Metabolite-based proxy association analyses revealed the inverse associations of Intestinimonas_massilliensis and Clostridium_phoceensis and the positive association of Acidaminococcus_fermentans with incident LVDD.

CONCLUSION

In this study of US Hispanics/Latinos, we identified multiple gut bacteria and related metabolites linked to LVDD, suggesting their potential roles in this preclinical HF entity. Video Abstract.

Volatiles of symbiotic bacterial origin explain ectoparasitism and fledging success of hoopoes

BACKGROUND

Some parasites use olfactory cues to detect their hosts and, since bacterial symbionts are partially responsible for animal odours, they could influence host parasitism. By autoclaving nest materials of hoopoe (Upupa epops) nests before reproduction started, we explored the hypothetical links between host-associated bacteria, volatiles and parasitism. During the nestling stage, we (i) estimated the level of ectoparasitism by chewing lice (Suborder Mallophaga) in adult hoopoe females and by Carnus haemapterus flies in nestlings, and (ii) characterized microbial communities and volatile profiles of nest environments (nest material and nest cavity, respectively) and uropygial secretions.

RESULTS

Experimental nests had less diverse bacterial communities and more diverse volatile profiles than control nests, while occupants experienced lower intensity of parasitism in experimental than in control nests. The experiment also affected beta diversity of the microbial communities of nest material and of the volatiles of the nestling uropygial secretions. Moreover, microbial communities of uropygial secretions and of nest materials covaried with their volatile profiles, while the volatile profile of the bird secretions explained nest volatile profile. Finally, a subset of the volatiles and bacteria detected in the nest material and uropygial secretions were associated with the ectoparasitism intensity of both adult females and nestlings, and with fledging success.

CONCLUSIONS

These results show that a component of animal odours is linked with the microbial communities of the host and its reproductive environment, and emphasize that the associations between bacteria, ectoparasitism and reproductive success are partially mediated by volatiles of bacterial origin. Future work should focus on mechanisms underlying the detected patterns.

CeO2 nanoparticle dose and exposure modulate soybean development and plant-mediated responses in root-associated bacterial communities

Agricultural soils are increasingly undergoing inadvertent and purposeful exposures to engineered CeO2 nanoparticles (NPs), which can impact crops and root-associated microbial communities. However, interactions between NP concentration and exposure duration on plant-mediated responses of root-associated bacterial communities are not well understood. Soybeans seedlings were grown in soil with uncoated NPs added at concentrations of 0, 1 or 100 mg kg-1. Total soil exposure durations were either 190 days, starting 106 days before planting or 84 days with NP amendments coinciding with planting. We assessed plant development, bacterial diversity, differential abundance and inferred functional changes across rhizosphere, rhizoplane, and root tissue compartments. Plant non-monotonic dose responses were mirrored in bacterial communities. Most notably, effects were magnified in the rhizoplane under low-dose, short-exposures. Enriched metabolic pathways were primarily related to biosynthesis and degradation/utilization/assimilation, rather than responses to metals or oxidative stress. Our results indicate that plant-mediated bacterial responses were greater than direct NP impacts. Also, we identify needs for modeling non-monotonic legume stress responses that account for coinfection with mutualistic and parasitic bacteroids. Our findings provide new insights regarding effects of applications of soil amendments such as biosolids containing NPs or nano-enabled formulations used in cultivation of legumes and other crops.

Rational Design of Live Biotherapeutic Products for the Prevention of Clostridioides difficile Infection

Clostridioides difficile infection (CDI) is one of the leading causes of healthcare- and antibiotic-associated diarrhea. While fecal microbiota transplantation (FMT) has emerged as a promising therapy for recurrent CDI, its exact mechanisms of action and long-term safety are not fully understood. Defined consortia of clonal bacterial isolates, known as live biotherapeutic products (LBPs), have been proposed as an alternative therapeutic option. However, the rational design of LBPs remains challenging. Here, we employ a computational pipeline and three independent metagenomic datasets to systematically identify microbial strains that have the potential to inhibit CDI. We first constructed the CDI-related microbial genome catalog, comprising 3,741 non-redundant metagenome-assembled genomes (nrMAGs) at the strain level. We then identified multiple potential protective nrMAGs that can be candidates for the design of microbial consortia targeting CDI, including strains from Dorea formicigenerans, Oscillibacter welbionis, and Faecalibacterium prausnitzii. Importantly, some of these potential protective nrMAGs were found to play an important role in the success of FMT, and the majority of the top protective nrMAGs can be validated by various previously reported findings. Our results demonstrate a computational framework for the rational selection of microbial strains targeting CDI, paving the way for the computational design of microbial consortia against other enteric infections.

Microbiome changes under enteral deprivation are dynamic and dependent on intestinal location

BACKGROUND

The microbiome has a pivotal role in intestinal health, and nutrition has a major role shaping its structure. Enteral deprivation, in which no oral/enteral nutrition is administered, is common in hospitalized/gastrointestinal patients. The dynamics that enteral deprivation exerts on the microbial community, specifically in the small intestine, are not well understood.

METHODS

Enteral deprivation was modeled with exclusive parenteral nutrition (EPN) mice. Mice were allocated to receive either EPN or saline and chow (control) and euthanized after 0, 2, 4, or 6 days. DNA was extracted from jejunum, ileum, and colon content. 16S sequencing was used to compare changes in microbial communities between groups. Functional pathways were predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States.

RESULTS

EPN-treated mice showed community changes throughout the intestine. Beta diversity in colon showed clear separation between the groups (Bray-Curtis, P < 0.001). Time-dependent dynamics were seen in ileal but not jejunal samples. Alpha diversity was lower in the colon of EPN mice compared with control/baseline mice (Chao1, P < 0.01) but not in ileum/jejunum. Progressive loss of single-taxon domination was seen, most notably in the small intestine. This was accompanied by increases/decreases in specific taxa. A clear separation was seen in the functional capacity of the community between fed and enterally deprived mice at the ileum and colon, which was observed early on.

CONCLUSIONS

Enteral deprivation disturbs the microbial community in a spatial and dynamic manner. There should be further focus on studying the effect of these changes on the host.

Elexacaftor-tezacaftor-ivacaftor decreases pseudomonas abundance in the sinonasal microbiome in cystic fibrosis

BACKGROUND

Chronic rhinosinusitis (CRS) is common in individuals with cystic fibrosis (CF) and is marked by chronic inflammation and episodes of infection that negatively impact quality of life. Several studies have shown that elexacaftor-tezacaftor-ivacaftor (ETI) improves symptoms and examination findings in CF-CRS. The current study determines the effect of ETI on the sinonasal microbiota in CF.

METHODS

Sinonasal samples were collected under endoscopic visualization before and after starting ETI. Samples were subjected to 16S amplicon sequencing and sequences were processed with the QIIME2 pipeline with subsequent analysis using the vegan R-package.

RESULTS

Twenty-nine individual baseline samples and 23 sample pairs pre-/post-ETI were available. At baseline, the cohort had samples dominated by Staphylococcus, and alpha diversity was lower than that of a published reference set of individuals without sinonasal disease. Individuals with prior sinus surgery had lower alpha diversity as measured by Shannon Index, Observed Richness, and Faith's phylogenetic diversity Index. Beta diversity differed between individuals with and without allergic rhinitis, with higher Staphylococcus abundance in those with allergic rhinitis. No change in alpha or beta diversity was seen after a median of 9 months on ETI. With ETI, the Pseudomonas genus and the genus containing Burkholderia decreased in samples containing these taxa at baseline. Pseudomonas abundance decreased with treatment as measured by qPCR. Core sinonasal microbiome members Staphylococcus, Corynebacterium, and Streptococcus were unchanged, while Moraxella increased with ETI.

CONCLUSIONS

Treatment with ETI leads to a reduction in Pseudomonas abundance within the sinonasal microbiome of individuals with Pseudomonas at baseline.

A metagenomic approach to unveil the association between fecal gut microbiota and short-chain fatty acids in diarrhea caused by diarrheagenic Escherichia coli in children

Diarrheagenic Escherichia coli (DEC) is the main cause of diarrhea in children under five years old. The virulence of DEC is tightly regulated by environmental signals influenced by the gut microbiota and its metabolites. Short-chain fatty acids (SCFAs) are the main metabolic product of anaerobic fermentation in the gut, but their role in DEC diarrhea has not yet been established. In this study, we determine the levels of acetate, propionate, and butyrate in stool samples from children with diarrhea caused by DEC, and we identify bacteria from the fecal gut microbiota associated with the production of SCFAs. The microbiota and SCFAs levels in stool samples obtained from 40 children with diarrhea and 43 healthy children were determined by 16S rRNA gene sequencing and HPLC, respectively. Additionally, shotgun metagenomics was used to identify metagenome-assembled genomes (MAGs) in a subgroup of samples. The results showed significantly higher levels of all SCFAs tested in diarrheal samples than in healthy controls. The abundance of Streptococcus sp., Limosilactobacillus, Blautia, Escherichia, Bacteroides, Megamonas, and Roseburia was higher in the DEC group than in healthy individuals. Functional analysis of bacteria and their main metabolic pathways made it possible to identify species MAGs that could be responsible for the detected SCFAs levels in DEC-positive diarrhea. In conclusion, based on our results and published data, we suggest that SCFAs may be important in the crosstalk between the microbiota and DEC pathogens in the gut.

Colon impairments and inflammation driven by an altered gut microbiota leads to social behavior deficits rescued by hyaluronic acid and celecoxib

BACKGROUND

The exact mechanisms linking the gut microbiota and social behavior are still under investigation. We aimed to explore the role of the gut microbiota in shaping social behavior deficits using selectively bred mice possessing dominant (Dom) or submissive (Sub) behavior features. Sub mice exhibit asocial, depressive- and anxiety-like behaviors, as well as systemic inflammation, all of which are shaped by their impaired gut microbiota composition.

METHODS

An age-dependent comparative analysis of the gut microbiota composition of Dom and Sub mice was performed using 16S rRNA sequencing, from early infancy to adulthood. Dom and Sub gastrointestinal (GI) tract anatomy, function, and immune profiling analyses were performed using histology, RT-PCR, flow cytometry, cytokine array, and dextran-FITC permeability assays. Short chain fatty acids (SCFA) levels in the colons of Dom and Sub mice were quantified using targeted metabolomics. To support our findings, adult Sub mice were orally treated with hyaluronic acid (HA) (30 mg/kg) or with the non-steroidal anti-inflammatory agent celecoxib (16 mg/kg).

RESULTS

We demonstrate that from early infancy the Sub mouse gut microbiota lacks essential bacteria for immune maturation, including Lactobacillus and Bifidobacterium genera. Furthermore, from birth, Sub mice possess a thicker colon mucin layer, and from early adulthood, they exhibit shorter colonic length, altered colon integrity with increased gut permeability, reduced SCFA levels and decreased regulatory T-cells, compared to Dom mice. Therapeutic intervention in adult Sub mice treated with HA, celecoxib, or both agents, rescued Sub mice phenotypes. HA treatment reduced Sub mouse gut permeability, increased colon length, and improved mouse social behavior deficits. Treatment with celecoxib increased sociability, reduced depressive- and anxiety-like behaviors, and increased colon length, and a combined treatment resulted in similar effects as celecoxib administered as a single agent.

CONCLUSIONS

Overall, our data suggest that treating colon inflammation and decreasing gut permeability can restore gut physiology and prevent social deficits later in life. These findings provide critical insights into the importance of early life gut microbiota in shaping gut immunity, functionality, and social behavior, and may be beneficial for the development of future therapeutic strategies.

Comparative analysis of root associated microbes in tropical cultivated and weedy rice (Oryza spp.) and temperate cultivated rice

Weedy rice is a major problem in paddy fields around the world. It is well known that weedy rice appears to grow faster and mature earlier than cultivated rice. It is possible that differences in the root microbial genetics are correlated with this characteristic. This study incorporated 16S rRNA amplicon sequencing to study the microbial composition in the rhizosphere and endosphere of rice root. No significant difference was found between the microbiota associated with weedy and cultivated rice lines grown in the same field. It was found that the endosphere had less microbial diversity compared to the rhizosphere. The major groups of bacteria found in the endosphere are from the phylum Proteobacteria, Myxococcota, Chloroflexota, and Actinobacteria. In addition, by analyzing the microbiome of japonica rice grown in the field in a temperate climate, we found that despite differences in genotype and location, some bacterial taxa were found to be common and these members of the putative rice core microbiome can also be detected by in situ hybridization. The delineation of a core microbiome in the endosphere of rice suggests that these bacterial taxa might be important in the life cycle of a wide range of rice types.

Gut microbiome composition reveals the distinctiveness between the Bengali people and the Indigenous ethnicities in Bangladesh

Ethnicity has a significant role in shaping the composition of the gut microbiome, which has implications in human physiology. This study intends to investigate the gut microbiome of Bengali people as well as several indigenous ethnicities (Chakma, Marma, Khyang, and Tripura) residing in the Chittagong Hill Tracts areas of Bangladesh. Following fecal sample collection from each population, part of the bacterial 16 s rRNA gene was amplified and sequenced using Illumina NovaSeq platform. Our findings indicated that Bangladeshi gut microbiota have a distinct diversity profile when compared to other countries. We also found out that Bangladeshi indigenous communities had a higher Firmicutes to Bacteroidetes ratio than the Bengali population. The investigation revealed an unclassified bacterium that was differentially abundant in Bengali samples while the genus Alistipes was found to be prevalent in Chakma samples. Further research on these bacteria might help understand diseases associated with these populations. Also, the current small sample-sized pilot study hindered the comprehensive understanding of the gut microbial diversity of the Bangladeshi population and its potential health implications. However, our study will help establish a basic understanding of the gut microbiome of the Bangladeshi population.

Comparison of canine colostrum and milk using a multi-omics approach

BACKGROUND

A mother's milk is considered the gold standard of nutrition in neonates and is a source of cytokines, immunoglobulins, growth factors, and other important components, yet little is known about the components of canine milk, specifically colostrum, and the knowledge related to its microbial and metabolic profiles is particularly underwhelming. In this study, we characterized canine colostrum and milk microbiota and metabolome for several breeds of dogs and examined profile shifts as milk matures in the first 8 days post-whelping.

RESULTS

Through untargeted metabolomics, we identified 63 named metabolites that were significantly differentially abundant between days 1 and 8 of lactation. Surprisingly, the microbial compositions of the colostrum and milk, characterized using 16S rRNA gene sequencing, were largely similar, with only two differentiating genera. The shifts observed, mainly increases in several sugars and amino sugars over time and shifts in amino acid metabolites, align with shifts observed in human milk samples and track with puppy development.

CONCLUSION

Like human milk, canine milk composition is dynamic, and shifts are well correlated with developing puppies' needs. Such a study of the metabolic profile of canine milk, and its relation to the microbial community, provides insights into the changing needs of the neonate, as well as the ideal nutrition profile for optimal functionality. This information will add to the existing knowledge base of canine milk composition with the prospect of creating a quality, tailored milk substitute or supplement for puppies.

Identification of novel small molecule inhibitors of twin arginine translocation (Tat) pathway and their effect on the control of Campylobacter jejuni in chickens

Introduction

Control of Campylobacter from farm to fork is challenging due to the frequent emergence of antimicrobial-resistant isolates. Furthermore, poultry production systems are known reservoirs of Campylobacter. The twin-arginine translocation (Tat) pathway is a crucial bacterial secretion system that allows Campylobacter to colonize the host intestinal tract by using formate as the main source of energy. However, Tat pathway is also a major contributing factor for resistance to copper sulfate (CuSO4).

Methods

Since mammals and chickens do not have proteins or receptors that are homologous to bacterial Tat proteins, identification of small molecule (SM) inhibitors targeting the Tat system would allow the development of safe and effective control methods to mitigate Campylobacter in infected or colonized hosts in both pre-harvest and post-harvest. In this study, we screened 11 commercial libraries (n = 50,917 SM) for increased susceptibility to CuSO4 (1 mM) in C. jejuni 81-176, a human isolate which is widely studied.

Results

Furthermore, we evaluated 177 SM hits (2.5 μg/mL and above) that increased the susceptibility to CuSO4 for the inhibition of formate dehydrogenase (Fdh) activity, a Tat-dependent substrate. Eight Tat-dependent inhibitors (T1-T8) were selected for further studies. These selected eight Tat inhibitors cleared all tested Campylobacter strains (n = 12) at >10 ng/mL in the presence of 0.5 mM CuSO4in vitro. These selected SMs were non-toxic to colon epithelial (Caco-2) cells when treated with 50 μg/mL for 24 h and completely cleared intracellular C. jejuni cells when treated with 0.63 μg/mL of SM for 24 h in the presence of 0.5 mM of CuSO4. Furthermore, 3 and 5-week-old chicks treated with SM candidates for 5 days had significantly decreased cecal colonization (up to 1.2 log; p < 0.01) with minimal disruption of microbiota. In silico analyses predicted that T7 has better drug-like properties than T2 inhibitor and might target a key amino acid residue (glutamine 165), which is located in the hydrophobic core of TatC protein.

Discussion

Thus, we have identified novel SM inhibitors of the Tat pathway, which represent a potential strategy to control C. jejuni spread on farms.

Systemic antibiotic treatment of cows with metritis early postpartum does not change the progression of uterine disease or the uterine microbiome at 1 month postpartum

Background

Postpartum uterine disease (metritis) is common in dairy cows. The disease develops within 1 week after calving and is associated with microbial dysbiosis, fever, and fetid uterine discharge. Cows with metritis have a greater likelihood of developing endometritis and infertility later postpartum. Antibiotic treatment is used to relieve symptoms of metritis but the capacity of antibiotic treatment to improve fertility later postpartum is inconsistent across published studies. We hypothesized that an antibiotic has only a short-term effect on the uterine microbiome and does not change the progression of disease from metritis to endometritis. To test this hypothesis, we studied the effects of systemic antibiotic given to cows diagnosed with metritis and healthy cows early postpartum on the development of endometritis and the uterine microbiome at 1 month postpartum.

Results

Cows diagnosed with metritis were compared to healthy ones in a 2 × 2 factorial design, where they were either treated with an antibiotic (ceftiofur hydrochloride) at 7 to 10 days postpartum or left untreated. Cows were slaughtered at one month postpartum and the uterus was assessed for endometritis (presence of purulent material in the uterine lumen and inflammation in the endometrium) and uterine samples were collected for bacteriology and metagenomics (16S rRNA gene sequencing). As expected, the uterine microbiome at disease diagnosis had dysbiosis of typical metritis pathogens (e.g., Fusobacterium, Bacteroides, and Porphyromonas) in diseased compared with healthy cows. At one month postpartum, there was a tendency for more endometritis in metritis cows compared with healthy but antibiotic treatment had no effect on endometritis prevalence regardless of the original disease diagnosis. Likewise, when bacteria were cultured or sequenced, there were a greater number of species (culture) or amplicon sequence variants (ASV; sequencing) in the uterine lumen of cows with metritis. However, antibiotic treatment had no effect on the prevalence of cultured species or the composition of the detected ASV. The uterine microbiome at 1 month postpartum was associated with the clinical observation of the uterus (endometritis or healthy).

Conclusions

Early postpartum antibiotic treatment only provides temporary resolution of uterine dysbiosis that is not sustained long-term. Failure to resolve the dysbiosis is associated with a greater prevalence of endometritis in cows with metritis, and the occurrence of endometritis significantly impacts fertility later postpartum.

Gut microbiome, T cell subsets, and cytokine analysis identify differential biomarkers in tuberculosis

Introduction

The gut microbiota, T cell subsets, and cytokines participate in tuberculosis (TB) pathogenesis. To date, the mechanisms by which these factors interactively promote TB development at different time points remain largely unclear. In the context of this study, We looked into the microorganisms in the digestive tract, T cell types, and cytokines related to tuberculosis.

Methods

According to QIIME2, we analyzed 16SrDNA sequencing of the gut microbiome on the Illumina MiSeq. Enzyme-linked immunosorbent assay was used to measure the concentrations of cytokines.

Results

We showed the presence of 26 identifiable differential microbiomes in the gut and 44 metabolic pathways between healthy controls and the different time points in the development of TB in patients. Five bacterial genera (Bacteroides, Bifidobacterium, Faecalibacterium, Collinsella, and Clostridium) were most closely associated with CD4/CD8, whereas three bacterial taxa (Faecalibacterium, Collinsella, and Clostridium) were most closely associated with CD4. Three bacterial taxa (Faecalibacterium, Ruminococcus, and Dorea) were most closely associated with IL-4. Ruminococcus was most closely associated with IL-2 and IL-10.

Conclusion

Diverse microorganisms, subsets of T cells, and cytokines, exhibiting varying relative abundances and structural compositions, were observed in both healthy controls and patients throughout distinct phases of tuberculosis. Gaining insight into the function of the gut microbiome, T cell subsets, and cytokines may help modulate therapeutic strategies for TB.

Impact of Equine Ocular Surface Squamous Neoplasia on Interactions between Ocular Transcriptome and Microbiome

Ocular surface squamous neoplasia (OSSN) represents the most common conjunctival tumor in horses and frequently results in vision loss and surgical removal of the affected globe. Multiple etiologic factors have been identified as contributing to OSSN progression, including solar radiation exposure, genetic mutations, and a lack of periocular pigmentation. Response to conventional treatments has been highly variable, though our recent work indicates that these tumors are highly responsive to local immunotherapy. In the present study, we extended our investigation of OSSN in horses to better understand how the ocular transcriptome responds to the presence of the tumor and how the ocular surface microbiome may also be altered by the presence of cancer. Therefore, we collected swabs from the ventral conjunctival fornix from 22 eyes in this study (11 with cytologically or histologically confirmed OSSN and 11 healthy eyes from the same horses) and performed RNA sequencing and 16S microbial sequencing using the same samples. Microbial 16s DNA sequencing and bulk RNA sequencing were both conducted using an Illumina-based platform. In eyes with OSSN, we observed significantly upregulated expression of genes and pathways associated with inflammation, particularly interferon. Microbial diversity was significantly reduced in conjunctival swabs from horses with OSSN. We also performed interactome analysis and found that three bacterial taxa (Actinobacillus, Helcococcus and Parvimona) had significant correlations with more than 100 upregulated genes in samples from animals with OSSN. These findings highlight the inflammatory nature of OSSN in horses and provide important new insights into how the host ocular surface interacts with certain microbial populations. These findings suggest new strategies for the management of OSSN in horses, which may entail immunotherapy in combination with ocular surface probiotics or prebiotics to help normalize ocular cell and microbe interactions.

Characterization of oral microbiota in 6-8-month-old small breed dogs

BACKGROUND

Periodontitis is the most common oral disease in dogs, and its progression and severity are influenced by risk factors, such as age and body size. Recent studies have assessed the canine oral microbiota in relation to different stages of periodontitis and niches within the oral cavity. However, knowledge of the bacterial composition at different ages and body sizes, especially in puppies, is limited. This study aimed to characterize the oral microbiota in the healthy gingiva of small breed puppies using next-generation sequencing. Additionally, we assessed the impact of dental care practices and the presence of retained deciduous teeth on the oral microbiota.

RESULTS

In this study, plaque samples were collected from the gingival margin of 20 small breed puppies (age, 6.9 ± 0.6 months). The plaque samples were subjected to next-generation sequencing targeting the V3-V4 region of the 16 S rRNA. The microbiota of the plaque samples was composed mostly of gram-negative bacteria, primarily Proteobacteria (54.12%), Bacteroidetes (28.79%), and Fusobacteria (5.11%). Moraxella sp. COT-017, Capnocytophaga cynodegmi COT-254, and Bergeyella zoohelcum COT-186 were abundant in the oral cavity of the puppies. In contrast, Neisseria animaloris were not detected. The high abundance of Pasteurellaceae suggests that this genus is characteristic of the oral microbiota in puppies. Dental care practices and the presence of retained deciduous teeth showed no effects on the oral microbiota.

CONCLUSIONS

In this study, many bacterial species previously reported to be detected in the normal oral cavity of adult dogs were also detected in 6-8-month-old small breed dogs. On the other hand, some bacterial species were not detected at all, while others were detected in high abundance. These data indicate that the oral microbiota of 6-8-month-old small breed dogs is in the process of maturating in to the adult microbiota and may also have characteristics of the small dog oral microbiota.

Urinary microbiome-based metagenomic signature for the noninvasive diagnosis of hepatocellular carcinoma

BACKGROUND

Gut microbial dysbiosis is implicated in chronic liver disease and hepatocellular carcinoma (HCC), but the role of microbiomes from various body sites remains unexplored. We assessed disease-specific alterations in the urinary microbiome in HCC patients, investigating their potential as diagnostic biomarkers.

METHODS

We performed cross-sectional analyses of urine samples from 471 HCC patients and 397 healthy controls and validated the results in an independent cohort of 164 HCC patients and 164 healthy controls. Urinary microbiomes were analyzed by 16S rRNA gene sequencing. A microbial marker-based model distinguishing HCC from controls was built based on logistic regression, and its performance was tested.

RESULTS

Microbial diversity was significantly reduced in the HCC patients compared with the controls. There were significant differences in the abundances of various bacteria correlated with HCC, thus defining a urinary microbiome-derived signature of HCC. We developed nine HCC-associated genera-based models with robust diagnostic accuracy (area under the curve [AUC], 0.89; balanced accuracy, 81.2%). In the validation, this model detected HCC with an AUC of 0.94 and an accuracy of 88.4%.

CONCLUSIONS

The urinary microbiome might be a potential biomarker for the detection of HCC. Further clinical testing and validation of these results are needed in prospective studies.

Modulation of the gut microbiome and Firmicutes phylum reduction by a nutraceutical blend in the obesity mouse model and overweight humans: A double-blind clinical trial

Overweight and obesity are closely linked to gut dysbiosis/dysmetabolism and disrupted De-Ritis ratio [aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio], which may contribute to chronic noncommunicable diseases onset. Concurrently, extensive research explores nutraceuticals, and health-enhancing supplements, for disease prevention or treatment. Thus, sedentary overweight volunteers were double-blind randomized into two groups: Novel Nutraceutical_(S) (without silymarin) and Novel Nutraceutical (with silymarin). Experimental formulations were orally administered twice daily over 180 consecutive days. We evaluated fecal gut microbiota, based on partial 16S rRNA sequences, biochemistry and endocrine markers, steatosis biomarker (AST/ALT ratio), and anthropometric parameters. Post-supplementation, only the Novel Nutraceutical group reduced Clostridium clostridioforme (Firmicutes), Firmicutes/Bacteroidetes ratio (F/B ratio), and De-Ritis ratio, while elevating Bacteroides caccae and Bacteroides uniformis (Bacteroidetes) in Brazilian sedentary overweight volunteers after 180 days. In summary, the results presented here allow us to suggest the gut microbiota as the action mechanism of the Novel Nutraceutical promoting metabolic hepatic recovery in obesity/overweight non-drug interventions.

Gut Microbiota and Blood Metabolites Related to Fiber Intake and Type 2 Diabetes

BACKGROUND

Consistent evidence suggests diabetes-protective effects of dietary fiber intake. However, the underlying mechanisms, particularly the role of gut microbiota and host circulating metabolites, are not fully understood. We aimed to investigate gut microbiota and circulating metabolites associated with dietary fiber intake and their relationships with type 2 diabetes (T2D).

METHODS

This study included up to 11 394 participants from the HCHS/SOL (Hispanic Community Health Study/Study of Latinos). Diet was assessed with two 24-hour dietary recalls at baseline. We examined associations of dietary fiber intake with gut microbiome measured by shotgun metagenomics (350 species/85 genera and 1958 enzymes; n=2992 at visit 2), serum metabolome measured by untargeted metabolomics (624 metabolites; n=6198 at baseline), and associations between fiber-related gut bacteria and metabolites (n=804 at visit 2). We examined prospective associations of serum microbial-associated metabolites (n=3579 at baseline) with incident T2D over 6 years.

RESULTS

We identified multiple bacterial genera, species, and related enzymes associated with fiber intake. Several bacteria (eg, Butyrivibrio, Faecalibacterium) and enzymes involved in fiber degradation (eg, xylanase EC3.2.1.156) were positively associated with fiber intake, inversely associated with prevalent T2D, and favorably associated with T2D-related metabolic traits. We identified 159 metabolites associated with fiber intake, 47 of which were associated with incident T2D. We identified 18 of these 47 metabolites associated with the identified fiber-related bacteria, including several microbial metabolites (eg, indolepropionate and 3-phenylpropionate) inversely associated with the risk of T2D. Both Butyrivibrio and Faecalibacterium were associated with these favorable metabolites. The associations of fiber-related bacteria, especially Faecalibacterium and Butyrivibrio, with T2D were attenuated after further adjustment for these microbial metabolites.

CONCLUSIONS

Among United States Hispanics/Latinos, dietary fiber intake was associated with favorable profiles of gut microbiota and circulating metabolites for T2D. These findings advance our understanding of the role of gut microbiota and microbial metabolites in the relationship between diet and T2D.

MIDASim: a fast and simple simulator for realistic microbiome data

Background

Advances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time.

Methods

We develop MIDASim ( MI crobiome DA ta Sim ulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, an inverse generalized gamma distribution is used in place of the empirical distribution.

Results

We demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PER-MANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model.

Conclusions

MIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods at both presence-absence level and relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets.

Temporal dynamics of gut microbiomes in non-industrialized urban Amazonia

Increasing levels of industrialization have been associated with changes in gut microbiome structure and loss of features thought to be crucial for maintaining gut ecological balance. The stability of gut microbial communities over time within individuals seems to be largely affected by these changes but has been overlooked among transitioning populations from low- to middle-income countries. Here, we used metagenomic sequencing to characterize the temporal dynamics in gut microbiomes of 24 individuals living an urban non-industrialized lifestyle in the Brazilian Amazon. We further contextualized our data with 165 matching longitudinal samples from an urban industrialized and a rural non-industrialized population. We show that gut microbiome composition and diversity have greater variability over time among non-industrialized individuals when compared to industrialized counterparts and that taxa may present diverse temporal dynamics across human populations. Enterotype classifications show that community types are generally stable over time despite shifts in microbiome structure. Furthermore, by tracking genomes over time, we show that levels of bacterial population replacements are more frequent among Amazonian individuals and that non-synonymous variants accumulate in genes associated with degradation of host dietary polysaccharides. Taken together, our results suggest that the stability of gut microbiomes is influenced by levels of industrialization and that tracking microbial population dynamics is important to understand how the microbiome will adapt to these transitions.IMPORTANCEThe transition from a rural or non-industrialized lifestyle to urbanization and industrialization has been linked to changes in the structure and function of the human gut microbiome. Understanding how the gut microbiomes changes over time is crucial to define healthy states and to grasp how the gut microbiome interacts with the host environment. Here, we investigate the temporal dynamics of gut microbiomes from an urban and non-industrialized population in the Amazon, as well as metagenomic data sets from urban United States and rural Tanzania. We showed that healthy non-industrialized microbiomes experience greater compositional shifts over time compared to industrialized individuals. Furthermore, bacterial strain populations are more frequently replaced in non-industrialized microbiomes, and most non-synonymous mutations accumulate in genes associated with the degradation of host dietary components. This indicates that microbiome stability is affected by transitions to industrialization, and that strain tracking can elucidate the ecological dynamics behind such transitions.

Differences in diversity and community composition of the shell microbiome of apparently healthy lobsters Homarus americanus across Atlantic Canada

Host-microbe dynamics are of increasing interest in marine research due to their role in host health and productivity. Changes in the shell microbiome of American lobsters have been associated with epizootic shell disease, a syndrome that is spreading northwards across the eastern U.S. and Canadian Atlantic coast. This study analyzed differences in alpha and beta diversity, as well as differentially abundant taxa, in the shell-associated bacterial community of apparently healthy lobsters from four lobster fishing areas (LFAs) in Atlantic Canada. Over 180 lobsters from New Brunswick, Nova Scotia and Prince Edward Island (PEI) were sampled during seven sampling events over four sampling months. The bacterial community was identified using novel PacBio long-read sequencing, while alpha and beta diversity parameters were analyzed using linear regression models and weighted UniFrac distances. The bacterial richness, diversity and evenness differed by sampling location, sampling month, and molt stage, but not by lobster sex or size, nor sampling depth. Similarly, based on LFA, sampling month, year and lobster molt stage, the shell microbiome differed in microbial community composition with up to 34 out of 162 taxa differing significantly in abundance between sampling groups. This large-scale microbial survey suggests that the shell microbial diversity of apparently healthy lobsters is influenced by spatial and temporal factors such as geographic location, as well as the length of time the carapace is exposed to the surrounding seawater.

Effect size of delayed freezing, diurnal variation, and hindgut location on the mouse fecal microbiome

Practical considerations in fecal sample collection for microbiome research include time to sample storage, time of collection, and hindgut position during terminal collections. Here, parallel experiments were performed to investigate the relative effect of these factors on microbiome composition in mice colonized with two different vendor-origin microbiomes. 16S rRNA amplicon sequencing of immediately flash-frozen feces showed no difference in alpha or beta diversity compared to samples incubated up to 9 h at room temperature. Samples collected in the morning showed greater alpha diversity compared to samples collected in the afternoon. While a significant effect of time was detected in all hindgut regions, the effect increased from cecum to distal colon. This study highlights common scenarios in microbiome research that may affect outcome measures of microbial community analysis. However, we demonstrate a relatively low effect size of these technical factors when compared to a primary experimental factor with large intergroup variability.

Gut microbiome-derived bacterial extracellular vesicles in patients with solid tumours

INTRODUCTION

Gut microbiome-derived nanoparticles, known as bacterial extracellular vesicles (bEVs), have garnered interest as promising tools for studying the link between the gut microbiome and human health. The diverse composition of bEVs, including their proteins, mRNAs, metabolites, and lipids, makes them useful for investigating diseases such as cancer. However, conventional approaches for studying gut microbiome composition alone may not be accurate in deciphering host-gut microbiome communication. In clinical microbiome research, there is a gap in the knowledge on the role of bEVs in solid tumor patients.

OBJECTIVES

Analyzing the functionality of bEVs using (meta)genomics and proteomics could highlight the unique aspects of host-gut microbiome interactions in solid tumor patients. Therefore, we performed a comparative analysis of the proteome and microbiota composition of gut microbiome-derived bEVs isolated from patients with solid tumors and healthy controls.

METHODS

After isolating bEVs from the feces of solid tumor patients and healthy controls, we performed spectrometry analysis of their proteomes and next-generation sequencing (NGS) of the 16S gene. We also investigated the gut microbiomes of feces from patients and controls using 16S sequencing and used machine learning to classify the samples into patients and controls based on their bEVs and fecal microbiomes.

RESULTS

Solid tumor patients showed decreased microbiota richness and diversity in both the bEVs and feces. However, the bEV proteomes were more diverse in patients than in the controls and were enriched with proteins associated with the metabolism of amino acids and carbohydrates, nucleotide binding, and oxidoreductase activity. Metadata classification of samples was more accurate using fecal bEVs (100%) compared with fecal samples (93%).

CONCLUSION

Our findings suggest that bEVs are unique functional entities. There is a need to explore bEVs together with conventional gut microbiome analysis in functional cancer research to decipher the potential of bEVs as cancer diagnostic or therapeutic biomarkers.

Study of the intestinal microbiota composition and the effect of treatment with intensive chemotherapy in patients recovered from acute leukemia

A dataset comprising metagenomes of outpatients (n = 28) with acute leukemia (AL) and healthy controls (n = 14) was analysed to investigate the associations between gut microbiota composition and metabolic activity and AL. According to the results obtained, no significant differences in the microbial diversity between AL outpatients and healthy controls were found. However, significant differences in the abundance of specific microbial clades of healthy controls and AL outpatients were found. We found some differences at taxa level. The relative abundance of Enterobacteriaceae, Prevotellaceae and Rikenellaceae was increased in AL outpatients, while Bacteirodaceae, Bifidobacteriaceae and Lachnospiraceae was decreased. Interestingly, the abundances of several taxa including Bacteroides and Faecalibacterium species showed variations based on recovery time from the last cycle of chemotherapy. Functional annotation of metagenome-assembled genomes (MAGs) revealed the presence of functional domains corresponding to therapeutic enzymes including L-asparaginase in a wide range of genera including Prevotella, Ruminococcus, Faecalibacterium, Alistipes, Akkermansia. Metabolic network modelling revealed potential symbiotic relationships between Veillonella parvula and Levyella massiliensis and several species found in the microbiota of AL outpatients. These results may contribute to develop strategies for the recovery of microbiota composition profiles in the treatment of patients with AL.