Composition Of Human Gut Microbiome Research Articles

Metagenome-assembled microbial genomes from Parkinson’s disease fecal samples

The human gut microbiome composition has been linked to Parkinson’s disease (PD). However, knowledge of the gut microbiota on the genome level is still limited. Here we performed deep metagenomic sequencing and binning to build metagenome-assembled genomes (MAGs) from 136 human fecal microbiomes (68 PD samples and 68 control samples). We constructed 952 non-redundant high-quality MAGs and compared them between PD and control groups. Among these MAGs, there were 22 different genomes of Collinsella and Prevotella, indicating high variability of those genera in the human gut environment. Microdiversity analysis indicated that Ruminococcus bromii was statistically significantly (p < 0.002) more diverse on the strain level in the control samples compared to the PD samples. In addition, by clustering all genes and performing presence-absence analysis between groups, we identified several control-specific (p < 0.05) related genes, such as speF and Fe-S oxidoreductase. We also report detailed annotation of MAGs, including Clusters of Orthologous Genes (COG), Cas operon type, antiviral gene, prophage, and secondary metabolites biosynthetic gene clusters, which can be useful for providing a reference for future studies.

Effects of processed oats and pinto beans on the composition of human gut microbiome: An in vitro study

Oats and pinto beans, which are rich in dietary fibers and plant proteins, are two common ingredients for many processed food products, such as puffed snacks and canned foods. The objective of this study was to investigate the gut microbiome response to processed oats and pinto beans food products. Raw oats and pinto beans were canned, boiled, and extruded at selected temperatures to simulate the commercial food processing practices. The processed oat and pinto bean samples were digested in an in vitro digestion system, and were subjected to in vitro fermentation by gut bacteria from human feces, which simulated the reactions between the undigested food components and the gut microbiome. The resulting metabolites were quantitatively and qualitatively measured, the compositions of the gut microbiome were determined by 16S rRNA sequencing, and the microbiota were classified and clustered based on their amplicon sequence variants (ASVs) and co-abundancies. The results showed that pinto beans generated more gas and short-chain fatty acids (SCFA) than oats. Boiled oats had a good retention of non-digestible fermentable contents (NDFCs) for the gut microbiota to act on, resulting in greater gas and acid production than other processed oat samples. However, for processed pinto beans, high-temperature extrusion and canning resulted in more NDFCs through starch gelatinization and retrogradation. Guild-based analysis was applied to microbiome analysis to identify key bacteria contributing to microbial shift. Bacteria such as Escherichia-Shigella, Streptococcus, Anaerostipes were promoted in extruded oats, while Lachnospiraceae, Eubacterium hallii, Butyricicoccus were significantly promoted in boiled and low-temperature extruded pinto beans.

Associations of Sedentary Behavior and Screen Time with Human Gut Microbiome Composition and Diversity.

Human gut microbiome richness, diversity, and composition are associated with physical activity and impaired glycemic control; however, the associations with sedentary behavior and screen time are not as well-established. This study evaluated associations of sedentary behavior and screen time with the alpha diversity and composition of the human gut microbiome in adults with and without impaired glycemic control. Sedentary behavior and screen time data were collected via survey from 47 adults (38% with impaired glycemic control). Microbiome composition and alpha diversity were determined in fecal microbial DNA. Sedentary behavior was negatively associated with the number of observed operational taxonomic units (OTUs), Chao 1 Index, and Fisher's Alpha Index. These associations were slightly attenuated but remained significant when controlling for covariates. Screen time was negatively associated with the number of observed OTUs, Shannon Index, and Fisher's Alpha Index; however, only the association with observed OTUs was independent of all covariates. Our findings suggest sedentary behavior and screen time may be significant influencers of compositional changes in human gut microbiota. This may be a potential mechanism linking sedentary behavior and screen time to an increased risk of type 2 diabetes.

Human Milk Components and the Infant Gut Microbiome at 6 Months: Understanding the Interconnected Relationship

BackgroundHuman milk oligosaccharides have been shown to relate to the infant gut microbiome. However, the impact of other human milk components on infant gut bacterial colonization remains unexplored. ObjectivesOur cross-sectional analysis aimed to investigate associations between human milk components (energy, macronutrients, free amino acids, inflammatory markers, and hormones) and infant gut microbiome diversity and composition (phylum, family, and genus) at 6 mo of age. MethodsHuman milk and infant stool samples were collected at 6 mo postpartum. The infant gut microbiome was profiled using 16S rRNA sequencing. Linear regression models were performed to examine associations, adjusting for pregravid BMI (kg/m2), delivery mode, duration of human milk feeding, and infant sex, with q < 0.2 considered significant. ResultsThis analysis included a total of 54 mothers (100% exclusively feeding human milk) and infants (n = 28 male; 51.9%). Total energy in human milk showed a negative association with α-diversity measures (Chao1 and Shannon). Interleukin (IL)-8 in human milk was positively associated with Chao1 and observed operational taxonomic units. At the family level, human milk glutamine and serine levels showed a negative association with the abundance of Veillonellaceae, whereas isoleucine showed a positive association with Bacteroidaceae. Human milk IL-8 and IL-6 concentrations were positively associated with Bacteroidaceae abundance. IL-8 also had a positive relationship with Bifidobacteriaceae, whereas it had a negative relationship with Streptococcacea and Clostridiaceae. Human milk IL-8 was positively associated with the phylum Bacteroidetes, and negatively associated with Proteobacteria. At the genus level, human milk IL-8 exhibited a positive relationship with Bacteroides, whereas human milk isoleucine had a negative relationship with Bacteroides and Ruminococcus. Pregravid BMI and sex effects were observed. ConclusionsIL-8 in human milk could potentially prepare the infant’s immune system to respond effectively to various microorganisms, potentially promoting the growth of beneficial gut bacteria and protecting against pathogens.

Ceftriaxone alters the gut microbiome composition and reduces alcohol intake in male and female Sprague–Dawley rats

Ceftriaxone is an antibiotic that increases central nervous system (CNS) protein expression of the glutamate transporters GLT-1 and xCT and ameliorates pathological behaviors in rodent models of neurological disease and substance use disorder. However, little ceftriaxone passes through the blood–brain barrier, the CNS binding partner of ceftriaxone is unknown, and ceftriaxone does not consistently upregulate GLT-1 and xCT in cell culture. Ceftriaxone alters the gut microbiome composition in rodents and humans, and the microbiome–gut–brain axis regulates drug-seeking. Thus, here we test the hypothesis that ceftriaxone reduces alcohol intake while ameliorating alcohol-induced disruption of the gut microbiome composition. Male and female Sprague–Dawley rats received intermittent access to alcohol (IAA) while controls received access to only water. Following 17 IAA sessions, ceftriaxone/vehicle treatment was given for 5 days. Analysis of the gut microbiome composition was assessed by 16S rRNA gene amplicon sequencing conducted on fecal pellets collected prior to and after alcohol consumption and following ceftriaxone treatment. Male rats displayed escalated alcohol intake and preference over the course of the 17 sessions; however, total alcohol intake did not differ between the sexes. Ceftriaxone reduced alcohol intake and preference in male and female rats. While alcohol affected a diverse set of amplicon sequencing variants (ASV), ceftriaxone markedly reduced the diversity of microbial communities reflected by a blooming of the Enterococcaceae family. The remaining effects of ceftriaxone, however, encompassed families both affected and unaffected by prior alcohol drinking and highlight the Ruminococcaceae and Muribaculaceae families as bidirectionally modulated by alcohol and ceftriaxone. Altogether, our study confirms that ceftriaxone reduces alcohol intake in rats and partially reverses alcohol-induced dysbiosis.

Food Decision Making in Overweight Adults can be Manipulated by Prebiotic Diet

In a recent issue of Gut, Medawar, et al. show that a prebiotic dietary intervention reduced reward-associated activation of brain during food decision-making via modulation of gut microbiome composition in humans (NCT03829189)

Assessing the causal association between sleep apnea and the human gut microbiome composition: A two-sample Mendelian randomization study.

Studies have linked gut microbiota dysbiosis with sleep apnea; however, no causal relationship was found in human subjects. Finding new targets for the pathophysiology of sleep apnea might be made possible by systematically investigating the causal relationship between the human gut microbiota and sleep apnea. A two-sample Mendelian randomization analysis was conducted. The human gut microbiome composition data, spanning five taxonomic levels, were acquired from a genome-wide association study that included 18,340 participants from 24 cohorts. Genome-wide association study data for sleep apnea were obtained from the Sleep Disorder Knowledge Portal for primary analysis and the FinnGen consortium for meta-analysis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Using inverse-variance weighted analysis, eight microbial taxa were initially found to be substantially linked with the apnea-hypopnea index. Only three microbial taxa remained significant associations with sleep apnea when combined with the FinnGen consortium (the class Bacilli: B = 8.21%, 95% CI = 0.93%-15.49%; p = 0.03; the order Lactobacillales: B = 7.55%, 95% CI = 0.25%-4.85%; p = 0.04; the genus RuminococcaceaeUCG009: B = -21.63%, 95% CI = -41.47% to -1.80%; p = 0.03). Sleep apnea may lead to gut dysbiosis as significant reductions in butyrate-producing bacteria and increases in lactate-producing bacteria. By integrating genomes and metabolism, the evidence that three microbiome species are causally linked to sleep apnea may offer a fresh perspective on the underlying mechanisms of the condition.

Impact of occupational pesticide exposure on the human gut microbiome.

The rising use of pesticides in modern agriculture has led to a shift in disease burden in which exposure to these chemicals plays an increasingly important role. The human gut microbiome, which is partially responsible for the biotransformation of xenobiotics, is also known to promote biotransformation of environmental pollutants. Understanding the effects of occupational pesticide exposure on the gut microbiome can thus provide valuable insights into the mechanisms underlying the impact of pesticide exposure on health. Here we investigate the impact of occupational pesticide exposure on human gut microbiome composition in 7198 participants from the Dutch Microbiome Project of the Lifelines Study. We used job-exposure matrices in combination with occupational codes to retrieve categorical and cumulative estimates of occupational exposures to general pesticides, herbicides, insecticides and fungicides. Approximately 4% of our cohort was occupationally exposed to at least one class of pesticides, with predominant exposure to multiple pesticide classes. Most participants reported long-term employment, suggesting a cumulative profile of exposure. We demonstrate that contact with insecticides, fungicides and a general "all pesticides" class was consistently associated with changes in the gut microbiome, showing significant associations with decreased alpha diversity and a differing beta diversity. We also report changes in the abundance of 39 different bacterial taxa upon exposure to the different pesticide classes included in this study. Together, the extent of statistically relevant associations between gut microbial changes and pesticide exposure in our findings highlights the impact of these compounds on the human gut microbiome.

Association between LEPR Genotype and Gut Microbiome in Healthy Non-Obese Korean Adults.

The LEPR (leptin receptor) genotype is associated with obesity. Gut microbiome composition differs between obese and non-obese adults. However, the impact of LEPR genotype on gut microbiome composition in humans has not yet been studied. In this study, the association between LEPR single nucleotide polymorphism (rs1173100, rs1137101, and rs790419) and the gut microbiome composition in 65 non-obese Korean adults was investigated. Leptin, triglyceride, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol levels were also measured in all participants. Mean ± SD (standard deviation) of age, body mass index, and leptin hormone levels of participants was 35.2 ± 8.1 years, 21.4 ± 1.8 kg/m2, and 7989.1 ± 6687.4 pg/mL, respectively. Gut microbiome analysis was performed at the phylum level by 16S rRNA sequencing. Among the 11 phyla detected, only one showed significantly different relative abundances between LEPR genotypes. The relative abundance of Candidatus Saccharibacteria was higher in the G/A genotype group than in the G/G genotype group for the rs1137101 single nucleotide polymorphism (p=0.0322). Participant characteristics, including body mass index, leptin levels, and other lipid levels, were similar between the rs1137101 G/G and G/A genotypes. In addition, the relative abundances of Fusobacteria and Tenericutes showed significant positive relationship with plasma leptin concentrations (p=0.0036 and p=0.0000, respectively). In conclusion, LEPR genotype and gut microbiome may be associated even in normal-weight Korean adults. However, further studies with a greater number of obese adults are needed to confirm whether LEPR genotype is related to gut microbiome composition.

Multigenerational adversity impacts on human gut microbiome composition and socioemotional functioning in early childhood

Adversity exposures in the prenatal and postnatal period are associated with an increased risk for psychopathology, which can be perpetuated across generations. Nonhuman animal research highlights the gut microbiome as a putative biological mechanism underlying such generational risks. In a sample of 450 mother-child dyads living in Singapore, we examined associations between three distinct adversity exposures experienced across two generations-maternal childhood maltreatment, maternal prenatal anxiety, and second-generation children's exposure to stressful life events-and the gut microbiome composition of second-generation children at 2 y of age. We found distinct differences in gut microbiome profiles linked to each adversity exposure, as well as some nonaffected microbiome features (e.g., beta diversity). Remarkably, some of the microbial taxa associated with concurrent and prospective child socioemotional functioning shared overlapping putative functions with those affected by adversity, suggesting that the intergenerational transmission of adversity may have a lasting impact on children's mental health via alterations to gut microbiome functions. Our findings open up a new avenue of research into the underlying mechanisms of intergenerational transmission of mental health risks and the potential of the gut microbiome as a target for intervention.

Enterosignatures define common bacterial guilds in the human gut microbiome

The human gut microbiome composition is generally in a stable dynamic equilibrium, but it can deteriorate into dysbiotic states detrimental to host health. To disentangle the inherent complexity and capture the ecological spectrum of microbiome variability, we used 5,230 gut metagenomes to characterize signatures of bacteria commonly co-occurring, termed enterosignatures (ESs). We find five generalizable ESs dominated by either Bacteroides, Firmicutes, Prevotella, Bifidobacterium, or Escherichia. This model confirms key ecological characteristics known from previous enterotype concepts, while enabling the detection of gradual shifts in community structures. Temporal analysis implies that the Bacteroides-associated ES is "core" in the resilience of westernized gut microbiomes, while combinations with other ESs often complement the functional spectrum. The model reliably detects atypical gut microbiomes correlated with adverse host health conditions and/or the presence of pathobionts. ESs provide an interpretable and generic model that enables an intuitive characterization of gut microbiome composition in health and disease.

Quorum sensing in human gut and food microbiomes: Significance and potential for therapeutic targeting.

Human gut and food microbiomes interact during digestion. The outcome of these interactions influences the taxonomical composition and functional capacity of the resident human gut microbiome, with potential consequential impacts on health and disease. Microbe-microbe interactions between the resident and introduced microbiomes, which likely influence host colonisation, are orchestrated by environmental conditions, elements of the food matrix, host-associated factors as well as social cues from other microorganisms. Quorum sensing is one example of a social cue that allows bacterial communities to regulate genetic expression based on their respective population density and has emerged as an attractive target for therapeutic intervention. By interfering with bacterial quorum sensing, for instance, enzymatic degradation of signalling molecules (quorum quenching) or the application of quorum sensing inhibitory compounds, it may be possible to modulate the microbial composition of communities of interest without incurring negative effects associated with traditional antimicrobial approaches. In this review, we summarise and critically discuss the literature relating to quorum sensing from the perspective of the interactions between the food and human gut microbiome, providing a general overview of the current understanding of the prevalence and influence of quorum sensing in this context, and assessing the potential for therapeutic targeting of quorum sensing mechanisms.

Neighborhood socioeconomic status and the human gut microbiome composition: relating socioeconomic environment to microbial diversity and MDRO colonization

Low socioeconomic status is correlated with a greater vulnerability to both chemical and non-chemical stressors, however, there is limited research on how socioeconomic status relates to the human gut microbiome, and subsequent associations with downstream health outcomes. Here, we aimed to examine associations between neighborhood level economic hardship, an indicator of overall cumulative risk, gut microbiome composition and additional cofactors that might be involved in this association including diet quality and food insecurity. We conducted a cross-sectional analysis of 721 adults living in geographically diverse (urban vs. rural) regions of Wisconsin (United States). 16S rRNA gene amplicons were analyzed from human stool samples using QIIME2 to evaluate both the composition and diversity of the gut microbiotas from 721 participants. Next, we determined correlations with each individual’s neighborhood score for socioeconomic status, or Economic Hardship Index (EHI), using simple and zero-inflated negative binomial regression models. Our model of EHI, with alpha diversity (Inverse-Simpson) as an outcome, found a correlation (β= 1.68, p=0.03) that it is partially mediated by food insecurity (p= 0.02). Moreover, we found differential abundances of known health-associated bacteria including members of the genera Bifidobacterium and Akkermansia, and the family Ruminococaceae between high and low levels of EHI that were robust to correction for multiple comparisons. Finally, we discovered a higher prevalence (p=0.03) and number (p=0.02) of multi-drug resistant bacteria isolated from individuals with low alpha-diversity and high EHI. Our analyses suggest that living in low socioeconomic communities is associated with lower gut microbial diversity and potential increase in colonization by multi-drug resistant microbial pathogens. Mediation of associations by food insecurity is consistent with previous work from our group examining impacts of metal exposures on gut microbiome dysbiosis indicating dietary factors play an important role in mitigating environmental influences on gut microbial diversity.

Individual Nutrition Is Associated with Altered Gut Microbiome Composition for Adults with Food Insecurity.

Diet is widely recognized as a key contributor to human gut microbiome composition and function. However, overall nutrition can be difficult to compare across a population with varying diets. Moreover, the role of food security in the relationship with overall nutrition and the gut microbiome is unclear. This study aims to investigate the association between personalized nutrition scores, variation in the adult gut microbiome, and modification by food insecurity. The data originate from the Survey of the Health of Wisconsin and the Wisconsin Microbiome Study. Individual nutrition scores were assessed using My Nutrition Index (MNI), calculated using data from food frequency questionnaires, and additional health history and demographic surveys. Food security and covariate data were measured through self-reported questionnaires. The gut microbiome was assessed using 16S amplicon sequencing of DNA extracted from stool samples. Associations, adjusted for confounding and interaction by food security, were estimated using Weighted Quantile Sum (WQS) regression models with Random Subset and Repeated Holdout extensions (WQSRSRH), with bacterial taxa used as components in the weighted index. Of 643 participants, the average MNI was 66.5 (SD = 31.9), and 22.8% of participants were food insecure. Increased MNI was significantly associated with altered gut microbial composition (β = 2.56, 95% CI = 0.52–4.61), with Ruminococcus, Oscillospira, and Blautia among the most heavily weighted of the 21 genera associated with the MNI score. In the stratified interaction WQSRSRH models, the bacterial taxa most heavily weighted in the association with MNI differed by food security, but the level of association between MNI and the gut microbiome was not significantly different. More bacterial genera are important in the association with higher nutrition scores for people with food insecurity versus food security, including Streptococcus, Parabacteroides Faecalibacterium, and Desulfovibrio. Individual nutrition scores are associated with differences in adult gut microbiome composition. The bacterial taxa most associated with nutrition vary by level of food security. While further investigation is needed, results showed a higher nutrition score was associated with a wider range of bacterial taxa for food insecure vs. secure, suggesting nutritional quality in food insecure individuals is important in maintaining health and reducing disparities.

Using the canine microbiome to bridge translation of cancer immunotherapy from pre-clinical murine models to human clinical trials.

The microbiome has clearly been established as a cutting-edge field in tumor immunology and immunotherapy. Growing evidence supports the role of the microbiome in immune surveillance, self-tolerance, and response to immune checkpoint inhibitors such as anti PD-L1 and CTLA-4 blockade (1–6). Moreover, recent studies including those using fecal microbial transplantation (FMT) have demonstrated that response to checkpoint immunotherapies may be conferred or eliminated through gut microbiome modulation (7, 8). Consequently, studies evaluating microbiota-host immune and metabolic interactions remain an area of high impact research. While observations in murine models have highlighted the importance of the microbiome in response to therapy, we lack sufficient understanding of the exact mechanisms underlying these interactions. Furthermore, mouse and human gut microbiome composition may be too dissimilar for discovery of all relevant gut microbial biomarkers. Multiple cancers in dogs, including lymphoma, high grade gliomas, melanomas and osteosarcoma (OSA) closely resemble their human analogues, particularly in regard to metastasis, disease recurrence and response to treatment. Importantly, dogs with these spontaneous cancers also have intact immune systems, suggesting that microbiome analyses in these subjects may provide high yield information, especially in the setting of novel immunotherapy regimens which are currently expanding rapidly in canine comparative oncology (9, 10). Additionally, as onco-microbiotic therapies are developed to modify gut microbiomes for maximal responsiveness, large animal models with intact immune systems will be useful for trialing interventions and monitoring adverse events. Together, pre-clinical mechanistic studies and large animal trials can help fully unlock the potential of the microbiome as a diagnostic and therapeutic target in cancer.

MetaProClust-MS1: an MS1 Profiling Approach for Large-Scale Microbiome Screening.

ABSTRACTMetaproteomics is used to explore the functional dynamics of microbial communities. However, acquiring metaproteomic data by tandem mass spectrometry (MS/MS) is time-consuming and resource-intensive, and there is a demand for computational methods that can be used to reduce these resource requirements. We present MetaProClust-MS1, a computational framework for microbiome feature screening developed to prioritize samples for follow-up MS/MS. In this proof-of-concept study, we tested and compared MetaProClust-MS1 results on gut microbiome data, from fecal samples, acquired using short 15-min MS1-only chromatographic gradients and MS1 spectra from longer 60-min gradients to MS/MS-acquired data. We found that MetaProClust-MS1 identified robust gut microbiome responses caused by xenobiotics with significantly correlated cluster topologies of comparable data sets. We also used MetaProClust-MS1 to reanalyze data from both a clinical MS/MS diagnostic study of pediatric patients with inflammatory bowel disease and an experiment evaluating the therapeutic effects of a small molecule on the brain tissue of Alzheimer’s disease mouse models. MetaProClust-MS1 clusters could distinguish between inflammatory bowel disease diagnoses (ulcerative colitis and Crohn’s disease) using samples from mucosal luminal interface samples and identified hippocampal proteome shifts of Alzheimer’s disease mouse models after small-molecule treatment. Therefore, we demonstrate that MetaProClust-MS1 can screen both microbiomes and single-species proteomes using only MS1 profiles, and our results suggest that this approach may be generalizable to any proteomics experiment. MetaProClust-MS1 may be especially useful for large-scale metaproteomic screening for the prioritization of samples for further metaproteomic characterization, using MS/MS, for instance, in addition to being a promising novel approach for clinical diagnostic screening.IMPORTANCE Growing evidence suggests that human gut microbiome composition and function are highly associated with health and disease. As such, high-throughput metaproteomic studies are becoming more common in gut microbiome research. However, using a conventional long liquid chromatography (LC)-MS/MS gradient metaproteomics approach as an initial screen in large-scale microbiome experiments can be slow and expensive. To combat this challenge, we introduce MetaProClust-MS1, a computational framework for microbiome screening using MS1-only profiles. In this proof-of-concept study, we show that MetaProClust-MS1 identifies clusters of gut microbiome treatments using MS1-only profiles similar to those identified using MS/MS. Our approach allows researchers to prioritize samples and treatments of interest for further metaproteomic analyses and may be generally applicable to any proteomic analysis. In particular, this approach may be especially useful for large-scale metaproteomic screening or in clinical settings where rapid diagnostic evidence is required.

Investigation of the Pectin Degradation Ability of Hominibacterium faecale Strain SF3T Isolated from Human Feces

Pectin is one of the most important dietary fibers as a prebiotic to determine the composition of human gut microbiome. The study was designed to investigate the pectin degradation ability of Hominibacterium faecale strain SF3T, its isolated from human feces and cultivated with different concentration pectin under anaerobic conditions in vitro. The growth ratio of strain SF3T formed in batch culture was examined every 10 h during the 60-h incubation time using the spectrophotometer, high-performance liquid chromatography, and gas-chromatography. The pure culture of Hominibacterium faecale pectin degradation activity was present and commonly increases the growth value of strain SF3T after pectin fermentation. Regarding volatile fatty acids, acetate, propionate and butyrate levels rapidly raised after 30 h of incubation. The results suggest that pectin fermentation displays the greatest contribution for human health and confirm that pectin degradation leads to the production of acetate, butyrate and propionate.

Compositional differences between gut microbiota of adult patients with asthma and healthy controls.

Asthma is a complex and multifactorial disorder, with severe public health implications. Over the last several years, our knowledge in the field of human gut microbiota has expanded and allowed us to understand its crucial role in the development of many diseases. To analyse the nature of human gut microbiota patterns among patients with asthma compared to healthy controls. Composition of the complex gut microbiota was analysed in faecal samples from 13 asthma patients and 7 healthy volunteers using Next-Generation Sequencing technology (NGS). The Kruskal-Wallis Analysis of Variance (ANOVA) and Mann-Whitney tests were used to compare the above two groups of subjects. The composition of the gut microbiota of asthma patients differed from that of healthy volunteers at each of the analysed levels (p < 0.05). Compared to healthy individuals, bacterial diversity was significantly lowered among the asthma group, which is the evidence of gut microbiota depletion in asthma patients. The analysis of beta diversity showed that the gut community compositions of asthma are widely dispersed in contrast to the tight clustering observed in the control group. Finally, the similarity index was found to be lower in the inter-group comparison than in the intra-group comparison, which confirmed changes in the gut microbial composition in the asthmatic group. The study revealed significant differences in the human gut microbiome composition between asthma patients and the healthy control group.

Analysing microbiome intervention design studies: Comparison of alternative multivariate statistical methods

The diet plays a major role in shaping gut microbiome composition and function in both humans and animals, and dietary intervention trials are often used to investigate and understand these effects. A plethora of statistical methods for analysing the differential abundance of microbial taxa exists, and new methods are constantly being developed, but there is a lack of benchmarking studies and clear consensus on the best multivariate statistical practices. This makes it hard for a biologist to decide which method to use. We compared the outcomes of generic multivariate ANOVA (ASCA and FFMANOVA) against statistical methods commonly used for community analyses (PERMANOVA and SIMPER) and methods designed for analysis of count data from high-throughput sequencing experiments (ALDEx2, ANCOM and DESeq2). The comparison is based on both simulated data and five published dietary intervention trials representing different subjects and study designs. We found that the methods testing differences at the community level were in agreement regarding both effect size and statistical significance. However, the methods that provided ranking and identification of differentially abundant operational taxonomic units (OTUs) gave incongruent results, implying that the choice of method is likely to influence the biological interpretations. The generic multivariate ANOVA tools have the flexibility needed for analysing multifactorial experiments and provide outputs at both the community and OTU levels; good performance in the simulation studies suggests that these statistical tools are also suitable for microbiome data sets.

Examining the Effects of an Anti-Salmonella Bacteriophage Preparation, BAFASAL®, on Ex-Vivo Human Gut Microbiome Composition and Function Using a Multi-Omics Approach.

Salmonella infections (salmonellosis) pose serious health risks to humans, usually via food-chain contamination. This foodborne pathogen causes major food losses and human illnesses, with significant economic impacts. Overuse of antibiotics in the food industry has led to multidrug-resistant strains of bacteria, and governments are now restricting their use, leading the food industry to search for alternatives to secure food chains. Bacteriophages, viruses that infect and kill bacteria, are currently being investigated and used as replacement treatments and prophylactics due to their specificity and efficacy. They are generally regarded as safe alternatives to antibiotics, as they are natural components of the ecosystem. However, when specifically used in the industry, they can also make their way into humans through our food chain or exposure, as is the case for antibiotics. In particular, agricultural workers could be repeatedly exposed to bacteriophages supplemented to animal feeds. To our knowledge, no studies have investigated the effects of such exposure to bacteriophages on the human gut microbiome. In this study, we used a novel in-vitro assay called RapidAIM to investigate the effect of a bacteriophage mixture, BAFASAL®, used in poultry farming on five individual human gut microbiomes. Multi-omics analyses, including 16S rRNA gene sequencing and metaproteomic, revealed that ex-vivo human gut microbiota composition and function were unaffected by BAFASAL® treatment, providing an additional measure for its safety. Due to the critical role of the gut microbiome in human health and the known role of bacteriophages in regulation of microbiome composition and function, we suggest assaying the impact of bacteriophage-cocktails on the human gut microbiome as a part of their safety assessment.