Tools for Analysis of the Microbiome

Microbiota profiling in esophageal diseases: Novel insights into molecular staining and clinical outcomes

Gut microbiota is recognized nowadays as one of the key players in the development of several gastro-intestinal diseases. The first studies focused mainly on healthy subjects with staining of main bacterial species via culture-based techniques. Subsequently, lots of studies tried to focus on principal esophageal disease enlarged the knowledge on esophageal microbial environment and its role in pathogenesis. Gastro Esophageal Reflux Disease (GERD), the most widespread esophageal condition, seems related to a certain degree of mucosal inflammation, via interleukin (IL) 8 potentially enhanced by bacterial components, lipopolysaccharide (LPS) above all. Gram- bacteria, producing LPS), such as Campylobacter genus, have been found associated with GERD. Barrett esophagus (BE) seems characterized by a Gram- and microaerophils-shaped microbiota. Esophageal cancer (EC) development leads to an overturn in the esophageal environment with the shift from an oral-like microbiome to a prevalently low-abundant and low-diverse Gram--shaped microbiome. Although underinvestigated, also changes in the esophageal microbiome are associated with rare chronic inflammatory or neuropathic disease pathogenesis. The paucity of knowledge about the microbiota-driven mechanisms in esophageal disease pathogenesis is mainly due to the scarce sensitivity of sequencing technology and culture methods applied so far to study commensals in the esophagus. However, the recent advances in molecular techniques, especially with the advent of non-culture-based genomic sequencing tools and the implementation of multi-omics approaches, have revolutionized the microbiome field, with promises of implementing the current knowledge, discovering more mechanisms underneath, and giving insights into the development of novel therapies aimed to re-establish the microbial equilibrium for ameliorating esophageal diseases..

Cabozantinib and nivolumab with or without live bacterial supplementation in metastatic renal cell carcinoma: a randomized phase 1 trial

Supplementation with CBM588, a bifidogenic live bacterial product, has been associated with improved clinical outcomes in persons with metastatic renal cell carcinoma (mRCC) receiving nivolumab and ipilimumab. However, its effect on those receiving tyrosine kinase inhibitor-based combinations is unknown. In this open-label, randomized, investigator-initiated, phase 1 study, 30 participants with locally advanced or mRCC with histological confirmation of clear cell, papillary or sarcomatoid component were randomized in a 2:1 fashion to receive cabozantinib (an inhibitor of vascular endothelial growth factor receptor, MET and AXL) and nivolumab (anti-programmed cell death protein 1) with or without CBM588 as first-line treatment. Metagenomic sequencing was performed on stool samples to characterize their gut microbiome at baseline and 13 weeks into treatment. The primary endpoint was a change in the relative abundance of Bifidobacterium spp.; secondary endpoints included objective response rate (ORR), progression-free survival (PFS) and toxicity profile. The primary endpoint of the study was not met and the addition of CBM588 to cabozantinib and nivolumab did not result in a difference in the relative abundance of Bifidobacterium spp. or alpha diversity (as measured by the Shannon index). However, ORR was significantly higher in participants treated with CBM588 compared to those in the control arm (14 of 19, 74% versus 2 of 10, 20%; P = 0.01). PFS at 6 months was 84% (16 of 19) and 60% (6 of 10) in the experimental and control arms, respectively. No significant difference in toxicity profile was seen between the study arms. Our results provide a preliminary signal of improved clinical activity with CBM588 in treatment-naive participants with mRCC receiving cabozantinib and nivolumab. Further investigation is needed to confirm these findings and better characterize the underlying mechanism driving this effect.ClinicalTrials.gov identifier: NCT05122546.

Insights into the seasonal changes in the taxonomic and functional diversity of bacteria in the eastern Arabian Sea: Shotgun metagenomics approach

The eastern Arabian Sea (EAS) is known for its unique oceanographic features such as the seasonal monsoonal winds, upwelling of nutrient-rich waters and a significant increase in primary productivity during the monsoon season. In this study, we utilised the shotgun metagenomics approach to determine the seasonal variations in bacterial taxonomic and functional profiles during the non-monsoon and monsoon seasons in the EAS. Significant seasonal variations in the bacterial community structure were observed at the phylum and genera levels. These findings also correspond with seasonal shifts in the functional profiles of the bacterial communities based on the variations of genes encoding enzymes associated with different metabolic pathways. Pronounced seasonal variation of bacterial taxa was evident with an increased abundance of Idiomarina, Marinobacter, Psychrobacter and Alteromonas of Proteobacteria, Bacillus and Staphylococcus of Firmicutes during the non-monsoon season. These taxa were linked to elevated nucleotide and amino acid biosynthesis, amino acid and lipid degradation. Conversely, during the monsoon, the taxa composition changed with Alteromonas, Candidatus Pelagibacter of Proteobacteria and Cyanobacteria Synechococcus; contributing largely to the amino acid and lipid biosynthesis, fermentation and inorganic nutrient metabolism which was evident from functional analysis. Regression analysis confirmed that increased seasonal primary productivity significantly influenced the abundance of genes associated with carbohydrate, protein and lipid metabolism. These highlight the pivotal role of seasonal changes in primary productivity in shaping the bacterial communities, their functional profiles and driving the biogeochemical cycling in the EAS.

Revealing the hierarchical structure of microbial communities

Measuring the dynamics of microbial communities results in high-dimensional measurements of taxa abundances over time and space, which is difficult to analyze due to complex changes in taxonomic compositions. This paper presents a new method to investigate and visualize the intrinsic hierarchical community structure implied by the measurements. The basic idea is to identify significant intersection sets, which can be seen as sub-communities making up the measured communities. Using the subset relationship, the intersection sets together with the measurements form a hierarchical structure visualized as a Hasse diagram. Chemical organization theory (COT) is used to relate the hierarchy of the sets of taxa to potential taxa interactions and to their potential dynamical persistence. The approach is demonstrated on a data set of community data obtained from bacterial 16S rRNA gene sequencing for samples collected monthly from four groundwater wells over a nearly 3-year period (n = 114) along a hillslope area. The significance of the hierarchies derived from the data is evaluated by showing that they significantly deviate from a random model. Furthermore, it is demonstrated how the hierarchy is related to temporal and spatial factors; and how the idea of a core microbiome can be extended to a set of interrelated core microbiomes. Together the results suggest that the approach can support developing models of taxa interactions in the future.

Bacterial diversity and composition on the rinds of specific melon cultivars and hybrids from across different growing regions in the United States

The goal of this study was to characterize the bacterial diversity on different melon varieties grown in different regions of the US, and determine the influence that region, rind netting, and variety of melon has on the composition of the melon microbiome. Assessing the bacterial diversity of the microbiome on the melon rind can identify antagonistic and protagonistic bacteria for foodborne pathogens and spoilage organisms to improve melon safety, prolong shelf-life, and/or improve overall plant health. Bacterial community composition of melons (n = 603) grown in seven locations over a four-year period were used for 16S rRNA gene amplicon sequencing and analysis to identify bacterial diversity and constituents. Statistically significant differences in alpha diversity based on the rind netting and growing region (p < 0.01) were found among the melon samples. Principal Coordinate Analysis based on the Bray-Curtis dissimilarity distance matrix found that the melon bacterial communities clustered more by region rather than melon variety (R2 value: 0.09 & R2 value: 0.02 respectively). Taxonomic profiling among the growing regions found Enterobacteriaceae, Bacillaceae, Microbacteriaceae, and Pseudomonadaceae present on the different melon rinds at an abundance of ≥ 0.1%, but no specific core microbiome was found for netted melons. However, a core of Pseudomonadaceae, Bacillaceae, and Exiguobacteraceae were found for non-netted melons. The results of this study indicate that bacterial diversity is driven more by the region that the melons were grown in compared to rind netting or melon type. Establishing the foundation for regional differences could improve melon safety, shelf-life, and quality as well as the consumers' health.

Faecal microbial transfer and complex carbohydrates mediate protection against COPD

OBJECTIVE

Chronic obstructive pulmonary disease (COPD) is a major cause of global illness and death, most commonly caused by cigarette smoke. The mechanisms of pathogenesis remain poorly understood, limiting the development of effective therapies. The gastrointestinal microbiome has been implicated in chronic lung diseases via the gut-lung axis, but its role is unclear.

DESIGN

Using an in vivo mouse model of cigarette smoke (CS)-induced COPD and faecal microbial transfer (FMT), we characterised the faecal microbiota using metagenomics, proteomics and metabolomics. Findings were correlated with airway and systemic inflammation, lung and gut histopathology and lung function. Complex carbohydrates were assessed in mice using a high resistant starch diet, and in 16 patients with COPD using a randomised, double-blind, placebo-controlled pilot study of inulin supplementation.

RESULTS

FMT alleviated hallmark features of COPD (inflammation, alveolar destruction, impaired lung function), gastrointestinal pathology and systemic immune changes. Protective effects were additive to smoking cessation, and transfer of CS-associated microbiota after antibiotic-induced microbiome depletion was sufficient to increase lung inflammation while suppressing colonic immunity in the absence of CS exposure. Disease features correlated with the relative abundance of Muribaculaceae, Desulfovibrionaceae and Lachnospiraceae family members. Proteomics and metabolomics identified downregulation of glucose and starch metabolism in CS-associated microbiota, and supplementation of mice or human patients with complex carbohydrates improved disease outcomes.

CONCLUSION

The gut microbiome contributes to COPD pathogenesis and can be targeted therapeutically.

Microbiome Dynamics: A Paradigm Shift in Combatting Infectious Diseases

Infectious diseases have long posed a significant threat to global health and require constant innovation in treatment approaches. However, recent groundbreaking research has shed light on a previously overlooked player in the pathogenesis of disease-the human microbiome. This review article addresses the intricate relationship between the microbiome and infectious diseases and unravels its role as a crucial mediator of host-pathogen interactions. We explore the remarkable potential of harnessing this dynamic ecosystem to develop innovative treatment strategies that could revolutionize the management of infectious diseases. By exploring the latest advances and emerging trends, this review aims to provide a new perspective on combating infectious diseases by targeting the microbiome.

Optimized bacterial community characterization through full-length 16S rRNA gene sequencing utilizing MinION nanopore technology

BACKGROUND

Accurate identification of bacterial communities is crucial for research applications, diagnostics, and clinical interventions. Although 16S ribosomal RNA (rRNA) gene sequencing is a widely employed technique for bacterial taxonomic classification, it often results in misclassified or unclassified bacterial taxa. This study sought to refine the full-length 16S rRNA gene sequencing protocol using the MinION sequencer, focusing on the V1-V9 regions. Our methodological enquiry examined several factors, including the number of PCR amplification cycles, choice of primers and Taq polymerase, and specific sequence databases and workflows employed. We used a microbial standard comprising eight bacterial strains (five gram-positive and three gram-negative) in known proportions as a validation control.

RESULTS

Based on the MinION protocol, we employed the microbial standard as the DNA template for the 16S rRNA gene amplicon sequencing procedure. Our analysis showed that an elevated number of PCR amplification cycles introduced PCR bias, and the selection of Taq polymerase and primer sets significantly affected the subsequent analysis. Bacterial identification at genus level demonstrated Pearson correlation coefficients ranging from 0.73 to 0.79 when assessed using BugSeq, Kraken-Silva and EPI2ME-16S workflows. Notably, the EPI2ME-16S workflow exhibited the highest Pearson correlation with the microbial standard, minimised misclassification, and increased alignment accuracy. At the species taxonomic level, the BugSeq workflow was superior, with a Pearson correlation coefficient of 0.92.

CONCLUSIONS

These findings emphasise the importance of careful selection of PCR settings and a well-structured analytical framework for 16S rRNA full-length gene sequencing. The results showed a robust correlation between the predicted and observed bacterial abundances at both the genus and species taxonomic levels, making these findings applicable across diverse research contexts and with clinical utility for reliable pathogen identification.

Associations of maternal prenatal psychological symptoms and saliva cortisol with neonatal meconium microbiota: A cross-sectional study

Alterations in the diversity and relative abundances of the gut microbiome have been associated with a broad spectrum of medical conditions. Maternal psychological symptoms during pregnancy may impact on offspring development by altering the maternal and the foetal gut microbiome. We aimed to investigate whether self-reported maternal anxiety, depressive symptoms, and distress as well as saliva cortisol levels in late pregnancy alter the bacterial composition of the infant's meconium.

METHODS

A total of N = 100 mother-infant pairs were included. Maternal psychological symptoms were measured using psychological questionnaires (EPDS, PSS-10, STAI) at 34-36 weeks gestation and salivary cortisol was measured at 34-36 and 38 weeks gestation. Infant meconium samples were collected in the first five days postpartum and analysed using 16S rRNA amplicon sequencing.

RESULTS

Correlations showed that lower alpha diversity of the meconium microbiome was significantly associated with increased maternal prenatal depressive symptoms in late gestation (τ = -0.15, p = .04). Increased saliva cortisol AUCg at T2 was significantly related to higher beta diversity of the meconium samples (Pr(>F) = 0.003*). Pseudomonas was the most abundant phylum and was associated with maternal saliva cortisol total decline. No other associations were found.

CONCLUSIONS

Maternal prenatal depressive symptoms are associated with infant faecal microbiome alpha diversity, whereas maternal saliva cortisol AUCg is linked to increased beta diversity and total decline related to increased Psuedomonas. Future studies are warranted to understand how these microbiota community alterations are linked to child health outcomes.

Plant Monoterpenes and Essential Oils as Potential Anti-Ageing Agents: Insights from Preclinical Data

Ageing is a natural process characterized by a time-dependent decline of physiological integrity that compromises functionality and inevitably leads to death. This decline is also quite relevant in major human pathologies, being a primary risk factor in neurodegenerative diseases, metabolic disorders, cardiovascular diseases and musculoskeletal disorders. Bearing this in mind, it is not surprising that research aiming at improving human health during this process has burst in the last decades. Importantly, major hallmarks of the ageing process and phenotype have been identified, this knowledge being quite relevant for future studies towards the identification of putative pharmaceutical targets, enabling the development of preventive/therapeutic strategies to improve health and longevity. In this context, aromatic plants have emerged as a source of potential bioactive volatile molecules, mainly monoterpenes, with many studies referring to their anti-ageing potential. Nevertheless, an integrated review on the current knowledge is lacking, with several research approaches studying isolated ageing hallmarks or referring to an overall anti-ageing effect, without depicting possible mechanisms of action. Herein, we aim to provide an updated systematization of the bioactive potential of volatile monoterpenes on recently proposed ageing hallmarks, and highlight the main mechanisms of action already identified, as well as possible chemical entity-activity relations. By gathering and categorizing the available scattered information, we also aim to identify important research gaps that could help pave the way for future research in the field.

Protecting the invisible: Establishing guideline values for copper toxicity to marine microbiomes

Understanding the rapid responses of marine microbiomes to environmental disturbances is paramount for supporting early assessments of harm to high-value ecosystems, such as coral reefs. Yet, management guidelines aimed at protecting aquatic life from environmental pollution remain exclusively defined for organisms at higher trophic levels. In this study, 16S rRNA gene amplicon sequencing was applied in conjunction with propidium monoazide for cell-viability assessment as a sensitive tool to determine taxon- and community-level changes in a seawater microbial community under copper (Cu) exposure. Bayesian model averaging was used to establish concentration-response relationships to evaluate the effects of copper on microbial composition, diversity, and richness for the purpose of estimating microbiome Hazard Concentration (mHCx) values. Predicted mHC5 values at which a 5 % change in microbial composition, diversity, and richness occurred were 1.05, 0.72, and 0.38 μg Cu L-1, respectively. Threshold indicator taxa analysis was applied across the copper concentrations to identify taxon-specific change points for decreasing taxa. These change points were then used to generate a Prokaryotic Sensitivity Distribution (PSD), from which mHCxdec values were derived for copper, suitable for the protection of 99, 95, 90, and 80 % of the marine microbiome. The mHC5dec guideline value of 0.61 μg Cu L-1, protective of 95 % of the marine microbial community, was lower than the equivalent Australian water quality guideline value based on eukaryotic organisms at higher trophic levels. This suggests that marine microbial communities might be more vulnerable, highlighting potential insufficiencies in their protection against copper pollution. The mHCx values proposed here provide approaches to quantitatively assess the effects of contaminants on microbial communities towards the inclusion of prokaryotes in future water quality guidelines.

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.

Role of gastrointestinal health in managing children with autism spectrum disorder

Children with autism spectrum disorders (ASD) or autism are more prone to gastrointestinal (GI) disorders than the general population. These disorders can significantly affect their health, learning, and development due to various factors such as genetics, environment, and behavior. The causes of GI disorders in children with ASD can include gut dysbiosis, immune dysfunction, food sensitivities, digestive enzyme deficiencies, and sensory processing differences. Many studies suggest that numerous children with ASD experience GI problems, and effective management is crucial. Diagnosing autism is typically done through genetic, neurological, functional, and behavioral assessments and observations, while GI tests are not consistently reliable. Some GI tests may increase the risk of developing ASD or exacerbating symptoms. Addressing GI issues in individuals with ASD can improve their overall well-being, leading to better behavior, cognitive function, and educational abilities. Proper management can improve digestion, nutrient absorption, and appetite by relieving physical discomfort and pain. Alleviating GI symptoms can improve sleep patterns, increase energy levels, and contribute to a general sense of well-being, ultimately leading to a better quality of life for the individual and improved family dynamics. The primary goal of GI interventions is to improve nutritional status, reduce symptom severity, promote a balanced mood, and increase patient independence.

The Influence of Protein Secretomes of Enterococcus durans on ex vivo Human Gut Microbiome

The gut microbiome plays a critical role to all animals and humans health. Methods based on ex vivo cultures are time and cost-effective solutions for rapid evaluation of probiotic effects on microbiomes. In this study, we assessed whether the protein secretome from the potential probiotic Enterococcus durans LAB18S grown on fructoligosaccharides (FOS) and galactoligosaccharides (GOS) had specific effects on ex vivo cultured intestinal microbiome obtained from a healthy individual. Metaproteomics was used to evaluate changes in microbial communities of the human intestinal microbiome. Hierarchical clustering analysis revealed 654 differentially abundant proteins from the metaproteome samples, showing that gut microbial protein expression varied on the presence of different E. durans secretomes. Increased amount of Bacteroidetes phylum was observed in treatments with secretomes from E. durans cultures on FOS, GOS and albumin, resulting in a decrease of the Firmicutes to Bacteroidetes (F/B) ratio. The most functionally abundant bacterial taxa were Roseburia, Bacteroides, Alistipes and Faecalibacterium. The results suggest that the secretome of E. durans may have favorable effects on the intestinal microbial composition, stimulating growth and different protein expression of beneficial bacteria. These findings suggest that proteins secreted by E. durans growing on FOS and GOS have different effects on the modulation of gut microbiota functional activities during cultivation.

Exploration of acupuncture therapy in the treatment of MCI patients with the ApoE ε4 gene based on the brain-gut axis theory

BACKGROUND

Mild cognitive impairment (MCI) is the predementia phase of Alzheimer's disease (AD). The intestinal microbiome is altered in MCI and AD, and apolipoprotein E (ApoE) ε4 gene polymorphism is a risk factor for the progression of MCI to AD. This study aims to investigate the improvement in cognitive function of MCI patients with and without ApoE ε4 due to acupuncture and the changes in gut microbiota community composition and abundance in MCI.

METHODS

This randomized assessor-blind controlled study will enrol MCI patients with and without the ApoE ε4 gene (n = 60/60). Sixty subjects with the ApoE ε4 gene and 60 subjects without the ApoE ε4 gene will be randomly allocated into treatment and control groups in a 1:1 ratio. Intestinal microbiome profiles will be evaluated by 16 S rRNA sequencing of faecal samples and compared between the groups.

RESULTS/CONCLUSIONS

Acupuncture is an effective method to improve cognitive function in MCI. This study will provide data on the relationship between the gut microbiota and the effectiveness of acupuncture in patients with MCI from a new angle. This study will also provide data on the relationship between the gut microbiota and an AD susceptibility gene by integrating microbiologic and molecular approaches.

TRIAL REGISTRATION

www.chictr.org.cn , ID: ChiCTR2100043017, recorded on 4 February 2021.

Contribution of the Oral and Gastrointestinal Microbiomes to Bloodstream Infections in Leukemia Patients

Bloodstream infections (BSIs) pose a significant mortality risk for acute myeloid leukemia (AML) patients. It has been previously reported that intestinal domination (>30% relative abundance [RA] attributed to a single taxon) with the infecting taxa often precedes BSI in stem cell transplant patients. Using 16S rRNA amplicon sequencing, we analyzed oral and stool samples from 63 AML patients with BSIs to determine the correlation between the infectious agent and microbiome composition. Whole-genome sequencing and antimicrobial susceptibilities were performed on all BSI isolates. Species-level detection of the infectious agent and presence of antibiotic resistance determinants in the stool (blaCTX-M-15, blaCTX-M-14, cfrA, and vanA) were confirmed via digital droplet PCR (ddPCR). Individuals with Escherichia coli (stool P < 0.001), Pseudomonas aeruginosa (oral P = 0.004, stool P < 0.001), and viridans group streptococci (VGS) (oral P = 0.001) bacteremia had a significantly higher relative abundance of those respective genera than other BSI patients, which appeared to be site specific. Although 78% of patients showed presence of the infectious genera in the stool and/or saliva, only 7 exhibited microbiome domination. ddPCR confirmed species specificity of the 16S data and detected the antibiotic resistance determinants found in the BSI isolates within concurrent stools. Although gastrointestinal (GI) domination by an infecting organism was not present at the time of most BSIs in AML, the pathogens, along with AMR elements, were detectable in the majority of patients. Thus, rapid genetic assessment of oral and stool samples for the presence of potential pathogens and AMR determinants might inform personalized therapeutic approaches in immunocompromised patients with suspected infection. IMPORTANCE A major cause of mortality in hematologic malignancy patients is BSI. Previous studies have demonstrated that bacterial translocation from the GI microbiome is a major source of BSIs and is often preceded by increased levels of the infectious taxa in the GI (>30% abundance by 16S rRNA sequencing). In this study, we sought to better understand how domination and abundance levels of the oral and gut microbiome relate to bacteremia occurrence in acute myeloid leukemia patients. We conclude that analyses of both oral and stool samples can help identify BSI and antimicrobial resistance determinants, thus potentially improving the timing and tailoring of antibiotic treatment strategies for high-risk patients.

Alterations of gut microbiome following gastrointestinal surgical procedures and their potential complications

Intestinal microorganisms play a crucial role in shaping the host immunity and maintaining homeostasis. Nevertheless, alterations in gut bacterial composition may occur and these alterations have been linked with the pathogenesis of several diseases. In surgical practice, studies revealed that the microbiome of patients undergoing surgery changes and several post-operative complications seem to be associated with the gut microbiota composition. In this review, we aim to provide an overview of gut microbiota (GM) in surgical disease. We refer to several studies which describe alterations of GM in patients undergoing different types of surgery, we focus on the impacts of peri-operative interventions on GM and the role of GM in development of post-operative complications, such as anastomotic leak. The review aims to enhance comprehension regarding the correlation between GM and surgical procedures based in the current knowledge. However, preoperative and postoperative synthesis of GM needs to be further examined in future studies, so that GM-targeted measures could be assessed and the different surgery complications could be reduced.

Infants' gut microbiome data: A Bayesian Marginal Zero-inflated Negative Binomial regression model for multivariate analyses of count data

The infants' gut microbiome is dynamic in nature. Literature has shown high inter-individual variability of gut microbial composition in the early years of infancy compared to adulthood. Although next-generation sequencing technologies are rapidly evolving, several statistical analysis aspects need to be addressed to capture the variability and dynamic nature of the infants' gut microbiome. In this study, we proposed a Bayesian Marginal Zero-inflated Negative Binomial (BAMZINB) model, addressing complexities associated with zero-inflation and multivariate structure of the infants' gut microbiome data. Here, we simulated 32 scenarios to compare the performance of BAMZINB with glmFit and BhGLM as the two other widely similar methods in the literature in handling zero-inflation, over-dispersion, and multivariate structure of the infants' gut microbiome. Then, we showed the performance of the BAMZINB approach on a real dataset using SKOT cohort (I and II) studies. Our simulation results showed that the BAMZINB model performed as well as those two methods in estimating the average abundance difference and had a better fit for almost all scenarios when the signal and sample size were large. Applying BAMZINB on SKOT cohorts showed remarkable changes in the average absolute abundance of specific bacteria from 9 to 18 months for infants of healthy and obese mothers. In conclusion, we recommend using the BAMZINB approach for infants' gut microbiome data taking zero-inflation and over-dispersion properties into account in multivariate analysis when comparing the average abundance difference.

The Contribution of the Human Oral Microbiome to Oral Disease: A Review

The oral microbiome is an emerging field that has been a topic of discussion since the development of next generation sequencing and the implementation of the human microbiome project. This article reviews the current literature surrounding the oral microbiome, briefly highlighting most recent methods of microbiome characterization including cutting edge omics, databases for the microbiome, and areas with current gaps in knowledge. This article also describes reports on microorganisms contained in the oral microbiome which include viruses, archaea, fungi, and bacteria, and provides an in-depth analysis of their significant roles in tissue homeostasis. Finally, we detail key bacteria involved in oral disease, including oral cancer, and the current research surrounding their role in stimulation of inflammatory cytokines, the role of gingival crevicular fluid in periodontal disease, the creation of a network of interactions between microorganisms, the influence of the planktonic microbiome and cospecies biofilms, and the implications of antibiotic resistance. This paper provides a comprehensive literature analysis while also identifying gaps in knowledge to enable future studies to be conducted.

In vitro human gut microbiota fermentation models: opportunities, challenges, and pitfalls

The human gut microbiota (HGM) plays a pivotal role in health and disease. Consequently, nutritional and medical research focusing on HGM modulation strategies as a means of improving host health is steadily increasing. In vitro HGM fermentation models offer a valid complement to human and animal studies when it comes to the mechanistic exploration of novel modulation approaches and their direct effects on HGM composition and activity, while excluding interfering host effects. However, in vitro cultivation of HGM can be challenging due to its high oxygen sensitivity and the difficulties of accurately modeling the physio-chemical complexity of the gut environment. Despite the increased use of in vitro HGM models, there is no consensus about appropriate model selection and operation, sometimes leading to major deficiencies in study design and result interpretation. In this review paper, we aim to analyze crucial aspects of the application, setup and operation, data validation and result interpretation of in vitro HGM models. When carefully designed and implemented, in vitro HGM modeling is a powerful strategy for isolating and investigating biotic and abiotic factors in the HGM, as well as evaluating their effects in a controlled environment akin to the gut. Furthermore, complementary approaches combining different in vitro and in vivo models can strengthen the design and interpretation of human studies.

Gut microbiota changes associated with Clostridioides difficile infection and its various treatment strategies

Human gut microbiota are critical to both the development of and recovery from Clostridioides difficile infection (CDI). Antibiotics are the mainstay of CDI treatment, yet inherently cause further imbalances in the gut microbiota, termed dysbiosis, complicating recovery. A variety of microbiota-based therapeutic approaches are in use or in development to limit disease- and treatment-associated dysbiosis and improve rates of sustained cure. These include the recently FDA-approved fecal microbiota, live-jslm (formerly RBX2660) and fecal microbiota spores, live-brpk (formerly SER-109), which represent a new class of live biotherapeutic products (LBPs), traditional fecal microbiota transplantation (FMT), and ultra-narrow-spectrum antibiotics. Here, we aim to review the microbiome changes associated with CDI as well as a variety of microbiota-based treatment approaches.

Gut microbiome in type 1 diabetes: the immunological perspective

INTRODUCTION

Type 1 diabetes (T1D) is a prevalent, and yet uncurable, autoimmune disease targeting insulin-producing pancreatic β-cells. Despite a known genetic component in T1D onset, genetics alone cannot explain the alarming worldwide rise in T1D incidence, which is attributed to a growing impact of environmental factors, including perturbations of the gut microbiome.

AREAS COVERED

Intestinal commensal bacteria plays a crucial role in host physiology in health and disease by regulating endocrine and immune functions. An aberrant gut microbiome structure and metabolic function have been documented prior and during T1D onset. In this review, we summarize and discuss the current studies depicting the taxonomic profile and role of the gut microbial communities in murine models of T1D, diabetic patients and human interventional trials.

EXPERT OPINION

Compelling evidence have shown that the intestinal microbiota is instrumental in driving differentiation and functions of immune cells. Therefore, any alterations in the intestinal microbiome composition or microbial metabolite production, particularly early in life, may impact disease susceptibility and amplify inflammatory responses and hence accelerate the course of T1D pathogenesis.

Effect of Husbandry Practices on the Fecal Microbiota of C57BL/6J Breeding Colonies Housed in 2 Different Barrier Facilities in the Same Institution

Evidence showing a relationship between the mouse gut microbiome and properties such as phenotype and reaction to therapeutic agents and other treatments has increased significantly over the past 20 to 30 y. Recent concerns regarding the reproducibility of animal experiments have underscored the importance of understanding this relationship and how differences in husbandry practices can affect the gut microbiome. The current study focuses on effects of different barrier practices in 2 barrier facilities at the same institution on the fecal microbiome of breeding C57Bl/6J mice. Ten female and 10 male C57Bl/6J mice were obtained in one shipment from Jackson Laboratories and were housed under different barrier conditions upon arrival. Fecal samples were collected on arrival and periodically thereafter and were sent to TransnetYX for microbiome analysis. Mice used for collection of feces were housed as breeding pairs, with a total of 5 breeding pairs per barrier. An additional fecal sample was collected from these mice at 8 wk after arrival. One F1 female and one F1 male from each breeding cage were housed as brother-sister breeding pairs and a fecal sample was collected from them at 8 wk of age. Brother-sister breeding colonies were continued through F3, with fecal samples for microbiome analysis were collected from each generation at 8 wk of age. Breeding colonies in the 2 barriers showed differences in relative abundance, α -diversity, and β -diversity. Our data indicate that differences in barrier husbandry practices, including the use of autoclaved cages, the degree of restricted access, feed treatment practices, and water provision practices, can affect fecal microbiome divergence in both the parental and filial generations of different breeding colonies. To our knowledge, this is the first study to examine the effect of barrier husbandry practices on the microbiome of breeding colonies through the F3 generation.

Gut microbiota diversity in human strongyloidiasis differs little in two different regions in endemic areas of Thailand

Human gastrointestinal helminthic infections have a direct and/or indirect effect on the composition of the host gut microbial flora. Here, we investigated the effect of infection with a soil-transmitted intestinal nematode, Strongyloides stercoralis, on the gut microbiota of the human host. We also investigated whether composition of the microbiota in infected persons might vary across endemic regions. Fecal samples were obtained from volunteers from two areas endemic for strongyloidiasis, Khon Kaen Province in northeastern Thailand and Nakhon Si Thammarat Province in southern Thailand. Samples from Khon Kaen were from infected (SsNE) and uninfected (NegNE) individuals. Similarly, samples from the latter province were from infected (SsST) and uninfected (NegST) individuals. DNA sequences of the V3-V4 regions of the bacterial 16S rRNA gene were obtained from the fecal samples. No statistical difference in alpha diversity between groups in terms of richness or diversity were found. Statistical difference in beta diversity was observed only between NegNE and NegST. Some significant differences in species abundance were noted between geographical isolates. The SsNE group had a higher abundance of Tetragenococcus holophilus than did the SsST group, whereas Bradyrhizobium sp. was less abundant in the SsNE than the SsST group. For the uninfected groups, the NegNE had a higher abundance of T. holophilus than the NegST group. Our data showed that S. stercoralis infection leads to only minor alterations in the relative abundance of individual bacterial species in the human gut: no detectable effect was observed on community structure and diversity.

Approaching the Gut and Nasal Microbiota in Parkinson's Disease in the Era of the Seed Amplification Assays

Parkinson's disease (PD) is a neurodegenerative disorder often associated with pre-motor symptoms involving both gastrointestinal and olfactory tissues. PD patients frequently suffer from hyposmia, hyposalivation, dysphagia and gastrointestinal dysfunctions. During the last few years it has been speculated that microbial agents could play a crucial role in PD. In particular, alterations of the microbiota composition (dysbiosis) might contribute to the formation of misfolded α-synuclein, which is believed to be the leading cause of PD. However, while several findings confirmed that there might be an important link between intestinal microbiota alterations and PD onset, little is known about the potential contribution of the nasal microbiota. Here, we describe the latest findings on this topic by considering that more than 80% of patients with PD develop remarkable olfactory deficits in their prodromal disease stage. Therefore, the nasal microbiota might contribute to PD, eventually boosting the gut microbiota in promoting disease onset. Finally, we present the applications of the seed amplification assays to the study of the gut and olfactory mucosa of PD patients, and how they could be exploited to investigate whether pathogenic bacteria present in the gut and the nose might promote α-synuclein misfolding and aggregation.

Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review

The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful methods for PMI estimation. In the last two decades, innovations in sequencing technologies have made it possible to generate large volumes of data, allowing all members of a bacterial community to be sequenced. The aim of this manuscript is to provide a review regarding new advances in PMI estimation through cadaveric microbiota identification using 16S rRNA sequencing, in order to correlate specific microbiome profiles obtained from different body sites to PMI. The systematic review was performed according to PRISMA guidelines. For this purpose, 800 studies were identified through database searching (Pubmed). Articles that dealt with PMI estimation in correlation with microbiome composition and contained data about species, body site of sampling, monitoring time and sequencing method were selected and ultimately a total of 25 studies were considered. The selected studies evaluated the contribution of the various body sites to determine PMI, based on microbiome sequencing, in human and animal models. The results of this systematic review highlighted that studies conducted on both animals and humans yielded results that were promising. In order to fully exploit the potential of the microbiome in the estimation of PMI, it would be desirable to identify standardized body sampling sites and specific sampling methods in order to align data obtained by different research groups.

The effects of fermented vegetable consumption on the composition of the intestinal microbiota and levels of inflammatory markers in women: A pilot and feasibility study

The primary objective of this pilot study was to investigate the feasibility of regular consumption of fermented vegetables for six weeks on markers of inflammation and the composition of the gut microflora in women (clinical trials ID: NTC03407794). Thirty-one women were randomized into one of three groups: 100 g/day of fermented vegetables (group A), 100 g/day pickled vegetables (group B), or no vegetables (group C) for six weeks. Dietary intake was assessed by a food frequency questionnaire and blood and stool samples were provided before and after the intervention for measurement of C-reactive protein (CRP), tumor necrosis factor alpha (TNF-α), and lipopolysaccharide binding protein (LBP). Next-generation sequencing of the V4 region of the 16S rRNA gene was performed on the Illumina MiSeq platform. Participants' ages ranged between 18 and 69 years. Both groups A and B had a mean daily consumption of 91g of vegetables for 32 and 36 days, respectively. Serum CRP ranged between 0.9 and 265 ng/mL (SD = 92.4) at baseline, while TNF-α and LBP concentrations ranged between 0 and 9 pg/mL (SD = 2.3), and 7 and 29 μg/mL (SD = 4.4), respectively. There were no significant changes in levels of inflammatory markers among groups. At timepoint 2, group A showed an increase in Faecalibacterium prausnitzii (P = 0.022), a decrease in Ruminococcus torques (P<0.05), and a trend towards greater alpha diversity measured by the Shannon index (P = 0.074). The findings indicate that consumption of ~100 g/day of fermented vegetables for six weeks is feasible and may result in beneficial changes in the composition of the gut microbiota. Future trials should determine whether consumption of fermented vegetables is an effective strategy against gut dysbiosis.

Characterization of a novel thermophilic metagenomic GH5 endoglucanase heterologously expressed in Escherichia coli and Saccharomyces cerevisiae

Background

Endoglucanases from thermophilic microorganisms are a valuable resource as they can be used in a wide variety of biotechnological applications including the valorisation of biomass and the production of biofuels. In the present work we analysed the metagenome from the hot spring Muiño da Veiga, located in the northwest of Spain (in the Galicia region), in search for novel thermostable endoglucanases.

Results

Sequence analysis of the metagenome revealed a promising enzyme (Cel776). Predictions on protein structure and conserved amino acid sequences were conducted, as well as expression in heterologous systems with Escherichia coli and Saccharomyces cerevisiae as the host. Cel776Ec was correctly expressed and purified by taking advantage of the His-Tag system, with a yield of 0.346 U/mL in the eluted fraction. Cel776Sc was expressed extracellulary and was easily recovered from the supernatant without the need of further purification, requiring only a concentration step by ultrafiltration, with a significantly higher yield of 531.95 U/mL, revealing a much more suitable system for production of large amounts of the enzyme. Their biochemical characterization revealed biotechnologically interesting enzymes. Both Cel776Ec and Cel776Sc had an optimal temperature of 80 °C and optimal pH of 5. Cel776Ec exhibited high thermostability maintaining its activity for 24 h at 60 °C and maintained its activity longer than Cel776Sc at increasing incubation temperatures. Moreover, its substrate specificity allowed the degradation of both cellulose and xylan. Whereas Cel776Ec was more active in the presence of calcium and magnesium, manganese was found to increase Cel776Sc activity. A stronger inhibitory effect was found for Cel776Ec than Cel776Sc adding detergent SDS to the reaction mix, whereas EDTA only significantly affected Cel776Sc activity.

Conclusions

Our study reports the discovery of a new promising biocatalyst for its application in processes, such as the production of biofuel and the saccharification of plant biomass, due to its bifunctional enzymatic activity as an endoglucanase and as a xylanase, as well as highlights the advantages of a yeast expression system over bacteria.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02172-4.

Differences in composition of interdigital skin microbiota predict sheep and feet that develop footrot

Footrot has a major impact on health and productivity of sheep worldwide. The current paradigm for footrot pathogenesis is that physical damage to the interdigital skin (IDS) facilitates invasion of the essential pathogen Dichelobacter nodosus. The composition of the IDS microbiota is different in healthy and diseased feet, so an alternative hypothesis is that changes in the IDS microbiota facilitate footrot. We investigated the composition and diversity of the IDS microbiota of ten sheep, five that did develop footrot and five that did not (healthy) at weekly intervals for 20 weeks. The IDS microbiota was less diverse on sheep 2 + weeks before they developed footrot than on healthy sheep. This change could be explained by only seven of > 2000 bacterial taxa detected. The incubation period of footrot is 8–10 days, and there was a further reduction in microbial diversity on feet that developed footrot in that incubation period. We conclude that there are two stages of dysbiosis in footrot: the first predisposes sheep to footrot and the second occurs in feet during the incubation of footrot. These findings represent a step change in our understanding of the role of the IDS microbiota in footrot pathogenesis.

Machine Learning Advances in Microbiology: A Review of Methods and Applications

Microorganisms play an important role in natural material and elemental cycles. Many common and general biology research techniques rely on microorganisms. Machine learning has been gradually integrated with multiple fields of study. Machine learning, including deep learning, aims to use mathematical insights to optimize variational functions to aid microbiology using various types of available data to help humans organize and apply collective knowledge of various research objects in a systematic and scaled manner. Classification and prediction have become the main achievements in the development of microbial community research in the direction of computational biology. This review summarizes the application and development of machine learning and deep learning in the field of microbiology and shows and compares the advantages and disadvantages of different algorithm tools in four fields: microbiome and taxonomy, microbial ecology, pathogen and epidemiology, and drug discovery.

The Role of Gut Dysbiosis in Malnutrition Mechanism in CKD-5 HD Patients

Patients with terminal stage chronic kidney disease who have undergone hemodialysis (PGK-5 HD) have a high risk of developing malnutrition, which is characterized by wasting protein-energy and micronutrient deficiencies. Studies show a high prevalence of malnutrition in CKD-5 HD patients. The pathogenic mechanisms of malnutrition in CKD-5 HD are complex and involve the interaction of several pathophysiological changes including decreased appetite and nutrient intake, hormonal disturbances, metabolic imbalances, inflammation, increased catabolism, and abnormalities associated with dialysis action. A clear understanding of the pathophysiological mechanisms involved in the development of malnutrition in CKD-5 HD is required to develop strategies and interventions that are appropriate, effective, and reduce negative clinical outcomes. This article is a review of the pathophysiological mechanisms of malnutrition in CKD-5 HD patients caused by chronic inflammation due to intestinal dysbiosis.

EasyMap - An Interactive Web Tool for Evaluating and Comparing Associations of Clinical Variables and Microbiome Composition

One of the most common tasks in microbiome studies is comparing microbial profiles across various groups of people (e.g., sick vs. healthy). Routinely, researchers use multivariate linear regression models to address these challenges, such as linear regression packages, MaAsLin2, LEfSe, etc. In many cases, it is unclear which metadata variables should be included in the linear model, as many human-associated variables are correlated with one another. Thus, multiple models are often tested, each including a different set of variables, however the challenge of selecting the metadata variables in the final model remains. Here, we present EasyMap, an interactive online tool allowing for (1) running multiple multivariate linear regression models, on the same features and metadata; (2) visualizing the associations between microbial features and clinical metadata found in each model; and (3) comparing across the various models to identify the critical metadata variables and select the optimal model. EasyMap provides a side-by-side visualization of association results across the various models, each with additional metadata variables, enabling us to evaluate the impact of each metadata variable on the associated feature. EasyMap’s interface enables filtering associations by significance, focusing on specific microbes and finding the robust associations that are found across multiple models. While EasyMap was designed to analyze microbiome data, it can handle any other tabular data with numeric features and metadata variables. EasyMap takes the common task of multivariate linear regression to the next level, with an intuitive and simple user interface, allowing for wide comparisons of multiple models to identify the robust microbial feature associations. EasyMap is available at http://yassour.rcs.huji.ac.il/easymap.

Quantifying and Cataloguing Unknown Sequences within Human Microbiomes

Advances in genome sequencing technologies and lower costs have enabled the exploration of a multitude of known and novel environments and microbiomes. This has led to an exponential growth in the raw sequence data that are deposited in online repositories. Metagenomic and metatranscriptomic data sets are typically analysed with regard to a specific biological question. However, it is widely acknowledged that these data sets are comprised of a proportion of sequences that bear no similarity to any currently known biological sequence, and this so-called "dark matter" is often excluded from downstream analyses. In this study, a systematic framework was developed to assemble, identify, and measure the proportion of unknown sequences present in distinct human microbiomes. This framework was applied to 40 distinct studies, comprising 963 samples, and covering 10 different human microbiomes including fecal, oral, lung, skin, and circulatory system microbiomes. We found that while the human microbiome is one of the most extensively studied, on average 2% of assembled sequences have not yet been taxonomically defined. However, this proportion varied extensively among different microbiomes and was as high as 25% for skin and oral microbiomes that have more interactions with the environment. A rate of taxonomic characterization of 1.64% of unknown sequences being characterized per month was calculated from these taxonomically unknown sequences discovered in this study. A cross-study comparison led to the identification of similar unknown sequences in different samples and/or microbiomes. Both our computational framework and the novel unknown sequences produced are publicly available for future cross-referencing. Our approach led to the discovery of several novel viral genomes that bear no similarity to sequences in the public databases. Some of these are widespread as they have been found in different microbiomes and studies. Hence, our study illustrates how the systematic characterization of unknown sequences can help the discovery of novel microbes, and we call on the research community to systematically collate and share the unknown sequences from metagenomic studies to increase the rate at which the unknown sequence space can be classified.

The Intestinal Microbiota May Be a Potential Theranostic Tool for Personalized Medicine

The human intestine is colonized by a huge number of microorganisms from the moment of birth. This set of microorganisms found throughout the human body, is called the microbiota; the microbiome indicates the totality of genes that the microbiota can express, i.e., its genetic heritage. Thus, microbiota participates in and influences the proper functioning of the organism. The microbiota is unique for each person; it differs in the types of microorganisms it contains, the number of each microorganism, and the ratio between them, but mainly it changes over time and under the influence of many factors. Therefore, the correct functioning of the human body depends not only on the expression of its genes but also on the expression of the genes of the microorganisms it coexists with. This fact makes clear the enormous interest of community science in studying the relationship of the human microbiota with human health and the incidence of disease. The microbiota is like a unique personalized “mold” for each person; it differs quantitatively and qualitatively for the microorganisms it contains together with the relationship between them, and it changes over time and under the influence of many factors. We are attempting to modulate the microbial components in the human intestinal microbiota over time to provide positive feedback on the health of the host, from intestinal diseases to cancer. These interventions to modulate the intestinal microbiota as well as to identify the relative microbiome (genetic analysis) can range from dietary (with adjuvant prebiotics or probiotics) to fecal transplantation. This article researches the recent advances in these strategies by exploring their advantages and limitations. Furthermore, we aim to understand the relationship between intestinal dysbiosis and pathologies, through the research of resident microbiota, that would allow the personalization of the therapeutic antibiotic strategy.

Translational multi-omics microbiome research for strategies to improve cattle production and health

Cattle microbiome plays a vital role in cattle growth and performance and affects many economically important traits such as feed efficiency, milk/meat yield and quality, methane emission, immunity and health. To date, most cattle microbiome research has focused on metataxonomic and metagenomic characterization to reveal who are there and what they may do, preventing the determination of the active functional dynamics in vivo and their causal relationships with the traits. Therefore, there is an urgent need to combine other advanced omics approaches to improve microbiome analysis to determine their mode of actions and host-microbiome interactions in vivo. This review will critically discuss the current multi-omics microbiome research in beef and dairy cattle, aiming to provide insights on how the information generated can be applied to future strategies to improve production efficiency, health and welfare, and environment-friendliness in cattle production through microbiome manipulations.

Applications and Comparison of Dimensionality Reduction Methods for Microbiome Data

Dimensionality reduction techniques are a key component of most microbiome studies, providing both the ability to tractably visualize complex microbiome datasets and the starting point for additional, more formal, statistical analyses. In this review, we discuss the motivation for applying dimensionality reduction techniques, the special characteristics of microbiome data such as sparsity and compositionality that make this difficult, the different categories of strategies that are available for dimensionality reduction, and examples from the literature of how they have been successfully applied (together with pitfalls to avoid). We conclude by describing the need for further development in the field, in particular combining the power of phylogenetic analysis with the ability to handle sparsity, compositionality, and non-normality, as well as discussing current techniques that should be applied more widely in future analyses.

A review on the application of bioinformatics tools in food microbiome studies

There is currently a transformed interest toward understanding the impact of fermentation on functional food development due to growing consumer interest on modified health benefits of sustainable foods. In this review, we attempt to summarize recent findings regarding the impact of Next-generation sequencing and other bioinformatics methods in the food microbiome and use prediction software to understand the critical role of microbes in producing fermented foods. Traditionally, fermentation methods and starter culture development were considered conventional methods needing optimization to eliminate errors in technique and were influenced by technical knowledge of fermentation. Recent advances in high-output omics innovations permit the implementation of additional logical tactics for developing fermentation methods. Further, the review describes the multiple functions of the predictions based on docking studies and the correlation of genomic and metabolomic analysis to develop trends to understand the potential food microbiome interactions and associated products to become a part of a healthy diet.

Analysis methods for the gut microbiome in neuropsychiatric and neurodegenerative disorders

For a long time, the central nervous system was believed to be the only regulator of cognitive functions. However, accumulating evidence suggests that the composition of the microbiome is strongly associated with brain functions and diseases. Indeed, the gut microbiome is involved in neuropsychiatric diseases (e.g., depression, autism spectrum disorder, and anxiety) and neurodegenerative diseases (e.g., Parkinson’s disease and Alzheimer’s disease). In this review, we provide an overview of the link between the gut microbiome and neuropsychiatric or neurodegenerative disorders. We also introduce analytical methods used to assess the connection between the gut microbiome and the brain. The limitations of the methods used at present are also discussed. The accurate translation of the microbiome information to brain disorder could promote better understanding of neuronal diseases and aid in finding alternative and novel therapies.

Pilot Study on Poultry Meat from Antibiotic Free and Conventional Farms: Can Metagenomics Detect Any Difference?

Antibiotic free farms are increasing in the poultry sector in order to address new EU regulations and consumer concerns. In this pilot study, we investigated whether the efforts of raising chickens without the use antibiotics make any difference in the microbiome of poultry meat eaten by consumers. To this aim we compared the microbiomes characterizing caeca and the corresponding carcasses of two groups of chickens reared, one reared on a conventional farm and one on an antibiotic-free intensive farm. The results showed a clear separation between the taxonomic, functional and antibiotic resistant genes in the caeca of the birds reared on the conventional and antibiotic free farm. However, that separation was completely lost on carcasses belonging to the two groups. The antibiotic-free production resulted in statistically significant lower antimicrobial resistance load in the caeca in comparison to the conventional production. Moreover, the antimicrobial resistance load on carcasses was much higher than in the caeca, without any significant difference between carcasses coming from the two types of farms. All in all, the results of this research highlighted the need to reduce sources of microbial contamination and antimicrobial resistance not only at the farm level but also at the post-harvest one.

Exploring the Microbiome Analysis and Visualization Landscape

Research on the microbiome has boomed recently, which resulted in a wide range of tools, packages, and algorithms to analyze microbiome data. Here we investigate and map currently existing tools that can be used to perform visual analysis on the microbiome, and associate the including methods, visual representations and data features to the research objectives currently of interest in microbiome research. The analysis is based on a combination of a literature review and workshops including a group of domain experts. Both the reviewing process and workshops are based on domain characterization methods to facilitate communication and collaboration between researchers from different disciplines. We identify several research questions related to microbiomes, and describe how different analysis methods and visualizations help in tackling them.

Microbiome Forensic Biobanking: A Step toward Microbial Profiling for Forensic Human Identification

In recent years many studies have highlighted the great potential of microbial analysis in human identification for forensic purposes, with important differences in microbial community composition and function across different people and locations, showing a certain degree of uncertainty. Therefore, further studies are necessary to enable forensic scientists to evaluate the risk of microbial transfer and recovery from various items and to further critically evaluate the suitability of current human DNA recovery protocols for human microbial profiling for identification purposes. While the establishment and development of microbiome research biobanks for clinical applications is already very structured, the development of studies on the applicability of microbiome biobanks for forensic purposes is still in its infancy. The creation of large population microbiome biobanks, specifically dedicated to forensic human identification, could be worthwhile. This could also be useful to increase the practical applications of forensic microbiology for identification purposes, given that this type of evidence is currently absent from most real casework investigations and judicial proceedings in courts.

Analysis of the gut microbiome in dogs and cats

The gut microbiome is an important immune and metabolic organ. Intestinal bacteria produce various metabolites that influence the health of the intestine and other organ systems, including kidney, brain, and heart. Changes in the microbiome in diseased states are termed dysbiosis. The concept of dysbiosis is constantly evolving and includes changes in microbiome diversity and/or structure and functional changes (eg, altered production of bacterial metabolites). Molecular tools are now the standard for microbiome analysis. Sequencing of microbial genes provides information about the bacteria present and their functional potential but lacks standardization and analytical validation of methods and consistency in the reporting of results. This makes it difficult to compare results across studies or for individual clinical patients. The Dysbiosis Index (DI) is a validated quantitative PCR assay for canine fecal samples that measures the abundance of seven important bacterial taxa and summarizes the results as one single number. Reference intervals are established for dogs, and the DI can be used to assess the microbiome in clinical patients over time and in response to therapy (eg, fecal microbiota transplantation). In situ hybridization or immunohistochemistry allows the identification of mucosa‐adherent and intracellular bacteria in animals with intestinal disease, especially granulomatous colitis. Future directions include the measurement of bacterial metabolites in feces or serum as markers for the appropriate function of the microbiome. This article summarizes different approaches to the analysis of gut microbiota and how they might be applicable to research studies and clinical practice in dogs and cats.

Microbial dynamics in biogas digesters treating lipid-rich substrates via genome-centric metagenomics

Co-digestion with lipid-rich substrates is a likely strategy in biogas plants, due to their high energy content. However, the process stability is vulnerable to inhibition due to the sudden increase of fatty-acid concentration. Therefore, techniques that promote the adaptation of the microorganisms to the presence of lipids have been proposed. In this frame, the initial hypothesis of the work was that a gradual change in feedstock composition would enable us to elucidate the microbial organisation as a result of deterministic (i.e. chemical composition of influent) and stochastic (e.g. interspecies interactions) factors. This study investigates the response of the biogas microbiome to gradual increment of the Organic Loading Rate by supplementing the influent feedstock with Na-Oleate. The results showed that as a response to the feedstock shifts three clusters describing microbes behaviours were formed. The dynamics and the functional role of the formed microbial clusters were unveiled, providing explanations for their abundance and behavior. Process monitoring indicated that the reactors responded immediately to lipid supplementation and they managed to stabilize their performance in a short period of time. The dominance of Candidatus Methanoculleus thermohydrogenotrophicum in the biogas reactors fed exclusively with cattle manure indicated that the predominant methanogenic pathway was hydrogenotrophic. Additionally, the abundance of this methanogen was further enhanced upon lipid supplementation and its growth was supported by syntrophic bacteria capable to metabolize fatty acids. However, with the shift back to the original feedstock (i.e. solely cattle manure), the microbial dynamicity significantly altered with a remarkable increment in the abundance of a propionate degrader affiliated to the order of Bacteroidales, which became the predominant microorganism of the consortium.

An infectious diseases perspective on the microbiome and allogeneic stem cell transplant

PURPOSE OF REVIEW

The gut microbiome presents a novel source of diagnostic and therapeutic potential to modify post allogeneic stem cell transplant complications. There is an explosion of interest in microbiome research, mostly in the form of single-centre prospective time-series cohorts utilizing a variety of sampling frequencies and metagenomic technologies to sequence the microbiome. The purpose of this review is to summarize important recent publications and contextualize them within what has already been described in this rapidly growing field.

RECENT FINDING

Results from observational human cohort and animal transplant models add to the growing body of evidence that the microbiome modulates the immunopathogenesis of posttransplant complications. This is particularly the case for recipients of grafts replete with T cells where the evidence that acute graft-versus-host disease is mediated by anaerobic commensal-associated short-chain fatty acids, which interact with mucosa-associated (CD4FOXP3) T-regulatory cells.

SUMMARY

Future human research into the role of the microbiome in allogeneic stem transplant should incorporate rigorous and considered experimental design in addition to next-generation sequencing technology to better portray microbiome functional potential and active gene expression. In combination with host immune phenotyping, which would facilitate a robust understanding of the host--microbiome interaction that is required before meaningful translation into clinical diagnostics and therapeutics can be expected.

Metagenomics Approaches to Investigate the Gut Microbiome of COVID-19 Patients

Over the last decade, it has become increasingly apparent that the microbiome is a central component in human well-being and illness. However, to establish innovative therapeutic methods, it is crucial to learn more about the microbiota. Thereby, the area of metagenomics and associated bioinformatics methods and tools has become considerable in the study of the human microbiome biodiversity. The application of these metagenomics approaches to studying the gut microbiome in COVID-19 patients could be one of the promising areas of research in the fight against the SARS-CoV-2 infection and disparity. Therefore, understanding how the gut microbiome is affected by or could affect the SARS-CoV-2 is very important. Herein, we present an overview of approaches and methods used in the current published studies on COVID-19 patients and the gut microbiome. The accuracy of these researches depends on the appropriate choice and the optimal use of the metagenomics bioinformatics platforms and tools. Interestingly, most studies reported that COVID-19 patients' microbiota are enriched with opportunistic microorganisms. The choice and use of appropriate computational tools and techniques to accurately investigate the gut microbiota is therefore critical in determining the appropriate microbiome profile for diagnosis and the most reliable antiviral or preventive microbial composition.

Impact of Altered Gut Microbiota and Its Metabolites in Cystic Fibrosis

Cystic fibrosis (CF) is the most common lethal, multisystemic genetic disorder in Caucasians. Mutations in the gene encoding the cystic fibrosis transmembrane regulator (CFTR) protein are responsible for impairment of epithelial anionic transport, leading to impaired fluid regulation and pH imbalance across multiple organs. Gastrointestinal (GI) manifestations in CF may begin in utero and continue throughout the life, resulting in a chronic state of an altered intestinal milieu. Inherent dysfunction of CFTR leads to dysbiosis of the gut. This state of dysbiosis is further perpetuated by acquired factors such as use of antibiotics for recurrent pulmonary exacerbations. Since the gastrointestinal microbiome and their metabolites play a vital role in nutrition, metabolic, inflammatory, and immune functions, the gut dysbiosis will in turn impact various manifestations of CF-both GI and extra-GI. This review focuses on the consequences of gut dysbiosis and its metabolic implications on CF disease and possible ways to restore homeostasis.

A comprehensive review for gut microbes: technologies, interventions, metabolites and diseases

Gut microbes have attracted much more attentions in the recent decade since their essential roles in the development of metabolic diseases, cancer and neurological diseases. Considerable evidence indicates that the metabolism of gut microbes exert influences on intestinal homeostasis and human diseases. Here, we first reviewed two mainstream sequencing technologies involving 16s rRNA sequencing and metagenomic sequencing for gut microbes, and data analysis methods assessing alpha and beta diversity. Next, we introduced some observational studies reflecting that many factors, such as lifestyle and intake of diets, drugs, contribute to gut microbes' quantity and diversity. Then, metabolites produced by gut microbes were presented to understand that gut microbes exert on host homeostasis in the intestinal epithelium and immune system. Finally, we focused on the molecular mechanism of gut microbes on the occurrence and development of several common diseases. In-depth knowledge of the relationship among interventions, gut microbes and diseases might provide new insights in to disease prevention and treatment.

The complex microbiome in aquaponics: significance of the bacterial ecosystem

Purpose

Aquaponics is a technology that has minimal impact on the environment and which is often promoted as a solution for sustainable food production. Developing aquaponics sustainably requires a thorough understanding of the biological components of the system. Recent reports on the bacterial populations of aquaponics systems using new DNA sequencing technologies are revealing a complex and diverse microbial ecosystem. The purpose of this review is to present information on microbial composition and various factors affecting bacterial activity in aquaponics systems. Approaches for establishing a bacterial ecosystem during the setup of an aquaponics system, and microbiological safety of aquaponics products are also highlighted.

Methods

This review was developed by evaluating and synthesising current literature of peer-reviewed publications related to aquaponics and microbial communities. Based on the results from credible academic journals, publications were categorised into five groups: methods used to characterise microbiomes, biofiltration microorganisms, bacterial diversity, biofilter establishment, and safety of aquaponics products.

Results

The microbial ecosystem is essential for biological filtration of water through the mineralisation of nutrients required for plant growth in an integrated system. The aquaponics microbiome is complex, and bacterial composition varies between the different compartments of these systems. Establishing these bacterial ecosystems is essential for optimal functioning of aquaponics. At the phylum level, Proteobacteria and Bacteroidetes are dominant in aquaponics systems. Despite bacteria being fundamental to aquaponics, there are currently no reports of human pathogens in aquaponics products.

Conclusion

Knowledge of the composition of bacterial populations in aquaponics systems will enhance understanding of relationships and functions within the microbiome. This in turn will allow for the establishment of sustainable and healthy aquaponics systems for food production.