Microbiota Analysis Using an Illumina MiSeq Platform to Sequence 16S rRNA Genes

Metformin reprograms tryptophan metabolism via gut microbiome-derived bile acid metabolites to ameliorate depression-Like behaviors in mice

As an adjunct therapy, metformin enhances the efficacy of conventional antidepressant medications. However, its mode of action remains unclear. Here, metformin was found to ameliorate depression-like behaviors in mice exposed to chronic restraint stress (CRS) by normalizing the dysbiotic gut microbiome. Fecal transplants from metformin-treated mice ameliorated depressive behaviors in stressed mice. Microbiome profiling revealed that Akkermansia muciniphila (A. muciniphila), in particular, was markedly increased in the gut by metformin and that oral administration of this species alone was sufficient to reverse CRS-induced depressive behaviors and normalize aberrant stress-induced 5-hydroxytryptamine (5-HT) metabolism in the brain and gut. Untargeted metabolomic profiling further identified the bile acid metabolites taurocholate and deoxycholic acid as direct A. muciniphila-derived molecules that are, individually, sufficient to rescue the CRS-induced impaired 5-HT metabolism and depression-like behaviors. Thus, we report metformin reprograms 5-HT metabolism via microbiome-brain interactions to mitigate depressive syndromes, providing novel insights into gut microbiota-derived bile acids as potential therapeutic candidates for depressive mood disorders from bench to bedside.

Preliminary profile of the gut microbiota from amerindians in the Brazilian amazon experiencing a process of transition to urbanization

The Yanomami are one of the oldest indigenous tribes in the Amazon and are direct descendants of the first people to colonize South America 12,000 years ago. They are located on the border between Venezuela and Brazil, with the Venezuelan side remaining uncontacted. While they maintain a hunter-gatherer society, they are currently experiencing contact with urbanized populations in Brazil. The human gut microbiota of traditional communities has become the subject of recent studies due to the Westernization of their diet and the introduction of antibiotics and other chemicals, which have affected microbial diversity in indigenous populations, thereby threatening their existence. In this study, we preliminarily characterized the diversity of the gut microbiota of the Yanomami, a hunter-gatherer society from the Amazon, experiencing contact with urbanized populations. Similarly, we compared their diversity with the population in Manaus, Amazonas. A metabarcoding approach of the 16 S rRNA gene was carried out on fecal samples. Differences were found between the two populations, particularly regarding the abundance of genera (e.g., Prevotella and Bacteroides) and the higher values of the phyla Bacteroidetes over Firmicutes, which were significant only in the Yanomami. Some bacteria were found exclusively in the Yanomami (Treponema and Succinivibrio). However, diversity was statistically equal between them. In conclusion, the composition of the Yanomami gut microbiota still maintains the profile characteristic of a community with a traditional lifestyle. However, our results suggest an underlying Westernization process of the Yanomami microbiota when compared with that of Manaus, which must be carefully monitored by authorities, as the loss of diversity can be a sign of growing danger to the health of the Yanomami.

Modelling lung infection with Klebsiella pneumoniae after murine traumatic brain injury

Pneumonia is a common comorbidity in patients with severe traumatic brain injury (TBI), and is associated with increased morbidity and mortality. In this study, we established a model of intratracheal Klebsiella pneumoniae administration in young adult male and female mice, at 4 days following an experimental TBI, to investigate how K. pneumoniae infection influences acute post-TBI outcomes. A dose-response curve determined the optimal dose of K. pneumoniae for inoculation (1 x 10^6 colony forming units), and administration at 4 days post-TBI resulted in transient body weight loss and sickness behaviors (hypoactivity and acute dyspnea). K. pneumoniae infection led to an increase in pro-inflammatory cytokines in serum and bronchoalveolar lavage fluid at 24 h post-infection, in both TBI and sham (uninjured) mice. By 7 days, when myeloperoxidase + neutrophil numbers had returned to baseline in all groups, lung histopathology was observed with an increase in airspace size in TBI + K. pneumoniae mice compared to TBI + vehicle mice. In the brain, increased neuroinflammatory gene expression was observed acutely in response to TBI, with an exacerbated increase in Ccl2 and Hmox1 in TBI + K. pneumoniae mice compared to either TBI or K. pneumoniae alone. However, the presence of neuroinflammatory immune cells in the injured brain, and the extent of damage to cortical and hippocampal brain tissue, was comparable between K. pneumoniae and vehicle-treated mice by 7 days. Examination of the fecal microbiome across a time course did not reveal any pronounced effects of either injury or K. pneumoniae on bacterial diversity or abundance. Together, these findings demonstrate that K. pneumoniae lung infection after TBI induces an acute and transient inflammatory response, primarily localized to the lungs with some systemic effects. However, this infection had minimal impact on secondary injury processes in the brain following TBI. Future studies are needed to evaluate the potential longer-term consequences of this dual-hit insult.

The longitudinal microbial and metabolic landscape of infant cystic fibrosis: the gut-lung axis

BACKGROUND AND AIM

In cystic fibrosis, gastrointestinal dysfunction and lower airway infection occur early and are independently associated with poorer outcomes in childhood. This study aimed to define the relationship between the microbiota at each niche during the first 2 years of life, its association with growth and airway inflammation, and explanatory features in the metabolome.

MATERIALS AND METHODS

67 bronchoalveolar lavage fluid (BALF), 62 plasma and 105 stool samples were collected from 39 infants with cystic fibrosis between 0 and 24 months who were treated with prophylactic antibiotics. 16S rRNA amplicon and shotgun metagenomic sequencing were performed on BALF and stool samples, respectively; metabolomic analyses were performed on all sample types. Sequencing data from healthy age-matched infants were used as controls.

RESULTS

Bacterial diversity increased over the first 2 years in both BALF and stool, and microbial maturation was delayed in comparison to healthy controls from the RESONANCE cohort. Correlations between their respective abundance in both sites suggest stool may serve as a noninvasive alternative for detecting BALF Pseudomonas and Veillonella. Multisite metabolomic analyses revealed age- and growth-related changes, associations with neutrophilic airway inflammation, and a set of core systemic metabolites. BALF Pseudomonas abundance was correlated with altered stool microbiome composition and systemic metabolite alterations, highlighting a complex gut-plasma-lung interplay and new targets with therapeutic potential.

CONCLUSION

Exploration of the gut-lung microbiome and metabolome reveals diverse multisite interactions in cystic fibrosis that emerge in early life. Gut-lung metabolomic links with airway inflammation and Pseudomonas abundance warrant further investigation for clinical utility, particularly in non-expectorating patients.

Atopic dermatitis: Pathophysiology, microbiota, and metabolome - A comprehensive review

Atopic dermatitis (AD) is a prevalent inflammatory skin condition that commonly occurs in children. Genetics, environment, and defects in the skin barrier are only a few of the factors that influence how the disease develops. As human microbiota research has advanced, more scientific evidence has shown the critical involvement of the gut and skin bacteria in the pathogenesis of atopic dermatitis. Microbiome dysbiosis, defined by changed diversity and composition, as well as the development of pathobionts, has been identified as a potential cause for recurring episodes of atopic dermatitis. Gut dysbiosis causes "leaky gut syndrome" by disrupting the epithelial lining of the gut, which allows bacteria and other endotoxins to enter the bloodstream and cause inflammation. The same is true for the disruption of cutaneous homeostasis caused by skin dysbiosis, which enables bacteria and other pathogens to reach deeper skin layers or even systemic circulation, resulting in inflammation. Furthermore, it is now recognized that the gut and skin microbiota releases both beneficial and toxic metabolites. Here, this review covers a range of topics related to AD, including its pathophysiology, the microbiota-AD connection, commonly used treatments, and the significance of metabolomics in AD prevention, treatment, and management, recognizing its potential in providing valuable insights into the disease.

Interrelation between gut microbiota, SCFA, and fatty acid composition in pigs

The gut microbiota is a key player in the host metabolism. Some bacteria are able to ferment non-digestible compounds and produce short-chain fatty acids that the host can later transform and accumulate in tissue. In this study, we aimed to better understand the relationships between the microorganisms and the short-chain fatty acid composition of the rectal content, including the possible linkage with the fatty acid composition in backfat and muscle of the pig. We studied a Duroc × Iberian crossbred population, and we found significant correlations between different bacterial and archaeal genera and the fatty acid profile. The abundance of n-butyric acid in the rectal content was positively associated with Prevotella spp. and negatively associated with Akkermansia spp., while conversely, the abundance of acetic acid was negatively and positively associated with the levels of Prevotella spp. and Akkermansia spp., respectively. The most abundant genus, Rikenellaceae RC9 gut group, had a positive correlation with palmitic acid in muscle and negative correlations with stearic acid in backfat and oleic acid in muscle. These results suggest the possible role of Prevotella spp. and Akkermansia spp. as biomarkers for acetic and n-butyric acids, and the relationship of Rikenellaceae RC9 gut group with the lipid metabolism, building up the potential, although indirect, role of the microbiota in the modification of the backfat and muscle fatty acid composition of the host.IMPORTANCEThe vital role of the gut microbiota on its host metabolism makes it essential to know how its modulation is mirrored on the fatty acid composition of the host. Our findings suggest Prevotella spp. and Akkermansia spp. as potential biomarkers for the levels of beneficial short-chain fatty acids and the possible influence of Rikenellaceae RC9 gut group in the backfat and muscle fatty acid composition of the pig.

Ecological strategies of bacterial communities in prehistoric stone wall paintings across weathering gradients: A case study from the Borana zone in southern Ethiopia

Rock art paintings represent fragile ecosystems supporting complex microbial communities tuned to the lithic substrate and climatic conditions. The composition and activity of these microbial communities associated with different weathering patterns affecting rock art sites remain unexplored. This study aimed to explore how bacterial communities adapt their ecological strategies based on substrate weathering, while also examining the role of their metabolic pathways in either biodeterioration or bioprotection of the underlying stone. SEM-EDS investigations coupled with 16S rRNA gene sequencing and PICRUSt2 analysis were applied on different weathered surfaces that affect southern Ethiopian rock paintings to investigate the relationships between the current stone microbiome and weathering patterns. The findings revealed that samples experiencing low and high weathering reached a climax stage characterized by stable microenvironments and limited resources. This condition favored K-strategist microorganisms, leading to reduced α-biodiversity and a community with a positive or neutral impact on the substrate. In contrast, moderately-weathered samples displayed diverse microhabitats, resulting in the prevalence of r-strategist bacteria, increased α-biodiversity, and the presence of specialist microorganisms. Moreover, the bacterial communities in moderately-weathered samples demonstrated the highest potential for carbon fixation, stress responses, and complete nitrogen and sulfur cycles. This bacterial community also showed the potential to negatively impact the underlying substrate. This research provided valuable insights into the little-understood ecology of bacterial communities inhabiting deteriorated surfaces, shedding light on the potential role of these microorganisms in the sustainable conservation of rock art.

MK-BMC: a Multi-Kernel framework with Boosted distance metrics for Microbiome data for Classification

MOTIVATION

Research on human microbiome has suggested associations with human health, opening opportunities to predict health outcomes using microbiome. Studies have also suggested that diverse forms of taxa such as rare taxa that are evolutionally related and abundant taxa that are evolutionally unrelated could be associated with or predictive of a health outcome. Although prediction models were developed for microbiome data, no prediction models currently exist that use multiple forms of microbiome-outcome associations.

RESULTS

We developed MK-BMC, a Multi-Kernel framework with Boosted distance Metrics for Classification using microbiome data. We propose to first boost widely used distance metrics for microbiome data using taxon-level association signal strengths to up-weight taxa that are potentially associated with an outcome of interest. We then propose a multi-kernel prediction model with one kernel capturing one form of association between taxa and the outcome, where a kernel measures similarities of microbiome compositions between pairs of samples being transformed from a proposed boosted distance metric. We demonstrated superior prediction performance of (i) boosted distance metrics for microbiome data over original ones and (ii) MK-BMC over competing methods through extensive simulations. We applied MK-BMC to predict thyroid, obesity, and inflammatory bowel disease status using gut microbiome data from the American Gut Project and observed much-improved prediction performance over that of competing methods. The learned kernel weights help us understand contributions of individual microbiome signal forms nicely.

AVAILABILITY AND IMPLEMENTATION

Source code together with a sample input dataset is available at https://github.com/HXu06/MK-BMC.

Investigation of Gut Microbiota Disorders in Sepsis and Sepsis Complicated with Acute Gastrointestinal Injury Based on 16S rRNA Genes Illumina Sequencing

Background

Sepsis is a life-threatening organ dysfunction caused by the host's dysfunctional response to infection, which can cause acute gastrointestinal injury (AGI). The gut microbiota is dynamic and plays a role in the immune and metabolic. The aim of this study was to investigate the composition and function of gut microbiota in patients with sepsis, as well as the gut microbiome that may be involved in the occurrence of AGI.

Methods

A total of 23 stool samples from healthy control individuals and 41 stool samples from sepsis patients were collected. Patients with sepsis were followed up for one week to observe whether AGI has occurred. Finally, 41 patients included 21 sepsis complicated with AGI (referred to as Com-AGI) and 20 sepsis without complicated with AGI (referred to as No-AGI). The gut microbiota was analyzed by 16S rRNA gene sequencing, followed by composition analysis, difference analysis, correlation analysis, functional prediction analysis.

Results

The diversity and evenness of gut microbiota were decreased in patients with sepsis. Compared with No-AGI, the gut microbiota of Com-AGI has higher community diversity, richness, and phylogenetic diversity. Escherichia-Shigella, Blautia and Enterococcus may be important indicators of sepsis. The correlation analysis showed that aspartate aminotransferase (AST) and Barnesiella have the most significant positive correlation. Moreover, Clostridium_innocuum_group, Christensenellaceae_R-7_group and Eubacterium were all significantly correlated with LAC and DAO. Clostridium_innocuum_group, Barnesiella, Christensenellaceae_R-7_group and Eubacterium may play important roles in the occurrence of AGI in sepsis. PICRUSt analysis revealed multiple functional pathways involved in the relationship between gut microbiota and sepsis, including starch degradation V, glycogen degradation I (bacterial), Lipoic acid metabolism and Valine, leucine and isoleucine biosynthesis. BugBase analysis showed that the gut microbiota with Aerobic phenotype may play an important role in sepsis.

Conclusion

Dysfunction of gut microbiota was associated with sepsis and AGI in patients with sepsis.

A Two-Step Single Plex PCR Method for Evaluating Key Colonic Microbiota Markers in Young Mexicans with Autism Spectrum Disorders: Protocol and Pilot Epidemiological Application

Many neurological disorders have a distinctive colonic microbiome (CM) signature. Particularly, children with autism spectrum disorders (ASD) exhibit a very dissimilar CM when compared to neurotypical (NT) ones, mostly at the species level. Thus far, knowledge on this matter comes from high-throughput (yet very expensive and time-consuming) analytical platforms, such as massive high-throughput sequencing of bacterial 16S rRNA. Here, pure (260/280 nm, ~1.85) stool DNA samples (200 ng.µL^-1) from 48 participants [39 ASD, 9 NT; 3-13 y] were used to amplify four candidate differential CM markers [Bacteroides fragilis (BF), Faecalibacterium prausnitzii (FP), Desulfovibrio vulgaris (DV), Akkermansia muciniphila (AM)], using micro-organism-specific oligonucleotide primers [265 bp (BF), 198 bp (FP), 196 bp (DV), 327 bp (AM)] and a standardized two-step [low (step 1: °Tm-5 °C) to high (stage 2: °Tm-0 °C) astringent annealing] PCR protocol (2S-PCR). The method was sensitive enough to differentiate all CM biomarkers in the studied stool donors [↑ abundance: NT (BF, FP, AM), ASD (DV)], and phylogenetic analysis confirmed the primers' specificity.

The skin microbiome in the first year of life and its association with atopic dermatitis

BACKGROUND

Early-life microbial colonization of the skin may modulate the immune system and impact the development of atopic dermatitis (AD) and allergic diseases later in life. To address this question, we assessed the association between the skin microbiome and AD, skin barrier integrity and allergic diseases in the first year of life. We further explored the evolution of the skin microbiome with age and its possible determinants, including delivery mode.

METHODS

Skin microbiome was sampled from the lateral upper arm on the first day of life, and at 3, 6, and 12 months of age. Bacterial communities were assessed by 16S rRNA gene amplicon sequencing in 346 infants from the PreventADALL population-based birth cohort study, representing 970 samples. Clinical investigations included skin examination and skin barrier function measured as trans-epidermal water loss (TEWL) at the site and time of microbiome sampling at 3, 6, and 12 months. Parental background information was recorded in electronic questionnaires, and delivery mode (including vaginal delivery (VD), VD in water, elective caesarean section (CS) and emergency CS) was obtained from maternal hospital charts.

RESULTS

Strong temporal variations in skin bacterial community composition were found in the first year of life, with distinct patterns associated with different ages. Confirming our hypothesis, skin bacterial community composition in the first year of life was associated with skin barrier integrity and later onsets of AD. Delivery mode had a strong impact on the microbiome composition at birth, with each mode leading to distinct patterns of colonization. Other possible determinants of the skin microbiome were identified, including environmental and parental factors as well as breastfeeding.

CONCLUSION

Skin microbiome composition during infancy is defined by age, transiently influenced by delivery mode as well as environmental, parental factors and breastfeeding. The microbiome is also associated with skin barrier integrity and the onset of AD.

MKMR: a multi-kernel machine regression model to predict health outcomes using human microbiome data

Studies have found that human microbiome is associated with and predictive of human health and diseases. Many statistical methods developed for microbiome data focus on different distance metrics that can capture various information in microbiomes. Prediction models were also developed for microbiome data, including deep learning methods with convolutional neural networks that consider both taxa abundance profiles and taxonomic relationships among microbial taxa from a phylogenetic tree. Studies have also suggested that a health outcome could associate with multiple forms of microbiome profiles. In addition to the abundance of some taxa that are associated with a health outcome, the presence/absence of some taxa is also associated with and predictive of the same health outcome. Moreover, associated taxa may be close to each other on a phylogenetic tree or spread apart on a phylogenetic tree. No prediction models currently exist that use multiple forms of microbiome-outcome associations. To address this, we propose a multi-kernel machine regression (MKMR) method that is able to capture various types of microbiome signals when doing predictions. MKMR utilizes multiple forms of microbiome signals through multiple kernels being transformed from multiple distance metrics for microbiomes and learn an optimal conic combination of these kernels, with kernel weights helping us understand contributions of individual microbiome signal types. Simulation studies suggest a much-improved prediction performance over competing methods with mixture of microbiome signals. Real data applicants to predict multiple health outcomes using throat and gut microbiome data also suggest a better prediction of MKMR than that of competing methods.

Age matters: Microbiome depletion prior to repeat mild traumatic brain injury differentially alters microbial composition and function in adolescent and adult rats

Dysregulation of the gut microbiome has been shown to perpetuate neuroinflammation, alter intestinal permeability, and modify repetitive mild traumatic brain injury (RmTBI)-induced deficits. However, there have been no investigations regarding the comparative effects that the microbiome may have on RmTBI in adolescents and adults. Therefore, we examined the influence of microbiome depletion prior to RmTBI on microbial composition and metabolome, in adolescent and adult Sprague Dawley rats. Rats were randomly assigned to standard or antibiotic drinking water for 14 days, and to subsequent sham or RmTBIs. The gut microbiome composition and metabolome were analysed at baseline, 1 day after the first mTBI, and at euthanasia (11 days following the third mTBI). At euthanasia, intestinal samples were also collected to quantify tight junction protein (TJP1 and occludin) expression. Adolescents were significantly more susceptible to microbiome depletion via antibiotic administration which increased pro-inflammatory composition and metabolites. Furthermore, RmTBI induced a transient increase in 'beneficial bacteria' (Lachnospiraceae and Faecalibaculum) in only adolescents that may indicate compensatory action in response to the injury. Finally, microbiome depletion prior to RmTBI generated a microbiome composition and metabolome that exemplified a potentially chronic pathogenic and inflammatory state as demonstrated by increased Clostridium innocuum and Erysipelatoclostridium and reductions in Bacteroides and Clostridium Sensu Stricto. Results highlight that adolescents are more vulnerable to RmTBI compared to adults and dysbiosis prior to injury may exacerbate secondary inflammatory cascades.

Early life inter-kingdom interactions shape the immunological environment of the airways

BACKGROUND

There is increasing evidence that the airway microbiome plays a key role in the establishment of respiratory health by interacting with the developing immune system early in life. While it has become clear that bacteria are involved in this process, there is a knowledge gap concerning the role of fungi. Moreover, the inter-kingdom interactions that influence immune development remain unknown. In this prospective exploratory human study, we aimed to determine early post-natal microbial and immunological features of the upper airways in 121 healthy newborns.

RESULTS

We found that the oropharynx and nasal cavity represent distinct ecological niches for bacteria and fungi. Breastfeeding correlated with changes in microbiota composition of oropharyngeal samples with the greatest impact upon the relative abundance of Streptococcus species and Candida. Host transcriptome profiling revealed that genes with the highest expression variation were immunological in nature. Multi-omics factor analysis of host and microbial data revealed unique co-variation patterns.

CONCLUSION

These data provide evidence of a diverse multi-kingdom microbiota linked with local immunological characteristics in the first week of life that could represent distinct trajectories for future respiratory health.

TRIAL REGISTRATION

NHS Health Research Authority, IRAS ID 199053. Registered 5 Oct 2016. https://www.hra.nhs.uk/planning-and-improving-research/application-summaries/research-summaries/breathing-together/ Video abstract.

Mucosal Microbiota and Metabolome in the Ileum of Hu Sheep Offered a Low-Grain, Pelleted or Non-pelleted High-Grain Diet

Alterations in mucosal microbiota and metabolites are critical to intestinal homeostasis and host health. This study used a combination of 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC/MS) to investigate mucosal microbiota and their metabolic profiles in the ileum of Hu sheep fed different diets. Here, we randomly allocated 15 Hu sheep to three diets, a non-pelleted low-grain diet (control diet; CON), a non-pelleted high-grain diet (HG), and a pelleted high-grain diet (HP). After 60 days of treatment, ileal mucosal samples were collected for microbiome and metabolome analysis. The results of principal coordinate analysis and permutation multivariate analysis showed that there was a tendency for microbial differentiation between the CON and HG groups (P < 0.1), although no significant difference between the HG and HP groups was observed (P > 0.05). Compared with the CON diet, the HG diet decreased (P < 0.05) the abundance of some probiotic species (e.g., Sphingomonas and Candidatus Arthromitus) and increased (P < 0.05) the abundance of acid-producing microbiota (e.g., Succiniclasticum, Nesterenkonia, and Alloprevotella) in the ileal mucosa. Compared with the HG diet, the HP diet decreased (P < 0.05) the abundance of Alloprevotella and increased (P < 0.05) the abundance of Mycoplasma in the ileal mucosa. Furthermore, partial least squares discriminant analysis and orthogonal partial least-squared discriminant analysis indicated that different dietary treatments resulted in different metabolic patterns in the ileal mucosa of the CON, HG, and HP groups. The HG diet altered (VIP > 1 and P < 0.05) the metabolic patterns of amino acids, fatty acids, and nucleotides/nucleosides (such as increased amounts of ornithine, tyrosine, cis-9-palmitoleic acid, and adenosine) compared with the CON diet. However, 10 differential metabolites (VIP > 1 and P < 0.05; including tyrosine, ornithine, and cis-9-palmitoleic acid) identified in the HG group exhibited a diametrically opposite trend in the HP group, suggesting that the HP diet could partially eliminate the changes brought upon by the HG diet. Collectively, our findings demonstrate that different diets altered the ileal mucosal microbiota and metabolites and provide new insight into the effects of high-grain diets on the intestinal health of ruminant animals.

FOXC2 controls adult lymphatic endothelial specialization, function, and gut lymphatic barrier preventing multiorgan failure

The mechanisms maintaining adult lymphatic vascular specialization throughout life and their role in coordinating inter-organ communication to sustain homeostasis remain elusive. We report that inactivation of the mechanosensitive transcription factor Foxc2 in adult lymphatic endothelium leads to a stepwise intestine-to-lung systemic failure. Foxc2 loss compromised the gut epithelial barrier, promoted dysbiosis and bacterial translocation to peripheral lymph nodes, and increased circulating levels of purine metabolites and angiopoietin-2. Commensal microbiota depletion dampened systemic pro-inflammatory cytokine levels, corrected intestinal lymphatic dysfunction, and improved survival. Foxc2 loss skewed the specialization of lymphatic endothelial subsets, leading to populations with mixed, pro-fibrotic identities and to emergence of lymph node-like endothelial cells. Our study uncovers a cross-talk between lymphatic vascular function and commensal microbiota, provides single-cell atlas of lymphatic endothelial subtypes, and reveals organ-specific and systemic effects of dysfunctional lymphatics. These effects potentially contribute to the pathogenesis of diseases, such as inflammatory bowel disease, cancer, or lymphedema.

Lipocalin 2 modulates dendritic cell activity and shapes immunity to influenza in a microbiome dependent manner

Lipocalin 2 (LCN2) is a secreted glycoprotein with roles in multiple biological processes. It contributes to host defense by interference with bacterial iron uptake and exerts immunomodulatory functions in various diseases. Here, we aimed to characterize the function of LCN2 in lung macrophages and dendritic cells (DCs) using Lcn2-/- mice. Transcriptome analysis revealed strong LCN2-related effects in CD103+ DCs during homeostasis, with differential regulation of antigen processing and presentation and antiviral immunity pathways. We next validated the relevance of LCN2 in a mouse model of influenza infection, wherein LCN2 protected from excessive weight loss and improved survival. LCN2-deficiency was associated with enlarged mediastinal lymph nodes and increased lung T cell numbers, indicating a dysregulated immune response to influenza infection. Depletion of CD8+ T cells equalized weight loss between WT and Lcn2-/- mice, proving that LCN2 protects from excessive disease morbidity by dampening CD8+ T cell responses. In vivo T cell chimerism and in vitro T cell proliferation assays indicated that improved antigen processing by CD103+ DCs, rather than T cell intrinsic effects of LCN2, contribute to the exacerbated T cell response. Considering the antibacterial potential of LCN2 and that commensal microbes can modulate antiviral immune responses, we speculated that LCN2 might cause the observed influenza phenotype via the microbiome. Comparing the lung and gut microbiome of WT and Lcn2-/- mice by 16S rRNA gene sequencing, we observed profound effects of LCN2 on gut microbial composition. Interestingly, antibiotic treatment or co-housing of WT and Lcn2-/- mice prior to influenza infection equalized lung CD8+ T cell counts, suggesting that the LCN2-related effects are mediated by the microbiome. In summary, our results highlight a novel regulatory function of LCN2 in the modulation of antiviral immunity.

The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology

Characterizing the microbial communities inhabiting specimens is one of the primary objectives of microbiome studies. A short-read sequencing platform for reading partial regions of the 16S rRNA gene is most commonly used by reducing the cost burden of next-generation sequencing (NGS), but misclassification at the species level due to its length being too short to consider sequence similarity remains a challenge. Loop Genomics recently proposed a new 16S full-length-based synthetic long-read sequencing technology (sFL16S). We compared a 16S full-length-based synthetic long-read (sFL16S) and V3-V4 short-read (V3V4) methods using 24 human GUT microbiota samples. Our comparison analyses of sFL16S and V3V4 sequencing data showed that they were highly similar at all classification resolutions except the species level. At the species level, we confirmed that sFL16S showed better resolutions than V3V4 in analyses of alpha-diversity, relative abundance frequency and identification accuracy. Furthermore, we demonstrated that sFL16S could overcome the microbial misidentification caused by different sequence similarity in each 16S variable region through comparison the identification accuracy of Bifidobacterium, Bacteroides, and Alistipes strains classified from both methods. Therefore, this study suggests that the new sFL16S method is a suitable tool to overcome the weakness of the V3V4 method.

Dynamics of bacterial communities and substrate conversion during olive-mill waste dark fermentation: Prediction of the metabolic routes for hydrogen production

The aim of this work was to study the biological catalysts and possible substrate conversion routes in mesophilic dark fermentation reactors aimed at producing H₂ from olive mill wastewater. Bacillus and Clostridium were the most abundant phylotypes during the rapid stage of H₂ production. Chemical analyses combined with predictive functional profiling of the bacterial communities indicated that the lactate fermentation was the main H₂-producing route. In fact, during the fermentation process, lactate and acetate were consumed, while H₂ and butyrate were being produced. The fermentation process was rich in genes that encode enzymes for lactate generation from pyruvate. Lactate conversion to butyrate through the generation of pyruvate produced H₂ through the recycling of electron carriers via the pyruvate ferredoxin oxydoreductase pathway. Overall, these findings showed the synergy among lactate-, acetate- and H₂-producing bacteria, which complex interactions determine the H₂ production routes in the bioreactors.

Effect of Sample Collection (Manual Expression vs. Pumping) and Skimming on the Microbial Profile of Human Milk Using Culture Techniques and Metataxonomic Analysis

Human milk microbiota is a unique bacterial community playing a relevant role in infant health, but its composition depends on different factors (woman health, lactation stage, and geographical lactation). However, information is lacking regarding some other factors that may affect the bacterial community of human milk. In this study we aimed to study the impact of the sample collection method and the skimming procedure using culture-dependent and culture-independent techniques to study the human milk microbial profile. One set of milk samples was provided by women (n = 10) in two consecutive days; half of the samples were collected the first day by manual expression and the other half on the second day by pumping. The rest of the participants (n = 17) provided milk samples that were fractionated by centrifugation; the bacterial profiles of whole milk and skimmed milk were compared by culture techniques in 10 milk samples, while those of whole milk, fat and skimmed milk were subjected to metataxonomic analysis in seven samples. Globally, the results obtained revealed high interindividual variability but that neither the use of single-use sterile devices to collect the sample nor the skimming procedure have a significant impact of the microbial profile of human samples.

Geomicrobial Investigations of Colored Outer Coatings from an Ethiopian Rock Art Gallery

The open rock shelter of Yabelo in Ethiopia hosts diverse Holocene paintings of great cultural importance. The paintings are characterized by the presence of different mineral coatings, whose features have not been studied yet. Our goal was to understand whether different rock samples from the Yabelo paintings collected in close proximity may reveal coatings with different minerology and biology. Thus, elemental analyses combined with microscopic and molecular investigations were performed on two coatings, one whitish (sample 1) and one reddish (sample 2). Although both samples were dominated by heterotrophic bacteria, the two coatings showed distinct mineralogical and microbiological characteristics. Sample 1 contained higher amounts of Ca and P than sample 2, which was likely related to the presence of organic matter. Sample 1 hosted bacterial genera that are potentially involved in biomineralization processes, metal redox cycles and metal resistance. In contrast, sample 2 showed mainly pathogenic and commensal bacteria that are characteristic of animal and human microbiota, and other microorganisms that are involved in nitrogen and metal biogeochemical cycles. Overall, our results indicated that the bacterial communities were particular to the coating mineralogy, suggesting a potential role of the biological components in the crust genesis.

Aesthetic Alteration of Marble Surfaces Caused by Biofilm Formation: Effects of Chemical Cleaning

Despite the massive presence of biofilms causing aesthetic alteration to the façade of the Monza Cathedral, our team in a previous work proved that the biocolonization was not a primary damaging factor if compared to chemical-physical deterioration due to the impact of air pollution. Nonetheless, the conservators tried to remove the sessile dwelling microorganisms to reduce discolouration. In this research, two nearby sculpted leaves made of Candoglia marble were selected to study the effects of a chemical treatment combining the biocides benzalkonium chloride, hydrogen peroxide and Algophase® and mechanical cleaning procedures. One leaf was cleaned with the biocides and mechanically, and the other was left untreated as control. The impact of the treatment was investigated after 1 month from the cleaning by digital microscopy, environmental scanning electron microscopy, confocal microscopy and molecular methods to determine the composition and the functional profiles of the bacterial communities. Despite the acceptable aesthetic results obtained, the overall cleaning treatment was only partially effective in removing the biofilm from the colonized surfaces and, therefore, not adequately suitable for the specific substrate. Furthermore, the cleaning process selected microorganisms potentially more resistant to biocides so that the efficacy of future re-treatment by antimicrobial agents could be negatively affected.

A Calm, Dispassionate Look at Skin Microbiota in Atopic Dermatitis: An Integrative Literature Review

Atopic dermatitis (AD) is a chronic common inflammatory skin disorder with clinical characteristics of pruritic, dry, and recurrent flares that involve the whole body. Recent studies have demonstrated that the skin microbiota, characterized by an overgrowth of Staphylococcus aureus (S. aureus), plays a critical role in the manifestation of AD. There is striking evidence that skin microbiota can modulate the development and progression of AD. Therefore, more and more therapeutic approaches are adopted for modifying skin microbiota. Here we discuss the role of skin microbiota in the etiology and maintenance of AD; furthermore, we summarize the effects of therapeutic treatments on skin microbiota in AD based on published literature. With the help of the theoretical guidance suggested by microbial metagenome analysis, the reconstitution of microbiota should be a promising way to harness the pathogens of AD and could be used as a brand-new therapeutic strategy in clinical trials. We believe that the targeted therapy of dysbiosis in AD may possibly become a unique approach to an integrated treatment program in the near future.

Age-Related Changes in the Gut Microbiota Modify Brain Lipid Composition

Understanding the molecular mechanisms underlying the changes observed during aging is a prerequisite to design strategies to prevent age-related diseases. Aging is associated with metabolic changes, including alteration in the brain lipid metabolism. These alterations may contribute to the development of pathophysiological conditions. Modifications in the gut microbiota composition are also observed during aging. As communication axes exist between the gut microbiota and the brain and knowing that microbiota influences the host metabolism, we speculated on whether age-associated modifications in the gut microbiota could be involved in the lipid changes observed in aging brain. For that purpose, germ-free mice were colonized by the fecal microbiota of young or old donor mice. Lipid classes and fatty acid profiles were determined in the brain (cortex), plasma and liver by thin-layer chromatography on silica gel-coated quartz rods and gas chromatography. Gut colonization by microbiota of old mice resulted in a significant increase in total monounsaturated fatty acids (MUFA) and a significant decrease in the relative amounts of cholesterol and total polyunsaturated fatty acids (PUFA) in the cortex. Among the eight most represented fatty acids in the cortex, the relative abundances of five (C18:1n-9, C22:6n-3, C20:4n-6, C18:1n-7, and C20:1n-9) were significantly altered in mice inoculated with an aged microbiota. Liquid chromatography analyses revealed that the relative abundance of major species among phosphatidyl and plasmenylcholine (PC 16:0/18:1), phosphatidyl and plasmenylethanolamine (PE 18:0/22:6), lysophosphatidylethanolamine (LPE 22:6) and sphingomyelins (SM d18:1/18:0) were significantly altered in the cortex of mice colonized by the microbiota obtained from aged donors. Transplantation of microbiota from old mice also modified the lipid class and fatty acid content in the liver. Finally, we found that the expression of several genes involved in MUFA and PUFA synthesis (Scd1, Fads1, Fads2, Elovl2, and Elovl5) was dysregulated in mice inoculated with an aged microbiota. In conclusion, our data suggest that changes in gut microbiota that are associated with aging can impact brain and liver lipid metabolisms. Lipid changes induced by an aged microbiota recapitulate some features of aging, thus pointing out the potential role of microbiota alterations in the age-related degradation of the health status.

Integrative analysis of time course metabolic data and biomarker discovery

Background

Metabolomics time-course experiments provide the opportunity to understand the changes to an organism by observing the evolution of metabolic profiles in response to internal or external stimuli. Along with other omic longitudinal profiling technologies, these techniques have great potential to uncover complex relations between variations across diverse omic variables and provide unique insights into the underlying biology of the system. However, many statistical methods currently used to analyse short time-series omic data are i) prone to overfitting, ii) do not fully take into account the experimental design or iii) do not make full use of the multivariate information intrinsic to the data or iv) are unable to uncover multiple associations between different omic data. The model we propose is an attempt to i) overcome overfitting by using a weakly informative Bayesian model, ii) capture experimental design conditions through a mixed-effects model, iii) model interdependencies between variables by augmenting the mixed-effects model with a conditional auto-regressive (CAR) component and iv) identify potential associations between heterogeneous omic variables by using a horseshoe prior.

Results

We assess the performance of our model on synthetic and real datasets and show that it can outperform comparable models for metabolomic longitudinal data analysis. In addition, our proposed method provides the analyst with new insights on the data as it is able to identify metabolic biomarkers related to treatment, infer perturbed pathways as a result of treatment and find significant associations with additional omic variables. We also show through simulation that our model is fairly robust against inaccuracies in metabolite assignments. On real data, we demonstrate that the number of profiled metabolites slightly affects the predictive ability of the model.

Conclusions

Our single model approach to longitudinal analysis of metabolomics data provides an approach simultaneously for integrative analysis and biomarker discovery. In addition, it lends better interpretation by allowing analysis at the pathway level. An accompanying R package for the model has been developed using the probabilistic programming language Stan. The package offers user-friendly functions for simulating data, fitting the model, assessing model fit and postprocessing the results. The main aim of the R package is to offer freely accessible resources for integrative longitudinal analysis for metabolomics scientists and various visualization functions easy-to-use for applied researchers to interpret results.

Infection with a small intestinal helminth, Heligmosomoides polygyrus bakeri, consistently alters microbial communities throughout the murine small and large intestine

Increasing evidence suggests that intestinal helminth infection can alter intestinal microbial communities with important impacts on the mammalian host. However, all of the studies to date utilize different techniques to study the microbiome and access different sites of the intestine with little consistency noted between studies. In the present study, we set out to perform a comprehensive analysis of the impact of intestinal helminth infection on the mammalian intestinal bacterial microbiome. For this purpose, we investigated the impact of experimental infection using the natural murine small intestinal helminth, Heligmosomoides polygyrus bakeri and examined possible alterations in both the mucous and luminal bacterial communities along the entire small and large intestine. We also explored the impact of common experimental variables including the parasite batch and pre-infection microbiome, on the outcome of helminth-bacterial interactions. This work provides evidence that helminth infection reproducibly alters intestinal microbial communities, with an impact of infection noted along the entire length of the intestine. Although the exact nature of helminth-induced alterations to the intestinal microbiome differed depending on the microbiome community structure present prior to infection, changes extended well beyond the introduction of new bacterial species by the infecting larvae. Moreover, striking similarities between different experiments were noted, including the consistent outgrowth of a bacterium belonging to the Peptostreptococcaceae family throughout the intestine.

Microbiome of the Skin and Gut in Atopic Dermatitis (AD): Understanding the Pathophysiology and Finding Novel Management Strategies

Atopic dermatitis (AD) is a long-standing inflammatory skin disease that is highly prevalent worldwide. Multiple factors contribute to AD, with genetics as well as the environment affecting disease development. Although AD shows signs of skin barrier defect and immunological deviation, the mechanism underlying AD is not well understood, and AD treatment is often very difficult. There is substantial data that AD patients have a disturbed microbial composition and lack microbial diversity in their skin and gut compared to controls, which contributes to disease onset and atopic march. It is not clear whether microbial change in AD is an outcome of barrier defect or the cause of barrier dysfunction and inflammation. However, a cross-talk between commensals and the immune system is now noticed, and their alteration is believed to affect the maturation of innate and adaptive immunity during early life. The novel concept of modifying skin and gut microbiome by applying moisturizers that contain nonpathogenic biomass or probiotic supplementation during early years may be a preventive and therapeutic option in high risk groups, but currently lacks evidence. This review discusses the nature of the skin and gut flora in AD, possible mechanisms of skin-gut interaction, and the therapeutic implications of microbiome correction in AD.

Sperm Microbiota and Its Impact on Semen Parameters

Compared to its female counterpart, the microbiota of the male genital tract has not been studied extensively. With this study, we aimed to evaluate the bacterial composition of seminal fluid and its impact on sperm parameters. We hypothesized that a dysbiotic microbiota composition may have an influence on sperm quality. Semen samples of 26 men with normal spermiogram and 68 men with at least one abnormal spermiogram parameter were included in the study. Samples were stratified based on total sperm count, spermatozoa concentration, progressive motility, total motility and spermatozoa morphology. Microbiota profiling was performed using 16S rRNA gene amplicons sequencing and total bacterial load was determined using a panbacterial quantitative PCR. Semen samples broadly clustered into three microbiota profiles: Prevotella-enriched, Lactobacillus-enriched, and polymicrobial. Prevotella-enriched samples had the highest bacterial load (p < 0.05). Network analysis identified three main co-occurrence modules, among which two contained bacteria commonly found in the vaginal flora. Genera from the same module displayed similar oxygen requirements, arguing for the presence of different ecological niches for bacteria that colonize semen through the passage. Contrary to our hypothesis, shifts in overall microbiota composition (beta-diversity) did not correlate with spermiogram parameters. Similarly, we did not find any difference in microbial richness or diversity (alpha-diversity). Differential abundance testing, however, revealed three specific genera that were significantly enriched or depleted in some of the sperm quality groups (p < 0.05). Prevotella relative abundance was increased in samples with defective sperm motility while Staphylococcus was increased in the corresponding control group. In addition, we observed an increased relative abundance of Lactobacillus in samples with normal sperm morphology. Our study indicates that overall bacterial content of sperm might not play a major role in male infertility. Although no major shifts in microbiota composition or diversity were found, the differential abundance of specific bacterial genera in the sperm suggests that a small subset of microbes might impact the spermatozoal physiology during sperm transition, more specifically motility and morphology. Further studies are required to challenge this finding and develop potential strategies to induce the formation of a healthy seminal microbiota.

Impacts of dietary silver nanoparticles and probiotic administration on the microbiota of an in-vitro gut model

Ingestion of silver nanoparticles (AgNPs) is inevitable linked to their widespread use in food, medicines and other consumer products. However, their effects on human microbiota at non-lethal concentrations remain poorly understood. In this study, the interactions among 1 μg mL^-1 AgNPs, the intestinal microbiota, and the probiotic Bacillus subtilis (BS) were tested using in-vitro batch fermentation models inoculated with human fecal matter. Results from metagenomic investigations revealed that the core bacterial community was not affected by the exposure of AgNPs and BS at the later stage of fermentation, while the proportions of rare species changed drastically with the treatments. Furthermore, shifts in the Firmicutes/Bacteriodetes (F/B) ratios were observed after 24 h with an increase in the relative abundance of Firmicutes species and a decrease in Bacteroidetes in all fermentation cultures. The co-exposure to AgNPs and BS led to the lowest F/B ratio. Fluorescent in-situ hybridization analyses indicated that non-lethal concentration of AgNPs negatively affected the relative percentage of Faecalibacterium prausnitzii and Clostridium coccoides/Eubacterium rectales taxa in the fermentation cultures after 24 h. However, exposure to single and combined treatments of AgNPs and BS did not change the overall diversity of the fecal microflora. Functional differences in cell motility, translation, transport, and xenobiotics degradation occurred in AgNPs-treated fermentation cultures but not in AgNPs+BS-treated samples. Compared to the control samples, treated fecal cultures showed no significant statistical differences in terms of short-chain fatty acids profiles, cytotoxic and genotoxic effects on Caco-2 cell monolayers. Overall, AgNPs did not affect the composition and diversity of the core fecal microflora and its metabolic and toxic profiles. This work indicated a chemopreventive role of probiotic on fecal microflora against AgNPs, which were shown by the decrease of F/B ratio and the unaltered state of some key metabolic pathways.