Multiomics of the intestine-liver-adipose axis in multiple studies unveils a consistent link of the gut microbiota and the antiviral response with systemic glucose metabolism.

BACKGROUND: The microbiota is emerging as a key factor in the predisposition to insulin resistance and obesity. OBJECTIVE: To understand the interplay among gut microbiota and insulin sensitivity in multiple tissues. DESIGN: Integrative multiomics and multitissue approach across six studies, combining euglycaemic clamp measurements (used in four of the six studies) with other measurements of glucose metabolism and insulin resistance (glycated haemoglobin (HbA1c) and fasting glucose). RESULTS: Several genera and species from the Proteobacteria phylum were consistently negatively associated with insulin sensitivity in four studies (ADIPOINST, n=15; IRONMET, n=121, FLORINASH, n=67 and FLOROMIDIA, n=24). Transcriptomic analysis of the jejunum, ileum and colon revealed T cell-related signatures positively linked to insulin sensitivity. Proteobacteria in the ileum and colon were positively associated with HbA1c but negatively with the number of T cells. Jejunal deoxycholic acid was negatively associated with insulin sensitivity. Transcriptomics of subcutaneous adipose tissue (ADIPOMIT, n=740) and visceral adipose tissue (VAT) (ADIPOINST, n=29) revealed T cell-related signatures linked to HbA1c and insulin sensitivity, respectively. VAT Proteobacteria were negatively associated with insulin sensitivity. Multiomics and multitissue integration in the ADIPOINST and FLORINASH studies linked faecal Proteobacteria with jejunal and liver deoxycholic acid, as well as jejunal, VAT and liver transcriptomic signatures involved in the actin cytoskeleton, insulin and T cell signalling. Fasting glucose was consistently linked to interferon-induced genes and antiviral responses in the intestine and VAT. Studies in Drosophila melanogaster validated these human insulin sensitivity-associated changes. CONCLUSION: These data provide comprehensive insights into the microbiome-gut-adipose-liver axis and its impact on systemic insulin action, suggesting potential therapeutic targets.Cite Now.

Unraveling the gut-brain connection: The association of microbiota-linked structural brain biomarkers with behavior and mental health.

AIM: The gut microbiota can influence human behavior. However, due to the massive multiple-testing problem, research into the relationship between microbiome ecosystems and the human brain faces drawbacks. This problem arises when attempting to correlate thousands of gut bacteria with thousands of brain voxels. METHODS: We performed brain magnetic resonance imaging (MRI) scans on 133 participants and applied machine-learning algorithms (Ridge regressions) combined with permutation tests. Using this approach, we were able to correlate specific gut bacterial families with brain MRI signals, circumventing the difficulties of massive multiple testing while considering sex, age, and body mass index as confounding factors. RESULTS: The relative abundance (RA) of the Selenomonadaceae, Clostridiaceae, and Veillonellaceae families in the gut was associated with altered cerebellar, visual, and frontal T2-mapping and diffusion tensor imaging measures. Conversely, decreased relative abundance of the Eubacteriaceae family was also linked to T2-mapping values in the cerebellum. Significantly, the brain regions associated with the gut microbiome were also correlated with depressive symptoms and attentional deficits. CONCLUSIONS: Our analytical strategy offers a promising approach for identifying potential brain biomarkers influenced by gut microbiota. By gathering a deeper understanding of the microbiota-brain connection, we can gain insights into the underlying mechanisms and potentially develop targeted interventions to mitigate the detrimental effects of dysbiosis on brain function and mental health.

Intestinal mycobiota composition and changes in children with thalassemia who underwent allogeneic hematopoietic stem cell transplantation.

BACKGROUND: Allogeneic hematopoietic stem cell transplantation (HSCT) alters the diversity of the intestinal bacterial microbiota. This study aimed to evaluate human mycobiota composition pre-HSCT and post-HSCT in children with thalassemia. METHOD: Ten children with thalassemia undergoing allogeneic HSCT were enrolled. The stool samples were collected before the transplantation regimen, before the transplant day, and +15, +30 days, and three months after transplantation. Stool samples were also collected from the donor and the patient's caregivers. Gut mycobiota composition was evaluated with metagenomic analysis. RESULTS: Pretransplant mycobiota of children with thalassemia (the predominant genus was Saccharomyces, 64.1%) has been shown to approximate the diverse mycobiota compositions of healthy adult donors but becomes altered (lower diversity) following transplant procedures. Three months after HSCT, phyla Ascomycota and Basidiomycota were 83.4% and 15.6%, respectively. The predominant species were Saccaharomyces_uc and Saccharomyces cerevisiae (phylum Ascomycota); we also observed Malassezia restricta and Malassezia globosa (phylum Basidiomycota) (∼13%). On day 90 after HSCT, we observed 65.3% M. restricta and 18.4% M. globosa predominance at the species level in a four-year-old boy with acute graft-versus-host disease (GVHD) (skin and gut involvement) 19 days after transplantation included. CONCLUSION: The mycobiota composition of children with thalassemia altered after HSCT. We observed Malassezia predominance in a child with GVHD. Further studies in children with GVHD will identify this situation.

Obesity-associated deficits in inhibitory control are phenocopied to mice through gut microbiota changes in one-carbon and aromatic amino acids metabolic pathways.

BACKGROUND: Inhibitory control (IC) is critical to keep long-term goals in everyday life. Bidirectional relationships between IC deficits and obesity are behind unhealthy eating and physical exercise habits. METHODS: We studied gut microbiome composition and functionality, and plasma and faecal metabolomics in association with cognitive tests evaluating inhibitory control (Stroop test) and brain structure in a discovery (n=156), both cross-sectionally and longitudinally, and in an independent replication cohort (n=970). Faecal microbiota transplantation (FMT) in mice evaluated the impact on reversal learning and medial prefrontal cortex (mPFC) transcriptomics. RESULTS: An interplay among IC, brain structure (in humans) and mPFC transcriptomics (in mice), plasma/faecal metabolomics and the gut metagenome was found. Obesity-dependent alterations in one-carbon metabolism, tryptophan and histidine pathways were associated with IC in the two independent cohorts. Bacterial functions linked to one-carbon metabolism (thyX,dut, exodeoxyribonuclease V), and the anterior cingulate cortex volume were associated with IC, cross-sectionally and longitudinally. FMT from individuals with obesity led to alterations in mice reversal learning. In an independent FMT experiment, human donor's bacterial functions related to IC deficits were associated with mPFC expression of one-carbon metabolism-related genes of recipient's mice. CONCLUSION: These results highlight the importance of targeting obesity-related impulsive behaviour through the induction of gut microbiota shifts.

The intestinal mycobiota and its relationship with overweight, obesity and nutritional aspects.

BACKGROUND: The fungal community of the gastrointestinal tract has recently become of interest, and knowledge of its relationship with the development of obesity is scarce. The present study aimed to evaluate the cultivable fungal fraction from the microbiota and to analyze its relationship with obesity. METHODS: Samples were taken from 99 participants with normal weight, overweight and obesity (n = 31, 34 and 34, respectively) and were cultivated in selective medium, and the cultivable yeasts were identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Anthropometric and biochemical measures were also evaluated. RESULTS: Eutrophic, overweight and obese groups presented concentrations of 1.6, 2.16 and 2.19 log10  colony-forming units g-1 yeast, respectively. Ascomycota and Basidiomycota were the two identified phyla. At the genus level, Candida spp. showed a relatively high prevalence, and 10 different species were detected: Candida glabrata, Candida orthopsilosis, Candida lambica, Candida kefyr, Candida albicans, Candida krusei, Candida valida, Candida parapsilosis, Candida utilis and Candida humilis (with relative abundances of 71.72%, 5.05%, 21.21%, 6.06%, 29.29%, 27.27%, 8.08%, 16.16%, 1.01% and 2.02%, respectively). CONCLUSIONS: The obese group presented a higher prevalence of Candida albicans. Furthermore, Candida albicans, Candida kefyr and Rhodotorula mucilaginosa showed a high positive correlation with obesity, weight gain and fat mass and showed a negative correlation with high-density lipoprotein and lean mass, parameters related to weight loss.

Intestinal microbiota composition of patients with Behçet's disease: differences between eye, mucocutaneous and vascular involvement. The Rheuma-BIOTA study.

OBJECTIVES: Changes in microbiota composition affect the aetiology and patho-genesis of chronic diseases, including Behçet's disease (BD). However, no studies have analysed the potential gut microbiota changes among different clinical forms of BD. This study evaluated the intestinal microbiota composition of patients with BD and healthy controls and also compared differences between patients with BD with respect to eye, mucocutaneous, and vascular involvement. METHODS: In this prospective cohort study, 27 patients diagnosed with BD according to the International Study Group criteria and 10 age- and sex-matched healthy controls were included. Detailed intestinal microbiota analysis was performed. RESULTS: There were no differences between the BD group and the control group in terms of alpha and beta microbial diversity and abundance indices (p>0.05). Actinomyces, Libanicoccus, Collinsella, Eggerthella, Enetrohabdus, Catenibacterium, and Enterobacter were significantly higher in the BD group than in the control group. In addition, Bacteroides, Cricetibacter, Alistipes, Lachnospira, Dielma, Akkermansia, Sutterella, Anaerofilum, Ruminococcease-UCG007, Acetanaerobacterium, and Copropaacter were lower in the BD group than in the control group. When we compared three different system involvement (eye, mucocutaneous, and vascular), the linear discriminant analysis effective size revealed a difference for the following genera: Lachnospiraceae NK4A136 in the uveitis group; Dialister, Intestinomonas, and Marvinbryantia in the mucocutaneous group; and Gemella in the vascular group. CONCLUSIONS: The composition of intestinal microbiota was significantly different in patients with BD compared with healthy adults. Ours is the first study to show differences in microbiota composition in isolated mucocutaneous, eye, and vascular involvement. These findings should be evaluated in a larger series.

The microbiome in respiratory medicine: current challenges and future perspectives.

The healthy lung has previously been considered to be a sterile organ because standard microbiological culture techniques consistently yield negative results. However, culture-independent techniques report that large numbers of microorganisms coexist in the lung. There are many unknown aspects in the field, but available reports show that the lower respiratory tract microbiota: 1) is similar in healthy subjects to the oropharyngeal microbiota and dominated by members of the Firmicutes, Bacteroidetes and Proteobacteria phyla; 2) shows changes in smokers and well-defined differences in chronic respiratory diseases, although the temporal and spatial kinetics of these changes are only partially known; and 3) shows relatively abundant non-cultivable bacteria in chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, cystic fibrosis and bronchiectasis, with specific patterns for each disease. In all of these diseases, a loss of diversity, paralleled by an over-representation of Proteobacteria (dysbiosis), has been related to disease severity and exacerbations. However, it is unknown whether dysbiosis is a cause or a consequence of the damage to bronchoalveolar surfaces.Finally, little is known about bacterial functionality and the interactions between viruses, fungi and bacteria. It is expected that future research in bacterial gene expressions, metagenomics longitudinal analysis and host-microbiome animal models will help to move towards targeted microbiome interventions in respiratory diseases.

The respiratory microbiome in bronchial mucosa and secretions from severe IgE-mediated asthma patients.

BACKGROUND: The bronchial microbiome in chronic lung diseases presents an abnormal pattern, but its microbial composition and regional differences in severe asthma have not been sufficiently addressed. The aim of the study was to describe the bacterial community in bronchial mucosa and secretions of patients with severe chronic asthma chronically treated with corticosteroids in addition to usual care according to Global Initiative for Asthma. Bacterial community composition was obtained by 16S rRNA gene amplification and sequencing, and functional capabilities through PICRUSt. RESULTS: Thirteen patients with severe asthma were included and provided 11 bronchial biopsies (BB) and 12 bronchial aspirates (BA) suitable for sequence analyses. Bacteroidetes, Firmicutes, Proteobacteria and Actinobacteria showed relative abundances (RAs) over 5% in BB, a cutoff that was reached by Streptococcus and Prevotella at genus level. Legionella genus attained a median RA of 2.7 (interquartile range 1.1-4.7) in BB samples. In BA a higher RA of Fusobacteria was found, when compared with BB [8.7 (5.9-11.4) vs 4.2 (0.8-7.5), p = 0.037], while the RA of Proteobacteria was lower in BA [4.3 (3.7-6.5) vs 17.1 (11.2-33.4), p = 0.005]. RA of the Legionella genus was also significantly lower in BA [0.004 (0.001-0.02) vs. 2.7 (1.1-4.7), p = 0.005]. Beta-diversity analysis confirmed the differences between the microbial communities in BA and BB (R2 = 0.20, p = 0.001, Adonis test), and functional analysis revealed also statistically significant differences between both types of sample on Metabolism, Cellular processes, Human diseases, Organismal systems and Genetic information processing pathways. CONCLUSIONS: The microbiota in the bronchial mucosa of severe asthma has a specific pattern that is not accurately represented in bronchial secretions, which must be considered a different niche of bacteria growth.

Comparison of different assembly and annotation tools on analysis of simulated viral metagenomic communities in the gut.

BACKGROUND: The main limitations in the analysis of viral metagenomes are perhaps the high genetic variability and the lack of information in extant databases. To address these issues, several bioinformatic tools have been specifically designed or adapted for metagenomics by improving read assembly and creating more sensitive methods for homology detection. This study compares the performance of different available assemblers and taxonomic annotation software using simulated viral-metagenomic data. RESULTS: We simulated two 454 viral metagenomes using genomes from NCBI's RefSeq database based on the list of actual viruses found in previously published metagenomes. Three different assembly strategies, spanning six assemblers, were tested for performance: overlap-layout-consensus algorithms Newbler, Celera and Minimo; de Bruijn graphs algorithms Velvet and MetaVelvet; and read probabilistic model Genovo. The performance of the assemblies was measured by the length of resulting contigs (using N50), the percentage of reads assembled and the overall accuracy when comparing against corresponding reference genomes. Additionally, the number of chimeras per contig and the lowest common ancestor were estimated in order to assess the effect of assembling on taxonomic and functional annotation. The functional classification of the reads was evaluated by counting the reads that correctly matched the functional data previously reported for the original genomes and calculating the number of over-represented functional categories in chimeric contigs. The sensitivity and specificity of tBLASTx, PhymmBL and the k-mer frequencies were measured by accurate predictions when comparing simulated reads against the NCBI Virus genomes RefSeq database. CONCLUSIONS: Assembling improves functional annotation by increasing accurate assignations and decreasing ambiguous hits between viruses and bacteria. However, the success is limited by the chimeric contigs occurring at all taxonomic levels. The assembler and its parameters should be selected based on the focus of each study. Minimo's non-chimeric contigs and Genovo's long contigs excelled in taxonomy assignation and functional annotation, respectively.tBLASTx stood out as the best approach for taxonomic annotation for virus identification. PhymmBL proved useful in datasets in which no related sequences are present as it uses genomic features that may help identify distant taxa. The k-frequencies underperformed in all viral datasets.

Severity-related changes of bronchial microbiome in chronic obstructive pulmonary disease.

Bronchial colonization by potentially pathogenic microorganisms (PPMs) is often demonstrated in chronic obstructive pulmonary disease (COPD), but culture-based techniques identify only a portion of the bacteria in mucosal surfaces. The aim of the study was to determine changes in the bronchial microbiome of COPD associated with the severity of the disease. The bronchial microbiome of COPD patients was analyzed by 16S rRNA gene amplification and pyrosequencing in sputum samples obtained during stable disease. Seventeen COPD patients were studied (forced expiratory volume in the first second expressed as a percentage of the forced vital capacity [FEV1%] median, 35.0%; interquartile range [IQR], 31.5 to 52.0), providing a mean of 4,493 (standard deviation [SD], 2,598) sequences corresponding to 47 operational taxonomic units (OTUs) (SD, 17) at a 97% identity level. Patients were dichotomized according to their lung function as moderate to severe when their FEV1% values were over the median and as advanced when FEV1% values were lower. The most prevalent phyla in sputum were Proteobacteria (44%) and Firmicutes (16%), followed by Actinobacteria (13%). A greater microbial diversity was found in patients with moderate-to-severe disease, and alpha diversity showed a statistically significant decrease in patients with advanced disease when assessed by Shannon (ρ = 0.528; P = 0.029, Spearman correlation coefficient) and Chao1 (ρ = 0.53; P = 0.028, Spearman correlation coefficient) alpha-diversity indexes. The higher severity that characterizes advanced COPD is paralleled by a decrease in the diversity of the bronchial microbiome, with a loss of part of the resident flora that is replaced by a more restricted microbiota that includes PPMs.

Symbionts and pathogens: what is the difference?

The ecological relationships that organisms establish with others can be considered as broad and diverse as the forms of life that inhabit and interact in our planet. Those interactions can be considered as a continuum spectrum, ranging from beneficial to detrimental outcomes. However, this picture has revealed as more complex and dynamic than previously thought, involving not only factors that affect the two or more members that interact, but also external forces, with chance playing a crucial role in this interplay. Thus, defining a particular symbiont as mutualist or pathogen in an exclusive way, based on simple rules of classification is increasingly challenging if not unfeasible, since new methodologies are providing more evidences that depict exceptions, reversions and transitions within either side of this continuum, especially evident at early stages of symbiotic associations. This imposes a wider and more dynamic view of a complex landscape of interactions.

Comparison of Experimental Methodologies Based on Bulk-Metagenome and Virus-like Particle Enrichment: Pros and Cons for Representativeness and Reproducibility in the Study of the Fecal Human Virome.

Studies on the human virome based on the application of metagenomic approaches involve overcoming a series of challenges and limitations inherent not only to the biological features of viruses, but also to methodological pitfalls which different approaches have tried to minimize. These approaches fall into two main categories: bulk-metagenomes and virus-like particle (VLP) enrichment. In order to address issues associated with commonly used experimental procedures to assess the degree of reliability, representativeness, and reproducibility, we designed a comparative analysis applied to three experimental protocols, one based on bulk-metagenomes and two based on VLP enrichment. These protocols were applied to stool samples from 10 adult participants, including two replicas per protocol and subject. We evaluated the performances of the three methods, not only through the analysis of the resulting composition, abundance, and diversity of the virome via taxonomical classification and type of molecule (DNA versus RNA, single stranded vs. double stranded), but also according to how the a priori identical replicas differed from each other according to the extraction methods used. Our results highlight the strengths and weaknesses of each approach, offering valuable insights and tailored recommendations for drawing reliable conclusions based on specific research goals.

Correlated Responses to Selection for Intramuscular Fat on the Gut Microbiome in Rabbits.

Intramuscular fat (IMF) content is important for meat production and human health, where the host genetics and its microbiome greatly contribute to its variation. The aim of this study is to describe the consequences of the genetic modification of IMF by selecting the taxonomic composition of the microbiome, using rabbits from the 10th generation of a divergent selection experiment for IMF (high (H) and low (L) lines differ by 3.8 standard deviations). The selection altered the composition of the gut microbiota. Correlated responses were better distinguished at the genus level (51 genera) than at the phylum level (10 phyla). The H-line was enriched in Hungateiclostridium, Limosilactobacillus, Legionella, Lysinibacillus, Phorphyromonas, Methanosphaera, Desulfovibrio, and Akkermansia, while the L-line was enriched in Escherichia, Methanobrevibacter, Fonticella, Candidatus Amulumruptor, Methanobrevibacter, Exiguobacterium, Flintibacter, and Coprococcus, among other genera with smaller line differences. A microbial biomarker generated from the abundance of four of these genera classified the lines with 78% accuracy in a logit regression. Our results demonstrate different gut microbiome compositions in hosts with divergent IMF genotypes. Furthermore, we provide a microbial biomarker to be used as an indicator of hosts genetically predisposed to accumulate muscle lipids, which opens up the opportunity for research to develop probiotics or microbiome-based breeding strategies targeting IMF.

Associations between bacterial and fungal communities in the human gut microbiota and their implications for nutritional status and body weight.

This study examined the interplay between bacterial and fungal communities in the human gut microbiota, impacting on nutritional status and body weight. Cohorts of 10 participants of healthy weight, 10 overweight, and 10 obese individuals, underwent comprehensive analysis, including dietary, anthropometric, and biochemical evaluations. Microbial composition was studied via gene sequencing of 16S and ITS rDNA regions, revealing bacterial (bacteriota) and fungal (mycobiota) profiles. Bacterial diversity exceeded fungal diversity. Statistically significant differences in bacterial communities were found within healthy-weight, overweight, and obese groups. The Bacillota/Bacteroidota ratio (previously known as the Firmicutes/Bacteroidetes ratio) correlated positively with body mass index. The predominant fungal phyla were Ascomycota and Basidiomycota, with the genera Nakaseomyces, Kazachstania, Kluyveromyces, and Hanseniaspora, inversely correlating with weight gain; while Saccharomyces, Debaryomyces, and Pichia correlated positively with body mass index. Overweight and obese individuals who harbored a higher abundance of Akkermansia muciniphila, demonstrated a favorable lipid and glucose profiles in contrast to those with lower abundance. The overweight group had elevated Candida, positively linked to simple carbohydrate consumption. The study underscores the role of microbial taxa in body mass index and metabolic health. An imbalanced gut bacteriota/mycobiota may contribute to obesity/metabolic disorders, highlighting the significance of investigating both communities.

Composition of Microbiota in Transient and Mature Human Milk: Significant Changes in Large for Gestational Age Group.

The composition of the human milk (HM) microbiota and, consequently, the microorganisms that are passed on to the infant through breastfeeding, can be influenced by various factors such as the mother's health and diet, gestational age, delivery mode, lactation stage, method of infant feeding, and geographical location. The aim of the Human Milk-Gest Study was to compare the microbiota of transient (postpartum 7-15 days) and mature HM (postpartum 45-90 days) of 44 mothers, and to investigate any potential changes associated with preterm birth, mode of delivery, and birth weight in relation to gestational age. The data were classified into five study groups: normal spontaneous delivery-term (NS-T) newborns, cesarean delivery-term (CS-T) newborns, preterm (PT) newborns (with a gestational age of less than 37 weeks), small for gestational age (SGA) newborns, and large for gestational age (LGA) newborns. An analysis of differential abundance was conducted using ANCOM-BC to compare the microbial genera between transient and mature HM samples as well as between other study groups. A significant difference was detected between HM samples at different sampling times and between the study groups (p < 0.01). In transient HM samples, Ralstonia, Burkholderiaceae_uc, and Pelomonas were significantly dominant in the LGA group compared to the NS-T, CS-T, PT, and SGA groups. In mature HM samples, Burkholderiaceae_uc, Ralstonia, Pelomonas, and Klebsiella were significantly dominant in the LGA group compared to the NS-T, CS-T, and PT groups, while Ralstonia, Burkholderiaceae_uc, and Pelomonas were significantly dominant in the LGA group compared to the SGA group. Differences were also detected between the transient and mature HM samples in the CS-T, PT, SGA, and LGA groups, but no differences occurred in the NS-T groups. In conclusion, we showed that Ralstonia, Burkholderiaceae_uc, and Pelomonas were significantly dominant in the LGA group in transient HM and continued in mature HM. The body mass index (BMI) of the mothers in the LGA group was not >30 at conception, however, the maternal BMI at birth and maternal weight gain during pregnancy were higher than in the other groups. The nutritional composition of HM is specifically designed to meet infant nutritional requirements during early life. Evaluating the effects of HM microbiota on infant microbiota composition and short- and long-term health effects in larger studies would be useful.

Metformin-induced changes in the gut microbiome and plasma metabolome are associated with cognition in men.

BACKGROUND: An altered gut microbiome characterized by reduced abundance of butyrate producing bacteria and reduced gene richness is associated with type 2 diabetes (T2D). An important complication of T2D is increased risk of cognitive impairment and dementia. The biguanide metformin is a commonly prescribed medication for the control of T2D and metformin treatment has been associated with a significant reduction in the risk of dementia and improved cognition, particularly in people with T2D. AIM: To investigate the associations of metformin use with cognition exploring potential mechanisms by analyzing the gut microbiome and plasma metabolome using shotgun metagenomics and HPLC-ESI-MS/MS, respectively. METHODS: We explored two independent cohorts: an observational study (Aging Imageomics) and a phase IV, randomized, double-blind, parallel-group, randomized pilot study (MEIFLO). From the two studies, we analyzed four study groups: (1) individuals with no documented medical history or medical treatment (n = 172); (2) people with long-term T2D on metformin monotherapy (n = 134); (3) people with long-term T2D treated with oral hypoglycemic agents other than metformin (n = 45); (4) a newly diagnosed T2D subjects on metformin monotherapy (n = 22). Analyses were also performed stratifying by sex. RESULTS: Several bacterial species belonging to the Proteobacteria (Escherichia coli) and Verrucomicrobia (Akkermansia muciniphila) phyla were positively associated with metformin treatment, while bacterial species belonging to the Firmicutes phylum (Romboutsia timonensis, Romboutsia ilealis) were negatively associated. Due to the consistent increase in A. muciniphila and decrease in R.ilealis in people with T2D subjects treated with metformin, we investigated the association between this ratio and cognition. In the entire cohort of metformin-treated T2D subjects, the A.muciniphila/R.ilealis ratio was not significantly associated with cognitive test scores. However, after stratifying by sex, the A.muciniphila/R. ilealis ratio was significantly and positively associated with higher memory scores and improved memory in men. Metformin treatment was associated with an enrichment of microbial pathways involved in the TCA cycle, and butanoate, arginine, and proline metabolism in both cohorts. The bacterial genes involved in arginine metabolism, especially in production of glutamate (astA, astB, astC, astD, astE, putA), were enriched following metformin intake. In agreement, in the metabolomics analysis, metformin treatment was strongly associated with the amino acid proline, a metabolite involved in the metabolism of glutamate. CONCLUSIONS: The beneficial effects of metformin may be mediated by changes in the composition of the gut microbiota and microbial-host-derived co-metabolites.

Human Mastadenovirus A Infection in a Child During the Course of Hematopoietic Stem Cell Transplant.

Following primary infection, human mastadeno- viruses can persist in various tissues. We report a case of a pediatric patient with Fanconi anemia who had a complicated posttransplant course after allogeneic hematopoietic stem cell transplant that was associated with human mastadenovirus infection. Human mastadenovirus reactivation was detected with metagenomic analysis during a 3-month follow- up period; the predominant rate of occurrence of human mastadenoviruses was 1.1% on day 0, 84% on day +15, 90% on day +30, and 42% on day +82. Virus shedding continued up to 3 months after transplant. At 36 months after hematopoietic stem cell transplant, the patient was in good clinical condition with full donor chimerism. Long-term follow-up studies for human mastadenoviruses are needed to determine latency period.

Gut Microbiota Composition and Functionality Are Associated With REM Sleep Duration and Continuous Glucose Levels.

CONTEXT: Sleep disruption is associated with worse glucose metabolic control and altered gut microbiota in animal models. OBJECTIVE: We aimed to evaluate the possible links among rapid eye movement (REM) sleep duration, continuous glucose levels, and gut microbiota composition. METHODS: This observational, prospective, real-life, cross-sectional case-control study included 118 (60 with obesity), middle-aged (39.1-54.8 years) healthy volunteers recruited at a tertiary hospital. Glucose variability and REM sleep duration were assessed by 10-day continuous glucose monitoring (CGM) (Dexcom G6) and wrist actigraphy (Fitbit Charge 3), respectively. The coefficient of variation (CV), interquartile range (IQR), and SD of glucose variability was assessed and the percentage of time in range (% TIR), at 126-139 mg/dL (TIR2), and 140-199 mg/dL (TIR3) were calculated. Shotgun metagenomics sequencing was applied to study gut microbiota taxonomy and functionality. RESULTS: Increased glycemic variability (SD, CV, and IQR) was observed among subjects with obesity in parallel to increased % TIR2 and % TIR3. REM sleep duration was independently associated with % TIR3 (ß = -.339; P < .001) and glucose variability (SD, ß = -.350; P < .001). Microbial taxa from the Christensenellaceae family (Firmicutes phylum) were positively associated with REM sleep and negatively with CGM levels, while bacteria from Enterobacteriacea family and bacterial functions involved in iron metabolism showed opposite associations. CONCLUSION: Decreased REM sleep duration was independently associated with a worse glucose profile. The associations of species from Christensenellaceae and Enterobacteriaceae families with REM sleep duration and continuous glucose values suggest an integrated picture of metabolic health.

Gut microbiota links to serum ferritin and cognition.

Iron is required for the replication and growth of almost all bacterial species and in the production of myelin and neurotransmitters. Increasing clinical studies evidence that the gut microbiota plays a critical role in iron metabolism and cognition. However, the understanding of the complex iron-microbiome-cognition crosstalk remains elusive. In a recent study in the Aging Imageomics cohort (n = 1,030), we identified a positive association of serum ferritin (SF) with executive function (EF) as inferred from the semantic verbal fluency (SVF,) the total digit span (TDS) and the phonemic verbal fluency tests (PVF). Here, we explored the potential mechanisms by analyzing the gut microbiome and plasma metabolome using shotgun metagenomics and HPLC-ESI-MS/MS, respectively. Different bacterial species belonging to the Proteobacteria phylum (Klebsiella pneumoniae, Klebsiella michiganensis, Unclassified Escherichia) were negatively associated both with SF and executive function. At the functional level, an enrichment of microbial pathways involved in phenylalanine, arginine, and proline metabolism was identified. Consistently, phenylacetylglutamine, a metabolite derived from microbial catabolism of phenylalanine, was negatively associated with SF, EF, and semantic memory. Other metabolites such as ureidobutyric acid and 19,20-DiHDPA, a DHA-derived oxylipin, were also consistently and negatively associated with SF, EF, and semantic memory, while plasma eicosapentaenoic acid was positively associated. The associations of SF with cognition could be mediated by the gut microbiome through microbial-derived metabolites.

Analysis of Intestinal and Nasopharyngeal Microbiota of Children with Meningococcemia in Pediatric Intensive Care Unit: INMACS-PICU Study.

Microbiota composition might play a role in the pathophysiology and course of sepsis, and understanding its dynamics is of clinical interest. Invasive meningococcal disease (IMD) is an important cause of community-acquired serious infection, and there is no information regarding microbiota composition in children with meningococcemia. In this study, we aimed to evaluate the intestinal and nasopharyngeal microbiota composition of children with IMD. Materials and Methods: In this prospective, multi-center study, 10 children with meningococcemia and 10 age-matched healthy controls were included. Nasopharyngeal and fecal samples were obtained at admission to the intensive care unit and on the tenth day of their hospital stay. The V3 and V4 regions of the 16S rRNA gene were amplified following the 16S Metagenomic Sequencing Library Preparation. Results: Regarding the alpha diversity on the day of admission and on the tenth day at the PICU, the Shannon index was significantly lower in the IMD group compared to the control group (p = 0.002 at admission and p = 0.001, on the tenth day of PICU). A statistical difference in the stool samples was found between the IMD group at Day 0 vs. the controls in the results of the Bray-Curtis and Jaccard analyses (p = 0.005 and p = 0.001, respectively). There were differences in the intestinal microbiota composition between the children with IMD at admission and Day 10 and the healthy controls. Regarding the nasopharyngeal microbiota analysis, in the children with IMD at admission, at the genus level, Neisseria was significantly more abundant compared to the healthy children (p < 0.001). In the children with IMD at Day 10, genera Moraxella and Neisseria were decreased compared to the healthy children. In the children with IMD on Day 0, for paired samples, Moraxella, Neisseria, and Haemophilus were significantly more abundant compared to the children with IMD at Day 10. In the children with IMD at Day 10, the Moraxella and Neisseria genera were decreased, and 20 different genera were more abundant compared to Day 0. Conclusions: We first found alterations in the intestinal and nasopharyngeal microbiota composition in the children with IMD. The infection itself or the other care interventions also caused changes to the microbiota composition during the follow-up period. Understanding the interaction of microbiota with pathogens, e.g., N. meningitidis, could give us the opportunity to understand the disease's dynamics.