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Background: Despite mounting evidence of gut-brain involvement in psychiatric conditions, functional data remain limited, and analyses of other microbial niches, such as the vaginal microbiota, are lacking in relation to mental health. This aim of this study was to investigate if the connections between the gut microbiome and mental health observed in populations with a clinical diagnosis of mental illness extend to healthy women experiencing stress and depressive symptoms. Additionally, this study examined the functional pathways of the gut microbiota according to the levels of psychological symptoms. Furthermore, the study aimed to explore potential correlations between the vaginal microbiome and mental health parameters in young women without psychiatric diagnoses. Methods: In this cross-sectional study, 160 healthy Danish women (aged 18-40 years) filled out questionnaires with validated scales measuring symptoms of stress and depression and frequency of dietary intake. Fecal and vaginal microbiota samples were collected at the beginning of the menstrual cycle and vaginal samples were also collected at cycle day 8-12 and 18-22. Shotgun metagenomic profiling of the gut and vaginal microbiome was performed. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for functional profiling and 56 Gut Brain Modules were analyzed in the fecal samples. Results: The relative abundance in the gut of the genera Escherichia, Parabacteroides, and Shigella was higher in women with elevated depressive symptoms. Women with high perceived stress showed a tendency of increased abundance of Escherichia, Shigella, and Blautia. Amongst others, the potentially pathogenic genera, Escherichia and Shigella correlate with alterations in the neuroactive pathways such as the glutamatergic, GABAeric, dopaminergic, and Kynurenine pathways. Vaginosis symptoms were more prevalent in women reporting high levels of stress and depressive symptoms. Conclusions: The findings of this study suppor, De två första författarna delar förstaförfattarskapet.De två sista författarna delar sistaförfattarskapet.

Multidrug-resistant microorganisms have become a major public health concern around the world. The gut microbiome is a gold mine for bioactive compounds that protect the human body from pathogens. We used a multi-omics approach that integrated whole-genome sequencing (WGS) of 74 commensal gut microbiome isolates with metabolome analysis to discover their metabolic interaction with Salmonella and other antibiotic-resistant pathogens. We evaluated differences in the functional potential of these selected isolates based on WGS annotation profiles. Furthermore, the top altered metabolites in co-culture supernatants of selected commensal gut microbiome isolates were identified including a series of dipeptides and examined for their ability to prevent the growth of various antibiotic-resistant bacteria. Our results provide compelling evidence that the gut microbiome produces metabolites, including the compound class of dipeptides that can potentially be applied for anti-infection medication, especially against antibiotic-resistant pathogens. Our established pipeline for the discovery and validation of bioactive metabolites from the gut microbiome as novel candidates for multidrug-resistant infections represents a new avenue for the discovery of antimicrobial lead structures.

Species composition of the healthy adult gut microbiota tends to be stable over time. Destabilization of the gut microbiome under the influence of different factors is the main driver of the microbial dysbiosis and subsequent impacts on host physiology. Here, we used metagenomics data from a Swedish longitudinal cohort, to determine the stability of the gut microbiome and uncovered two distinct microbial species groups; persistent colonizing species (PCS) and transient colonizing species (TCS). We validated the continuation of this grouping, generating gut metagenomics data for additional time points from the same Swedish cohort. We evaluated the existence of PCS/TCS across different geographical regions and observed they are globally conserved features. To characterize PCS/TCS phenotypes, we performed bioreactor fermentation with faecal samples and metabolic modeling. Finally, using chronic disease gut metagenome and other multi-omics data, we identified roles of TCS in microbial dysbiosis and link with abnormal changes to host physiology., QC 20240926

We explored opportunities for personalized and predictive health care by collecting serial clinical measurements, health surveys, genomics, proteomics, autoantibodies, metabolomics, and gut microbiome data from 96 individuals who participated in a data-driven health coaching program over a 16-month period with continuous digital monitoring of activity and sleep. We generated a resource of >20,000 biological samples from this study and a compendium of >53 million primary data points for 558,032 distinct features. Multiomics factor analysis revealed distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet, and hormonal effects. For example, ethinyl estradiol, a common oral contraceptive, produced characteristic molecular and physiological effects, including increased levels of inflammation and impact on thyroid, cortisol levels, and pulse, that were distinct from other sources of variability observed in our study. In total, this work illustrates the value of combining deep molecular and digital monitoring of human health. A record of this paper's transparent peer review process is included in the supplemental information.

We explored opportunities for personalized and predictive health care by collecting serial clinical measurements, health surveys, genomics, proteomics, autoantibodies, metabolomics, and gut microbiome data from 96 individuals who participated in a data-driven health coaching program over a 16-month period with continuous digital monitoring of activity and sleep. We generated a resource of >20,000 biological samples from this study and a compendium of >53 million primary data points for 558,032 distinct features. Multiomics factor analysis revealed distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet, and hormonal effects. For example, ethinyl estradiol, a common oral contraceptive, produced characteristic molecular and physiological effects, including increased levels of inflammation and impact on thyroid, cortisol levels, and pulse, that were distinct from other sources of variability observed in our study. In total, this work illustrates the value of combining deep molecular and digital monitoring of human health. A record of this paper's transparent peer review process is included in the supplemental information., QC 20220407

Purpose The Swedish Maternal Microbiome (SweMaMi) project was initiated to better understand the dynamics of the microbiome in pregnancy, with longitudinal microbiome sampling, shotgun metagenomics, extensive questionnaires and health registry linkage. Participants Pregnant women were recruited before the 20th gestational week during 2017-2021 in Sweden. In total, 5439 pregnancies (5193 unique women) were included. For 3973 pregnancies (73%), samples were provided at baseline, and for 3141 (58%) at all three timepoints (second and third trimester and postpartum). In total, 38 591 maternal microbiome samples (vaginal, faecal and saliva) and 3109 infant faecal samples were collected. Questionnaires were used to collect information on general, reproductive and mental health, diet and lifestyle, complemented by linkage to the nationwide health registries, also used to follow up the health of the offspring (up to age 10). Findings to date The cohort is fairly representative for the total Swedish pregnant population (data from 2019), with 41% first-time mothers. Women with university level education, born in Sweden, with normal body mass index, not using tobacco-products and aged 30-34 years were slightly over-represented. Future plans The sample and data collection were finalised in November 2021. The next steps are the characterisation of the microbial DNA and linkage to the health and demographic information from the questionnaires and registries. The role of the microbiome on maternal and neonatal outcomes and early-childhood diseases will be explored (including preterm birth, miscarriage) and the role and interaction of other risk factors and confounders (including endometriosis, polycystic ovarian syndrome, diet, drug use). This is currently among the largest pregnancy cohorts in the world with longitudinal design and detailed and standardised microbiome sampling enabling follow-up of both mothers and children. The findings are expected to contribute greatly to the

STUDY QUESTION What is the microbiome profile across different body sites in relation to the normal menstrual cycle (with and without hormonal contraception), recurrent pregnancy loss (RPL) (before and during pregnancy, pregnancy loss or birth) and endometriosis (before, during and after surgery)? How do these profiles interact with genetics, environmental exposures, immunological and endocrine biomarkers? WHAT IS KNOWN ALREADY The microbiome is a key factor influencing human health and disease in areas as diverse as immune functioning, gastrointestinal disease and mental and metabolic disorders. There is mounting evidence to suggest that the reproductive microbiome may be influential in general and reproductive health, fertility and pregnancy outcomes. STUDY DESIGN, SIZE, DURATION This is a prospective, longitudinal, observational study using a systems biology approach in three cohorts totalling 920 participants. Since microbiome profiles by shot-gun sequencing have never been investigated in healthy controls during varying phases of the menstrual cycle, patients with RPL and patients with endometriosis, no formal sample size calculation can be performed. The study period is from 2017 to 2024 and allows for longitudinal profiling of study participants to enable deeper understanding of the role of the microbiome and of host–microbe interactions in reproductive health. PARTICIPANTS/MATERIALS, SETTING, METHODS Participants in each cohort are as follows: Part 1 MiMens—150 healthy women with or without hormonal contraception; Part 2 MiRPL—200 couples with RPL, 50 healthy couples with prior uncomplicated pregnancy and 150 newborns; Part 3 MiEndo—120 patients with endometriosis requiring surgery with or without hormonal treatment. Microbiome profiles from saliva, faeces, rectal mucosa, vaginal fluid and endometrium will be studied, as well as the Omics profile, endocrine disrupting chemicals and endocrine and immune factors in blood, hair, saliva and urine. Pregnancy loss

Temporal dynamics of the gut microbiota potentially limit the identification of microbial features associated with health status. Here, we used whole-genome metagenomic and 16S rRNA gene sequencing to characterize the intra-and inter-individual variations of gut microbiota composition and functional potential of a disease-free Swedish population (n = 75) over one year. We found that 23% of the total compositional variance was explained by intra-individual variation. The degree of intra-individual compositional variability was negatively associated with the abundance of Faecalibacterium prausnitzii (a butyrate producer) and two Bifidobacterium species. By contrast, the abundance of facultative anaerobes and aerotolerant bacteria such as Escherichia coli and Lactobacillus acidophilus varied extensively, independent of compositional stability. The contribution of intra-individual variance to the total variance was greater for functional pathways than for microbial species. Thus, reliable quantification of microbial features requires repeated samples to address the issue of intra-individual variations of the gut microbiota., QC 20220916

Temporal dynamics of the gut microbiota potentially limit the identification of microbial features associated with health status. Here, we used whole-genome metagenomic and 16S rRNA gene sequencing to characterize the intra- and inter-individual variations of gut microbiota composition and functional potential of a disease-free Swedish population (n = 75) over one year. We found that 23% of the total compositional variance was explained by intra-individual variation. The degree of intra-individual compositional variability was negatively associated with the abundance of Faecalibacterium prausnitzii (a butyrate producer) and two Bifidobacterium species. By contrast, the abundance of facultative anaerobes and aerotolerant bacteria such as Escherichia coli and Lactobacillus acidophilus varied extensively, independent of compositional stability. The contribution of intra-individual variance to the total variance was greater for functional pathways than for microbial species. Thus, reliable quantification of microbial features requires repeated samples to address the issue of intra-individual variations of the gut microbiota.

Background: The placenta plays an important role in the modulation of pregnancy immunity; however, there is no consensus regarding the existence of a placental microbiome in healthy full-term pregnancies. Objective: This study aimed to investigate the existence and origin of a placental microbiome. Study Design: A cross-sectional study comparing samples (3 layers of placental tissue, amniotic fluid, vernix caseosa, and saliva, vaginal, and rectal samples) from 2 groups of full-term births: 50 women not in labor with elective cesarean deliveries and 26 with vaginal deliveries. The comparisons were performed using polymerase chain reaction amplification and DNA sequencing techniques and bacterial culture experiments. Result: There were no significant differences regarding background characteristics between women who delivered by elective cesarean and those who delivered vaginally. Quantitative measurements of bacterial content in all 3 placental layers (quantitative polymerase chain reaction of the 16S ribosomal RNA gene) did not show any significant difference among any of the sample types and the negative controls. Here, 16S ribosomal RNA gene sequencing of the maternal side of the placenta could not differentiate between bacteria in the placental tissue and contamination of the laboratory reagents with bacterial DNA. Probe-specific quantitative polymerase chain reaction for bacterial taxa suspected to be present in the placenta could not detect any statistically significant difference between the 2 groups. In bacterial cultures, substantially more bacteria were observed in the placenta layers from vaginal deliveries than those from cesarean deliveries. In addition, 16S ribosomal RNA gene sequencing of bacterial colonies revealed that most of the bacteria that grew on the plates were genera typically found in human skin; moreover, it revealed that placentas delivered vaginally contained a high prevalence of common vaginal bacteria. Bacterial growth inhibition experi, De tre första författarna delar förstaförfattarskapet

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Motivation Full length, high resolution 16s rRNA marker gene sequencing has been challenging historically. Short amplicons provide high accuracy reads with widely available equipment, at the cost of taxonomic resolution. One recent proposal has been to reconstruct multiple amplicons along the full-length marker gene, however no barcode-free computationally tractable approach for this is available. To address this gap, we present Sidle (SMURF Implementation Done to acceLerate Efficiency), an implementation of the Short MUltiple Reads Framework algorithm with a novel tree building approach to reconstruct rRNA genes from individually amplified regions. Results Using simulated and real data, we compared Sidle to two other approaches of leveraging multiple gene region data. We found that Sidle had the least bias in non-phylogenetic alpha diversity, feature-based measures of beta diversity, and the reconstruction of individual clades. With a curated database, Sidle also provided the most precise species-level resolution. Availability and Implementation Sidle is available under a BSD 3 license from https://github.com/jwdebelius/q2-sidle

BACKGROUND: The placenta plays an important role in the modulation of pregnancy immunity; however, there is no consensus regarding the existence of a placental microbiome in healthy full-term pregnancies. OBJECTIVE: This study aimed to investigate the existence and origin of a placental microbiome. STUDY DESIGN: A cross-sectional study comparing samples (3 layers of placental tissue, amniotic fluid, vernix caseosa, and saliva, vaginal, and rectal samples) from 2 groups of full-term births: 50 women not in labor with elective cesarean deliveries and 26 with vaginal deliveries. The comparisons were performed using polymerase chain reaction amplification and DNA sequencing techniques and bacterial culture experiments. RESULTS: There were no significant differences regarding background characteristics between women who delivered by elective cesarean and those who delivered vaginally. Quantitative measurements of bacterial content in all 3 placental layers (quantitative polymerase chain reaction of the 16S ribosomal RNA gene) did not show any significant difference among any of the sample types and the negative controls. Here, 16S ribosomal RNA gene sequencing of the maternal side of the placenta could not differentiate between bacteria in the placental tissue and contamination of the laboratory reagents with bacterial DNA. Probe-specific quantitative polymerase chain reaction for bacterial taxa suspected to be present in the placenta could not detect any statistically significant difference between the 2 groups. In bacterial cultures, substantially more bacteria were observed in the placenta layers from vaginal deliveries than those from cesarean deliveries. In addition, 16S ribosomal RNA gene sequencing of bacterial colonies revealed that most of the bacteria that grew

The vaginal microbiome has been connected to a wide range of health outcomes. This has led to a thriving research environment but also to the use of conflicting methodologies to study its microbial composition. Here, we systematically assessed best practices for the sequencing-based characterization of the human vaginal microbiome. As far as 16S rRNA gene sequencing is concerned, the V1-V3 region performed best in silico, but limitations of current sequencing technologies meant that the V3-V4 region performed equally well. Both approaches presented very good agreement with qPCR quantification of key taxa, provided that an appropriate bioinformatic pipeline was used. Shotgun metagenomic sequencing presents an interesting alternative to 16S rRNA gene amplification and sequencing but requires deeper sequencing and more bioinformatic expertise and infrastructure. We assessed different tools for the removal of host reads and the taxonomic annotation of metagenomic reads, including a new, easy-to-build and -use reference database of vaginal taxa. This curated database performed as well as the best-performing previously published strategies. Despite the many advantages of shotgun sequencing, none of the shotgun approaches assessed here agreed with the qPCR data as well as the 16S rRNA gene sequencing. IMPORTANCE The vaginal microbiome has been connected to various aspects of host health, including susceptibility to sexually transmitted infections as well as gynecological cancers and pregnancy outcomes. This has led to a thriving research environment but also to conflicting available methodologies, including many studies that do not report their molecular biological and bioinformatic methods in sufficient detail to be considered reproducible. This can lead to conflicting messages and delay progress from descriptive to intervention studies. By systematically assessing best practices for the characterization of the human vaginal microbiome, this study will enable past studies, Correction in: MSPHERE, Volume:5, Issue:6, Article Number:e01253-20, DOI:10.1128/mSphere.01253-20 Page 1: This article was published on 18 November 2020 with the 11th author’s name misspelled. The byline was updated in the current version, posted on 16 December 2020.

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