Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics

The Characteristics of Gut Microbiota and Its Relation with Diet in Postmenopausal Osteoporosis

The gut microbiome is linked to osteoporosis. Previous clinical studies showed inconsistent results. This study aimed to characterize the gut microbiota feature and reveal its relation with diet in postmenopausal osteoporosis. Fifty-five postmenopausal women with osteoporosis (Op group) and forty-four age-matched postmenopausal women (normal bone mineral density, Con group) were included in this study. Fecal microbiota was collected and analyzed by shallow shotgun sequencing. Food frequency questionnaires were collected from both groups, and Spearman analysis was used to clarify its correlation with gut microbiota. A total of 2671 species from 29 phyla, 292 families, 152 orders, 80 classes were detected in the study. The two groups had no significant difference in the α and β diversity (p > 0.05). At the genus level, Anaerostipes was enriched in Op group (p < 0.05). At species level, Methanobrevibacter smithii, Bifidobacterium animalis, Rhodococcus defluvii, Lactobacillus plantarum, and Carnobacterium mobile were enriched in the Op group, while Bacillus luciferensis, Acetivibrio cellulolyticus, Citrobacter amalonaticus, and Bifidobacterium breve were differentially enriched in the Con group. Food frequency questionnaire showed that postmenopausal women with osteoporosis intaked more red meat, beer, white and red wine (p < 0.05), and the Con group had more yogurt, fruit, and tea consumption. Red meat consumption had a significant negative correlation with Streptosporangiales (p < 0.01) and Actinomadura (p < 0.05). Fruits intake negatively correlated with Nocardiaceae, Rhodococcus, and Rhodococcus defluvii (p < 0.05). More yogurt intake was consistently correlated with a greater abundance of Streptosporangiales. This study suggests that gut microbiota is significantly altered in the postmenopausal osteoporosis population at genus and species levels, and specific dietary intake might relate to these changes.

Probiotics Alleviate Microcystin-LR-Induced Developmental Toxicity in Zebrafish Larvae

Microcystin-LR (MCLR) poses a significant threat to aquatic ecosystems and public health. This study investigated the protective effects of the probiotic Lactobacillus rhamnosus against MCLR-induced developmental toxicity in zebrafish larvae. Zebrafish larvae were exposed to various concentrations of MCLR (0, 0.9, 1.8, and 3.6 mg/L) with or without L. rhamnosus from 72 to 168 h post-fertilization (hpf). Probiotic supplementation significantly improved survival, hatching, and growth rates and reduced malformation rates in MCLR-exposed larvae. L. rhamnosus alleviated MCLR-induced oxidative stress by reducing reactive oxygen species (ROS) levels and enhancing glutathione (GSH) content and catalase (CAT) activity. Probiotics also mitigated MCLR-induced lipid metabolism disorders by regulating key metabolites (triglycerides, cholesterol, bile acids, and free fatty acids) and gene expression (ppara, pparb, srebp1, and nr1h4). Moreover, 16S rRNA sequencing revealed that L. rhamnosus modulated the gut microbiome structure and diversity in MCLR-exposed larvae, promoting beneficial genera like Shewanella and Enterobacter and inhibiting potential pathogens like Vibrio. Significant correlations were found between gut microbiota composition and host antioxidant and lipid metabolism parameters. These findings suggest that L. rhamnosus exerts protective effects against MCLR toxicity in zebrafish larvae by alleviating oxidative stress, regulating lipid metabolism, and modulating the gut microbiome, providing insights into probiotic-based strategies for mitigating MCLR toxicity in aquatic organisms.

Host-Gut Microbiota Metabolic Interactions and Their Role in Precision Diagnosis and Treatment of Gastrointestinal Cancers

The critical role of the gut microbiome in gastrointestinal cancers is becoming increasingly clear. Imbalances in the gut microbial community, referred to as dysbiosis, are linked to increased risks for various forms of gastrointestinal cancers. Pathogens like Fusobacterium and Helicobacter pylori relate to the onset of esophageal and gastric cancers, respectively, while microbes such as Porphyromonas gingivalis and Clostridium species have been associated with a higher risk of pancreatic cancer. In colorectal cancer, bacteria such as Fusobacterium nucleatum are known to stimulate the growth of tumor cells and trigger cancer-promoting pathways. On the other hand, beneficial microbes like Bifidobacteria offer a protective effect, potentially inhibiting the development of gastrointestinal cancers. The potential for therapeutic interventions that manipulate the gut microbiome is substantial, including strategies to engineer anti-tumor metabolites and employ microbiota-based treatments. Despite the progress in understanding the influence of the microbiome on gastrointestinal cancers, significant challenges remain in identifying and understanding the precise contributions of specific microbial species and their metabolic products. This knowledge is essential for leveraging the role of the gut microbiome in the development of precise diagnostics and targeted therapies for gastrointestinal cancers.

Modulation of gut microbiota composition and predicted metabolic capacity after nutritional programming with a plant-rich diet in Atlantic salmon (Salmo salar): insights across developmental stages

To promote sustainable aquaculture, the formulation of Atlantic salmon (Salmo salar) feeds has changed in recent decades, focusing on replacing standard marine-based ingredients with plant-based alternatives, increasingly demonstrating successful outcomes in terms of fish performance. However, little is known about how these plant-based diets may impact the gut microbiota at first feeding and onwards. Nutritional programming (NP) is one strategy applied for exposing fish to a plant-based (V) diet at an early stage in life to promote full utilisation of plant-based ingredients and prevent potential adverse impacts of exposure to a plant-rich diet later in life. We investigated the impact of NP on gut microbiota by introducing fish to plant ingredients (V fish) during first feeding for a brief period of two weeks (stimulus phase) and compared those to fish fed a marine-based diet (M fish). Results demonstrated that V fish not only maintained growth performance at 16 (intermediate phase) and 22 (challenge phase) weeks post first feeding (wpff) when compared to M fish but also modulated gut microbiota. PERMANOVA general effects revealed gut microbiota dissimilarity by fish group (V vs. M fish) and phases (stimulus vs. intermediate vs. challenge). However, no interaction effect of both groups and phases was demonstrated, suggesting a sustained impact of V diet (nutritional history) on fish across time points/phases. Moreover, the V diet exerted a significant cumulative modulatory effect on the Atlantic salmon gut microbiota at 16 wpff that was not demonstrated at two wpff, although both fish groups were fed the M diet at 16 wpff. The nutritional history/dietary regime is the main NP influencing factor, whereas environmental and host factors significantly impacted microbiota composition in M fish. Microbial metabolic reactions of amino acid metabolism were higher in M fish when compared to V fish at two wpff suggesting microbiota played a role in digesting the essential amino acids of M feed. The excessive mucin O-degradation revealed in V fish at two wpff was mitigated in later life stages after NP, suggesting physiological adaptability and tolerance to V diet. Future studies are required to explore more fully how the microbiota functionally contributes to the NP.

A long journey to treat epilepsy with the gut microbiota

Epilepsy is a common neurological disorder that affects approximately 10.5 million children worldwide. Approximately 33% of affected patients exhibit resistance to all available antiseizure medications, but the underlying mechanisms are unknown and there is no effective treatment. Increasing evidence has shown that an abnormal gut microbiota may be associated with epilepsy. The gut microbiota can influence the function of the brain through multiple pathways, including the neuroendocrine, neuroimmune, and autonomic nervous systems. This review discusses the interactions between the central nervous system and the gastrointestinal tract (the brain-gut axis) and the role of the gut microbiota in the pathogenesis of epilepsy. However, the exact gut microbiota involved in epileptogenesis is unknown, and no consistent results have been obtained based on current research. Moreover, the target that should be further explored to identify a novel antiseizure drug is unclear. The role of the gut microbiota in epilepsy will most likely be uncovered with the development of genomics technology.

Isolation, molecular identification, and genomic analysis of Mangrovibacter phragmitis strain ASIOC01 from activated sludge harboring the bioremediation prowess of glycerol and organic pollutants in high-salinity

The physiological and genotypic characteristics of Mangrovibacter (MGB) remain largely unexplored, including their distribution and abundance within ecosystems. M. phragmitis (MPH) ASIOC01 was successfully isolated from activated sludge (AS), which was pre-enriched by adding 1,3-dichloro-2-propanol and 3-chloro-1,2-propanediol as carbon sources. The new isolate, MPH ASIOC01, exhibited resilience in a medium containing sodium chloride concentration up to 11% (with optimal growth observed at 3%) and effectively utilizing glycerol as their sole carbon source. However, species delimitation of MGBs remains challenging due to high 16S rRNA sequence similarity (greater than 99% ANI) among different MGBs. In contrast, among the housekeeping gene discrepancies, the tryptophan synthase beta chain gene can serve as a robust marker for fast species delimitation among MGBs. Furthermore, the complete genome of MPH ASIOC01 was fully sequenced and circlized as a single contig using the PacBio HiFi sequencing method. Comparative genomics revealed genes potentially associated with various phenotypic features of MGBs, such as nitrogen-fixing, phosphate-solubilizing, cellulose-digesting, Cr-reducing, and salt tolerance. Computational analysis suggested that MPH ASIOC01 may have undergone horizontal gene transfer events, possibly contributing unique traits such as antibiotic resistance. Finally, our findings also disclosed that the introduction of MPH ASIOC01 into AS can assist in the remediation of wastewater chemical oxygen demand, which was evaluated using gas chromatograph-mass spectrometry. To the best of our knowledge, this study offers the most comprehensive understanding of the phenotypic and genotypic features of MGBs to date.

Gut microbiome dynamics and predictive value in hospitalized COVID-19 patients: a comparative analysis of shallow and deep shotgun sequencing

The COVID-19 pandemic caused by SARS-CoV-2 has led to a wide range of clinical presentations, with respiratory symptoms being common. However, emerging evidence suggests that the gastrointestinal (GI) tract is also affected, with angiotensin-converting enzyme 2, a key receptor for SARS-CoV-2, abundantly expressed in the ileum and colon. The virus has been detected in GI tissues and fecal samples, even in cases with negative results of the reverse transcription polymerase chain reaction in the respiratory tract. GI symptoms have been associated with an increased risk of ICU admission and mortality. The gut microbiome, a complex ecosystem of around 40 trillion bacteria, plays a crucial role in immunological and metabolic pathways. Dysbiosis of the gut microbiota, characterized by a loss of beneficial microbes and decreased microbial diversity, has been observed in COVID-19 patients, potentially contributing to disease severity. We conducted a comprehensive gut microbiome study in 204 hospitalized COVID-19 patients using both shallow and deep shotgun sequencing methods. We aimed to track microbiota composition changes induced by hospitalization, link these alterations to clinical procedures (antibiotics administration) and outcomes (ICU referral, survival), and assess the predictive potential of the gut microbiome for COVID-19 prognosis. Shallow shotgun sequencing was evaluated as a cost-effective diagnostic alternative for clinical settings. Our study demonstrated the diverse effects of various combinations of clinical parameters, microbiome profiles, and patient metadata on the precision of outcome prognostication in patients. It indicates that microbiological data possesses greater reliability in forecasting patient outcomes when contrasted with clinical data or metadata. Furthermore, we established that shallow shotgun sequencing presents a viable and cost-effective diagnostic alternative to deep sequencing within clinical environments.

The interplay between the microbiota and opioid in the treatment of neuropathic pain

Neuropathic pain (NP) is characterized by its complex and multifactorial nature and limited responses to opioid therapy; NP is associated with risks of drug resistance, addiction, difficulty in treatment cessation, and psychological disorders. Emerging research on gut microbiota and their metabolites has demonstrated their effectiveness in alleviating NP and augmenting opioid-based pain management, concurrently mitigating the adverse effects of opioids. This review addresses the following key points: (1) the current advances in gut microbiota research and the challenges in using opioids to treat NP, (2) the reciprocal effects and benefits of gut microbiota on NP, and (3) the interaction between opioids with gut microbiota, as well as the benefits of gut microbiota in opioid-based treatment of NP. Through various intricate mechanisms, gut microbiota influences the onset and progression of NP, ultimately enhancing the efficacy of opioids in the management of NP. These insights pave the way for further pragmatic clinical research, ultimately enhancing the efficacy of opioid-based pain management.

New Molecules in Type 2 Diabetes: Advancements, Challenges and Future Directions

Although good glycemic control in patients with type 2 diabetes (T2D) can prevent cardiovascular complications, many diabetic patients still have poor optimal control. A new class of antidiabetic drugs (e.g., glucagon-like peptide-1-GLP-1 receptor agonists, sodium-glucose co-transporters-SGLT2 inhibitors), in addition to the low hypoglycemic effect, exert multiple beneficial effects at a metabolic and cardiovascular level, through mechanisms other than antihyperglycemic agents. This review aims to discuss the effects of these new antidiabetic drugs, highlighting cardiovascular and metabolic benefits, through the description of their action mechanisms as well as available data by preclinical and clinical studies. Moreover, new innovative tools in the T2D field will be described which may help to advance towards a better targeted T2D personalized care in future.

A metagenomic analysis of the phase 2 Anopheles gambiae 1000 genomes dataset reveals a wide diversity of cobionts associated with field collected mosquitoes

The Anopheles gambiae 1000 Genomes (Ag1000G) Consortium previously utilized deep sequencing methods to catalogue genetic diversity across African An. gambiae populations. We analyzed the complete datasets of 1142 individually sequenced mosquitoes through Microsoft Premonition's Bayesian mixture model based (BMM) metagenomics pipeline. All specimens were confirmed as either An. gambiae sensu stricto (s.s.) or An. coluzzii with a high degree of confidence ( > 98% identity to reference). Homo sapiens DNA was identified in all specimens indicating contamination may have occurred either at the time of specimen collection, preparation and/or sequencing. We found evidence of vertebrate hosts in 162 specimens. 59 specimens contained validated Plasmodium falciparum reads. Human hepatitis B and primate erythroparvovirus-1 viral sequences were identified in fifteen and three mosquito specimens, respectively. 478 of the 1,142 specimens were found to contain bacterial reads and bacteriophage-related contigs were detected in 27 specimens. This analysis demonstrates the capacity of metagenomic approaches to elucidate important vector-host-pathogen interactions of epidemiological significance.

A review of machine learning methods for cancer characterization from microbiome data

Recent studies have shown that the microbiome can impact cancer development, progression, and response to therapies suggesting microbiome-based approaches for cancer characterization. As cancer-related signatures are complex and implicate many taxa, their discovery often requires Machine Learning approaches. This review discusses Machine Learning methods for cancer characterization from microbiome data. It focuses on the implications of choices undertaken during sample collection, feature selection and pre-processing. It also discusses ML model selection, guiding how to choose an ML model, and model validation. Finally, it enumerates current limitations and how these may be surpassed. Proposed methods, often based on Random Forests, show promising results, however insufficient for widespread clinical usage. Studies often report conflicting results mainly due to ML models with poor generalizability. We expect that evaluating models with expanded, hold-out datasets, removing technical artifacts, exploring representations of the microbiome other than taxonomical profiles, leveraging advances in deep learning, and developing ML models better adapted to the characteristics of microbiome data will improve the performance and generalizability of models and enable their usage in the clinic.

Association of gastrointestinal microbiome and obesity with gestational diabetes mellitus-an updated globally based review of the high-quality literatures

OBJECTIVES

The purpose of this review is to investigate the relationship between gastrointestinal microbiome, obesity, and gestational diabetes mellitus (GDM) in an objective manner.

METHODS

We conducted a thorough and comprehensive search of the English language literatures published in PubMed, Web of Science, and the Cochrane Library from the establishment of the library until 12 December 2023. Our search strategy included both keywords and free words searches, and we strictly applied inclusion and exclusion criteria. Meta-analyses and systematic reviews were prepared.

RESULTS

Six high-quality literature sources were identified for meta-analysis. However, after detailed study and analysis, a certain degree of heterogeneity was found, and the credibility of the combined analysis results was limited. Therefore, descriptive analyses were conducted. The dysbiosis of intestinal microbiome, specifically the ratio of Firmicutes/Bacteroides, is a significant factor in the development of metabolic diseases such as obesity and gestational diabetes. Patients with intestinal dysbiosis and obesity are at a higher risk of developing GDM.

CONCLUSIONS

During pregnancy, gastrointestinal microbiome disorders and obesity may contribute to the development of GDM, with all three factors influencing each other. This finding could aid in the diagnosis and management of patients with GDM through further research on their gastrointestinal microbiome.

The macroecology of butyrate-producing bacteria via metagenomic assessment of butyrate production capacity

Butyrate-producing bacteria are found in many outdoor ecosystems and host organisms, including humans, and are vital to ecosystem functionality and human health. These bacteria ferment organic matter, producing the short-chain fatty acid butyrate. However, the macroecological influences on their biogeographical distribution remain poorly resolved. Here we aimed to characterise their global distribution together with key explanatory climatic, geographical and physicochemical variables. We developed new normalised butyrate production capacity (BPC) indices derived from global metagenomic (n = 13,078) and Australia-wide soil 16S rRNA (n = 1331) data, using Geographic Information System (GIS) and modelling techniques to detail their ecological and biogeographical associations. The highest median BPC scores were found in anoxic and fermentative environments, including the human (BPC = 2.99) and non-human animal gut (BPC = 2.91), and in some plant-soil systems (BPC = 2.33). Within plant-soil systems, roots (BPC = 2.50) and rhizospheres (BPC = 2.34) had the highest median BPC scores. Among soil samples, geographical and climatic variables had the strongest overall effects on BPC scores (variable importance score range = 0.30-0.03), with human population density also making a notable contribution (variable importance score = 0.20). Higher BPC scores were in soils from seasonally productive sandy rangelands, temperate rural residential areas and sites with moderate-to-high soil iron concentrations. Abundances of butyrate-producing bacteria in outdoor soils followed complex ecological patterns influenced by geography, climate, soil chemistry and hydrological fluctuations. These new macroecological insights further our understanding of the ecological patterns of outdoor butyrate-producing bacteria, with implications for emerging microbially focused ecological and human health policies.

The maternal microbiome in pregnancy, delivery, and early-stage development of neonatal microbiome after cesarean section: A prospective longitudinal study

INTRODUCTION

Changes within the maternal microbiome during the last trimester of pregnancy and the determinants of the subsequent neonatal microbiome establishment after delivery by elective cesarean section are described.

MATERIAL AND METHODS

Maternal vaginal and rectal microbiome samples were collected in the last trimester and before cesarean section; intrauterine cavity, placenta, neonatal buccal mucosa, skin, and meconium samples were obtained at birth; neonatal sample collection was repeated 2-3 days postnatally. Microbial community composition was analyzed by 16S rRNA gene amplicon sequencing. Relative abundance measurements of amplicon sequencing variants and sum counts at higher taxonomic levels were compared to test for significant overlap or differences in microbial community compositions.

CLINICALTRIALS

gov ID: NCT04489056.

RESULTS

A total of 30 mothers and their neonates were included with available microbiome samples for all maternal, intrauterine cavity and placenta samples, as well as for 18 of 30 neonates. The composition of maternal vaginal and rectal microbiomes during the last trimester of healthy pregnancies did not significantly change (permutational multivariate analysis of variance [PERMANOVA], p > 0.05). No robust microbial signature was detected in the intrauterine cavity, placenta, neonatal buccal mucosa, skin swabs, or meconium samples collected at birth. After birth, the neonatal microbiome was rapidly established, and significantly different microbial communities were detectable 2-3 days postnatally in neonate buccal mucosa and stool samples (PERMANOVA, p < 0.01).

CONCLUSIONS

Maternal vaginal and rectal microbiomes in healthy pregnancies remain stable during the third trimester. No microbial colonization of the neonate was observed before birth in healthy pregnancies. Neonatal microbiomes in infants delivered by cesarean section displayed a taxonomic composition distinct from maternal vaginal and rectal microbiomes at birth, indicating that postnatal exposure to the extrauterine environment is the driving source of initial neonatal microbiome development in this cohort.

Microbiome in gynecologic malignancies: a bibliometric analysis from 2012 to 2022

Microbiome and microbial dysbiosis have been proven to be involved in the carcinogenesis and treatment of gynecologic malignancies. However, there is a noticeable gap in the literature, as no comprehensive papers have covered general information, research status, and research frontiers in this field. This study addressed this gap by exploring the relationship between the gut and female reproductive tract (FRT) microbiome and gynecological cancers from a bibliometric perspective. Using VOSviewer 1.6.18, CiteSpace 6.1.R6, and HistCite Pro 2.1 software, we analyzed data retrieved from the Web of Science (WOS) Core Collection (WoSCC) database. Our dataset, consisting of 204 articles published from 2012 to 2022, revealed a consistent and upward publication trend. The United States and the United Kingdom were the primary driving forces, attributed to their prolificacy, high-quality output, and extensive cooperation. The University of Arizona Cancer Center, which is affiliated with the United States, ranked first among the top ten most prolific institutions. Frontiers in Cellular and Infection Microbiology emerged as the leading publisher. Herbst-Kralovetz MM led as the most productive author. Mitra A was the most influential author. Cervical cancer is notably associated with the microbiome, while endometrial and ovarian cancers are receiving increased attention in the last year. Intersections between the gut microbiome and estrogen are of growing importance. Current research focuses on identifying specific microbial species for etiological diagnosis, while frontiers mainly focus on the anticancer potential of microorganisms, such as regulating the effects of immune checkpoint inhibitors. In conclusion, this study sheds light on a novel and burgeoning direction of research, providing a one-stop overview of the microbiome in gynecologic malignancies. Its findings aim to help young researchers to identify research directions and future trends for ongoing investigations.

Variability and bias in microbiome metagenomic sequencing: an interlaboratory study comparing experimental protocols

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

Contact with caregivers is associated with composition of the infant gastrointestinal microbiome in the first 6 months of life

OBJECTIVES

Little is known about how physical contact at birth and early caregiving environments influence the colonization of the infant gastrointestinal microbiome. We investigated how infant contact with caregivers at birth and within the first 2 weeks of life relates to the composition of the gastrointestinal microbiome in a sample of U.S. infants (n = 60).

METHODS

Skin-to-skin and physical contact with caregivers at birth and early caregiving environments were surveyed at 2 weeks postpartum. Stool samples were collected from infants at 2 weeks, 2, 6, and 12 months of age and underwent 16S rRNA sequencing as a proxy for the gastrointestinal microbiome. Associations between early caregiving environments and alpha and beta diversity, and differential abundance of bacteria at the genus level were assessed using PERMANOVA, and negative binomial mixed models in DEseq2.

RESULTS

Time in physical contact with caregivers explained 10% of variation in beta diversity at 2 weeks' age. The number of caregivers in the first few weeks of life explained 9% of variation in beta diversity at 2 weeks and the number of individuals in physical contact at birth explained 11% of variation in beta diversity at 6 months. Skin-to-skin contact on the day of birth was positively associated with the abundance of eight genera. Infants held for by more individuals had greater abundance of eight genera.

DISCUSSION

Results reveal a potential mechanism (skin-to-skin and physical contact) by which caregivers influence the infant gastrointestinal microbiome. Our findings contribute to work exploring the social transmission of microbes.

Interwoven processes in fish development: microbial community succession and immune maturation

Fishes are hosts for many microorganisms that provide them with beneficial effects on growth, immune system development, nutrition and protection against pathogens. In order to avoid spreading of infectious diseases in aquaculture, prevention includes vaccinations and routine disinfection of eggs and equipment, while curative treatments consist in the administration of antibiotics. Vaccination processes can stress the fish and require substantial farmer's investment. Additionally, disinfection and antibiotics are not specific, and while they may be effective in the short term, they have major drawbacks in the long term. Indeed, they eliminate beneficial bacteria which are useful for the host and promote the raising of antibiotic resistance in beneficial, commensal but also in pathogenic bacterial strains. Numerous publications highlight the importance that plays the diversified microbial community colonizing fish (i.e., microbiota) in the development, health and ultimately survival of their host. This review targets the current knowledge on the bidirectional communication between the microbiota and the fish immune system during fish development. It explores the extent of this mutualistic relationship: on one hand, the effect that microbes exert on the immune system ontogeny of fishes, and on the other hand, the impact of critical steps in immune system development on the microbial recruitment and succession throughout their life. We will first describe the immune system and its ontogeny and gene expression steps in the immune system development of fishes. Secondly, the plurality of the microbiotas (depending on host organism, organ, and development stage) will be reviewed. Then, a description of the constant interactions between microbiota and immune system throughout the fish's life stages will be discussed. Healthy microbiotas allow immune system maturation and modulation of inflammation, both of which contribute to immune homeostasis. Thus, immune equilibrium is closely linked to microbiota stability and to the stages of microbial community succession during the host development. We will provide examples from several fish species and describe more extensively the mechanisms occurring in zebrafish model because immune system ontogeny is much more finely described for this species, thanks to the many existing zebrafish mutants which allow more precise investigations. We will conclude on how the conceptual framework associated to the research on the immune system will benefit from considering the relations between microbiota and immune system maturation. More precisely, the development of active tolerance of the microbiota from the earliest stages of life enables the sustainable establishment of a complex healthy microbial community in the adult host. Establishing a balanced host-microbiota interaction avoids triggering deleterious inflammation, and maintains immunological and microbiological homeostasis.

Contigs directed gene annotation (ConDiGA) for accurate protein sequence database construction in metaproteomics

BACKGROUND

Microbiota are closely associated with human health and disease. Metaproteomics can provide a direct means to identify microbial proteins in microbiota for compositional and functional characterization. However, in-depth and accurate metaproteomics is still limited due to the extreme complexity and high diversity of microbiota samples. It is generally recommended to use metagenomic data from the same samples to construct the protein sequence database for metaproteomic data analysis. Although different metagenomics-based database construction strategies have been developed, an optimization of gene taxonomic annotation has not been reported, which, however, is extremely important for accurate metaproteomic analysis.

RESULTS

Herein, we proposed an accurate taxonomic annotation pipeline for genes from metagenomic data, namely contigs directed gene annotation (ConDiGA), and used the method to build a protein sequence database for metaproteomic analysis. We compared our pipeline (ConDiGA or MD3) with two other popular annotation pipelines (MD1 and MD2). In MD1, genes were directly annotated against the whole bacterial genome database; in MD2, contigs were annotated against the whole bacterial genome database and the taxonomic information of contigs was assigned to the genes; in MD3, the most confident species from the contigs annotation results were taken as reference to annotate genes. Annotation tools, including BLAST, Kaiju, and Kraken2, were compared. Based on a synthetic microbial community of 12 species, it was found that Kaiju with the MD3 pipeline outperformed the others in the construction of protein sequence database from metagenomic data. Similar performance was also observed with a fecal sample, as well as in silico mixed datasets of the simulated microbial community and the fecal sample.

CONCLUSIONS

Overall, we developed an optimized pipeline for gene taxonomic annotation to construct protein sequence databases. Our study can tackle the current taxonomic annotation reliability problem in metagenomics-derived protein sequence database and can promote the in-depth metaproteomic analysis of microbiome. The unique metagenomic and metaproteomic datasets of the 12 bacterial species are publicly available as a standard benchmarking sample for evaluating various analysis pipelines. The code of ConDiGA is open access at GitHub for the analysis of microbiota samples. Video Abstract.

Maternal gut microbiota in the health of mothers and offspring: from the perspective of immunology

Due to the physiological alteration during pregnancy, maternal gut microbiota changes following the metabolic processes. Recent studies have revealed that maternal gut microbiota is closely associated with the immune microenvironment in utero during pregnancy and plays a vital role in specific pregnancy complications, including preeclampsia, gestational diabetes, preterm birth and recurrent miscarriages. Some other evidence has also shown that aberrant maternal gut microbiota increases the risk of various diseases in the offspring, such as allergic and neurodevelopmental disorders, through the immune alignment between mother and fetus and the possible intrauterine microbiota. Probiotics and the high-fiber diet are effective inventions to prevent mothers and fetuses from diseases. In this review, we summarize the role of maternal gut microbiota in the development of pregnancy complications and the health condition of future generations from the perspective of immunology, which may provide new therapeutic strategies for the health management of mothers and offspring.

Functional contribution of the intestinal microbiome in autism spectrum disorder, attention deficit hyperactivity disorder, and Rett syndrome: a systematic review of pediatric and adult studies

Introduction

Critical phases of neurodevelopment and gut microbiota diversification occur in early life and both processes are impacted by genetic and environmental factors. Recent studies have shown the presence of gut microbiota alterations in neurodevelopmental disorders. Here we performed a systematic review of alterations of the intestinal microbiota composition and function in pediatric and adult patients affected by autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Rett syndrome (RETT).

Methods

We searched selected keywords in the online databases of PubMed, Cochrane, and OVID (January 1980 to December 2021) with secondary review of references of eligible articles. Two reviewers independently performed critical appraisals on the included articles using the Critical Appraisal Skills Program for each study design.

Results

Our systematic review identified 18, 7, and 3 original articles describing intestinal microbiota profiles in ASD, ADHD, and RETT, respectively. Decreased Firmicutes and increased Bacteroidetes were observed in the gut microbiota of individuals affected by ASD and ADHD. Proinflammatory cytokines, short-chain fatty acids and neurotransmitter levels were altered in ASD and RETT. Constipation and visceral pain were related to changes in the gut microbiota in patients affected by ASD and RETT. Hyperactivity and impulsivity were negatively correlated with Faecalibacterium (phylum Firmicutes) and positively correlated with Bacteroides sp. (phylum Bacteroidetes) in ADHD subjects. Five studies explored microbiota-or diet-targeted interventions in ASD and ADHD. Probiotic treatments with Lactobacillus sp. and fecal microbiota transplantation from healthy donors reduced constipation and ameliorated ASD symptoms in affected children. Perinatal administration of Lactobacillus sp. prevented the onset of Asperger and ADHD symptoms in adolescence. Micronutrient supplementation improved disease symptomatology in ADHD without causing significant changes in microbiota communities' composition.

Discussion

Several discrepancies were found among the included studies, primarily due to sample size, variations in dietary practices, and a high prevalence of functional gastrointestinal symptoms. Further studies employing longitudinal study designs, larger sample sizes and multi-omics technologies are warranted to identify the functional contribution of the intestinal microbiota in developmental trajectories of the human brain and neurobehavior.

Systematic review registration

https://clinicaltrials.gov/, CRD42020158734.

Skin aging-related microbial types separated by Cutibacterium and α-diversity

BACKGROUND

Studies on the skin microbiome have been conducted to uncover the relationship between skin microbes and the host. However, most of these studies have primarily focused on analyzing individual microbial compositions, which has resulted in a limited understanding of the overall relationship.

METHODS

We analyzed the facial skin characteristics and microbial profiles of 100 healthy Korean female volunteers using the V1-V2 region of the 16S ribosomal RNA gene.

RESULTS

The two most prominent features of the facial skin microbiome, the proportion of Cutibacterium and α-diversity, were associated with most of the skin characteristics. Based on clustering results, we proposed four types of facial skin microbiome: type C for Cutibacterium, type B for balanced, type CB for those between types C and B, and type O for others. Type C, which has a high proportion of Cutibacterium, showed high levels of pigmentation, wrinkles, pores, and sagging pores, indicating a tendency for severe skin aging. Type B, which has no dominant species and high microbial diversity, had lower values for pigmentation and wrinkles indicating less severe skin aging. Type CB was an intermediate type between type C and type B in terms of microbial composition and the level of skin aging. Type O dominated by microorganisms other than Cutibacterium, had high levels of sebum and pores but low levels of wrinkles.

CONCLUSION

We proposed a criterion for classifying facial skin microbial types, each of which showed distinct facial skin aging features. Our simplified microbial types will contribute to a better understanding of facial skin microbial studies.

Benchmarking a targeted 16S ribosomal RNA gene enrichment approach to reconstruct ancient microbial communities

The taxonomic characterization of ancient microbiomes is a key step in the rapidly growing field of paleomicrobiology. While PCR amplification of the 16S ribosomal RNA (rRNA) gene is a widely used technique in modern microbiota studies, this method has systematic biases when applied to ancient microbial DNA. Shotgun metagenomic sequencing has proven to be the most effective method in reconstructing taxonomic profiles of ancient dental calculus samples. Nevertheless, shotgun sequencing approaches come with inherent limitations that could be addressed through hybridization enrichment capture. When employed together, shotgun sequencing and hybridization capture have the potential to enhance the characterization of ancient microbial communities. Here, we develop, test, and apply a hybridization enrichment capture technique to selectively target 16S rRNA gene fragments from the libraries of ancient dental calculus samples generated with shotgun techniques. We simulated data sets generated from hybridization enrichment capture, indicating that taxonomic identification of fragmented and damaged 16S rRNA gene sequences was feasible. Applying this enrichment approach to 15 previously published ancient calculus samples, we observed a 334-fold increase of ancient 16S rRNA gene fragments in the enriched samples when compared to unenriched libraries. Our results suggest that 16S hybridization capture is less prone to the effects of background contamination than 16S rRNA amplification, yielding a higher percentage of on-target recovery. While our enrichment technique detected low abundant and rare taxa within a given sample, these assignments may not achieve the same level of specificity as those achieved by unenriched methods.

Understanding gut microbiome-based machine learning platforms: A review on therapeutic approaches using deep learning

Human beings possess trillions of microbial cells in a symbiotic relationship. This relationship benefits both partners for a long time. The gut microbiota helps in many bodily functions from harvesting energy from digested food to strengthening biochemical barriers of the gut and intestine. But the changes in microbiota composition and bacteria that can enter the gastrointestinal tract can cause infection. Several approaches like culture-independent techniques such as high-throughput and meta-omics projects targeting 16S ribosomal RNA (rRNA) sequencing are popular methods to investigate the composition of the human gastrointestinal tract microbiota and taxonomically characterizing microbial communities. The microbiota conformation and diversity should be provided by whole-genome shotgun metagenomic sequencing of site-specific community DNA associating genome mapping, gene inventory, and metabolic remodelling and reformation, to ease the functional study of human microbiota. Preliminary examination of the therapeutic potency for dysbiosis-associated diseases permits investigation of pharmacokinetic-pharmacodynamic changes in microbial communities for escalation of treatment and dosage plan. Gut microbiome study is an integration of metagenomics which has influenced the field in the last two decades. And the incorporation of artificial intelligence and deep learning through "omics-based" methods and microfluidic evaluation enhanced the capability of identification of thousands of microbes.

Gut Microbiome Changes in Anorexia Nervosa: A Comprehensive Review

Anorexia nervosa (AN) remains a challenging condition in psychiatric management and its pathogenesis is not yet fully understood. An imbalance in the gut microbiota composition may contribute to its pathophysiology. This review aims to explore the link between the human gut microbiota and AN (objective 1) or refeeding syndrome in AN (objective 2). The online databases MEDLINE and PsycINFO were searched for relevant studies. A total of 14 studies met the inclusion and exclusion criteria and only answered objective 1. A total of 476 AN patients, 554 healthy-weight (HC) controls, and 0 patients with other psychiatric disorders were included. Compared to HC, there were consistently reduced abundances of Faecalibacterium prausnitzii and Roseburia inulinivorans, and increased Methanobrevibacter smithii, in AN patients. Changes in alpha diversity were inconsistent, while beta diversity increased in four of six studies. Our model suggests that an imbalance in gut microbiota composition leads to reduced short-chain fatty acids, contributing to a proinflammatory state in AN, which is also common in other psychiatric comorbidities. Microbial changes may also contribute to the semistarvation state through endocrine changes and altered energy utilization.

Emerging tools for uncovering genetic and transcriptomic heterogeneities in bacteria

Bacterial communities display an astonishing degree of heterogeneities among their constituent cells across both the genomic and transcriptomic levels, giving rise to diverse social interactions and stress-adaptation strategies indispensable for proliferating in the natural environment (Ackermann in Nat Rev Microbiol 13:497-508, 2015). Our knowledge about bacterial heterogeneities and their physiological ramifications critically depends on our ability to unambiguously resolve the genetic and phenotypic states of the individual cells that make up the population. In this short review, I highlight several recently developed methods for studying bacterial heterogeneities, primarily focusing on single-cell techniques based on advanced sequencing and microscopy technologies. I will discuss the working principle of each technique as well as the types of problems each technique is best positioned to address. With significant improvements in resolution and throughput, these emerging tools together offer unprecedented and complementary views of various types of heterogeneities found within bacterial populations, paving the way for mechanistic dissections and systematic interventions in laboratory and clinical settings.

Association between primary Sjögren's syndrome and gut microbiota disruption: a systematic review and meta-analysis

Evidence of gut microbiota disruption for numerous autoimmune diseases has accumulated. Recently, the relationship between the microbiota and primary Sjögren's disease has been increasingly investigated but has yet to be systematically elucidated. Therefore, a meta-analysis of publications dealing on topic was conducted. Case-control studies comparing primary Sjögren's syndrome patients and healthy controls (HCs) were systematically searched in nine databases from inception to March 1, 2023. The primary result quantitatively evaluated in this meta-analysis was the α-diversity. The secondary results qualitatively extracted and analyzed were the β-diversity and relative abundance. In total, 22 case-control studies covering 915 pSS patients and 2103 HCs were examined. The quantitative analysis revealed a slight reduction in α-diversity in pSS patients compared to HCs, with a lower Shannon-Wiener index (SMD =  - 0.46, (- 0.68, - 0.25), p < 0.0001, I2 = 71%), Chao1 richness estimator (SMD =  - 0.59, (- 0.86, - 0.32), p < 0.0001, I2 = 81%), and ACE index (SMD =  - 0.92, (- 1.64, - 0.19), p = 0.01, I2 = 86%). However, the Simpson index (SMD = 0.01, (- 0.43, 0.46) p = 0.95, I2 = 86%) was similar in the two groups. The β-diversity significantly differed between pSS patients and HCs. Variations in the abundance of specific microbes and their metabolites and potential functions contribute to the pSS pathogenesis. Notably, the abundance of the phylum Firmicutes decreased, while that of Proteobacteria increased. SCFA-producing microbes including Ruminococcaceae, Lachnospiraceae, Faecalibacterium, Butyricicoccus, and Eubacterium hallii were depleted. In addition to diversity, the abundances of some specific microbes were related to clinical parameters. According to this systematic review and meta-analysis, gut microbiota dysbiosis, including reduced diversity, was associated with proinflammatory bacterium enrichment and anti-inflammatory bacterium depletion in pSS patients. Further research on the relationship between the gut microbiota and pSS is warranted.

Hierarchical eco-evo dynamics mediated by the gut microbiome

The concept of eco-evolutionary (eco-evo) dynamics, stating that ecological and evolutionary processes occur at similar time scales and influence each other, has contributed to our understanding of responses of populations, communities, and ecosystems to environmental change. Phenotypes, central to these eco-evo processes, can be strongly impacted by the gut microbiome. The gut microbiome shapes eco-evo dynamics in the host community through its effects on the host phenotype. Complex eco-evo feedback loops between the gut microbiome and the host communities might thus be common. Bottom-up dynamics occur when eco-evo interactions shaping the gut microbiome affect host phenotypes with consequences at population, community, and ecosystem levels. Top-down dynamics occur when eco-evo dynamics shaping the host community structure the gut microbiome.

The gut microbiota and its biogeography

Biogeography is the study of species distribution and diversity within an ecosystem and is at the core of how we understand ecosystem dynamics and interactions at the macroscale. In gut microbial communities, a historical reliance on bulk sequencing to probe community composition and dynamics has overlooked critical processes whereby microscale interactions affect systems-level microbiota function and the relationship with the host. In recent years, higher-resolution sequencing and novel single-cell level data have uncovered an incredible heterogeneity in microbial composition and have enabled a more nuanced spatial understanding of the gut microbiota. In an era when spatial transcriptomics and single-cell imaging and analysis have become key tools in mammalian cell and tissue biology, many of these techniques are now being applied to the microbiota. This fresh approach to intestinal biogeography has given important insights that span temporal and spatial scales, from the discovery of mucus encapsulation of the microbiota to the quantification of bacterial species throughout the gut. In this Review, we highlight emerging knowledge surrounding gut biogeography enabled by the observation and quantification of heterogeneity across multiple scales.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

Microbial ensemble in the hives: deciphering the intricate gut ecosystem of hive and forager bees of Apis mellifera

BACKGROUND

The gut microbiome of honey bees significantly influences vital traits and metabolic processes, including digestion, detoxification, nutrient provision, development, and immunity. However, there is a limited information is available on the gut bacterial diversity of western honey bee populations in India. This study addresses the critical knowledge gap and outcome of which would benefit the beekeepers in India.

METHODS AND RESULTS

This study investigates the gut bacterial diversity in forager and hive bees of Indian Apis mellifera, employing both culture-based and culture-independent methods. In the culturable study, a distinct difference in gut bacterial alpha and beta diversity between forager and hive bees emerges. Firmicutes, Proteobacteria, and Actinobacteria dominate, with hive bees exhibiting a Firmicutes-rich gut (65%), while foragers showcase a higher proportion of Proteobacteria (37%). Lactobacillus in the hive bee foregut aligns with the findings by other researchers. Bacterial amplicon sequencing analysisreveals a more intricate bacterial composition with 18 identified phyla, expanding our understanding compared to culturable methods. Hive bees exhibit higher community richness and diversity, likely due to diverse diets and increased social interactions. The core microbiota includes Snodgrassella alvi, Gilliamella apicola, and Bombilactobacillus mellis and Lactobacillus helsingborgensis, crucial for digestion, metabolism, and pathogen resistance. The study emphasises bacteria's role in pollen and nectar digestion, with specific groups like Lactobacillus and Bifidobobacterium spp. associated with carbohydrate metabolism and polysaccharide breakdown. These microbes aid in starch and sucrose digestion, releasing beneficial short-chain fatty acids.

CONCLUSION

This research highlights the intricate relationship between honey bees and their gut microbiota, showcasing how the diverse and complex microbiome helps bees overcome dietary challenges and enhances overall host health. Understanding these interactions contributes to bee ecology knowledge and has implications for honey bee health management, emphasising the need for further exploration and conservation efforts.

Performance of a Shotgun Prediction Model for Colorectal Cancer When Using 16S rRNA Sequencing Data

Colorectal cancer (CRC), the third most common cancer globally, has shown links to disturbed gut microbiota. While significant efforts have been made to establish a microbial signature indicative of CRC using shotgun metagenomic sequencing, the challenge lies in validating this signature with 16S ribosomal RNA (16S) gene sequencing. The primary obstacle is reconciling the differing outputs of these two methodologies, which often lead to divergent statistical models and conclusions. In this study, we introduce an algorithm designed to bridge this gap by mapping shotgun-derived taxa to their 16S counterparts. This mapping enables us to assess the predictive performance of a shotgun-based microbiome signature using 16S data. Our results demonstrate a reduction in performance when applying the 16S-mapped taxa in the shotgun prediction model, though it retains statistical significance. This suggests that while an exact match between shotgun and 16S data may not yet be feasible, our approach provides a viable method for comparative analysis and validation in the context of CRC-associated microbiome research.

The adolescent and young adult microbiome and its association with substance use: a scoping review

AIMS

The microbiome is a critical factor in health throughout human development. The aims of this scoping review are to (i) elucidate the differences between the youth (post-natal day 21-65 for rodents, 2-7 years for non-human primates, and 10-25 years for humans) microbiome with other life stages and (ii) identify youth-specific microbial changes associated with substance use.

METHODS

Peer-reviewed studies published up to May 2023 were identified in PubMed and SCOPUS and included gut and oral microbiome studies from rodents, non-human primates, and humans (N = 1733). Twenty-six articles were determined eligible based on inclusion criteria (aim 1: n = 19, aim 2: n = 7).

RESULTS

The adolescent and young adult oral and gut microbiomes are distinct compared to other life stages, within both non-human and human models. While there is limited research in this area, the microbiome appears to be vulnerable to substance use exposure earlier in life, including substances commonly initiated and escalated during adolescence and young adulthood (i.e. alcohol, cannabis, and tobacco).

CONCLUSIONS

Studies across the lifespan indicate that adolescence and young adulthood are distinct periods of development, where the microbiome is sensitive to exposures, including substance use. There is a need for more studies focused on the adolescent and young adult microbiome and substance use, as well as focused on the oral microbiome during this developmental period. Understanding the gut and oral microbiome during adolescence and young adulthood may provide insight into the pathophysiology of substance use disorders.

The Evolving Microbiome of Dental Caries

Dental caries is a significant oral and public health problem worldwide, especially in low-income populations. The risk of dental caries increases with frequent intake of dietary carbohydrates, including sugars, leading to increased acidity and disruption of the symbiotic diverse and complex microbial community of health. Excess acid production leads to a dysbiotic shift in the bacterial biofilm composition, demineralization of tooth structure, and cavities. Highly acidic and acid-tolerant species associated with caries include Streptococcus mutans, Lactobacillus, Actinomyces, Bifidobacterium, and Scardovia species. The differences in microbiotas depend on tooth site, extent of carious lesions, and rate of disease progression. Metagenomics and metatranscriptomics not only reveal the structure and genetic potential of the caries-associated microbiome, but, more importantly, capture the genetic makeup of the metabolically active microbiome in lesion sites. Due to its multifactorial nature, caries has been difficult to prevent. The use of topical fluoride has had a significant impact on reducing caries in clinical settings, but the approach is costly; the results are less sustainable for high-caries-risk individuals, especially children. Developing treatment regimens that specifically target S. mutans and other acidogenic bacteria, such as using nanoparticles, show promise in altering the cariogenic microbiome, thereby combatting the disease.

Limited impact of weathered residues from the Deepwater Horizon oil spill on the gut-microbiome and foraging behavior of sheepshead minnows (Cyprinodon variegatus)

The Deepwater Horizon disaster of April 2010 was the largest oil spill in U.S. history and exerted catastrophic effects on several ecologically important fish species in the Gulf of Mexico (GoM). Within fish, the microbiome plays a key symbiotic role in maintaining host health and aids in acquiring nutrients, supporting immune function, and modulating behavior. The aim of this study was to examine if exposure to weathered oil might produce significant shifts in fish gut-associated microbial communities as determined from taxa and genes known for hydrocarbon degradation, and whether foraging behavior was affected. The gut microbiome (16S rRNA and shotgun metagenomics) of sheepshead minnow (Cyprinodon variegatus) was characterized after fish were exposed to oil in High Energy Water Accommodated Fractions (HEWAF; tPAH = 81.1 ± 12.4 µg/L) for 7 days. A foraging behavioral assay was used to determine feeding efficiency before and after oil exposure. The fish gut microbiome was not significantly altered in alpha or beta diversity. None of the most abundant taxa produced any significant shifts as a result of oil exposure, with only rare taxa showing significant shifts in abundance between treatments. However, several bioindicator taxa known for hydrocarbon degradation were detected in the oil treatment, primarily Sphingomonas and Acinetobacter. Notably, the genus Stenotrophomonas was detected in high abundance in 16S data, which previously was not described as a core member of fish gut microbiomes. Data also demonstrated that behavior was not significantly affected by oil exposure. Potential low bioavailability of the oil may have been a factor in our observation of minor shifts in taxa and no behavioral effects. This study lays a foundation for understanding the microbiome of captive sheepshead minnows and indicates the need for further research to elucidate the responses of the fish gut-microbiome under oil spill conditions.

The Diversity of Bacteriophages in the Human Gut

Bacteriophages, commonly referred to as phages, are viruses that infect bacteria and are among the most numerous microorganisms on the planet. They occur throughout nature occupying every habitat where their bacterial hosts can be found. Within these communities, phages are responsible for shaping the bacterial community structure and function through their interactions. Phages shape the community structure and function within the human gut but are also able to influence the human host. As such, there is increased interest in understanding the composition and activity of the gastrointestinal phages, although these studies have been hindered by the difficulties accompanying the study of the human gut. Here, we summarize the methods and findings pertaining to the diversity of the human gastrointestinal phages.

Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach

Next-generation sequencing workflows, using either metabarcoding or metagenomic approaches, have massively contributed to expanding knowledge of the human gut microbiota, but methodological bias compromises reproducibility across studies. Where these biases have been quantified within several comparative analyses on their own, none have measured inter-laboratory reproducibility using similar DNA material. Here, we designed a multicenter study involving seven participating laboratories dedicated to partial- (P1 to P5), full-length (P6) metabarcoding, or metagenomic profiling (MGP) using DNA from a mock microbial community or extracted from 10 fecal samples collected at two time points from five donors. Fecal material was collected, and the DNA was extracted according to the IHMS protocols. The mock and isolated DNA were then provided to the participating laboratories for sequencing. Following sequencing analysis according to the laboratories' routine pipelines, relative taxonomic-count tables defined at the genus level were provided and analyzed. Large variations in alpha-diversity between laboratories, uncorrelated with sequencing depth, were detected among the profiles. Half of the genera identified by P1 were unique to this partner and two-thirds of the genera identified by MGP were not detected by P3. Analysis of beta-diversity revealed lower inter-individual variance than inter-laboratory variances. The taxonomic profiles of P5 and P6 were more similar to those of MGP than those obtained by P1, P2, P3, and P4. Reanalysis of the raw sequences obtained by partial-length metabarcoding profiling, using a single bioinformatic pipeline, harmonized the description of the bacterial profiles, which were more similar to each other, except for P3, and closer to the profiles obtained by MGP. This study highlights the major impact of the bioinformatics pipeline, and primarily the database used for taxonomic annotation. Laboratories need to benchmark and optimize their bioinformatic pipelines using standards to monitor their effectiveness in accurately detecting taxa present in gut microbiota.

Twnbiome: a public database of the healthy Taiwanese gut microbiome

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. Database URL: http://twnbiome.cgm.ntu.edu.tw/ .

Association between Dietary Intake and Faecal Microbiota in Children with Cystic Fibrosis

A "high-fat, high-energy diet" is commonly recommended for children with cystic fibrosis (CF), leading to negative consequences on dietary patterns that could contribute to altered colonic microbiota. The aim of this study was to assess dietary intake and to identify possible associations with the composition of faecal microbiota in a cohort of children with CF. A cross-sectional observational study was conducted, including a 3-day food record simultaneously with the collection of faecal samples. The results showed a high fat intake (43.9% of total energy intake) and a mean dietary fibre intake of 10.6 g/day. The faecal microbiota was characterised at the phylum level as 54.5% Firmicutes and revealed an altered proportion between Proteobacteria (32%) and Bacteroidota (2.2%). Significant associations were found, including a negative association between protein, meat, and fish intake and Bifidobacterium, a positive association between lipids and Escherichia/Shigella and Streptococcus, a negative association between carbohydrates and Veillonella and Klebsiella, and a positive association between total dietary fibre and Bacteroides and Roseburia. The results reveal that a "high-fat, high-energy" diet does not satisfy dietary fibre intake from healthy food sources in children with CF. Further interventional studies are encouraged to explore the potential of shifting to a high-fibre or standard healthy diet to improve colonic microbiota.

A metagenomic analysis for combination therapy of multiple classes of antibiotics on the prevention of the spread of antibiotic-resistant genes

Antibiotics used systemically to treat infections may have off-target effects on the gut microbiome, potentially resulting in the emergence of drug-resistant bacteria or selection of pathogenic species. These organisms may present a risk to the host and spread to the environment with a risk of transmission in the community. To investigate the risk of emergent antibiotic resistance in the gut microbiome following systemic treatment with antibiotics, this metagenomic analysis project used next-generation sequencing, a custom-built metagenomics pipeline, and differential abundance analysis to study the effect of antibiotics (ampicillin, ciprofloxacin, and fosfomycin) in monotherapy and different combinations at high and low doses, to determine the effect on resistome and taxonomic composition in the gut of Balb/c mice. The results showed that low-dose monotherapy treatments showed little change in microbiome composition but did show an increase in expression of many antibiotic-resistant genes (ARGs) posttreatment. Dual combination treatments allowed the emergence of some conditionally pathogenic bacteria and some increase in the abundance of ARGs despite a general decrease in microbiota diversity. Triple combination treatment was the most successful in inhibiting emergence of relevant opportunistic pathogens and completely suppressed all ARGs after 72 h of treatment. The relative abundances of mobile genetic elements that can enhance transmission of antibiotic resistance either decreased or remained the same for combination therapy while increasing for low-dose monotherapy. Combination therapy prevented the emergence of ARGs and decreased bacterial diversity, while low-dose monotherapy treatment increased ARGs and did not greatly change bacterial diversity.

The Next Generation Fecal Microbiota Transplantation: To Transplant Bacteria or Virome

Fecal microbiota transplantation (FMT) has emerged as a promising therapeutic approach for dysbiosis-related diseases. However, the clinical practice of crude fecal transplants presents limitations in terms of acceptability and reproductivity. Consequently, two alternative solutions to FMT are developed: transplanting bacteria communities or virome. Advanced methods for transplanting bacteria mainly include washed microbiota transplantation and bacteria spores treatment. Transplanting the virome is also explored, with the development of fecal virome transplantation, which involves filtering the virome from feces. These approaches provide more palatable options for patients and healthcare providers while minimizing research heterogeneity. In general, the evolution of the next generation of FMT in global trends is fecal microbiota components transplantation which mainly focuses on transplanting bacteria or virome.

MiTree: A Unified Web Cloud Analytic Platform for User-Friendly and Interpretable Microbiome Data Mining Using Tree-Based Methods

The advent of next-generation sequencing has greatly accelerated the field of human microbiome studies. Currently, investigators are seeking, struggling and competing to find new ways to diagnose, treat and prevent human diseases through the human microbiome. Machine learning is a promising approach to help such an effort, especially due to the high complexity of microbiome data. However, many of the current machine learning algorithms are in a "black box", i.e., they are difficult to understand and interpret. In addition, clinicians, public health practitioners and biologists are not usually skilled at computer programming, and they do not always have high-end computing devices. Thus, in this study, we introduce a unified web cloud analytic platform, named MiTree, for user-friendly and interpretable microbiome data mining. MiTree employs tree-based learning methods, including decision tree, random forest and gradient boosting, that are well understood and suited to human microbiome studies. We also stress that MiTree can address both classification and regression problems through covariate-adjusted or unadjusted analysis. MiTree should serve as an easy-to-use and interpretable data mining tool for microbiome-based disease prediction modeling, and should provide new insights into microbiome-based diagnostics, treatment and prevention. MiTree is an open-source software that is available on our web server.

Natural products derived from medicinal plants and microbes might act as a game-changer in breast cancer: a comprehensive review of preclinical and clinical studies

Breast cancer (BC) is the most prevalent neoplasm among women. Genetic and environmental factors lead to BC development and on this basis, several preventive - screening and therapeutic interventions have been developed. Hormones, both in the form of endogenous hormonal signaling or hormonal contraceptives, play an important role in BC pathogenesis and progression. On top of these, breast microbiota includes both species with an immunomodulatory activity enhancing the host's response against cancer cells and species producing proinflammatory cytokines associated with BC development. Identification of novel multitargeted therapeutic agents with poly-pharmacological potential is a dire need to combat advanced and metastatic BC. A growing body of research has emphasized the potential of natural compounds derived from medicinal plants and microbial species as complementary BC treatment regimens, including dietary supplements and probiotics. In particular, extracts from plants such as Artemisia monosperma Delile, Origanum dayi Post, Urtica membranacea Poir. ex Savigny, Krameria lappacea (Dombey) Burdet & B.B. Simpson and metabolites extracted from microbes such as Deinococcus radiodurans and Streptomycetes strains as well as probiotics like Bacillus coagulans and Lactobacillus brevis MK05 have exhibited antitumor effects in the form of antiproliferative and cytotoxic activity, increase in tumors' chemosensitivity, antioxidant activity and modulation of BC - associated molecular pathways. Further, bioactive compounds like 3,3'-diindolylmethane, epigallocatechin gallate, genistein, rutin, resveratrol, lycopene, sulforaphane, silibinin, rosmarinic acid, and shikonin are of special interest for the researchers and clinicians because these natural agents have multimodal action and act via multiple ways in managing the BC and most of these agents are regularly available in our food and fruit diets. Evidence from clinical trials suggests that such products had major potential in enhancing the effectiveness of conventional antitumor agents and decreasing their side effects. We here provide a comprehensive review of the therapeutic effects and mechanistic underpinnings of medicinal plants and microbial metabolites in BC management. The future perspectives on the translation of these findings to the personalized treatment of BC are provided and discussed.

The Future Is Now: Unraveling the Expanding Potential of Human (Necro)Microbiome in Forensic Investigations

The relevance of postmortem microbiological examinations has been controversial for decades, but the boom in advanced sequencing techniques over the last decade is increasingly demonstrating their usefulness, namely for the estimation of the postmortem interval. This comprehensive review aims to present the current knowledge about the human postmortem microbiome (the necrobiome), highlighting the main factors influencing this complex process and discussing the principal applications in the field of forensic sciences. Several limitations still hindering the implementation of forensic microbiology, such as small-scale studies, the lack of a universal/harmonized workflow for DNA extraction and sequencing technology, variability in the human microbiome, and limited access to human cadavers, are discussed. Future research in the field should focus on identifying stable biomarkers within the dominant Bacillota and Pseudomonadota phyla, which are prevalent during postmortem periods and for which standardization, method consolidation, and establishment of a forensic microbial bank are crucial for consistency and comparability. Given the complexity of identifying unique postmortem microbial signatures for robust databases, a promising future approach may involve deepening our understanding of specific bacterial species/strains that can serve as reliable postmortem interval indicators during the process of body decomposition. Microorganisms might have the potential to complement routine forensic tests in judicial processes, requiring robust investigations and machine-learning models to bridge knowledge gaps and adhere to Locard's principle of trace evidence.

Metagenomic characterization of the cecal microbiota community and functions in finishing pigs fed fermented Boehmeria nivea

Ramie (Boehmeria nivea, BN) is used as livestock forage through suitable silage fermentation owing to its nutritional value. To date, relatively few studies have investigated the effects of dietary fermented BN (FBN) on gut health in finishing pigs. The aim of the present study was to investigate the effects of dietary supplementation with 20% FBN on intestinal morphology, gene expression, and the functional response of the gut microbiota in finishing pigs. We found that FBN did not significantly affect serum antioxidant enzyme activities, ileal morphology, or the expression of genes encoding antioxidant enzymes, inflammatory cytokines, or tight junction proteins in the liver of the pigs. However, the gene expression levels of aryl hydrocarbon receptor (AHR) and interleukin 6 (IL6) were significantly downregulated in the ileum. A metagenomic analysis demonstrated that, compared with that seen in the control group, the cecal microbiota of pigs in the FBN treatment group was more closely clustered and contained a greater number of unique microbes. Bacteria were the predominant kingdom in the cecal microbiota, while Firmicutes, Bacteroidetes, and Proteobacteria were the dominant phyla, and Streptococcus, Lactobacillus, and Prevotella were the dominant genera. Dietary FBN significantly increased the abundance of the probiotic bacterium Roseburia inulinivorans (p < 0.05). Functional analysis of the cecal microbiota showed that ABC transporter levels and glycolysis/gluconeogenesis-associated functions were diminished in FBN-fed pigs. Meanwhile, CAZyme analysis revealed that dietary FBN significantly downregulated the contents of carbohydrate-active enzymes, such as GT2, GH1, GH25, and GH13_31. In addition, cytochrome P450 analysis revealed that the abundance of CYP51 and CYP512 decreased with FBN treatment. An assessment of antibiotic resistance based on the Comprehensive Antibiotic Resistance Database (CARD) annotation indicated that the cecal microbes from pigs in the FBN treatment group had increased resistance to lincosamide, streptogramin, and chloramphenicol and reduced resistance to amikacin, isepamicin, neomycin, lividomycin, gentamicin, paromomycin, ribostamycin, and butirosin. Finally, virulence factor-related analysis showed that putative hemolysin-associated functions were decreased, whereas fibronectin-binding protein, flagella, and alginate-associated functions were increased. Taken together, our data showed that FBN supplementation exerted only minor effects on intestinal morphology and microbial community composition, suggesting that it is potentially safe for use as a supplement in the diets of finishing pigs. However, more studies are needed to validate its functionality.

Shotgun metagenomics captures more microbial diversity than targeted 16S rRNA gene sequencing for field specimens and preserved museum specimens

The use of museum specimens for research in microbial evolutionary ecology remains an under-utilized investigative dimension with important potential. Despite this potential, there remain barriers in methodology and analysis to the wide-spread adoption of museum specimens for such studies. Here, we hypothesized that there would be significant differences in taxonomic prediction and related diversity among sample type (museum or fresh) and sequencing strategy (medium-depth shotgun metagenomic or 16S rRNA gene). We found dramatically higher predicted diversity from shotgun metagenomics when compared to 16S rRNA gene sequencing in museum and fresh samples, with this differential being larger in museum specimens. Broadly confirming these hypotheses, the highest diversity found in fresh samples was with shotgun sequencing using the Rep200 reference inclusive of viruses and microeukaryotes, followed by the WoL reference database. In museum-specimens, community diversity metrics also differed significantly between sequencing strategies, with the alpha-diversity ACE differential being significantly greater than the same comparisons made for fresh specimens. Beta diversity results were more variable, with significance dependent on reference databases used. Taken together, these findings demonstrate important differences in diversity results and prompt important considerations for future experiments and downstream analyses aiming to incorporate microbiome datasets from museum specimens.

The Human Ocular Surface Microbiome and Its Associations with the Tear Proteome in Dry Eye Disease

Although dry eye disease (DED) is one of the most common ocular surface diseases worldwide, its pathogenesis is incompletely understood, and treatment options are limited. There is growing evidence that complex interactions between the ocular surface microbiome (OSM) and tear fluid constituents, potentially leading to inflammatory processes, are associated with ocular surface diseases such as DED. In this study, we aimed to find unique compositional and functional features of the OSM associated with human and microbial tear proteins in patients with DED. Applying whole-metagenome shotgun sequencing of forty lid and conjunctival swabs, we identified 229 taxa, with Actinobacteria and Proteobacteria being the most abundant phyla and Propionibacterium acnes the dominating species in the cohort. When DED patients were compared to controls, the species Corynebacterium tuberculostearicum was more abundant in conjunctival samples, whereas the family Propionibacteriaceae was more abundant in lid samples. Functional analysis showed that genes of L-lysine biosynthesis, tetrapyrrole biosynthesis, 5-aminoimidazole ribonucleotide biosynthesis, and the super pathway of L-threonine biosynthesis were enriched in conjunctival samples of controls. The relative abundances of Acinetobacter johnsonii correlated with seven human tear proteins, including mucin-16. The three most abundant microbial tear proteins were the chaperone protein DnaK, the arsenical resistance protein ArsH, and helicase. Compositional and functional features of the OSM and the tear proteome are altered in patients with DED. Ultimately, this may help to design novel interventional therapeutics to target DED.

Meta-Analysis of Publicly Available Clinical and Preclinical Microbiome Data From Studies of Burn Injury

Following burn injury, alterations in host commensal microbiota across body spaces may leave patients susceptible to opportunistic pathogens and serious sequelae such as sepsis. Generally, studies examining the microbiome postburn have had a limited sample size and lack of longitudinal data, which coupled with experimental and analytic variation, impacts overall interpretation. We performed a meta-analysis of publicly available sequencing data from preclinical and clinical burn studies to determine if there were consistent alterations in the microbiome across various anatomical sites and hosts. Ten human and animal 16S rRNA sequencing studies spanning respiratory, urinary, cutaneous, and gastrointestinal microbiomes were included. Taxonomic classification and alpha and beta diversity metrics were analyzed using QIIME2 v2021.8. Alpha diversity was consistently higher in control samples compared to burn-injured samples which were also different based on host and anatomical location; however, phylogenetic evaluation (ie, Faith PD) elucidated more significant differences compared to taxonomic metrics (ie, Shannon entropy). Beta diversity analysis based on weighted UniFrac showed that rodent specimens clustered less closely to humans than pig samples for both rectal and skin sources. Host species and performing institute were found to have a significant impact on community structure. In rectal samples, bacterial composition in pig and human burn samples included Bacteroidetes, Firmicutes, and Proteobacteria, while rodent samples were dominated by Firmicutes. Proteobacteria and Firmicutes increased on burned skin in each host species. Our results suggest that host species and the performing institute strongly influence microbiome structure. Burn-induced alterations in microbiome diversity and taxa exist across hosts, with phylogenetic metrics more valuable than others. Coordinated, multicenter studies, both clinical and preclinical, within the burn community are needed to more completely realize the diagnostic and therapeutic potential of the microbiome for improving outcomes postburn.

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes. IMPORTANCE Mapping the interrelationships between different species in a microbial community is important for understanding and controlling their structure and function. The surge in the high-throughput sequencing of microbial communities has led to the creation of thousands of data sets containing information about microbial abundances. These abundances can be transformed into co-occurrence networks, providing a glimpse into the associations within microbiomes. However, processing these data sets to obtain co-occurrence information relies on several complex steps, each of which involves numerous choices of tools and corresponding parameters. These multiple options pose questions about the robustness and uniqueness of the inferred networks. In this study, we address this workflow and provide a systematic analysis of how these choices of tools affect the final network and guidelines on appropriate tool selection for a particular data set. We also develop a consensus network algorithm that helps generate more robust co-occurrence networks based on benchmark synthetic data sets.

Deciphering the functional diversity of the gut microbiota of the black soldier fly (Hermetia illucens): recent advances and future challenges

Bioconversion using insects is a promising strategy to convert organic waste (catering leftovers, harvest waste, food processing byproducts, etc.) into biomass that can be used for multiple applications, turned into high added-value products, and address environmental, societal and economic concerns. Due to its ability to feed on a tremendous variety of organic wastes, the black soldier fly (Hermetia illucens) has recently emerged as a promising insect for bioconversion of organic wastes on an industrial scale. A growing number of studies have highlighted the pivotal role of the gut microbiota in the performance and health of this insect species. This review aims to provide a critical overview of current knowledge regarding the functional diversity of the gut microbiota of H. illucens, highlighting its importance for bioconversion, food safety and the development of new biotechnological tools. After providing an overview of the different strategies that have been used to outline the microbial communities of H. illucens, we discuss the diversity of these gut microbes and the beneficial services they can provide to their insect host. Emphasis is placed on technical strategies and aspects of host biology that require special attention in the near future of research. We also argue that the singular digestive capabilities and complex gut microbiota of H. illucens make this insect species a valuable model for addressing fundamental questions regarding the interactions that insects have evolved with microorganisms. By proposing new avenues of research, this review aims to stimulate research on the microbiota of a promising insect to address the challenges of bioconversion, but also fundamental questions regarding bacterial symbiosis in insects.