Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants

Early-life exposures and the microbiome: implications for IBD prevention

The early-life period is one of microbiome establishment and immune maturation. Early-life exposures are increasingly being recognised to play an important role in IBD risk. The composition of functions of the gut microbiome in the prenatal, perinatal, and postnatal period may be crucial towards development of health or disease, including IBD, later in life. We herein present a comprehensive summary of the interplay between early-life factors and microbiome perturbations, and their association with risk of IBD. In addition, we provide an overview of host and external factors in early life that are known to impact gut microbiome maturation and exposures implicated in IBD risk. Considering the emerging concept of IBD prevention, we propose strategies to minimise maternal and offspring exposure to potentially harmful variables and recommend protective measures during pregnancy and the postpartum period. This holistic view of early-life factors and microbiome signatures among mothers and their offspring will help frame our current understanding of their importance towards IBD pathogenesis and frame the roadmap for preventive strategies.

Initial Post-Release Performance of Cultured Cyprinus chilia Juveniles in a Shallow Lake in Southwestern China

The post-release performance of cultured fish is crucial for understanding the viability of cultured fish and assessing the effects of stock enhancement programs. This study aimed to investigate the initial post-release performance of cultured Cyprinus chilia juveniles by examining their movement, spatial distribution, gut fullness, and gut microbiota in nature. In July 2022, a total of 20,000 C. chilia juveniles, tagged with visible implant fluorescence (VIE), were released into Qilu Lake, a shallow lake in southwestern China. Subsequently, continuous recapture was conducted at fixed recapture sites using trap nets during the first 7 days, one month and three months after release. Out of the released fish, 512 were recaptured, resulting in a recapture rate of 2.56%. The recaptured fish had a 100% tag retention rate. The majority (98.05%) of the recaptured fish were found in the recapture sites located on the eastern or western lakeshore, while only 10 fish were recaptured from the recapture sites in the northern lake area. The water depth range where the recaptured fish were found ranged from 190 to 350 cm, with most fish preferring depths less than 300 cm. The majority of the released fish migrated towards the eastern and western lakeshore, with long-distance movement (greater than 100 m) primarily occurring within the first four days after release. The level of gut fullness in the released fish initially decreased and then increased over time following release. Regarding gut microbiota, the dominant phyla observed in most samples were Firmicutes, Proteobacteria, Cyanobacteria, and Fusobacteria. Furthermore, significant variations in the dominant genera were observed across different samples. Principal coordinates analysis (PCoA) revealed clear separation between the microbial communities of pre-release and post-release C. chilia juveniles. This study demonstrated that VIE tagging was a suitable method for short-term marking of C. chilia juveniles. Lakeshores with water depths less than 300 cm were identified as preferred habitats for C. chilia juveniles. The primary adaptation period for cultured C. chilia juveniles released into the natural environment was found to be approximately 4-5 days. These findings contribute to our understanding of the post-release performance of cultured fish and may provide guidance for the management and evaluation of relevant stock enhancement programs.

Early gut microbiota intervention in premature infants: Application perspectives

BACKGROUND

Preterm birth is the leading cause of death in children under the age of five. One of the major factors contributing to the high risk of diseases and deaths in premature infants is the incomplete development of the intestinal immune system. The gut microbiota has been widely recognized as a critical factor in promoting the development and function of the intestinal immune system after birth. However, the gut microbiota of premature infants is at high risk of dysbiosis, which is highly associated with adverse effects on the development and education of the early life immune system. Early intervention can modulate the colonization and development of gut microbiota and has a long-term influence on the development of the intestinal immune system.

AIM OF REVIEW

This review aims to summarize the characterization, interconnection, and underlying mechanism of gut microbiota and intestinal innate immunity in premature infants, and to discuss the status, applicability, safety, and prospects of different intervention strategies in premature infants, thus providing an overview and outlook of the current applications and remaining gaps of early intervention strategies in premature infants.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review is focused on three key concepts. Firstly, the gut microbiota of premature infants is at high risk of dysbiosis, resulting in dysfunctional intestinal immune system processes. Secondly, contributing roles of early intervention have been observed in improving the intestinal environment and promoting gut microbiota colonization, which is significant in the development and function of gut immunity in premature infants. Thirdly, different strategies of early intervention, such as probiotics, fecal microbiota transplantation, and nutrients, show different safety, applicability, and outcome in premature infants, and the underlying mechanism is complex and poorly understood.

Selecting 16S rRNA Primers for Microbiome Analysis in a Host-Microbe System: The Case of the Jellyfish Rhopilema nomadica

Amplicon sequencing of the 16S rRNA gene is extensively used to characterize bacterial communities, including those living in association with eukaryotic hosts. Deciding which region of the 16S rRNA gene to analyze and selecting the appropriate PCR primers remains a major decision when initiating any new microbiome study. Based on a detailed literature survey of studies focusing on cnidarian microbiomes, we compared three commonly used primers targeting different hypervariable regions of the 16S rRNA gene, V1V2, V3V4, and V4V5, using the jellyfish Rhopilema nomadica as a model. Although all primers exhibit a similar pattern in bacterial community composition, the performance of the V3V4 primer set was superior to V1V2 and V4V5. The V1V2 primers misclassified bacteria from the Bacilli class and exhibited low classification resolution for Rickettsiales, which represent the second most abundant 16S rRNA gene sequence in all the primers. The V4V5 primer set detected almost the same community composition as the V3V4, but the ability of these primers to also amplify the eukaryotic 18S rRNA gene may hinder bacterial community observations. However, after overcoming the challenges possessed by each one of those primers, we found that all three of them show very similar bacterial community dynamics and compositions. Nevertheless, based on our results, we propose that the V3V4 primer set is potentially the most suitable for studying jellyfish-associated bacterial communities. Our results suggest that, at least for jellyfish samples, it may be feasible to directly compare microbial community estimates from different studies, each using different primers but otherwise similar experimental protocols. More generally, we recommend specifically testing different primers for each new organism or system as a prelude to large-scale 16S rRNA gene amplicon analyses, especially of previously unstudied host-microbe associations.

Resveratrol Attenuates Ankylosing Spondylitis in Mice by Inhibiting the TLR4/NF-κB/NLRP3 Pathway and Regulating Gut Microbiota

Ankylosing spondylitis (AS) is an autoimmune disease associated with disturbed gut microbiota. Currently, the treatments and outcomes of AS are not satisfactory. It is reported that resveratrol (RES) is a major phytoalexin with anti-inflammatory, antibacterial and some other pharmacological effects. However, there are no studies on the role of RES in AS. Therefore, this study aimed to explore the effect and mechanism of RES on AS. Proteoglycan and complete freund's adjuvant were used to conduct an AS mouse model, and then the AS mice were gavaged with RES (20 mg/kg and 50 mg/kg) daily for 4 weeks. Subsequently, the effect of RES on AS mice was assessed by detecting disease severity, inflammatory cytokines, NLRP3 inflammasome, TLR4/NF-κB pathway, intestinal mucosal barrier function, intestinal microbial barrier function. The assessment results indicated that RES could significantly relieve progression and severity of AS, inhibit the expression of pro-inflammatory cytokines (tumor necrosis factor-α, interleukin-6, interleukin-17A, interferon-γ), and promote the expression of anti-inflammatory cytokines (interleukin-4). RES intervention caused the inhibition of NLRP3 inflammasome and TLR4/NF-κB pathway. In terms of intestinal barrier function, experimental results found RES increased zonula occludens-1 and occludin expression, and additionally, changed the composition of the gut microbiota by increasing levels of Lactobacillus and Bifidobacterium and reducing levels of Enterococcus faecalis and Escherichia coli. Collectively, RES protects PG-induced AS mice by inhibiting inflammatory responses and TLR4/NF-κB/NLRP3 pathway, restoring intestinal mucosal barrier function, and regulating the composition of the gut microbiota. In other words, RES is a potential candidate for the treatment of AS.

The power of DNA based methods in probiotic authentication

Introduction

The global probiotic market is growing rapidly, and strict quality control measures are required to ensure probiotic product efficacy and safety. Quality assurance of probiotic products involve confirming the presence of specific probiotic strains, determining the viable cell counts, and confirming the absence of contaminant strains. Third-party evaluation of probiotic quality and label accuracy is recommended for probiotic manufacturers. Following this recommendation, multiple batches of a top selling multi-strain probiotic product were evaluated for label accuracy.

Methods

A total of 55 samples (five multi-strain finished products and 50 single-strain raw ingredients) containing a total of 100 probiotic strains were evaluated using a combination of molecular methods including targeted PCR, non-targeted amplicon-based High Throughput Sequencing (HTS), and non-targeted Shotgun Metagenomic Sequencing (SMS).

Results

Targeted testing using species-specific or strain-specific PCR methods confirmed the identity of all strains/species. While 40 strains were identified to strain level, 60 strains were identified to species level only due to lack of strain-specific identification methods. In amplicon based HTS, two variable regions of 16S rRNA gene were targeted. Based on V5-V8 region data, ~99% of total reads per sample corresponded to target species, and no undeclared species were detected. Based on V3-V4 region data, ~95%-97% of total reads per sample corresponded to target species, while ~2%-3% of reads matched undeclared species (Proteus species), however, attempts to culture Proteus confirmed that all batches were free from viable Proteus species. Reads from SMS assembled to the genomes of all 10 target strains in all five batches of the finished product.

Discussion

While targeted methods enable quick and accurate identification of target taxa in probiotic products, non-targeted methods enable the identification of all species in a product including undeclared species, with the caveats of complexity, high cost, and long time to result.

Gastrointestinal, vaginal, nasopharyngeal, and breast milk microbiota profiles and breast milk metabolomic changes in Gambian infants over the first two months of lactation: A prospective cohort study

Microbiota composition in breast milk affects intestinal and respiratory microbiota colonization and the mucosal immune system's development in infants. The metabolomic content of breast milk is thought to interact with the microbiota and may influence developing infant immunity. One hundred seven Gambian mothers and their healthy, vaginally delivered, exclusively breastfed infants were included in our study. We analyzed 32 breast milk samples, 51 maternal rectovaginal swabs and 30 infants' rectal swabs at birth. We also analyzed 9 breast milk samples and 18 infants' nasopharyngeal swabs 60 days post-delivery. We used 16S rRNA gene sequencing to determine the microbiota composition. Metabolomic profiling analysis was performed on colostrum and mature breast milk samples using a multiplatform approach combining 1-H Nuclear Magnetic Resonance Spectroscopy and Gas Chromatography-Mass Spectrometry. Bacterial communities were distinct in composition and diversity across different sample types. Breast milk composition changed over the first 60 days of lactation. α-1,4- and α-1,3-fucosylated human milk oligosaccharides, and other 33 key metabolites in breast milk (monosaccharides, sugar alcohols and fatty acids) increased between birth and day 60 of life. This study's results indicate that infant gut and respiratory microbiota are unique bacterial communities, distinct from maternal gut and breast milk, respectively. Breast milk microbiota composition and metabolomic profile change throughout lactation. These changes may contribute to the infant's immunological, metabolic, and neurological development and could consist the basis for future interventions to correct disrupted early life microbial colonization.

The Interaction among Microbiota, Epigenetic Regulation, and Air Pollutants in Disease Prevention

Environmental pollutants can influence microbiota variety, with important implications for the general wellbeing of organisms. In subjects at high-risk of cancer, gut, and lung microbiota are distinct from those of low-risk subjects, and disease progression is associated with microbiota alterations. As with many inflammatory diseases, it is the combination of specific host and environmental factors in certain individuals that provokes disease outcomes. The microbiota metabolites influence activity of epigenetic enzymes. The knowledge of the mechanisms of action of environmental pollution now includes not only the alteration of the gut microbiota but also the interaction between different human microbiota niches such as the lung–gut axis. The epigenetic regulations can reprogram differentiated cells in response to environmental changes. The microbiota can play a major role in the progression and suppression of several epigenetic diseases. Accordingly, the maintenance of a balanced microbiota by monitoring the environmental stimuli provides a novel preventive approach for disease prevention. Metagenomics technologies can be utilized to establish new mitigation approaches for diseases induced by polluted environments. The purpose of this review is to examine the effects of particulate matter exposure on the progression of disease outcomes as related to the alterations of gut and lung microbial communities and consequent epigenetic modifications.

Impact of Maternal Intrapartum Antibiotics, and Caesarean Section with and without Labour on Bifidobacterium and Other Infant Gut Microbiota

Background and Aims: Few studies consider the joint effect of multiple factors related to birth, delivery mode, intrapartum antibiotic prophylaxis and the onset of labour, on the abundance of Bifidobacterium and the quantity of this genus and its species Bifidobacterium longum subsp. infantis in the infant gut microbiota. We implemented such a study. Methods: Among 1654 Canadian full-term infants, the gut microbiota of faecal samples collected at 3 months were profiled by 16S rRNA sequencing; the genus Bifidobacterium and Bifidobacterium longum subsp. infantis were quantified by qPCR. Associations between Bifidobacterium and other gut microbiota were examined by Spearman’s rank correlation. Results: Following vaginal birth, maternal IAP exposure was associated with reduced absolute quantities of bifidobacteria among vaginally delivered infants (6.80 vs. 7.14 log₁₀ (gene-copies/g faeces), p < 0.05), as well as their lowered abundance relative to other gut microbiota. IAP differences in infant gut bifidobacterial quantity were independent of maternal pre-pregnancy body-mass-index (BMI), and remarkably, they were limited to breastfed infants. Pre-pregnancy BMI adjustment revealed negative associations between absolute quantities of bifidobacteria and CS with or without labour in non-breastfed infants, and CS with labour in exclusively breastfed infants. Significant correlations between Bifidobacterium abundance and other microbial taxa were observed. Conclusions: This study documented the impact of the birth mode and feeding status on the abundance of gut Bifidobacterium, and pointed to the important ecological role of the genus Bifidobacterium in gut microbiota due to its strong interaction with other gut microbiota in early infancy.

Weight shapes the intestinal microbiome in preterm infants: results of a prospective observational study

BACKGROUND

The intestinal microbiome in preterm infants differs markedly from term infants. It is unclear whether the microbiome develops over time according to infant specific factors.

METHODS

We analysed (clinical) metadata - to identify the main factors influencing the microbiome composition development - and the first meconium and faecal samples til the 4th week via 16 S rRNA amplican sequencing.

RESULTS

We included 41 infants (gestational age 25-30 weeks; birth weight 430-990 g. Birth via Caesarean section (CS) was associated with placental insufficiency during pregnancy and lower BW. In meconium samples and in samples from weeks 2 and 3 the abundance of Escherichia and Bacteroides (maternal faecal representatives) were associated with vaginal delivery while Staphylococcus (skin microbiome representative) was associated with CS. Secondly, irrespective of the week of sampling or the mode of birth, a transition was observed as children children gradually increased in weight from a microbiome dominated by Staphylococcus (Bacilli) towards a microbiome dominated by Enterobacteriaceae (Gammaproteobacteria).

CONCLUSIONS

Our data show that the mode of delivery affects the meconium microbiome composition. They also suggest that the weight of the infant at the time of sampling is a better predictor for the stage of progression of the intestinal microbiome development/maturation than postconceptional age as it less confounded by various infant-specific factors.

A protocol for characterization of extremely preterm infant gut microbiota in double-blind clinical trials

16S rRNA gene sequencing enables microbial community profiling, but recovering fecal DNA from extremely premature infants is challenging. Here, we describe an optimized protocol for fecal DNA isolation, library preparation for 16S rRNA gene sequencing, taxonomy assignation, and statistical analyses. The protocol is complemented with a quantitative PCR for probiotic L. reuteri identification. This protocol describes how to characterize preterm infant gut microbiota and relate it to probiotic supplementation and clinical outcomes. It is customizable for other clinical trials.

For complete details on the use and execution of this protocol, please refer to Martí et al. (2021) and Spreckels et al. (2021).

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Customizable protocol for characterization of infant gut microbiota in clinical trials

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Optimized sample preparation for 16S rRNA gene sequencing for infant fecal samples

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Quantitative PCR for probiotic Lactobacillus reuteri quantification in infant feces

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Easy-to-use bioinformatic and statistical analysis pipeline

Association and Occurrence of Bifidobacterial Phylotypes Between Breast Milk and Fecal Microbiomes in Mother-Infant Dyads During the First 2 Years of Life

Breast milk acts as an intermediary for the transfer of functionally important commensal bacteria from mother to infant, especially for Bifidobacterium that can colonize the infant gut. However, the vast majority of rRNA amplicon-based studies reported the conspicuous intercohort and interindividual variation for the prevalence of Bifidobacterium in breast milk. In order to elucidate whether Bifidobacterium phylotypes persistently co-occured at the species or strain level in mother–breast milk–infant triads, we analyzed collectively the next-generation sequencing (NGS) datasets of bacterial 16S rRNA gene and the Bifidobacterium-specific groEL gene from maternal feces, breast milk, and infant feces in a small yet very homogeneous cohort of 25 healthy Uyghur mother–infant pairs (lactation for 7–720 days) in Kashgar, Xinjiang, China. Overall, 16S rRNA gene analysis showed that microbiome in the newborn gut was closer to that of breast milk in the first 4 months of lactation, and subsequently showed an obvious trend of adulthood at 6–12 months. Based on the BLAST accurate taxonomic result of the representative sequences of all ASVs (amplicon sequencing variants), only three sets of ASVs could be clearly assigned into Bifidobacterium species, whereas the remaining eight sets of ASVs corresponded to four indefinite Bifidobacterium species group. By contrast, the groEL gene dataset was partitioned into 376 ASVs, at least belonging to 13 well-known Bifidobacterium species or subspecies, of which 15 ASVs, annotated to seven well-known Bifidobacterium species or subspecies, showed triadic synchronism in most 23 mother–infant pairs tested. However, several other rare bifidobacterial phylotypes, which were frequently encountered in animals, were found to display no correspondence of the presence between the three ecosystems of mother–infant pairs. Our test results were obviously to support the hypothesis that breast milk acts as an intermediary for the transfer of probiotic commensal bacteria from mother to infant, especially for endosymbiotic Bifidobacterium that can colonize the infant gut. Some oxygen-insensitive exogenous Bifidobacterium phylotypes with a cosmopolitan lifestyle may be indirectly transferred to breast milk and the infant’s intestinal tract through environmental contamination. Thus, the groEL gene proved to be a very effective target for the depth resolution of Bifidobacterium community by high-throughput sequencing technologies.

NGS plus bacterial culture: A more accurate method for diagnosing forensic-related nosocomial infections

Traditional autopsy and microscopic examination of pathological sections are the "gold standard" for the cause of death diagnosis. However, in some special cases, such as the deaths caused by bacterial infections, pathological sections are not always sufficient to provide convincing evidences for determining the causes of death. In recent years, with the development of Next Generation Sequencing (NGS), clinical medicine has already introduced it into the diagnosis of difficult diseases, which is rare in forensic pathological diagnoses. Here, we applied an NGS-based method combined with bacterial culture to examine a special case in which the deceased was suspected of having suffered from nosocomial infections. Results of the NGS and bacterial culture showed that Enterococcus and Acinetobacter baumannii, which are the most common bacteria causing nosocomial infections, were abundant in blood and hydropericardium of the deceased. Combining medical records and the results of the dissections, we proved that the death was actually caused by MODS which was the adverse consequence of nosocomial infections. In this case, the combination of NGS and bacterial culture was used to identify the pathogen which had caused the death. The results of NGS not only shorten the period of diagnosis, but also greatly increase the credibility of traditional anatomy and results of bacterial culture, which is expected to be further applied for forensic practices in the near future.

Refinement of 16S rRNA gene analysis for low biomass biospecimens

High-throughput phylogenetic 16S rRNA gene analysis has permitted to thoroughly delve into microbial community complexity and to understand host-microbiota interactions in health and disease. The analysis comprises sample collection and storage, genomic DNA extraction, 16S rRNA gene amplification, high-throughput amplicon sequencing and bioinformatic analysis. Low biomass microbiota samples (e.g. biopsies, tissue swabs and lavages) are receiving increasing attention, but optimal standardization for analysis of low biomass samples has yet to be developed. Here we tested the lower bacterial concentration required to perform 16S rRNA gene analysis using three different DNA extraction protocols, three different mechanical lysing series and two different PCR protocols. A mock microbiota community standard and low biomass samples (10⁸, 10⁷, 10⁶, 10⁵ and 10⁴ microbes) from two healthy donor stools were employed to assess optimal sample processing for 16S rRNA gene analysis using paired-end Illumina MiSeq technology. Three DNA extraction protocols tested in our study performed similar with regards to representing microbiota composition, but extraction yield was better for silica columns compared to bead absorption and chemical precipitation. Furthermore, increasing mechanical lysing time and repetition did ameliorate the representation of bacterial composition. The most influential factor enabling appropriate representation of microbiota composition remains sample biomass. Indeed, bacterial densities below 10⁶ cells resulted in loss of sample identity based on cluster analysis for all tested protocols. Finally, we excluded DNA extraction bias using a genomic DNA standard, which revealed that a semi-nested PCR protocol represented microbiota composition better than classical PCR. Based on our results, starting material concentration is an important limiting factor, highlighting the need to adapt protocols for dealing with low biomass samples. Our study suggests that the use of prolonged mechanical lysing, silica membrane DNA isolation and a semi-nested PCR protocol improve the analysis of low biomass samples. Using the improved protocol we report a lower limit of 10⁶ bacteria per sample for robust and reproducible microbiota analysis.

Primer, Pipelines, Parameters: Issues in 16S rRNA Gene Sequencing

Short-amplicon 16S rRNA gene sequencing is currently the method of choice for studies investigating microbiomes. However, comparative studies on differences in procedures are scarce. We sequenced human stool samples and mock communities with increasing complexity using a variety of commonly used protocols. Short amplicons targeting different variable regions (V-regions) or ranges thereof (V1-V2, V1-V3, V3-V4, V4, V4-V5, V6-V8, and V7-V9) were investigated for differences in the composition outcome due to primer choices. Next, the influence of clustering (operational taxonomic units [OTUs], zero-radius OTUs [zOTUs], and amplicon sequence variants [ASVs]), different databases (GreenGenes, the Ribosomal Database Project, Silva, the genomic-based 16S rRNA Database, and The All-Species Living Tree), and bioinformatic settings on taxonomic assignment were also investigated. We present a systematic comparison across all typically used V-regions using well-established primers. While it is known that the primer choice has a significant influence on the resulting microbial composition, we show that microbial profiles generated using different primer pairs need independent validation of performance. Further, comparing data sets across V-regions using different databases might be misleading due to differences in nomenclature (e.g., Enterorhabdus versus Adlercreutzia) and varying precisions in classification down to genus level. Overall, specific but important taxa are not picked up by certain primer pairs (e.g., Bacteroidetes is missed using primers 515F-944R) or due to the database used (e.g., Acetatifactor in GreenGenes and the genomic-based 16S rRNA Database). We found that appropriate truncation of amplicons is essential and different truncated-length combinations should be tested for each study. Finally, specific mock communities of sufficient and adequate complexity are highly recommended.

IMPORTANCE In 16S rRNA gene sequencing, certain bacterial genera were found to be underrepresented or even missing in taxonomic profiles when using unsuitable primer combinations, outdated reference databases, or inadequate pipeline settings. Concerning the last, quality thresholds as well as bioinformatic settings (i.e., clustering approach, analysis pipeline, and specific adjustments such as truncation) are responsible for a number of observed differences between studies. Conclusions drawn by comparing one data set to another (e.g., between publications) appear to be problematic and require independent cross-validation using matching V-regions and uniform data processing. Therefore, we highlight the importance of a thought-out study design including sufficiently complex mock standards and appropriate V-region choice for the sample of interest. The use of processing pipelines and parameters must be tested beforehand.

The Multiomics Analyses of Fecal Matrix and Its Significance to Coeliac Disease Gut Profiling

Gastrointestinal (GIT) diseases have risen globally in recent years, and early detection of the host’s gut microbiota, typically through fecal material, has become a crucial component for rapid diagnosis of such diseases. Human fecal material is a complex substance composed of undigested macromolecules and particles, and the processing of such matter is a challenge due to the unstable nature of its products and the complexity of the matrix. The identification of these products can be used as an indication for present and future diseases; however, many researchers focus on one variable or marker looking for specific biomarkers of disease. Therefore, the combination of genomics, transcriptomics, proteomics and metabonomics can give a detailed and complete insight into the gut environment. The proper sample collection, sample preparation and accurate analytical methods play a crucial role in generating precise microbial data and hypotheses in gut microbiome research, as well as multivariate data analysis in determining the gut microbiome functionality in regard to diseases. This review summarizes fecal sample protocols involved in profiling coeliac disease.

Multiomic features associated with mucosal healing and inflammation in paediatric Crohn's disease

BACKGROUND

The gastrointestinal microbiota has an important role in mucosal immune homoeostasis and may contribute to maintaining mucosal healing in Crohn's disease (CD).

AIM

To identify changes in the microbiota, metabolome and protease activity associated with mucosal healing in established paediatric CD METHODS: Twenty-five participants aged 3-18 years with CD, disease duration of over 6 months, and maintenance treatment with biological therapy were recruited. They were divided into a low calprotectin group (faecal calprotectin <100 μg/g, "mucosal healing," n = 11), and a high calprotectin group (faecal calprotectin >100 μg/g, "mucosal inflammation," n = 11). 16S gene-based metataxonomics, ¹ H-NMR spectroscopy-based metabolic profiling and protease activity assays were performed on stool samples.

RESULTS

Relative abundance of Dialister species was six-times greater in the low calprotectin group (q = 0.00999). Alpha and beta diversity, total protease activity and inferred metagenomic profiles did not differ between groups. Pentanoate (valerate) and lysine were principal discriminators in a machine-learning model which differentiated high and low calprotectin samples using NMR spectra (R² 0.87, Q² 0.41). Mean relative concentration of pentanoate was 1.35-times greater in the low calprotectin group (95% CI 1.03-1.68, P = 0.036) and was positively correlated with Dialister. Mean relative concentration of lysine was 1.54-times greater in the high calprotectin group (95% CI 1.05-2.03, P = 0.028).

CONCLUSIONS

This multiomic study identified an increase in Dialister species and pentanoate, and a decrease in lysine, in patients with "mucosal healing." It supports further investigation of these as potential novel therapeutic targets in CD.

Microbiota Supplementation with Bifidobacterium and Lactobacillus Modifies the Preterm Infant Gut Microbiota and Metabolome: An Observational Study

Supplementation with members of the early-life microbiota as “probiotics” is increasingly used in attempts to beneficially manipulate the preterm infant gut microbiota. We performed a large observational longitudinal study comprising two preterm groups: 101 infants orally supplemented with Bifidobacterium and Lactobacillus (Bif/Lacto) and 133 infants non-supplemented (control) matched by age, sex, and delivery method. 16S rRNA gene profiling on fecal samples (n = 592) showed a predominance of Bifidobacterium and a lower abundance of pathobionts in the Bif/Lacto group. Metabolomic analysis showed higher fecal acetate and lactate and a lower fecal pH in the Bif/Lacto group compared to the control group. Fecal acetate positively correlated with relative abundance of Bifidobacterium, consistent with the ability of the supplemented Bifidobacterium strain to metabolize human milk oligosaccharides into acetate. This study demonstrates that microbiota supplementation is associated with a Bifidobacterium-dominated preterm microbiota and gastrointestinal environment more closely resembling that of full-term infants.

Bifidobacterium dominates the gut microbiota in supplemented preterm infants

Supplemented preterm infants have lower abundance of potential pathobionts

Metabolomic analysis show higher fecal acetate and lower pH in supplemented infants

In vitro and genomic analysis confirm HMO metabolism in Bifidobacterium supplement

Untapped sponge microbiomes: structure specificity at host order and family levels

Sponges are complex holobionts in which the structure of the microbiome has seldom been characterized above the host species level. The hypothesis tested in this study is that the structure of the sponge microbiomes is specific to the host at the order and family levels. This was done by using 33 sponge species belonging to 19 families representing five orders. A combination of three primer sets covering the V1-V8 regions of the 16S rRNA gene provided a more comprehensive coverage of the microbiomes. Both the diversity and structure of sponge microbiomes were demonstrated to be highly specific to the host phylogeny at the order and family levels. There are always dominant operational taxonomic units (OTUs) (relative abundance >1%) shared between microbial communities of sponges within the same family or order, but these shared OTUs showed high levels of dissimilarity between different sponge families and orders. The unique OTUs for a particular sponge family or order could be regarded as their 'signature identity'. 70%-87% of these unique OTUs (class level) are unaffiliated and represent a vast resource of untapped microbiota. This study contributes to a deeper understanding on the concept of host-specificity of sponge microbiomes and highlights a hidden reservoir of sponge-associated microbial resources.

Improving causality in microbiome research: can human genetic epidemiology help?

Evidence supports associations between human gut microbiome variation and multiple health outcomes and diseases. Despite compelling results from in vivo and in vitro models, few findings have been translated into an understanding of modifiable causal relationships. Furthermore, epidemiological studies have been unconvincing in their ability to offer causal evidence due to their observational nature, where confounding by lifestyle and behavioural factors, reverse causation and bias are important limitations. Whilst randomized controlled trials have made steps towards understanding the causal role played by the gut microbiome in disease, they are expensive and time-consuming. This evidence that has not been translated between model systems impedes opportunities for harnessing the gut microbiome for improving population health. Therefore, there is a need for alternative approaches to interrogate causality in the context of gut microbiome research. The integration of human genetics within population health sciences have proved successful in facilitating improved causal inference (e.g., with Mendelian randomization [MR] studies) and characterising inherited disease susceptibility. MR is an established method that employs human genetic variation as natural "proxies" for clinically relevant (and ideally modifiable) traits to improve causality in observational associations between those traits and health outcomes. Here, we focus and discuss the utility of MR within the context of human gut microbiome research, review studies that have used this method and consider the strengths, limitations and challenges facing this research. Specifically, we highlight the requirements for careful examination and interpretation of derived causal estimates and host (i.e., human) genetic effects themselves, triangulation across multiple study designs and inter-disciplinary collaborations. Meeting these requirements will help support or challenge causality of the role played by the gut microbiome on human health to develop new, targeted therapies to alleviate disease symptoms to ultimately improve lives and promote good health.

Improving causality in microbiome research: can human genetic epidemiology help?

Evidence supports associations between human gut microbiome variation and multiple health outcomes and diseases. Despite compelling results from in vivo and in vitro models, few findings have been translated into an understanding of modifiable causal relationships. Furthermore, epidemiological studies have been unconvincing in their ability to offer causal evidence due to their observational nature, where confounding by lifestyle and behavioural factors, reverse causation and bias are important limitations. Whilst randomized controlled trials have made steps towards understanding the causal role played by the gut microbiome in disease, they are expensive and time-consuming. This evidence that has not been translated between model systems impedes opportunities for harnessing the gut microbiome for improving population health. Therefore, there is a need for alternative approaches to interrogate causality in the context of gut microbiome research. The integration of human genetics within population health sciences have proved successful in facilitating improved causal inference (e.g., with Mendelian randomization [MR] studies) and characterising inherited disease susceptibility. MR is an established method that employs human genetic variation as natural "proxies" for clinically relevant (and ideally modifiable) traits to improve causality in observational associations between those traits and health outcomes. Here, we focus and discuss the utility of MR within the context of human gut microbiome research, review studies that have used this method and consider the strengths, limitations and challenges facing this research. Specifically, we highlight the requirements for careful examination and interpretation of derived causal estimates and host (i.e., human) genetic effects themselves, triangulation across multiple study designs and inter-disciplinary collaborations. Meeting these requirements will help support or challenge causality of the role played by the gut microbiome on human health to develop new, targeted therapies to alleviate disease symptoms to ultimately improve lives and promote good health.

Bifidobacterium breve UCC2003 Exopolysaccharide Modulates the Early Life Microbiota by Acting as a Potential Dietary Substrate

BACKGROUND

Bifidobacterium represents an important early life microbiota member. Specific bifidobacterial components, exopolysaccharides (EPS), positively modulate host responses, with purified EPS also suggested to impact microbe-microbe interactions by acting as a nutrient substrate. Thus, we determined the longitudinal effects of bifidobacterial EPS on microbial communities and metabolite profiles using an infant model colon system.

METHODS

Differential gene expression and growth characteristics were determined for each strain; Bifidobacterium breve UCC2003 and corresponding isogenic EPS-deletion mutant (B. breve UCC2003del). Model colon vessels were inoculated with B. breve and microbiome dynamics monitored using 16S rRNA sequencing and metabolomics (NMR).

RESULTS

Transcriptomics of EPS mutant vs. B. breve UCC2003 highlighted discrete differential gene expression (e.g., eps biosynthetic cluster), though overall growth dynamics between strains were unaffected. The EPS-positive vessel had significant shifts in microbiome and metabolite profiles until study end (405 h); with increases of Tyzzerella and Faecalibacterium, and short-chain fatty acids, with further correlations between taxa and metabolites which were not observed within the EPS-negative vessel.

CONCLUSIONS

These data indicate that B. breve UCC2003 EPS is potentially metabolized by infant microbiota members, leading to differential microbial metabolism and altered metabolite by-products. Overall, these findings may allow development of EPS-specific strategies to promote infant health.

Rapid MinION profiling of preterm microbiota and antimicrobial-resistant pathogens

The MinION sequencing platform offers near real-time analysis of DNA sequence; this makes the tool attractive for deployment in fieldwork or clinical settings. We used the MinION platform coupled to the NanoOK RT software package to perform shotgun metagenomic sequencing and profile mock communities and faecal samples from healthy and ill preterm infants. Using Nanopore data, we reliably classified a 20-species mock community and captured the diversity of the immature gut microbiota over time and in response to interventions such as probiotic supplementation, antibiotic treatment or episodes of suspected sepsis. We also performed rapid real-time runs to assess gut-associated microbial communities in critically ill and healthy infants, facilitated by NanoOK RT software package, which analysed sequences as they were generated. Our pipeline reliably identified pathogenic bacteria (that is, Klebsiella pneumoniae and Enterobacter cloacae) and their corresponding antimicrobial resistance gene profiles within as little as 1 h of sequencing. Results were confirmed using pathogen isolation, whole-genome sequencing and antibiotic susceptibility testing, as well as mock communities and clinical samples with known antimicrobial resistance genes. Our results demonstrate that MinION (including cost-effective Flongle flow cells) with NanoOK RT can process metagenomic samples to a rich dataset in < 5 h, which creates a platform for future studies aimed at developing these tools and approaches in clinical settings with a focus on providing tailored patient antimicrobial treatment options.

The Impact of Primer Design on Amplicon-Based Metagenomic Profiling Accuracy: Detailed Insights into Bifidobacterial Community Structure

Next Generation Sequencing (NGS) technologies have overcome the limitations of cultivation-dependent approaches and allowed detailed study of bacterial populations that inhabit the human body. The consortium of bacteria residing in the human intestinal tract, also known as the gut microbiota, impacts several physiological processes important for preservation of the health status of the host. The most widespread microbiota profiling method is based on amplification and sequencing of a variable portion of the 16S rRNA gene as a universal taxonomic marker among members of the Bacteria domain. Despite its popularity and obvious advantages, this 16S rRNA gene-based approach comes with some important limitations. In particular, the choice of the primer pair for amplification plays a major role in defining the accuracy of the reconstructed bacterial profiles. In the current study, we performed an in silico PCR using all currently described 16S rRNA gene-targeting primer pairs (PP) in order to assess their efficiency. Our results show that V3, V4, V5, and V6 were the optimal regions on which to design 16S rRNA metagenomic primers. In detail, PP39 (Probio_Uni/Probio_Rev), PP41 (341F/534R), and PP72 (970F/1050R) were the most suitable primer pairs with an amplification efficiency of >98.5%. Furthermore, the Bifidobacterium genus was examined as a test case for accurate evaluation of intra-genus performances at subspecies level. Intriguingly, the in silico analysis revealed that primer pair PP55 (527f/1406r) was unable to amplify the targeted region of any member of this bacterial genus, while several other primer pairs seem to rather inefficiently amplify the target region of the main bifidobacterial taxa. These results highlight that selection of a 16S rRNA gene-based PP should be done with utmost care in order to avoid biases in microbiota profiling results.

Simultaneous detection and comprehensive analysis of HPV and microbiome status of a cervical liquid-based cytology sample using Nanopore MinION sequencing

Human papillomavirus (HPV) is a major pathogen that causes cervical cancer and many other related diseases. HPV infection related cervical microbiome could be an induce factor of cervical cancer. However, it is uncommon to find a single test on the market that can simultaneously provide information on both HPV and the microbiome. Herein, a novel method was developed in this study to simultaneously detect HPV infection and microbiota composition promptly and accurately. It provides a new and simple way to detect vaginal pathogen situation and also provide valuable information for clinical diagnose. This approach combined multiplex PCR, which targeted both HPV16 E6E7 and full-length 16S rRNA, and Nanopore sequencing to generate enough information to understand the vagina condition of patients. One HPV positive liquid-based cytology (LBC) sample was sequenced and analyzed. After comparing with Illumina sequencing, the results from Nanopore showed a similar microbiome composition. An instant sequencing evaluation showed that 15 min sequencing is enough to identify the top 10 most abundant bacteria. Moreover, two HPV integration sites were identified and verified by Sanger sequencing. This approach has many potential applications in pathogen detection and can potentially aid in providing a more rapid clinical diagnosis.

Improving causality in microbiome research: can human genetic epidemiology help?

Evidence supports associations between human gut microbiome variation and multiple health outcomes and diseases. Despite compelling results from in vivo and in vitro models, few findings have been translated into an understanding of modifiable causal relationships. Furthermore, epidemiological studies have been unconvincing in their ability to offer causal evidence due to their observational nature, where confounding by lifestyle and behavioural factors, reverse causation and bias are important limitations. Whilst randomized controlled trials have made steps towards understanding the causal role played by the gut microbiome in disease, they are expensive and time-consuming. This evidence that has not been translated between model systems impedes opportunities for harnessing the gut microbiome for improving population health. Therefore, there is a need for alternative approaches to interrogate causality in the context of gut microbiome research. The integration of human genetics within population health sciences have proved successful in facilitating improved causal inference (e.g., with Mendelian randomization [MR] studies) and characterising inherited disease susceptibility. MR is an established method that employs human genetic variation as natural "proxies" for clinically relevant (and ideally modifiable) traits to improve causality in observational associations between those traits and health outcomes. Here, we focus and discuss the utility of MR within the context of human gut microbiome research, review studies that have used this method and consider the strengths, limitations and challenges facing this research. Specifically, we highlight the requirements for careful examination and interpretation of derived causal estimates and host (i.e., human) genetic effects themselves, triangulation across multiple study designs and inter-disciplinary collaborations. Meeting these requirements will help support or challenge causality of the role played by the gut microbiome on human health to develop new, targeted therapies to alleviate disease symptoms to ultimately improve lives and promote good health.

The impact of storage conditions on human stool 16S rRNA microbiome composition and diversity

Background

Multiple factors can influence stool sample integrity upon sample collection. Preservation of faecal samples for microbiome studies is therefore an important step, particularly in tropical regions where resources are limited and high temperatures may significantly influence microbiota profiles. Freezing is the accepted standard to preserve faecal samples however, cold chain methods are often unfeasible in fieldwork scenarios particularly in low and middle-income countries and alternatives are required. This study therefore aimed to address the impact of different preservative methods, time-to-freezing at ambient tropical temperatures, and stool heterogeneity on stool microbiome diversity and composition under real-life physical environments found in resource-limited fieldwork conditions.

Methods

Inner and outer stool samples collected from one specimen obtained from three children were stored using different storage preservation methods (raw, ethanol and RNAlater) in a Ugandan field setting. Mixed stool was also stored using these techniques and frozen at different time-to-freezing intervals post-collection from 0-32 h. Metataxonomic profiling was used to profile samples, targeting the V1-V2 regions of 16S rRNA with samples run on a MiSeq platform. Reads were trimmed, combined and aligned to the Greengenes database. Microbial diversity and composition data were generated and analysed using Quantitative Insights Into Microbial Ecology and R software.

Results

Child donor was the greatest predictor of microbiome variation between the stool samples, with all samples remaining identifiable to their child of origin despite the stool being stored under a variety of conditions. However, significant differences were observed in composition and diversity between preservation techniques, but intra-preservation technique variation was minimal for all preservation methods, and across the time-to-freezing range (0-32 h) used. Stool heterogeneity yielded no apparent microbiome differences.

Conclusions

Stool collected in a fieldwork setting for comparative microbiome analyses should ideally be stored as consistently as possible using the same preservation method throughout.

Compositional and temporal stability of fecal taxon libraries for use with SourceTracker in sub-tropical catchments

Characterization of microbial communities using high-throughput amplicon sequencing is an emerging approach for microbial source tracking of fecal pollution. This study used SourceTracker software to examine temporal and geographical variability of fecal bacterial community profiles to identify pollutant sources in three freshwater catchments in sub-tropical Australia. Fecal bacterial communities from 10 animal species, humans, and composite wastewater samples from six sewage treatment plants were characterized and compared to freshwater samples using Illumina amplicon sequencing of the V5-V6 regions of the 16S rRNA gene. Source contributions were calculated in SourceTracker using new fecal taxon libraries as well as previously generated libraries to determine the effects of geographic and temporal variability on source assignments. SourceTracker determined 16S rRNA bacterial communites within freshwater samples, shared taxonomic similarities to that of wastewater at low levels (typically <3%). SourceTraker also predicted occasional fecal detection of deer and flying fox sources in the water samples. No significant differences in source contributions were observed within sequences from current and previously characterized fecal samples (P ≥ 0.107). However, significant differences were observed between previously characterized and newly characterized source communities (ANOSIM P ≤ 0.001), which shared <15% community composition. Results suggest temporal instability of fecal taxon libraries among tested sources and highlight continual evaluation of community-based MST using confirmatory qPCR analyses of marker genes.

Genomic analysis on broiler-associated Clostridium perfringens strains and exploratory caecal microbiome investigation reveals key factors linked to poultry necrotic enteritis

Background

Clostridium perfringens is a key pathogen in poultry-associated necrotic enteritis (NE). To date there are limited Whole Genome Sequencing based studies describing broiler-associated C. perfringens in healthy and diseased birds. Moreover, changes in the caecal microbiome during NE is currently not well characterised. Thus, the aim of this present study was to investigate C. perfringens virulence factors linked to health and diseased chickens, including identifying putative caecal microbiota signatures associated with NE.

Results

We analysed 88 broiler chicken C. perfringens genomes (representing 66 publicly available genomes and 22 newly sequenced genomes) using different phylogenomics approaches and identified a potential hypervirulent and globally-distributed clone spanning 20-year time-frame (1993-2013). These isolates harbored a greater number of virulence genes (including toxin and collagen adhesin genes) when compared to other isolates. Further genomic analysis indicated exclusive and overabundant presence of important NE-linked toxin genes including netB and tpeL in NE-associated broiler isolates. Secondary virulence genes including pfoA, cpb2, and collagen adhesin genes cna, cnaA and cnaD were also enriched in the NE-linked C. perfringens genomes. Moreover, an environmental isolate obtained from farm animal feeds was found to encode netB, suggesting potential reservoirs of NetB-positive C. perfringens strains (toxinotype G). We also analysed caecal samples from a small sub-set of 11 diseased and healthy broilers for exploratory microbiome investigation using 16S rRNA amplicon sequencing, which indicated a significant and positive correlation in genus Clostridium within the wider microbiota of those broilers diagnosed with NE, alongside reductions in beneficial microbiota members.

Conclusions

These data indicate a positive association of virulence genes including netB, pfoA, cpb2, tpeL and cna variants linked to NE-linked isolates. Potential global dissemination of specific hypervirulent lineage, coupled with distinctive microbiome profiles, highlights the need for further investigations, which will require a large worldwide sample collection from healthy and NE-associated birds.

Influence of a Serratia marcescens outbreak on the gut microbiota establishment process in low-weight preterm neonates

Adequate gut microbiota establishment is important for lifelong health. The aim was to sequentially analyze the gut microbiota establishment in low-birth-weight preterm neonates admitted to a single neonatal intensive care unit during their first 3 weeks of life, comparing two epidemiological scenarios. Seven control infants were recruited, and another 12 during a severe S. marcescens outbreak. Meconium and feces from days 7, 14, and 21 of life were collected. Gut microbiota composition was determined by 16S rDNA massive sequencing. Cultivable isolates were genotyped by pulsed-field gel electrophoresis, with four S. marcescens submitted for whole-genome sequencing. The expected bacterial ecosystem expansion after birth is delayed, possibly related to antibiotic exposure. The Proteobacteria phylum dominates, although with marked interindividual variability. The outbreak group considerably differed from the control group, with higher densities of Escherichia coli and Serratia to the detriment of Enterococcus and other Firmicutes. Curiously, obligate predators were only detected in meconium and at very low concentrations. Genotyping of cultivable bacteria demonstrated the high bacterial horizontal transmission rate that was confirmed with whole-genome sequencing for S. marcescens. Preterm infants admitted at NICU are initially colonized by homogeneous microbial communities, most of them from the nosocomial environment, which subsequently evolve according to the individual conditions. Our results demonstrate the hospital epidemiology pressure, particularly during outbreak situations, on the gut microbiota establishing process.

Streaming histogram sketching for rapid microbiome analytics

BACKGROUND

The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research, allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time. To address this need, we propose a new method for tyrhe compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching and classification of microbiome samples in near real time.

RESULTS

We apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed 'histosketch' that can efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using the pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we use a 'real life' example to show that histosketches can train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a random forest classifier that could accurately predict whether the neonate had received antibiotic treatment (97% accuracy, 96% precision) and could subsequently be used to classify microbiome data streams in less than 3 s.

CONCLUSIONS

Our method offers a new approach to rapidly process microbiome data streams, allowing samples to be rapidly clustered, indexed and classified. We also provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2 GB microbiome in 50 s on a standard laptop using four cores, with the sketch occupying 3000 bytes of disk space. ( https://github.com/will-rowe/hulk ).

Challenges of next-generation sequencing targeting anaerobes

Next-generation sequencing allows for investigating the composition of microbiomes that are associated with infection (clinical microbiology) or dysbiosis (microbial ecology). The most commonly applied short-read sequencing technologies are Illumina MiSeq/HiSeq and Ion Torrent PGM, however, other platforms that generate long-reads are under way and optimized. A pre-condition for representative results is an appropriate method for contamination-free collection, homogenization, storage of specimens and a subsequent efficient DNA extraction protocol. As some of the anaerobes such as Clostridia or anaerobe Archaea are robust while others of the same environment, such as spirochetes, possess a very thin cell wall, a chemico-mechanical lysing strategy is recommended but with some precautions to avoid DNA-sheering and overheating. For amplicon sequencing, the Silva-TestPrime online tool helps to find the optimal 16S directed primers for individual studies. For metagenome profiling, the classifier tool has to be selected with helpful decision trees available but a combination based on different strategies seems to be indispensable. Further development of both hard- and software is needed before microbiome results become free of a substantial technology-dependent bias.

Design and application of a novel two-amplicon approach for defining eukaryotic microbiota

BACKGROUND

Due to a lack of systematic diagnostics, our understanding of the diversity and role of eukaryotic microbiota in human health is limited. While studies have shown fungal communities to be significant modulators of human health, information on the prevalence of taxa such as protozoa and helminths has been limited to a small number of species for which targeted molecular diagnostics are available. To probe the diversity of eukaryotic microbes and their relationships with other members of the microbiota, we applied in silico and experimental approaches to design a novel two-amplicon surveillance tool, based on sequencing regions of ribosomal RNA genes and their internal transcribed spacers. We subsequently demonstrated the utility of our approach by characterizing the eukaryotic microbiota of 46 hospitalized Malawian children suffering from Severe Acute Malnutrition (SAM).

RESULTS

Through in silico analysis and validation on a diverse panel of eukaryotes, we identified 18S rRNA variable genetic regions 4 and 5 (18S V4 V5), together with a region encoding 28S rRNA variable genetic region 2 and the internal transcribed spacers (transITS), as optimal for the systematic classification of eukaryotes. Sequencing of these regions revealed protozoa in all stool samples from children with SAM and helminths in most, including several eukaryotes previously implicated in malnutrition and diarrheal disease. Clinical comparisons revealed no association between protozoan parasites and diarrhea or HIV reactivity. However, the presence of Blastocystis correlated with bacterial alpha diversity and increased abundance of specific taxa, including Sporobacter, Cellulosibacter, Oscillibacter, and Roseburia.

CONCLUSION

We suggest this novel two-amplicon based strategy will prove an effective tool to deliver new insights into the role of eukaryotic microbiota in health and disease.

Conjugated linoleic acid enriched skim milk prepared with Lactobacillus fermentum DDHI27 endorsed antiobesity in mice

Aim: This study evaluated the antiobesity effect of skim milk prepared with conjugated linoleic acid producing probiotic Lactobacillus fermentum DDHI27 (PCLA). Materials & methods: C57BL/6 J mice were divided into five groups, and different obesity-associated parameters were studied. Results: PCLA supplementation alleviated body weight, epididymal and mesenteric fats and improves lipid profiles. Significant ameliorations in leptin, blood glucose, hepatic steatosis and reduction in adipocytes size were also observed. Additionally, feeding also led to positive alterations in the adipogenesis transcription factors and key lipogenesis genes. Improvement in the gut microbiota dysbiosis was also revealed. Conclusion: Results inferred that PCLA exerted an antiobesity effect in diet-induced obese mice and may be further developed in the functional foods for the management of obesity.