Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold

Re-vitalizing wastewater: Nutrient recovery and carbon capture through microbe-algae synergy using omics-biology

Increasing amounts of wastewater is the most pervasive and challenging environmental problem globally. Conventional treatment methods are costly and entail huge energy, carbon consumption and greenhouse gas emissions. Owing to their unique ability of carbon capturing and resource recovery, microalgae-microbiome based treatment is a potential approach and is widely used for carbon-neutral wastewater treatment. Microalgae-bacteria synergy (i.e., the functionally beneficial microbial synthetic communities) performs better and enhances carbon-sequestration and nutrient recovery from wastewater treatment plants. This review presents a comprehensive information regarding the potential of microalgae-microbiome as a sustainable agent for wastewater and discusses synergistic approaches for effective nutrient removal. Moreover, this review discusses, the role of omics-biology and Insilco approaches in unravelling and understanding the algae-microbe synergism and their response toward wastewater treatment. Finally, it discusses various microbiome engineering approaches for developing the effective microalgae-bacteria partners for carbon sequestration and nutrient recovery from wastewater, and summarizes future research perspectives on microalgae-microbiome based bioremediation.

ASV vs OTUs clustering: Effects on alpha, beta, and gamma diversities in microbiome metabarcoding studies

In microbial community sequencing, involving bacterial ribosomal 16S rDNA or fungal ITS, the targeted genes are the basis for taxonomical assignment. The traditional bioinformatical procedure has for decades made use of a clustering protocol by which sequences are pooled into packages of shared percent identity, typically at 97%, to yield Operational Technical Units (OTUs). Progress in the data processing methods has however led to the possibility of minimizing technical sequencers errors, which were the main reason for the OTU choice, and to analyze instead the exact Amplicon Sequence Variants (ASV) which is a choice yielding much less agglomerated reads. We have tested the two procedures on the same 16S metabarcoded bacterial amplicons dataset encompassing a series of samples from 17 adjacent habitats, taken across a 700 meter-long transect of different ecological conditions unfolding in a gradient spanning from cropland, through meadows, forest and all successional transitions up to the seashore, within the same coastal area. This design allowed to scan a high biodiversity basin and to measure alpha, beta and gamma diversity of the area, to verify the effect of the bioinformatics on the same data as concerns the values of ten different ecological indexes and other parameters. Two levels of progressive OTUs clustering, (99% and 97%) were compared with the ASV data. The results showed that the OTUs clustering proportionally led to a marked underestimation of the ecological indicators values for species diversity and to a distorted behaviour of the dominance and evenness indexes with respect to the direct use of the ASV data. Multivariate ordination analyses resulted also sensitive in terms of tree topology and coherence. Overall, data support the view that reference-based OTU clustering carries several misleading disadvantageous biases, including the risk of missing novel taxa which are yet unreferenced in databases. Since its alternatives as de novo clustering have on the other hand drawbacks due to heavier computational demand and results comparability, especially for environmental studies which contain several yet uncharacterized species, the direct ASV based analysis, at least for prokaryotes, appears to warrant significand advantages in comparison to OTU clustering at every level of percent identity cutoff.

Networks as tools for defining emergent properties of microbiomes and their stability

The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. Video Abstract.

New insights into biologic interpretation of bioinformatic pipelines for fish eDNA metabarcoding: A case study in Pearl River estuary

Environmental DNA (eDNA) metabarcoding is an emerging tool for monitoring biological communities in aquatic ecosystems. The selection of bioinformatic pipelines significantly impacts the results of biodiversity assessments. However, there is currently no consensus on the appropriate bioinformatic pipelines for fish community analysis in eDNA metabarcoding. In this study, we compared three bioinformatic pipelines (Uparse, DADA2, and UNOISE3) using real and mock (constructed with 15/30 known fish) communities to investigate the differences in biological interpretation during the data analysis process in eDNA metabarcoding. Performance evaluation and diversity analyses revealed that the choice of bioinformatic pipeline could impact the biological results of metabarcoding experiments. Among the three pipelines, the operational taxonomic units (OTU)-based pipeline (Uparse) showed the best performance (sensitivity: 0.6250 ± 0.0166; compositional similarity: 0.4000 ± 0.0571), the highest richness (25-102) and minimal inter-group differences in alpha diversity. It suggested the OTU-based pipeline possessed superior capability in fish diversity monitoring compared to ASV/ZOTU-based pipeline. Additionally, the Bray-Curtis distance matrix achieved the highest discriminative effect in the PCoA (43.3%-53.89%) and inter-group analysis (P < 0.01), indicating it was better at distinguishing compositional differences or specific genera of fish community at different sampling sites than other distance matrices. These findings provide new insights into fish community monitoring through eDNA metabarcoding in estuarine environments.

Navigating the complex relationship between human gut microbiota and breast cancer: Physiopathological, prognostic and therapeutic implications

The human body represents the habitat of trillions of symbiotic microorganisms, collectively known as human microbiota, approximately half of which residing in the gut. The development of next-generation sequencing techniques has boosted the profiling of human microbiota in recent years. A growing body of evidence seems to support a strict relationship between the disruption of the mutualistic relationship between the microbiota and the host (i.e., dysbiosis) and the development of several diseases, including breast malignancies. Breast cancer still represents the most frequent cause of cancer-related death in women. Its complex relationship with gut microbiota is the object of a growing body of evidence. In fact, the interaction with the host immune system and a direct impact of gut microbiota on estrogen, lipid and polyphenols metabolism, seem to potentially affect breast tumor development, progression and response to treatments. In this review, in an attempt to help oncologists navigating this rapidly-evolving research field, we provide an essential overview on the taxonomy, main analytical techniques and terminology most commonly adopted. We discuss what is currently known regarding the interaction between gut microbiota and breast cancer and potential efforts to harness this complex interplay for therapeutic purposes, and revise main ongoing studies. We also briefly provide an overview on breast cancer intratumoral microbiota and its potential role beyond gut microbiota.

Lactobacillus-Polydopamine System for Targeted Drug Delivery in Overactive Bladder: Evidence from Bladder Cell Spheroids, Rat Models, and Urinary Microbiome Profiling

Introduction

Overactive bladder (OAB) is a highly prevalent condition with limited treatment options due to poor efficacy, side effects, and patient compliance. Novel drug delivery systems that can target the bladder wall may improve OAB therapy.

Methods

We explored a polydopamine (PDA)-coated lactobacillus platform as a potential carrier for localized OAB treatment. Urinary microbiome profiling was performed to identify the presence of lactobacillus in healthy and OAB groups. Lactobacillus-PDA nanoparticles were synthesized and characterized by electron microscopy and spectrophotometry. A rat bladder perfusion model and human bladder smooth muscle cell spheroids were used to assess the distribution and penetration of the nanoparticles. The efficacy of the Lactobacillus-PDA system (LPS) for delivering the antimuscarinic drug solifenacin was evaluated in an OAB rat model.

Results

Urinary microbiome profiling revealed lactobacillus as a dominant genus in both healthy and OAB groups. The synthesized Lactobacillus-PDA nanoparticles exhibited uniform size and optical properties. In the rat bladder perfusion model, the nanoparticles distributed throughout the bladder wall and smooth muscle without toxicity. The nanoparticles also penetrated human bladder smooth muscle cell spheroids. In the OAB rat model, LPS facilitated the delivery of solifenacin and improved treatment efficacy.

Discussion

The results highlight LPS as a promising drug carrier for targeted OAB therapy via penetration into bladder tissues. This bacteriotherapy approach may overcome limitations of current systemic OAB medications. Lactobacillus, a probiotic bacterium present in the urinary tract microbiome, was hypothesized to adhere to and penetrate the bladder wall when coated with PDA nanoparticles, making it a suitable candidate for localized drug delivery.

Distinct microdiversity of phosphate accumulating organisms (PAOs) between side-stream and conventional enhanced biological phosphorus removal (EBPR) systems with performance implications

Polyphosphate Accumulating Organisms (PAOs) microdiversity is a key factor to elucidate the mechanisms involved in the side-stream enhanced biological phosphorus removal (S2EBPR) systems, which has been shown to improve the process stability over conventional EBPR. However, fast, effective and cost-efficient methods to resolve PAO microdiversity in real-world activate sludge samples is still in absence. In this study, we applied oligotyping analysis following the regular 16S rRNA gene amplicon sequencing standard operation pipeline (SOP) to resolve subgenus-level PAO oligotypes, which cannot be achieved using traditional 16S rRNA sequencing SOP. The identified oligotype profiles of PAO-containing genera Ca. Accumulibacter, Tetrasphaera and Comamonas showed distinguished community-level differences across 12 water resource recovery facilities (WRRFs), which would not be revealed at the genus level. The WRRF-level differences were observed larger than the temporal differences in the same WRRF, indicating intrinsic sub-genus level microdiversity fingerprint between EBPR/S2EBPR systems. The identified oligotypes can be associated with known PAO clades phylogenetically, suggesting that oligotyping can suffice as a fast and cost-efficient approach for PAO microdiversity profiling. In addition, network analysis can be used to identify coexistence patterns between oligotypes with respect to EBPR/S2EBPR configurations and performance, enabling more detailed analysis between EBPR system performance and PAOs microdiversity. Correlation analyses between oligotype profiles and key EBPR performance parameters revealed potential different biological functional traits among these PAO species with P-removal performance implications.

Transforming gastrointestinal helminth parasite identification in vertebrate hosts with metabarcoding: a systematic review

BACKGROUND

Gastrointestinal helminths are a very widespread group of intestinal parasites that can cause major health issues in their hosts, including severe illness or death. Traditional methods of helminth parasite identification using microscopy are time-consuming and poor in terms of taxonomic resolution, and require skilled observers. DNA metabarcoding has emerged as a powerful alternative for assessing community composition in a variety of sample types over the last few decades. While metabarcoding approaches have been reviewed for use in other research areas, the use of metabarcoding for parasites has only recently become widespread. As such, there is a need to synthesize parasite metabarcoding methodology and highlight the considerations to be taken into account when developing a protocol.

METHODS

We reviewed published literature that utilized DNA metabarcoding to identify gastrointestinal helminth parasites in vertebrate hosts. We extracted information from 62 peer-reviewed papers published between 2014 and 2023 and created a stepwise guide to the metabarcoding process.

RESULTS

We found that studies in our review varied in technique and methodology, such as the sample type utilized, genetic marker regions targeted and bioinformatic databases used. The main limitations of metabarcoding are that parasite abundance data may not be reliably attained from sequence read numbers, metabarcoding data may not be representative of the species present in the host and the cost and bioinformatic expertise required to utilize this method may be prohibitive to some groups.

CONCLUSIONS

Overall, using metabarcoding to assess gastrointestinal parasite communities is preferable to traditional methods, yielding higher taxonomic resolution, higher throughput and increased versatility due to its utility in any geographical location, with a variety of sample types, and with virtually any vertebrate host species. Additionally, metabarcoding has the potential for exciting new discoveries regarding host and parasite evolution.

Comparison of Metabarcoding and Microscopy Methodologies to Analyze Diatom Communities in Five Estuaries Along the Southern Coast of the Korean Peninsula

The study of microalgal communities is critical for understanding aquatic ecosystems. These communities primarily comprise diatoms (Heterokontophyta), with two methods commonly used to study them: Microscopy and metabarcoding. However, these two methods often deliver different results; thus, their suitability for analyzing diatom communities is frequently debated and evaluated. This study used these two methods to analyze the diatom communities in identical water samples and compare the results. The taxonomy of the species constituting the diatom communities was confirmed, and both methods showed that species belonging to the orders Bacillariales and Naviculales (class Bacillariophyceae) are the most diverse. In the lower taxonomic levels (family, genus, and species), microscopy tended to show a bias toward detecting diatom species (Nitzschia frustulum, Nitzschia inconspicua, Nitzschia intermedia, Navicula gregaria, Navicula perminuta, Navicula recens, Navicula sp.) belonging to the Bacillariaceae and Naviculaceae families. The results of the two methods differed in identifying diatom species in the communities and analyzing their structural characteristics. These results are consistent with the fact that diatoms belonging to the genera Nitzschia and Navicula are abundant in the communities; furthermore, only the Illumina MiSeq data showed the abundance of the Melosira and Entomoneis genera. The results obtained from microscopy were superior to those of Illumina MiSeq regarding species-level identification. Based on the results obtained via microscopy and Illumina MiSeq, it was revealed that neither method is perfect and that each has clear strengths and weaknesses. Therefore, to analyze diatom communities effectively and accurately, these two methods should be combined.

Analysis of Intestinal Bacterial Microbiota in Individuals with and without Chronic Low Back Pain

Low back pain is a health problem that represents the greatest cause of years lived with disability. This research seeks to evaluate the bacterial composition of the intestinal microbiota of two similar groups: one with chronic low back pain (PG) and the control group (CG). Clinical data from 73 participants and bacterial genome sequencing data from stool samples were analyzed. There were 40 individuals in PG and 33 in CG, aged between 20 and 50 years and with a body mass index of up to 30 kg/m2. Thus, the intragroup alpha diversity and intergroup beta diversity were analyzed. The significant results (p < 0.05) showed greater species richness in PG compared to CG. Additionally, a greater abundance of the species Clostridium difficile in PG was found along with 52 species with significantly different average relative abundances between groups (adjusted p < 0.05), with 36 more abundant species in PG and 16 in CG. We are the first to unveil significant differences in the composition of the intestinal bacterial microbiota of individuals with chronic low back pain who are non-elderly, non-obese and without any other serious chronic diseases. It could be a reference for a possible intestinal bacterial microbiota signature in chronic low back pain.

Comparison of Yamuna (India) and Mississippi River (United States of America) bacterial communities reveals greater diversity below the Yamunotri Glacier

The Yamuna River in India and the Mississippi River in the United States hold significant commercial, cultural, and ecological importance. This preliminary survey compares the bacterial communities sampled in surface waters at 11 sites (Yamuna headwaters, Mississippi headwaters, Yamuna River Yamunotri Town, Mississippi River at Winona, Tons River, Yamuna River at Paonta Sahib, Yamuna River Delhi-1, Yamuna River Delhi-2, Yamuna River before Sangam, Sangam, Ganga River before Sangam). Bacterial 16S rDNA analyses demonstrate dominance of Proteobacteria and Bacteroidetes phyla. Actinobacteria were also dominant at sites near Sangam in India and sites in Minnesota. A dominance of Epsilonbacteraeota were found in Delhi, India. Principal component analysis (PCA) using unique operational taxonomic units (OTUs) resulted in the identification of 3 groups that included the Yamuna River locations in Delhi (Delhi locations), Yamuna headwaters and Yamuna River at Yamunotri (Yamuna River locations below the Glacier) and Mississippi, Ganga, Tons, and other Yamuna River locations. Diversity indices were significantly higher at the Yamuna River locations below the Glacier (Simpson D = 0.986 and Shannon H = 5.06) as compared (p value <0.001) to the Delhi locations (D = 0.951 and H = 4.23) and as compared (p value < 0.001) to Mississippi, Ganga, Tons, and other Yamuna River locations (D = 0.943 and H = 3.96). To our knowledge, this is the first survey to compare Mississippi and Yamuna River bacterial communities. We demonstrate higher diversity in the bacterial communities below the Yamunotri glacier in India.

The "Dry-Lab" Side of Food Authentication: Benchmark of Bioinformatic Pipelines for the Analysis of Metabarcoding Data

Next Generation Sequencing Technologies (NGS), particularly metabarcoding, are valuable tools for authenticating foodstuffs and detecting eventual fraudulent practices such as species substitution. This technique, mostly used for the analysis of prokaryotes in several environments (including food), is in fact increasingly applied to identify eukaryotes (e.g., fish, mammals, avian, etc.) in multispecies food products. Besides the "wet-lab" procedures (e.g., DNA extraction, PCR, amplicon purification, etc.), the metabarcoding workflow includes a final "dry-lab" phase in which sequencing data are analyzed using a bioinformatic pipeline (BP). BPs play a crucial role in the accuracy, reliability, and interpretability of the metabarcoding results. Choosing the most suitable BP for the analysis of metabarcoding data could be challenging because it might require greater informatics skills than those needed in standard molecular analysis. To date, studies comparing BPs for metabarcoding data analysis in foodstuff authentication are scarce. In this study, we compared the data obtained from two previous studies in which fish burgers and insect-based products were authenticated using a customizable, ASV-based, and command-line interface BP (BP1) by analyzing the same data with a customizable but OTU-based and graphical user interface BP (BP2). The final sample compositions were compared statistically. No significant difference in sample compositions was highlighted by applying BP1 and BP2. However, BP1 was considered as more user-friendly than BP2 with respect to data analysis streamlining, cost of analysis, and computational time consumption. This study can provide useful information for researchers approaching the bioinformatic analysis of metabarcoding data for the first time. In the field of food authentication, an effective and efficient use of BPs could be especially useful in the context of official controls performed by the Competent Authorities and companies' self-control in order to detect species substitution and counterfeit frauds.

Synthesis of current pediatric urinary microbiome research

The human urinary bladder hosts a complex microbial community of low biomass referred to as the urobiome. While the composition of the urobiome has been investigated in adults for over a decade now, only a few studies have considered the presence and composition of the urobiome in children. It is critical to explore how the urobiome develops throughout the life span and how it changes in the presence of various health conditions. Therefore, we set to review the available data on pediatric urobiome composition and its development with age and disease. In addition, we focused on identifying and reporting specific gaps in our knowledge of the pediatric urobiome that we hope will be addressed by future studies in this swiftly developing field with fast-improving methods and consensus.

The relationship between atmospheric particulate matter, leaf surface microstructure, and the phyllosphere microbial diversity of Ulmus L

BACKGROUND

Plants can retain atmospheric particulate matter (PM) through their unique foliar microstructures, which has a profound impact on the phyllosphere microbial communities. Yet, the underlying mechanisms linking atmospheric particulate matter (PM) retention by foliar microstructures to variations in the phyllosphere microbial communities remain a mystery. In this study, we conducted a field experiment with ten Ulmus lines. A series of analytical techniques, including scanning electron microscopy, atomic force microscopy, and high-throughput amplicon sequencing, were applied to examine the relationship between foliar surface microstructures, PM retention, and phyllosphere microbial diversity of Ulmus L.

RESULTS

We characterized the leaf microstructures across the ten Ulmus lines. Chun exhibited a highly undulated abaxial surface and dense stomatal distribution. Langya and Xingshan possessed dense abaxial trichomes, while Lieye, Zuiweng, and Daguo had sparsely distributed, short abaxial trichomes. Duomai, Qingyun, and Lang were characterized by sparse stomata and flat abaxial surfaces, whereas Jinye had sparsely distributed but extensive stomata. The mean leaf retention values for total suspended particulate (TSP), PM2.5, PM2.5-10, PM10-100, and PM> 100 were 135.76, 6.60, 20.10, 90.98, and 13.08 µg·cm- 2, respectively. Trichomes substantially contributed to PM2.5 retention, while larger undulations enhanced PM2.5-10 retention, as evidenced by positive correlations between PM2.5 and abaxial trichome density and between PM2.5-10 and the adaxial raw microroughness values. Phyllosphere microbial diversity patterns varied among lines, with bacteria dominated by Sediminibacterium and fungi by Mycosphaerella, Alternaria, and Cladosporium. Redundancy analysis confirmed that dense leaf trichomes facilitated the capture of PM2.5-associated fungi, while bacteria were less impacted by PM and struggled to adhere to leaf microstructures. Long and dense trichomes provided ideal microhabitats for retaining PM-borne microbes, as evidenced by positive feedback loops between PM2.5, trichome characteristics, and the relative abundances of microorganisms like Trichoderma and Aspergillus.

CONCLUSIONS

Based on our findings, a three-factor network profile was constructed, which provides a foundation for further exploration into how different plants retain PM through foliar microstructures, thereby impacting phyllosphere microbial communities.

Comparative analysis of gut microbiota in children with obstructive sleep apnea: assessing the efficacy of 16S rRNA gene sequencing in metabolic function prediction based on weight status

Background

Analyzing bacterial microbiomes consistently using next-generation sequencing (NGS) is challenging due to the diversity of synthetic platforms for 16S rRNA genes and their analytical pipelines. This study compares the efficacy of full-length (V1-V9 hypervariable regions) and partial-length (V3-V4 hypervariable regions) sequencing of synthetic 16S rRNA genes from human gut microbiomes, with a focus on childhood obesity.

Methods

In this observational and comparative study, we explored the differences between these two sequencing methods in taxonomic categorization and weight status prediction among twelve children with obstructive sleep apnea.

Results

The full-length NGS method by Pacbio® identified 118 genera and 248 species in the V1-V9 regions, all with a 0% unclassified rate. In contrast, the partial-length NGS method by Illumina® detected 142 genera (with a 39% unclassified rate) and 6 species (with a 99% unclassified rate) in the V3-V4 regions. These approaches showed marked differences in gut microbiome composition and functional predictions. The full-length method distinguished between obese and non-obese children using the Firmicutes/Bacteroidetes ratio, a known obesity marker (p = 0.046), whereas the partial-length method was less conclusive (p = 0.075). Additionally, out of 73 metabolic pathways identified through full-length sequencing, 35 (48%) were associated with level 1 metabolism, compared to 28 of 61 pathways (46%) identified through the partial-length method. The full-length NGS also highlighted complex associations between body mass index z-score, three bacterial species (Bacteroides ovatus, Bifidobacterium pseudocatenulatum, and Streptococcus parasanguinis ATCC 15912), and 17 metabolic pathways. Both sequencing techniques revealed relationships between gut microbiota composition and OSA-related parameters, with full-length sequencing offering more comprehensive insights into associated metabolic pathways than the V3-V4 technique.

Conclusion

These findings highlight disparities in NGS-based assessments, emphasizing the value of full-length NGS with amplicon sequence variant analysis for clinical gut microbiome research. They underscore the importance of considering methodological differences in future meta-analyses.

Intervertebral disc microbiome in Modic changes: Lack of result replication underscores the need for a consensus in low-biomass microbiome analysis

Introduction

The emerging field of the disc microbiome challenges traditional views of disc sterility, which opens new avenues for novel clinical insights. However, the lack of methodological consensus in disc microbiome studies introduces discrepancies. The aims of this study were to (1) compare the disc microbiome of non-Modic (nonMC), Modic type 1 change (MC1), and MC2 discs to findings from prior disc microbiome studies, and (2) investigate if discrepancies to prior studies can be explained with bioinformatic variations.

Methods

Sequencing of 16S rRNA in 70 discs (24 nonMC, 25 MC1, and 21 MC2) for microbiome profiling. The experimental setup included buffer contamination controls and was performed under aseptic conditions. Methodology and results were contrasted with previous disc microbiome studies. Critical bioinformatic steps that were different in our best-practice approach and previous disc microbiome studies (taxonomic lineage assignment, prevalence cut-off) were varied and their effect on results were compared.

Results

There was limited overlap of results with a previous study on MC disc microbiome. No bacterial genera were shared using the same bioinformatic parameters. Taxonomic lineage assignment using "amplicon sequencing variants" was more sensitive and detected 48 genera compared to 22 with "operational taxonomic units" (previous study). Increasing filter cut-off from 4% to 50% (previous study) reduced genera from 48 to 4 genera. Despite these differences, both studies observed dysbiosis with an increased abundance of gram-negative bacteria in MC discs as well as a lower beta-diversity. Cutibacterium was persistently detected in all groups independent of the bioinformatic approach, emphasizing its prevalence.

Conclusion

There is dysbiosis in MC discs. Bioinformatic parameters impact results yet cannot explain the different findings from this and a previous study. Therefore, discrepancies are likely caused by different sample preparations or true biologic differences. Harmonized protocols are required to advance understanding of the disc microbiome and its clinical implications.

Microbial community diversity from nearshore to offshore in the East China Sea

The Pollution Nagasaki (PN) section of the East China Sea (ECS) is a typical area for studying the complex hydrographic dynamics between Changjiang River discharge and Kuroshio, displaying intense variations of environmental gradients from nearshore to offshore. However, the temporal and spatial changes of microbial communities along the PN section have long been overlooked. In this study, we performed a comprehensive investigation into the abundance, diversity and ecology of free-living (FL) and particle-associated (PA) microbial communities in seawater samples along the PN section during both summer and winter. Distinct hydrological conditions and resulting environmental gradients were observed between summer and winter, with clear features of intrusive Kuroshio subsurface water in summer and strong vertical mixing of seawater in winter. Bacterial abundance along the PN section was higher in summer (1.11 × 108 copies·L-1 - 7.37 × 108 copies·L-1) than in winter (1.83 × 106 copies·L-1 - 1.34 × 108 copies·L-1). Microbial diversity, as indicated by α-diversity indices, remained at relatively stable levels in summer, while a clear decreasing trend was observed in winter along the PN section. Additionally, the winter communities exhibited a more evident spatial shift along the PN section compared to the summer communities. 16S rRNA gene amplicon sequencing showed that microbial community composition varied considerably between different seasons (summer and winter) and lifestyles (FL and PA), with a notable dominance of Ralstonia species. in winter. Regarding the assembly of microbial communities, the stochastic process represented by dispersal limitation was the dominant process in summer, while the deterministic homogeneous selection was the most important process in winter. Correspondingly, distinct topological properties of the microbial co-occurrence networks were shown between different seasons and along the PN section. These results enhance our understanding of how hydrological conditions influence dynamic changes of microbial communities along the PN section, providing new insights for the microbial community assembly and interactions in such a complex environment.

The effects of time-restricted eating and Ramadan fasting on gut microbiota composition: a systematic review of human and animal studies

CONTEXT

It is well known that the microbiome undergoes cyclical diurnal rhythms. It has thus been hypothesized that meal timing may affect gut microbial composition, function, and host health.

OBJECTIVE

This review aims to examine the effects of time-restricted eating (TRE) and Ramadan fasting (RF) on the composition of the gut microbiota in animal and human studies. The associations between composition of microbiota and host metabolic parameters are also examined.

DATA SOURCES

A search was performed on the PubMed, Cochrane, Scopus, and Web of Science databases up to December 31, 2022. The search strategy was performed using the Medical Subject Heading (MeSH) terms "intermittent fasting" and "gastrointestinal microbiome" and the key words "Ramadan fasting" and "microbes."

DATA EXTRACTION

Seven human studies (4 TRE and 3 RF) and 9 animal studies (7 TRE, 2 RF-like) were retrieved.

DATA ANALYSIS

TRE and RF in human studies lead to an increase in gut microbial community alpha-diversity. In animal studies (both TRE and RF-like), fasting is not associated with improved alpha-diversity, but enhancement of microbial fluctuation is observed, compared with high-fat diet ad libitum groups. Within Firmicutes and Bacteroidetes phyla, no specific direction of changes resulting from fasting are observed in both animals and human. After TRE or RF, a greater abundance of the Faecalibacterium genus is observed in human studies; changes in Lactobacillus abundance are found in animal studies; and increases in Akkermansia are seen both in humans and in animals fed a feed-pellet diet. Only 2 human studies show a beneficial correlation between microbiota changes and host metabolic (HDL cholesterol) or anthropometric parameters (body mass index).

CONCLUSIONS

These findings support the importance of both regimens in improving the gut microbiota composition. However, based on results of animal studies, it can be suggested that diet remains the essential factor in forming the microbiota's environment.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42021278918.

Ramírez CM, Peimbert M. Revealing the microbiome diversity and biocontrol potential of field Aedes ssp.: Implications for disease vector management

The mosquito Aedes spp. holds important relevance for human and animal health, as it serves as a vector for transmitting multiple diseases, including dengue and Zika virus. The microbiome's impact on its host's health and fitness is well known. However, most studies on mosquito microbiomes have been conducted in laboratory settings. We explored the mixed microbial communities within Aedes spp., utilizing the 16S rRNA gene for diversity analysis and shotgun metagenomics for functional genomics. Our samples, which included Ae. aegypti and Ae. albopictus, spanned various developmental stages-eggs, larvae, and adults-gathered from five semiurban areas in Mexico. Our findings revealed a substantial diversity of 8,346 operational taxonomic units (OTUs), representing 967 bacterial genera and 126,366 annotated proteins. The host developmental stage was identified as the primary factor associated with variations in the microbiome composition. Subsequently, we searched for genes and species involved in mosquito biocontrol. Wolbachia accounted for 9.6% of the 16S gene sequences. We observed a high diversity (203 OTUs) of Wolbachia strains commonly associated with mosquitoes, such as wAlb, with a noticeable increase in abundance during the adult stages. Notably, we detected the presence of the cifA and cifB genes, which are associated with Wolbachia's cytoplasmic incompatibility, a biocontrol mechanism. Additionally, we identified 221 OTUs related to Bacillus, including strains linked to B. thuringiensis. Furthermore, we discovered multiple genes encoding insecticidal toxins, such as Cry, Mcf, Vip, and Vpp. Overall, our study contributes to the understanding of mosquito microbiome biodiversity and metabolic capabilities, which are essential for developing effective biocontrol strategies against this disease vector.

Exploring the impact of Anaplasma phagocytophilum on colonization resistance of Ixodes scapularis microbiota using network node manipulation

Upon ingestion from an infected host, tick-borne pathogens (TBPs) have to overcome colonization resistance, a defense mechanism by which tick microbiota prevent microbial invasions. Previous studies have shown that the pathogen Anaplasma phagocytophilum alters the microbiota composition of the nymphs of Ixodes scapularis, but its impact on tick colonization resistance remains unclear. We analyzed tick microbiome genetic data using published Illumina 16S rRNA sequences, assessing microbial diversity within ticks (alpha diversity) through species richness, evenness, and phylogenetic diversity. We compared microbial communities in ticks with and without infection with A. phagocytophilum (beta diversity) using the Bray-Curtis index. We also built co-occurrence networks and used node manipulation to study the impact of A. phagocytophilum on microbial assembly and network robustness, crucial for colonization resistance. We examined network robustness by altering its connectivity, observing changes in the largest connected component (LCC) and the average path length (APL). Our findings revealed that infection with A. phagocytophilum does not significantly alter the overall microbial diversity in ticks. Despite a decrease in the number of nodes and connections within the microbial networks of infected ticks, certain core microbes remained consistently interconnected, suggesting a functional role. The network of infected ticks showed a heightened vulnerability to node removal, with smaller LCC and longer APL, indicating reduced resilience compared to the network of uninfected ticks. Interestingly, adding nodes to the network of infected ticks led to an increase in LCC and a decrease in APL, suggesting a recovery in network robustness, a trend not observed in networks of uninfected ticks. This improvement in network robustness upon node addition hints that infection with A. phagocytophilum might lower ticks' resistance to colonization, potentially facilitating further microbial invasions. We conclude that the compromised colonization resistance observed in tick microbiota following infection with A. phagocytophilum may facilitate co-infection in natural tick populations.

Analysis on the change of gut microbiota and metabolome in lung transplant patients

Previous studies have shown that the gut microbiota and its metabolites are associated with the success of organ transplantation. However, the specific changes in the gut microbiota of lung transplant patients remain unclear. Hence, this study aimed to elucidate the interplay between the gut microbiota, metabolome, and lung transplantation outcomes. Using 16S metagenomics sequencing and untargeted metabolic profiling, we conducted a comprehensive analysis of gut microbial and metabolic alterations in lung transplant recipients relative to non-transplant group. Our findings revealed the predominance of Enterococcus and Streptococcus genera within the lung transplant cohort, accompanied by the significant reduction in Bacteroides, Epulopiscium, Faecalibacterium, and Prevotella abundance. In addition, a significant reduction in ATRA (all-trans retinoic acid) levels and suppression of IgA production were observed in lung transplant recipients, which were found to be closely associated with the Enterococcus genus. It was speculated that the association might have implications for the prognosis of lung transplant patients. Notably, the differences in gut microbial composition and metabolomic profiles between successful transplant recipients and those experiencing chronic rejection were not statistically significant. These novel insights shed light on the putative implications of the gut microbiota and metabolome in shaping lung transplantation outcomes, and provide a foundation for future investigations and targeted therapeutic interventions.

IMPORTANCE

This study has profound implications for lung transplantation as it uncovers the important role of gut microbiota and metabolome in shaping transplantation outcomes. The identification of dominant bacterial genera, such as Enterococcus and Streptococcus, within the lung transplant cohort, along with the significant decrease in Bacteroides, Epulopiscium, Faecalibacterium, and Prevotella abundance, reveals potential microbial imbalances associated with lung transplantation. In addition, a significant reduction in ATRA (all-trans retinoic acid) levels and suppression of IgA production were observed in lung transplant recipients, which were found to be closely associated with the Enterococcus genus. It was speculated that the association might have implications for the prognosis of lung transplant patients. These findings hold immense clinical significance as they lay the groundwork for future research and targeted therapeutic interventions. Understanding the impact of the gut microbiota and metabolome on lung transplantation outcomes offers promising avenues for improving transplantation patient prognosis.

Saliva sampling method influences oral microbiome composition and taxa distribution associated with oral diseases

Saliva is a readily accessible and inexpensive biological specimen that enables investigation of the oral microbiome, which can serve as a biomarker of oral and systemic health. There are two routine approaches to collect saliva, stimulated and unstimulated; however, there is no consensus on how sampling method influences oral microbiome metrics. In this study, we analyzed paired saliva samples (unstimulated and stimulated) from 88 individuals, aged 7-18 years. Using 16S rRNA gene sequencing, we investigated the differences in bacterial microbiome composition between sample types and determined how sampling method affects the distribution of taxa associated with untreated dental caries and gingivitis. Our analyses indicated significant differences in microbiome composition between the sample types. Both sampling methods were able to detect significant differences in microbiome composition between healthy subjects and subjects with untreated caries. However, only stimulated saliva revealed a significant association between microbiome diversity and composition in individuals with diagnosed gingivitis. Furthermore, taxa previously associated with dental caries and gingivitis were preferentially enriched in individuals with each respective disease only in stimulated saliva. Our study suggests that stimulated saliva provides a more nuanced readout of microbiome composition and taxa distribution associated with untreated dental caries and gingivitis compared to unstimulated saliva.

Considerations for the inclusion of metabarcoding data in the plant protection product risk assessment of the soil microbiome

There is increasing interest in further developing the plant protection product (PPP) environmental risk assessment, particularly within the European Union, to include the assessment of soil microbial community composition, as measured by metabarcoding approaches. However, to date, there has been little discussion as to how this could be implemented in a standardized, reliable, and robust manner suitable for regulatory decision-making. Introduction of metabarcoding-based assessments of the soil microbiome into the PPP risk assessment would represent a significant increase in the degree of complexity of the data that needs to be processed and analyzed in comparison to the existing risk assessment on in-soil organisms. The bioinformatics procedures to process DNA sequences into community compositional data sets currently lack standardization, while little information exists on how these data should be used to generate regulatory endpoints and the ways in which these endpoints should be interpreted. Through a thorough and critical review, we explore these challenges. We conclude that currently, we do not have a sufficient degree of standardization or understanding of the required bioinformatics and data analysis procedures to consider their use in an environmental risk assessment context. However, we highlight critical knowledge gaps and the further research required to understand whether metabarcoding-based assessments of the soil microbiome can be utilized in a statistically and ecologically relevant manner within a PPP risk assessment. Only once these challenges are addressed can we consider if and how we should use metabarcoding as a tool for regulatory decision-making to assess and monitor ecotoxicological effects on soil microorganisms within an environmental risk assessment of PPPs. Integr Environ Assess Manag 2024;20:337-358. © 2023 SETAC.

Polyphasic molecular approach to the characterization of methanogens in the saliva of Tunisian adults

OBJECTIVES

Methanogenic archaea are a minor component of human oral microbiota. Due to their relatively low abundance, the detection of these neglected microorganisms is challenging. This study concerns the presence of methanogens in salivary samples collected from Tunisian adults to evaluate their prevalence and burden using a polyphasic molecular approach.

METHODS

A total of 43 saliva samples were included. Metagenomic and standard 16S rRNA sequencing were performed as an initial screening to detect the presence of methanogens in the oral microbiota of Tunisian adults. Further investigations were performed using specific quantitative real-time PCR targeting Methanobrevibacter oralis and Methanobrevibacter smithii.

RESULTS

Methanobrevibacter was detected in 5/43 (11.62 %) saliva samples after metagenomic 16S rRNA data analysis. The presence of M. oralis was confirmed in 6/43 samples by standard 16S rRNA sequencing. Using real-time PCR, methanogens were detected in 35/43 (81.39 %) samples, including 62.79 % positive for M. oralis and 76.74 % positive for M. smithii. These findings reflect the high prevalence of both methanogens, revealed by the high sensitivity of the real-time PCR approach. Interestingly, we also noted a significant statistical association between the detection of M. smithii and poor adherence to a Mediterranean diet, indicating the impact of diet on M. smithii prevalence.

CONCLUSION

Our study showed the presence of methanogens in the oral microbiota of Tunisian adults with an unprecedented relatively high prevalence. Choice of methodology is also central to picturing the real prevalence and diversity of such minor taxa in the oral microbiota.

A robust microbiome signature for autism spectrum disorder across different studies using machine learning

Autism spectrum disorder (ASD) is a highly complex neurodevelopmental disorder characterized by deficits in sociability and repetitive behaviour, however there is a great heterogeneity within other comorbidities that accompany ASD. Recently, gut microbiome has been pointed out as a plausible contributing factor for ASD development as individuals diagnosed with ASD often suffer from intestinal problems and show a differentiated intestinal microbial composition. Nevertheless, gut microbiome studies in ASD rarely agree on the specific bacterial taxa involved in this disorder. Regarding the potential role of gut microbiome in ASD pathophysiology, our aim is to investigate whether there is a set of bacterial taxa relevant for ASD classification by using a sibling-controlled dataset. Additionally, we aim to validate these results across two independent cohorts as several confounding factors, such as lifestyle, influence both ASD and gut microbiome studies. A machine learning approach, recursive ensemble feature selection (REFS), was applied to 16S rRNA gene sequencing data from 117 subjects (60 ASD cases and 57 siblings) identifying 26 bacterial taxa that discriminate ASD cases from controls. The average area under the curve (AUC) of this specific set of bacteria in the sibling-controlled dataset was 81.6%. Moreover, we applied the selected bacterial taxa in a tenfold cross-validation scheme using two independent cohorts (a total of 223 samples-125 ASD cases and 98 controls). We obtained average AUCs of 74.8% and 74%, respectively. Analysis of the gut microbiome using REFS identified a set of bacterial taxa that can be used to predict the ASD status of children in three distinct cohorts with AUC over 80% for the best-performing classifiers. Our results indicate that the gut microbiome has a strong association with ASD and should not be disregarded as a potential target for therapeutic interventions. Furthermore, our work can contribute to use the proposed approach for identifying microbiome signatures across other 16S rRNA gene sequencing datasets.

Multi-omic approaches for host-microbiome data integration

The gut microbiome interacts with the host through complex networks that affect physiology and health outcomes. It is becoming clear that these interactions can be measured across many different omics layers, including the genome, transcriptome, epigenome, metabolome, and proteome, among others. Multi-omic studies of the microbiome can provide insight into the mechanisms underlying host-microbe interactions. As more omics layers are considered, increasingly sophisticated statistical methods are required to integrate them. In this review, we provide an overview of approaches currently used to characterize multi-omic interactions between host and microbiome data. While a large number of studies have generated a deeper understanding of host-microbiome interactions, there is still a need for standardization across approaches. Furthermore, microbiome studies would also benefit from the collection and curation of large, publicly available multi-omics datasets.

Mock microbial community meta-analysis using different trimming of amplicon read lengths

Trimming of sequencing reads is a pre-processing step that aims to discard sequence segments such as primers, adapters and low quality nucleotides that will interfere with clustering and classification steps. We evaluated the impact of trimming length of paired-end 16S and 18S rRNA amplicon reads on the ability to reconstruct the taxonomic composition and relative abundances of communities with a known composition in both even and uneven proportions. We found that maximizing read retention maximizes recall but reduces precision by increasing false positives. The presence of expected taxa was accurately predicted across broad trim length ranges but recovering original relative proportions remains a difficult challenge. We show that parameters that maximize taxonomic recovery do not simultaneously maximize relative abundance accuracy. Trim length represents one of several experimental parameters that have non-uniform impact across microbial clades, making it a difficult parameter to optimize. This study offers insights, guidelines, and helps researchers assess the significance of their decisions when trimming raw reads in a microbiome analysis based on overlapping or non-overlapping paired-end amplicons.

Swarm and UNOISE outperform DADA2 and Deblur for denoising high-diversity marine seafloor samples

The performance of sequence variant resolution analytic tools for metabarcoding has not yet been adequately benchmarked for high-diversity environmental samples. We therefore evaluated the sequence variant tools DADA2, Deblur, Swarm, and UNOISE, using high-diversity seafloor samples, resulting in comparisons of 1800 sequence variant tables. The evaluation was based on 30 sediment grab samples, for which 3 replica samples were collected. Each replica sample was extracted using 5 common DNA extraction kits, resulting in 450 DNA extracts which were 16S rRNA gene sequenced (V3-V4), using Illumina. Assessments included variation across replica samples, extraction kits, and denoising methods, in addition to applying prior knowledge about alpha diversity correlations toward the cosmopolitan marine archaeon Nitrosopumilus with high diversity and the sulfide oxidizing Sulfurovum with low diversity. DADA2 displayed the highest variance between replicates (Manhattan distance 1.14), while Swarm showed the lowest variance (Manhattan distance 0.93). For the analysis based on prior biological knowledge, UNOISE displayed the highest alpha diversity (Simpson's D) correlation toward Nitrosopumilus (Spearman rho = 0.85), while DADA2 showed the lowest (Spearman rho = 0.10). Deblur completely eliminated Nitrosopumilus from the dataset. For Sulfurovum, on the other hand, all the methods showed comparable results. In conclusion, our evaluations show that Swarm and UNOISE performed better than DADA2 and Deblur for high-diversity seafloor samples.

Alterations to the bovine bacterial ocular surface microbiome in the context of infectious bovine keratoconjunctivitis

BACKGROUND

Infectious bovine keratoconjunctivitis (IBK) is a common cause of morbidity in cattle, resulting in significant economic losses. This study aimed to characterize the bovine bacterial ocular surface microbiome (OSM) through conjunctival swab samples from Normal eyes and eyes with naturally acquired, active IBK across populations of cattle using a three-part approach, including bacterial culture, relative abundance (RA, 16 S rRNA gene sequencing), and semi-quantitative random forest modeling (real-time polymerase chain reaction (RT-PCR)).

RESULTS

Conjunctival swab samples were obtained from eyes individually classified as Normal (n = 376) or IBK (n = 228) based on clinical signs. Cattle unaffected by IBK and the unaffected eye in cattle with contralateral IBK were used to obtain Normal eye samples. Moraxella bovis was cultured from similar proportions of IBK (7/228, 3.07%) and Normal eyes (1/159, 0.63%) (p = 0.1481). Moraxella bovoculi was cultured more frequently (p < 0.0001) in IBK (59/228, 25.88%) than Normal (7/159, 4.40%) eyes. RA (via 16 S rRNA gene sequencing) of Actinobacteriota was significantly higher in Normal eyes (p = 0.0045). Corynebacterium variabile and Corynebacterium stationis (Actinobacteriota) were detected at significantly higher RA (p = 0.0008, p = 0.0025 respectively) in Normal eyes. Rothia nasimurium (Actinobacteriota) was detected at significantly higher RA in IBK eyes (p < 0.0001). Alpha-diversity index was not significantly different between IBK and Normal eyes (p > 0.05). Alpha-diversity indices for geographic location (p < 0.001), age (p < 0.0001), sex (p < 0.05) and breed (p < 0.01) and beta-diversity indices for geographic location (p < 0.001), disease status (p < 0.01), age (p < 0.001), sex (p < 0.001) and breed (p < 0.001) were significantly different between groups. Modeling of RT-PCR values reliably categorized the microbiome of IBK and Normal eyes; primers for Moraxella bovoculi, Moraxella bovis, and Staphylococcus spp. were consistently the most significant canonical variables in these models.

CONCLUSIONS

The results provide further evidence that multiple elements of the bovine bacterial OSM are altered in the context of IBK, indicating the involvement of a variety of bacteria in addition to Moraxella bovis, including Moraxella bovoculi and R. nasimurium, among others. Actinobacteriota RA is altered in IBK, providing possible opportunities for novel therapeutic interventions. While RT-PCR modeling provided limited further support for the involvement of Moraxella bovis in IBK, this was not overtly reflected in culture or RA results. Results also highlight the influence of geographic location and breed type (dairy or beef) on the bovine bacterial OSM. RT-PCR modeling reliably categorized samples as IBK or Normal.

Yeast metagenomics: analytical challenges in the analysis of the eukaryotic microbiome

Even if their impact is often underestimated, yeasts and yeast-like fungi represent the most prevalent eukaryotic members of microbial communities on Earth. They play numerous roles in natural ecosystems and in association with their hosts. They are involved in the food industry and pharmaceutical production, but they can also cause diseases in other organisms, making the understanding of their biology mandatory. The ongoing loss of biodiversity due to overexploitation of environmental resources is a growing concern in many countries. Therefore, it becomes crucial to understand the ecology and evolutionary history of these organisms to systematically classify them. To achieve this, it is essential that our knowledge of the mycobiota reaches a level similar to that of the bacterial communities. To overcome the existing challenges in the study of fungal communities, the first step should be the establishment of standardized techniques for the correct identification of species, even from complex matrices, both in wet lab practices and in bioinformatic tools.

Microdiversity sustains the distribution of rhizosphere-associated bacterial species from the root surface to the bulk soil region in maize crop fields

Over the years, the microbial community of maize (Zea mays) rhizosphere has been extensively studied; however, the role of microdiversity sustain rhizosphere-associated microbial species distribution from root surface to bulk soil in mature maize is still unclear. Although operational taxonomic units (OTUs) have been used to classify species, amplicon sequence variants (ASVs) have been shown to be effective in representing microdiversity within OTUs at a finer genetic scale. Therefore, the aim of this study was to examine the role of microdiversity in influencing the distribution of rhizosphere-associated microbial species across environmental gradients from root surface to bulk soil at the OTU and ASV levels. Here, the microbial community structures of bulk, loosely bound, and tightly bound soil samples from maize rhizosphere were examined at OTU and ASV levels. The results showed that OTU and ASV methods exhibited similar microbial community structures in rhizosphere. Additionally, different ecotypes with varying distributions and habitat preferences were observed within the same bacterial OTU at the ASV level, indicating a rich bacterial microdiversity. In contrast, the fungal community exhibited low microdiversity, with no significant relationship between fungal microdiversity and persistence and variability. Moreover, the ecotypes observed within the bacterial OTUs were found to be positively or negatively associated with environmental factors, such as soil organic carbon (SOC), NO3 --N, NH4 +-N contents, and pH. Overall, the results showed that the rich microdiversity could sustain the distribution of rhizosphere-associated bacterial species across environmental gradients from root surface to bulk soil. Further genetic analyses of rhizosphere-associated bacterial species could have considerable implications for potential mediation of microdiversity for sustainable crop production.

Microbiome depiction through user-adapted bioinformatic pipelines and parameters

Introduction. The role of the microbiome in health and disease continues to be increasingly recognized. However, there is significant variability in the bioinformatic protocols for analysing genomic data. This, in part, has impeded the potential incorporation of microbiomics into the clinical setting and has challenged interstudy reproducibility. In microbial compositional analysis, there is a growing recognition for the need to move away from a one-size-fits-all approach to data processing.Gap Statement. Few evidence-based recommendations exist for setting parameters of programs that infer microbiota community profiles despite these parameters significantly impacting the accuracy of taxonomic inference.Aim. To compare three commonly used programs (DADA2, QIIME2, and mothur) and optimize them into four user-adapted pipelines for processing paired-end amplicon reads. We aim to increase the accuracy of compositional inference and help standardize microbiomic protocol.Methods. Two key parameters were isolated across four pipelines: filtering sequence reads based on a whole-number error threshold (maxEE) and truncating read ends based on a quality score threshold (QTrim). Closeness of sample inference was then evaluated using a mock community of known composition.Results. We observed that raw genomic data lost were proportionate to how stringently parameters were set. Exactly how much data were lost varied by pipeline. Accuracy of sample inference correlated with increased sequence read retention. Falsely detected taxa and unaccounted for microbial constituents were unique to pipeline and parameter. Implementation of optimized parameter values led to better approximation of the known mock community.Conclusions. Microbial compositions generated based on the 16S rRNA marker gene should be interpreted with caution. To improve microbial community profiling, bioinformatic protocols must be user-adapted. Analysis should be performed with consideration for the select target amplicon, pipelines and parameters used, and taxa of interest.

Shifts in the swine nasal microbiota following Bordetella bronchiseptica challenge in a longitudinal study

Bordetella bronchiseptica is a widespread, highly infectious bacterial pathogen that causes respiratory disease in swine and increases the severity of respiratory infections caused by other viral or bacterial pathogens. However, the impact of B. bronchiseptica infection on the swine respiratory microbiota has not been thoroughly investigated. Here, we aim to assess the influence of B. bronchiseptica infection on the community structure and abundance of members of the swine nasal microbiota. To do so, the nasal microbiota of a non-infected control group and a group infected with B. bronchiseptica (BB group) were characterized prior to B. bronchiseptica strain KM22 challenge (day 0) and on selected days in the weeks following B. bronchiseptica challenge (days 1, 3, 7, 10, 14, 21, 36, and 42). Bordetella bronchiseptica was cultured from nasal samples of the BB group to assess nasal colonization. The results showed that B. bronchiseptica colonization did not persistently affect the nasal bacterial diversity of either of the treatment groups (alpha diversity). However, the bacterial community structures (beta diversity) of the two treatment groups significantly diverged on day 7 when peak colonization levels of B. bronchiseptica were detected. This divergence continued through the last sampling time point. In addition, Pasteurella, Pasteurellaceae (unclassified), Mycoplasma, Actinobacillus, Streptococcus, Escherichia-Shigella, and Prevotellaceae (unclassified) showed increased abundances in the BB group relative to the control group at various time points. This study revealed that B. bronchiseptica colonization can disturb the upper respiratory tract microbiota, and further research is warranted to assess how these disturbances can impact susceptibility to secondary infections by other respiratory pathogens.

The gut microbiome in children with mood, anxiety, and neurodevelopmental disorders: An umbrella review

Research on the gut microbiome and mental health among children and adolescents is growing. This umbrella review provides a high-level overview of current evidence syntheses to amalgamate current research and inform future directions. Searches were conducted across seven databases for peer-reviewed pediatric (<18 years) review literature. Studies reporting gut microbiome composition and/or biotic supplementation on depression, bipolar disorder, anxiety, attention deficit hyperactivity disorder, autism spectrum disorder (ASD), or obsessive-compulsive disorder (OCD) were included. Deduplication and screening took place in Covidence. A sensitivity analysis was conducted to assess the degree of primary study overlap. Among the 39 included review studies, 23 (59%) were observational and 16 (41%) were interventional. Most reviews (92%) focused on ASD. Over half (56%) of the observational and interventional reviews scored low or critically low for methodological quality. A higher abundance of Clostridium clusters and a lower abundance of Bifidobacterium were consistently observed in ASD studies. Biotic supplementation was associated with ASD symptom improvement. Gut microbiome-mental health evidence syntheses in child and youth depression, anxiety, bipolar disorder, and OCD are lacking. Preliminary evidence suggests an association between specific microbiota and ASD symptoms, with some evidence supporting a role for probiotic supplementation ASD therapy.

Effect of bovine respiratory disease on the respiratory microbiome: a meta-analysis

Background

Bovine respiratory disease (BRD) is the most devastating disease affecting beef and dairy cattle producers in North America. An emerging area of interest is the respiratory microbiome's relationship with BRD. However, results regarding the effect of BRD on respiratory microbiome diversity are conflicting.

Results

To examine the effect of BRD on the alpha diversity of the respiratory microbiome, a meta-analysis analyzing the relationship between the standardized mean difference (SMD) of three alpha diversity metrics (Shannon's Diversity Index (Shannon), Chao1, and Observed features (OTUs, ASVs, species, and reads) and BRD was conducted. Our multi-level model found no difference in Chao1 and Observed features SMDs between calves with BRD and controls. The Shannon SMD was significantly greater in controls compared to that in calves with BRD. Furthermore, we re-analyzed 16S amplicon sequencing data from four previously published datasets to investigate BRD's effect on individual taxa abundances. Additionally, based on Bray Curtis and Jaccard distances, health status, sampling location, and dataset were all significant sources of variation. Using a consensus approach based on RandomForest, DESeq2, and ANCOM-BC2, we identified three differentially abundant amplicon sequence variants (ASVs) within the nasal cavity, ASV5_Mycoplasma, ASV19_Corynebacterium, and ASV37_Ruminococcaceae. However, no ASVs were differentially abundant in the other sampling locations. Moreover, based on SECOM analysis, ASV37_Ruminococcaceae had a negative relationship with ASV1_Mycoplasma_hyorhinis, ASV5_Mycoplasma, and ASV4_Mannheimia. ASV19_Corynebacterium had negative relationships with ASV1_Mycoplasma_hyorhinis, ASV4_Mannheimia, ASV54_Mycoplasma, ASV7_Mycoplasma, and ASV8_Pasteurella.

Conclusions

Our results confirm a relationship between bovine respiratory disease and respiratory microbiome diversity and composition, which provide additional insight into microbial community dynamics during BRD development. Furthermore, as sampling location and sample processing (dataset) can also affect results, consideration should be taken when comparing results across studies.

Systematic review of cnidarian microbiomes reveals insights into the structure, specificity, and fidelity of marine associations

Microorganisms play essential roles in the health and resilience of cnidarians. Understanding the factors influencing cnidarian microbiomes requires cross study comparisons, yet the plethora of protocols used hampers dataset integration. We unify 16S rRNA gene sequences from cnidarian microbiome studies under a single analysis pipeline. We reprocess 12,010 cnidarian microbiome samples from 186 studies, alongside 3,388 poriferan, 370 seawater samples, and 245 cultured Symbiodiniaceae, unifying ~6.5 billion sequence reads. Samples are partitioned by hypervariable region and sequencing platform to reduce sequencing variability. This systematic review uncovers an incredible diversity of 86 archaeal and bacterial phyla associated with Cnidaria, and highlights key bacteria hosted across host sub-phylum, depth, and microhabitat. Shallow (< 30 m) water Alcyonacea and Actinaria are characterized by highly shared and relatively abundant microbial communities, unlike Scleractinia and most deeper cnidarians. Utilizing the V4 region, we find that cnidarian microbial composition, richness, diversity, and structure are primarily influenced by host phylogeny, sampling depth, and ocean body, followed by microhabitat and sampling date. We identify host and geographical generalist and specific Endozoicomonas clades within Cnidaria and Porifera. This systematic review forms a framework for understanding factors governing cnidarian microbiomes and creates a baseline for assessing stress associated dysbiosis.

Impact of Intermittent Fasting on the Gut Microbiota: A Systematic Review

Obesity often results in severe negative health consequences and represents a growing issue for global health. Reducing food intake is a crucial factor for weight loss. Intermittent fasting is a relatively new intervention that contributes to weight reduction. Considering the intimate relationship between obesity and inflammatory pathologies with gut microbiota alterations, a systematic review of the literature was herein conducted to elucidate the relationship between time-restricted food intake and gut microbiota diversity in humans. Searches are carried out in three databases (PubMed, MedLine/OVID, and Academic Search Complete) between April 2019 and April 2022. Nine studies (all with longitudinal design) were identified as eligible by presenting data about the impact of intermittent fasting schemes on gut microbiota. At the phylum level, Firmicutes and Bacteroidetes increase throughout follow-ups, while 16 bacteria genera change their abundance in response to intermittent fasting. Finally, some genera associated with clinical predictors such as weight change, abdominal circumference, and metabolic variables were reported. Changes induced by fasting schemes positively impact the diversity and abundance of gut microbiota and the biomarkers described here. However, the changes previously reported have been studied in short periods and some return to their basal state after fasting intervention.

Presence of an ultra-small microbiome in fermented cabbages

Background

Ultramicrobacteria (UMB), also known as ultra-small bacteria, are tiny bacteria with a size less than 0.1 µm³. They have a high surface-to-volume ratio and are found in various ecosystems, including the human body. UMB can be classified into two types: one formed through cell contraction and the other that maintains a small size. The ultra-small microbiome (USM), which may contain UMB, includes all bacteria less than 0.2 µm in size and is difficult to detect with current methods. However, it poses a potential threat to food hygiene, as it can pass through sterilization filters and exist in a viable but non-culturable (VBNC) state. The data on the USM of foods is limited. Some bacteria, including pathogenic species, are capable of forming UMB under harsh conditions, making it difficult to detect them through conventional culture techniques.

Methods

The study described above focused on exploring the diversity of USM in fermented cabbage samples from three different countries (South Korea, China, and Germany). The samples of fermented cabbage (kimchi, suancai, and sauerkraut) were purchased and stored in chilled conditions at approximately 4 °C until filtration. The filtration process involved two steps of tangential flow filtration (TFF) using TFF cartridges with different pore sizes (0.2 µm and 100 kDa) to separate normal size bacteria (NM) and USM. The USM and NM isolated via TFF were stored in a refrigerator at 4 °C until DNA extraction. The extracted DNA was then amplified using PCR and the full-length 16S rRNA gene was sequenced using single-molecule-real-time (SMRT) sequencing. The transmission electron microscope (TEM) was used to confirm the presence of microorganisms in the USM of fermented cabbage samples.

Results

To the best of our knowledge, this is the first study to identify the differences between USM and NM in fermented cabbages. Although the size of the USM (average 2,171,621 bp) was smaller than that of the NM (average 15,727,282 bp), diversity in USM (average H' = 1.32) was not lower than that in NM (average H' = 1.22). In addition, some members in USM probably underwent cell shrinkage due to unfavorable environments, while others maintained their size. Major pathogens were not detected in the USM in fermented cabbages. Nevertheless, several potentially suspicious strains (genera Cellulomonas and Ralstonia) were detected. Our method can be used to screen food materials for the presence of USM undetectable via conventional methods. USM and NM were efficiently separated using tangential flow filtration and analyzed via single-molecule real-time sequencing. The USM of fermented vegetables exhibited differences in size, diversity, and composition compared with the conventional microbiome. This study could provide new insights into the ultra-small ecosystem in fermented foods, including fermented cabbages.

Assembly processes and functional diversity of marine protists and their rare biosphere

BACKGROUND

The mechanisms shaping the rare microbial biosphere and its role in ecosystems remain unclear. We developed an approach to study ecological patterns in the rare biosphere and use it on a vast collection of marine microbiomes, sampled in coastal ecosystems at a regional scale. We study the assembly processes, and the ecological strategies constituting the rare protistan biosphere. Using the phylogeny and morpho-trophic traits of these protists, we also explore their functional potential.

RESULTS

Taxonomic community composition remained stable along rank abundance curves. Conditionally rare taxa, driven by selection processes, and transiently rare taxa, with stochastic distributions, were evidenced along the rank abundance curves of all size-fractions. Specific taxa within the divisions Sagenista, Picozoa, Telonemia, and Choanoflagellida were rare across time and space. The distribution of traits along rank abundance curves outlined a high functional redundancy between rare and abundant protists. Nevertheless, trophic traits illustrated an interplay between the trophic groups of different size-fractions.

CONCLUSIONS

Our results suggest that rare and abundant protists are evolutionary closely related, most notably due to the high microdiversity found in the rare biosphere. We evidenced a succession of assembly processes and strategies of rarity along rank abundance curves that we hypothesize to be common to most microbiomes at the regional scale. Despite high functional redundancy in the rare protistan biosphere, permanently rare protists were evidenced, and they could play critical functions as bacterivores and decomposers from within the rare biosphere. Finally, changes in the composition of the rare protistan biosphere could be influenced by the trophic regime of aquatic ecosystems. Our work contributes to understanding the role of rare protists in microbiomes.

Relative and Quantitative Characterization of the Bovine Bacterial Ocular Surface Microbiome in the Context of Suspected Ocular Squamous Cell Carcinoma

The ocular surface microbiome is altered in certain disease states. The aim of this study was to characterize the bovine bacterial ocular surface microbiome (BBOSM) in the context of ocular squamous cell carcinoma (OSCC). The conjunctiva of normal (n = 28) and OSCC (n = 10) eyes of cows aged 2 to 13 years from two farms in Louisiana and Wyoming were sampled using individual sterile swabs. DNA extraction followed by 16S ribosomal ribonucleic acid (rRNA) gene sequencing and real-time polymerase chain reaction (RT-PCR) were performed to, respectively, assess the relative and absolute BBOSM. Discriminant analysis (DA) was performed using RT-PCR data, and relative abundance analysis was performed using 16S rRNA gene sequencing data. The 11 most abundant phyla in both normal and OSCC-affected cows were identified using 16S rRNA gene sequencing analysis. The relative abundance of Euryarchaeota was found to be significantly lower (p = 0.0372) in OSCC eyes compared to normal eyes. Relative abundance differences within and between geographic locations were also identified. Quadratic DA categorized samples as OSCC or normal with 100% sensitivity and 83.3-100% specificity. Relative abundance analysis identified relative BBOSM phylum alterations in OSCC. Quadratic DA can be used to accurately categorize BBOSM from normal and OSCC ocular surface samples.

Advances in cholera research: from molecular biology to public health initiatives

The aquatic bacterium Vibrio cholerae is the etiological agent of the diarrheal disease cholera, which has plagued the world for centuries. This pathogen has been the subject of studies in a vast array of fields, from molecular biology to animal models for virulence activity to epidemiological disease transmission modeling. V. cholerae genetics and the activity of virulence genes determine the pathogenic potential of different strains, as well as provide a model for genomic evolution in the natural environment. While animal models for V. cholerae infection have been used for decades, recent advances in this area provide a well-rounded picture of nearly all aspects of V. cholerae interaction with both mammalian and non-mammalian hosts, encompassing colonization dynamics, pathogenesis, immunological responses, and transmission to naïve populations. Microbiome studies have become increasingly common as access and affordability of sequencing has improved, and these studies have revealed key factors in V. cholerae communication and competition with members of the gut microbiota. Despite a wealth of knowledge surrounding V. cholerae, the pathogen remains endemic in numerous countries and causes sporadic outbreaks elsewhere. Public health initiatives aim to prevent cholera outbreaks and provide prompt, effective relief in cases where prevention is not feasible. In this review, we describe recent advancements in cholera research in these areas to provide a more complete illustration of V. cholerae evolution as a microbe and significant global health threat, as well as how researchers are working to improve understanding and minimize impact of this pathogen on vulnerable populations.

Profiling Microbiota from Multiple Sites in the Respiratory Tract to Identify a Biomarker for PM2.5 Nitrate Exposure-Induced Pulmonary Damages

The microbiota present in the respiratory tract (RT) responds to environmental stimuli and engages in a continuous interaction with the host immune system to maintain homeostasis. A total of 40 C57BL/6 mice were divided into four groups and exposed to varying concentrations of PM_2.5 nitrate aerosol and clean air. After 10 weeks of exposure, assessments were conducted on the lung and airway microbiome, lung functions, and pulmonary inflammation. Additionally, we analyzed data from both mouse and human respiratory tract (RT) microbiomes to identify possible biomarkers for PM_2.5 exposure-induced pulmonary damages. On average, 1.5 and 13.5% inter-individual microbiome variations in the lung and airway were explained by exposure, respectively. In the airway, among the 60 bacterial OTUs (operational taxonomic units) > 0.05% proportion, 40 OTUs were significantly affected by PM_2.5 exposure (FDR ≤ 10%). Further, the airway microbiome was associated with peak expiratory flow (PEF) (p = 0.003), pulmonary neutrophil counts (p = 0.01), and alveolar 8-OHdG oxidative lesions (p = 0.0078). The Clostridiales order bacteria showed the strongest signals. For example, the o_Clostridiales;f_;g_ OTU was elevated by PM_2.5 nitrate exposure (p = 4.98 × 10^-5) and negatively correlated with PEF (r = -0.585 and p = 2.4 × 10^-4). It was also associated with the higher pulmonary neutrophil count (p = 8.47 × 10^-5) and oxidative lesion (p = 7.17 × 10^-3). In human data, we confirmed the association of airway Clostridiales order bacteria with PM_2.5 exposure and lung function. For the first time, this study characterizes the impact of PM_2.5 exposure on the microbiome of multiple sites in the respiratory tract (RT) and its relevance to airflow obstructive diseases. By analyzing data from both humans and mice, we have identified bacteria belonging to the Clostridiales order as a promising biomarker for PM_2.5 exposure-induced decline in pulmonary function and inflammation.

Resilience of swine nasal microbiota to influenza A virus challenge in a longitudinal study

Influenza A virus (IAV) is an important contributing pathogen of porcine respiratory disease complex (PRDC) infections. Evidence in humans has shown that IAV can disturb the nasal microbiota and increase host susceptibility to bacterial secondary infections. Few, small-scale studies have examined the impact of IAV infection on the swine nasal microbiota. To better understand the effects of IAV infection on the nasal microbiota and its potential indirect impacts on the respiratory health of the host, a larger, longitudinal study was undertaken to characterize the diversity and community composition of the nasal microbiota of pigs challenged with an H3N2 IAV. The microbiome of challenged pigs was compared with non-challenged animals over a 6-week period using 16S rRNA gene sequencing and analysis workflows to characterize the microbiota. Minimal changes to microbial diversity and community structure were seen between the IAV infected and control animals the first 10 days post-IAV infection. However, on days 14 and 21, the microbial populations were significantly different between the two groups. Compared to the control, there were several genera showing significant increases in abundance in the IAV group during acute infection, such as Actinobacillus and Streptococcus. The results here highlight areas for future investigation, including the implications of these changes post-infection on host susceptibility to secondary bacterial respiratory infections.

Estuarine Sediment Microbiomes from a Chronosequence of Restored Urban Salt Marshes

Salt marshes play an important role in the global nutrient cycle. The sediments in these systems harbor diverse and complex bacterial communities possessing metabolic capacities that provide ecosystem services such as nutrient cycling and removal. On the East Coast of the USA, salt marshes have been experiencing degradation due to anthropogenic stressors. Salt marsh islands within Jamaica Bay, New York City (USA), are surrounded by a large highly urbanized watershed and have declined in area. Restoration efforts have been enacted to reduce further loss, but little is known about how microbial communities develop following restoration activities, or how processes such as nitrogen cycling are impacted. Sediment samples were collected at two sampling depths from five salt marsh islands to characterize the bacterial communities found in marsh sediment including a post-restoration chronosequence of 3-12 years. We used 16s rRNA amplicon sequencing to define alpha and beta diversity, taxonomic composition, and predicted metabolic profile of each sediment sample. We found significant differences in alpha diversity between sampling depths, and significant differences in beta diversity, taxonomic composition, and predicted metabolic capacity among the five sampling locations. The youngest restored site and the degraded natural sampling site exhibited the most distinct communities among the five sites. Our findings suggest that while the salt marsh islands are located in close proximity to each other, they harbor distinct bacterial communities that can be correlated with post-restoration age, marsh health, and other environmental factors such as availability of organic carbon. IMPORTANCE: Salt marshes play a critical role in the global nutrient cycle due to sediment bacteria and their metabolic capacities. Many East Coast salt marshes have experienced significant degradation over recent decades, thought largely to be due to anthropogenic stressors such as nitrogen loading, urban development, and sea-level rise. Salt marsh islands in Jamaica Bay (Queens/Brooklyn NY) are exposed to high water column nitrogen due to wastewater effluent. Several receding marsh islands have been subjected to restoration efforts to mitigate this loss. Little is known about the effect marsh restoration has on bacterial communities, their metabolic capacity, or how they develop post-restoration. Here, we describe the bacterial communities found in marsh islands including a post-restoration chronosequence of 3-12 years and one degraded marsh island that remains unrestored. We found distinct communities at marsh sites, despite their geographic proximity. Differences in diversity and community composition were consistent with changes in organic carbon availability that occur during marsh development, and may result in differences in ecosystem function among sites.

Gut microbiome signatures of Yorkshire Terrier enteropathy during disease and remission

The role of the gut microbiome in developing Inflammatory Bowel Disease (IBD) in humans and dogs has received attention in recent years. Evidence suggests that IBD is associated with alterations in gut microbial composition, but further research is needed in veterinary medicine. The impact of IBD treatment on the gut microbiome needs to be better understood, especially in a breed-specific form of IBD in Yorkshire Terriers known as Yorkshire Terrier Enteropathy (YTE). This study aimed to investigate the difference in gut microbiome composition between YTE dogs during disease and remission and healthy Yorkshire Terriers. Our results showed a significant increase in specific taxa such as Clostridium sensu stricto 1, Escherichia-Shigella, and Streptococcus, and a decrease in Bacteroides, Prevotella, Alloprevotella, and Phascolarctobacterium in YTE dogs compared to healthy controls. No significant difference was found between the microbiome of dogs in remission and those with active disease, suggesting that the gut microbiome is affected beyond clinical recovery.

Gut-Microbiota Dysbiosis in Stroke-Prone Spontaneously Hypertensive Rats with Diet-Induced Steatohepatitis

Metabolic-dysfunction-associated fatty-liver disease (MAFLD) is the principal worldwide cause of liver disease. Individuals with nonalcoholic steatohepatitis (NASH) have a higher prevalence of small-intestinal bacterial overgrowth (SIBO). We examined gut-microbiota isolated from 12-week-old stroke-prone spontaneously hypertensive-5 rats (SHRSP5) fed on a normal diet (ND) or a high-fat- and high-cholesterol-containing diet (HFCD) and clarified the differences between their gut-microbiota. We observed that the Firmicute/Bacteroidetes (F/B) ratio in both the small intestines and the feces of the SHRSP5 rats fed HFCD increased compared to that of the SHRSP5 rats fed ND. Notably, the quantities of the 16S rRNA genes in small intestines of the SHRSP5 rats fed HFCD were significantly lower than those of the SHRSP5 rats fed ND. As in SIBO syndrome, the SHRSP5 rats fed HFCD presented with diarrhea and body-weight loss with abnormal types of bacteria in the small intestine, although the number of bacteria in the small intestine did not increase. The microbiota of the feces in the SHRSP5 rats fed HFCD was different from those in the SHRP5 rats fed ND. In conclusion, there is an association between MAFLD and gut-microbiota alteration. Gut-microbiota alteration may be a therapeutic target for MAFLD.

Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding

DNA-metabarcoding is becoming more widely used for routine authentication of meat-based food and feed products. Several methods validating species identification methods through amplicon sequencing have already been published. These use a variety of barcodes and analysis workflows, however, no methodical comparison of available algorithms and parameter optimization are published hitherto for meat-based products' authenticity. Additionally, many published methods use very small subsets of the available reference sequences, thereby limiting the potential of the analysis and leading to over-optimistic performance estimates. We here predict and compare the ability of published barcodes to distinguish taxa in the BLAST NT database. We then use a dataset of 79 reference samples, spanning 32 taxa, to benchmark and optimize a metabarcoding analysis workflow for 16S rDNA Illumina sequencing. Furthermore, we provide recommendations as to the parameter choices, sequencing depth, and thresholds that should be used to analyze meat metabarcoding sequencing experiments. The analysis workflow is publicly available, and includes ready-to-use tools for validation and benchmarking.

A next-generation sequencing approach for the detection of mixed species in canned tuna

Tuna cans are relevant seafood products for which mixtures of different tuna species are not allowed according to European regulations. In order to support the prevention of food fraud and mislabelling, a next-generation sequencing methodology based on mitochondrial cytochrome b and control region markers has been tested. Analyses of defined mixtures of DNA, fresh tissue and canned tissue revealed a qualitative and, to some extent, semiquantitative identification of tuna species. While the choice of the bioinformatic pipeline had no influence in the results (p = 0.71), quantitative differences occurred depending on the treatment of the sample, marker, species, and mixture (p < 0.01). The results revealed that matrix-specific calibrators or normalization models should also be used in NGS. The method represents an important step towards a semiquantitative method for routine control of this analytically challenging food matrix. Tests of commercial samples uncovered mixed species in some cans, being not in compliance with EU regulations.

Summer thaw duration is a strong predictor of the soil microbiome and its response to permafrost thaw in arctic tundra

Climate warming has increased permafrost thaw in arctic tundra and extended the duration of annual thaw (number of thaw days in summer) along soil profiles. Predicting the microbial response to permafrost thaw depends largely on knowing how increased thaw duration affects the composition of the soil microbiome. Here, we determined soil microbiome composition from the annually thawed surface active layer down through permafrost from two tundra types at each of three sites on the North Slope of Alaska, USA. Variations in soil microbial taxa were found between sites up to ~90 km apart, between tundra types, and between soil depths. Microbiome differences at a site were greatest across transitions from thawed to permafrost depths. Results from correlation analysis based on multi-decadal thaw surveys show that differences in thaw duration by depth were significantly, positively correlated with the abundance of dominant taxa in the active layer and negatively correlated with dominant taxa in the permafrost. Microbiome composition within the transition zone was statistically similar to that in the permafrost, indicating that recent decades of intermittent thaw have not yet induced a shift from permafrost to active-layer microbes. We suggest that thaw duration rather than thaw frequency has a greater impact on the composition of microbial taxa within arctic soils.

Plasma Levels of Omega-3 and Omega-6 Derived Oxylipins Are Associated with Fecal Microbiota Composition in Young Adults

Pre-clinical studies suggest that circulating oxylipins, i.e., the oxidation products of polyunsaturated fatty acids (PUFAs), modulate gut microbiota composition in mice, but there is no information available in humans. Therefore, this study aimed to investigate the relationship between omega-3 and omega-6 derived oxylipins plasma levels and fecal microbiota composition in a cohort of young adults. 80 young adults (74% women; 21.9 ± 2.2 years old) were included in this cross-sectional study. Plasma levels of oxylipins were measured using liquid chromatography-tandem mass spectrometry. Fecal microbiota composition was analyzed by V3-V4 16S rRNA gene sequencing. We observed that plasma levels of omega-3 derived oxylipins were positively associated with the relative abundance of Clostridium cluster IV genus (Firmicutes phylum; rho ≥ 0.415, p ≤ 0.009) and negatively associated with the relative abundance of Sutterella genus (Proteobacteria phylum; rho ≥ -0.270, p ≤ 0.041), respectively. Moreover, plasma levels of omega-6 derived oxylipins were negatively associated with the relative abundance of Acidaminococcus and Phascolarctobacterium genera (Firmicutes phylum; all rho ≥ -0.263, p ≤ 0.024), as well as Sutterella, Succinivibrio, and Gemmiger genera (Proteobacteria phylum; all rho ≥ -0.263, p ≤ 0.024). Lastly, the ratio between omega-6 and omega-3 oxylipins plasma levels was negatively associated with the relative abundance of Clostridium cluster IV genus (Firmicutes phylum; rho = -0.334, p = 0.004) and Butyricimonas genus (Bacteroidetes phylum; rho = -0.292, p = 0.014). In conclusion, our results show that the plasma levels of omega-3 and omega-6 derived oxylipins are associated with the relative abundance of specific fecal bacteria genera.