Best practices for analysing microbiomes

SAMPL-seq reveals micron-scale spatial hubs in the human gut microbiome

The local arrangement of microbes can profoundly impact community assembly, function, and stability. To date, little is known about the spatial organization of the human gut microbiome. Here, we describe a high-throughput and streamlined method, dubbed SAMPL-seq, that samples microbial composition of micron-scale sub-communities with split-and-pool barcoding to capture spatial colocalization in a complex consortium. SAMPL-seq analysis of the gut microbiome of healthy humans identified bacterial taxa pairs that consistently co-occurred both over time and across multiple individuals. These colocalized microbes organize into spatially distinct groups or "spatial hubs" dominated by Bacteroideceae, Ruminococceae, and Lachnospiraceae families. From a dietary perturbation using inulin, we observed reversible spatial rearrangement of the gut microbiome, where specific taxa form new local partnerships. Spatial metagenomics using SAMPL-seq can unlock new insights to improve the study of microbial communities.

A metagenomic approach to demystify the anaerobic digestion black box and achieve higher biogas yield: a review

The increasing reliance on fossil fuels and the growing accumulation of organic waste necessitates the exploration of sustainable energy alternatives. Anaerobic digestion (AD) presents one such solution by utilizing secondary biomass to produce biogas while reducing greenhouse gas emissions. Given the crucial role of microbial activity in anaerobic digestion, a deeper understanding of the microbial community is essential for optimizing biogas production. While metagenomics has emerged as a valuable tool for unravelling microbial composition and providing insights into the functional potential in biodigestion, it falls short of interpreting the functional and metabolic interactions, limiting a comprehensive understanding of individual roles in the community. This emphasizes the significance of expanding the scope of metagenomics through innovative tools that highlight the often-overlooked, yet crucial, role of microbiota in biomass digestion. These tools can more accurately elucidate microbial ecological fitness, shared metabolic pathways, and interspecies interactions. By addressing current limitations and integrating metagenomics with other omics approaches, more accurate predictive techniques can be developed, facilitating informed decision-making to optimize AD processes and enhance biogas yields, thereby contributing to a more sustainable future.

Microbiome time series data reveal predictable patterns of change

The human gut microbiome is crucial in health and disease. Longitudinal studies are becoming increasingly important compared to traditional cross-sectional approaches, as precision medicine and individualized interventions are coming to the forefront. Investigating the temporal dynamics of the microbiome is essential for comprehending its function and impact on health. This knowledge has implications for targeted therapeutic strategies, such as personalized diets or probiotic therapy. In this study, we focused on developing and implementing methods specifically designed for analyzing gut microbiome time series. Our statistical framework provides researchers with tools to examine the temporal behavior of the gut microbiome. Key features of our framework include statistical tests for time series properties, predictive modeling, classification of bacterial species based on stability and noise, and clustering analyses to identify groups of bacteria with similar temporal patterns. We analyzed dense amplicon sequencing time series from four generally healthy subjects. Using our developed statistical framework, we analyzed both the overall community dynamics and the behavior of individual bacterial species. We showed six longitudinal regimes within the gut microbiome and discussed their features. Additionally, we explored whether specific bacterial clusters undergo similar fluctuations, suggesting potential functional relationships and interactions within the microbiome. Our development of specialized methods for analyzing human gut microbiome time series significantly enhances the understanding of its dynamic nature and implications for human health. The guidelines and tools provided by our framework support scientists in studying the complex dynamics of the gut microbiome, fostering further research and advancements in microbiome analysis. The gut microbiome is integral to human health, influencing various diseases. Longitudinal studies offer deeper insights into its temporal dynamics compared to cross-sectional approaches. In this study, we developed a statistical framework for analyzing the time series of the human gut microbiome. This framework provides robust tools for examining microbial community dynamics over time. It includes statistical tests for time series properties, predictive modeling, classification of bacterial species based on stability and noise, and clustering analyses. Our approach significantly enhances the methodologies available to researchers, promoting further exploration and innovation in microbiome analysis.

IMPORTANCE

This project developed innovative methods to analyze gut microbiome time series data, offering fresh insights into its dynamic nature. Unlike many studies that focus on static snapshots, we found that the healthy gut microbiome is predictably stable over time, with only a small subset of bacteria showing significant changes. By identifying groups of bacteria with diverse temporal behaviors and clusters that change together, we pave the way for more effective probiotic therapies and dietary interventions, addressing the overlooked dynamic aspects of gut microbiome changes.

Late-life dietary folate restriction reduces biosynthesis without compromising healthspan in mice

Folate is a vitamin required for cell growth and is present in fortified foods in the form of folic acid to prevent congenital abnormalities. The impact of low-folate status on life-long health is poorly understood. We found that limiting folate levels with the folate antagonist methotrexate increased the lifespan of yeast and worms. We then restricted folate intake in aged mice and measured various health metrics, metabolites, and gene expression signatures. Limiting folate intake decreased anabolic biosynthetic processes in mice and enhanced metabolic plasticity. Despite reduced serum folate levels in mice with limited folic acid intake, these animals maintained their weight and adiposity late in life, and we did not observe adverse health outcomes. These results argue that the effectiveness of folate dietary interventions may vary depending on an individual's age and sex. A higher folate intake is advantageous during the early stages of life to support cell divisions needed for proper development. However, a lower folate intake later in life may result in healthier aging.

Microbiota-gut-brain axis in perioperative neurocognitive and depressive disorders: Pathogenesis to treatment

An increasing number of people undergo anesthesia and surgery. Perioperative neurocognitive and depressive disorders are common central nervous system complications with similar pathogeneses. These conditions pose a deleterious threat to human health and a significant societal burden. In recent years, numerous studies have focused on the role of the gut microbiota and its metabolites in the central nervous system via the gut-brain axis. Its involvement in perioperative neurocognitive and depressive disorders has attracted considerable attention. This review aimed to elucidate the role of the gut microbiota and its metabolites in the pathogenesis of perioperative neurocognitive and depressive disorders, as well as the value of targeted interventions and treatments.

Oral specimens as a tool for accurate metagenomic analysis: A pilot study

OBJECTIVES

Acute oral mucosal damage, as well as other inflammatory processes seem to be related to dysbiosis of the oral microbiome. The need to study changes in the oral microbiome led us to hypothesize what type of sample would provide the most representative picture of the entire human oral microbiome.

MATERIALS AND METHODS

An observational, and cross-sectional study was carried out. Six healthy adult participants provided 3 different sample types each, that included saliva, oral rinse and mucosal biopsy tissue. We performed 16S rRNA sequencing of the V3-V4 region of the 18 samples using Illumina MiSeq technology.

RESULTS

Participants were 27 ± 6,3 years old. Bacterial alpha diversity was higher in oral rinse samples compared to whole unstimulated saliva and oral mucosa tissue (p = 0,005). However, saliva specimens showed a 56 % relative abundance of identified species followed by a 30 % in oral rinse and only 1 % in tissue samples.

CONCLUSIONS

This study found differences on oral microbiome composition for each type of sample. Oral rinse should be chosen when higher alpha diversity is needed, whereas whole unstimulated saliva should be more appropriate for larger amount of bacterial DNA.

CLINICAL RELEVANCE

The results obtained demonstrate the importance of a correct choice of the optimal type of oral sample for microbiome studies due to the differences found in its composition.

Host genetics and microbiota data analysis in colorectal cancer research

Colorectal cancer (CRC) is a heterogeneous disease with a complex aetiology influenced by a myriad of genetic and environmental factors. Despite advances in CRC research, it is a major burden of disease, with the second highest incidence and third leading cause of cancer deaths worldwide. To individualise diagnosis, prognosis, and treatment of CRC, developing new strategies combining precision medicine and bioinformatic procedures is promising. Precision medicine is based on omics technologies and aims to individualise the management of CRC based on patient host genetic characteristics and microbiota. Bioinformatics is central to the application of personalised medicine because it enables the analysis of large datasets generated by these technologies. At the level of host genetics, bioinformatics allows the identification of mutations, genes, molecular pathways, biomarkers and drugs relevant to colorectal carcinogenesis. At the microbiota level, bioinformatics is fundamental to analysing microbial communities' composition and functionality and developing biomarkers and personalised microbiota-based therapies. This paper explores the host and microbiota genetic data analysis in CRC research.

TimeNorm: a novel normalization method for time course microbiome data

Metagenomic time-course studies provide valuable insights into the dynamics of microbial systems and have become increasingly popular alongside the reduction in costs of next-generation sequencing technologies. Normalization is a common but critical preprocessing step before proceeding with downstream analysis. To the best of our knowledge, currently there is no reported method to appropriately normalize microbial time-series data. We propose TimeNorm, a novel normalization method that considers the compositional property and time dependency in time-course microbiome data. It is the first method designed for normalizing time-series data within the same time point (intra-time normalization) and across time points (bridge normalization), separately. Intra-time normalization normalizes microbial samples under the same condition based on common dominant features. Bridge normalization detects and utilizes a group of most stable features across two adjacent time points for normalization. Through comprehensive simulation studies and application to a real study, we demonstrate that TimeNorm outperforms existing normalization methods and boosts the power of downstream differential abundance analysis.

Implementing high-throughput insect barcoding in microbiome studies: impact of non-destructive DNA extraction on microbiome reconstruction

Background

Symbiotic relationships with diverse microorganisms are crucial for many aspects of insect biology. However, while our understanding of insect taxonomic diversity and the distribution of insect species in natural communities is limited, we know much less about their microbiota. In the era of rapid biodiversity declines, as researchers increasingly turn towards DNA-based monitoring, developing and broadly implementing approaches for high-throughput and cost-effective characterization of both insect and insect-associated microbial diversity is essential. We need to verify whether approaches such as high-throughput barcoding, a powerful tool for identifying wild insects, would permit subsequent microbiota reconstruction in these specimens.

Methods

High-throughput barcoding ("megabarcoding") methods often rely on non-destructive approaches for obtaining template DNA for PCR amplification by leaching DNA out of insect specimens using alkaline buffers such as HotSHOT. This study investigated the impact of HotSHOT on microbial abundance estimates and the reconstructed bacterial community profiles. We addressed this question by comparing quantitative 16S rRNA amplicon sequencing data for HotSHOT-treated or untreated specimens of 16 insect species representing six orders and selected based on the expectation of limited variation among individuals.

Results

We find that in 13 species, the treatment significantly reduced microbial abundance estimates, corresponding to an estimated 15-fold decrease in amplifiable 16S rRNA template on average. On the other hand, HotSHOT pre-treatment had a limited effect on microbial community composition. The reconstructed presence of abundant bacteria with known significant effects was not affected. On the other hand, we observed changes in the presence of low-abundance microbes, those close to the reliable detection threshold. Alpha and beta diversity analyses showed compositional differences in only a few species.

Conclusion

Our results indicate that HotSHOT pre-treated specimens remain suitable for microbial community composition reconstruction, even if abundance may be hard to estimate. These results indicate that we can cost-effectively combine barcoding with the study of microbiota across wild insect communities. Thus, the voucher specimens obtained using megabarcoding studies targeted at characterizing insect communities can be used for microbiome characterizations. This can substantially aid in speeding up the accumulation of knowledge on the microbiomes of abundant and hyperdiverse insect species.

Effects of Fertilization and Planting Modes on Soil Organic Carbon and Microbial Community Formation of Tree Seedlings

Biochar and organic fertilizer can significantly increase soil organic carbon (SOC) and promote agricultural production, but it is still unclear how they affect forest SOC after. Here, low-quality plantation soil was subjected to four distinct fertilization treatments: (CK, without fertilization; BC, tea seed shell biochar alone; OF, tea meal organic fertilizer alone; BCF, tea seed shell biochar plus tea meal organic fertilizer). Cunninghamia lanceolata (Lamb.) Hook and Cyclobalanopsis glauca (Thunb.) Oersted seedlings were then planted in pots at the ratios of 2:0, 1:1, and 0:2 (SS, SQ, QQ) and grown for one year. The results showed that the BCF treatment had the best effect on promoting seedling growth and increasing SOC content. BCF changed soil pH and available nutrient content, resulting in the downregulation of certain oligotrophic groups (Acidobacteria and Basidiomycetes) and the upregulation of eutrophic groups (Ascomycota and Proteobacteria). Key bacterial groups, which were identified by Line Discriminant Analysis Effect Size analysis, were closely associated with microbial biomass carbon (MBC) and SOC. Pearson correlation analysis showed that bacterial community composition exhibited a positive correlation with SOC, MBC, available phosphorus, seedling biomass, and plant height, whereas fungal community composition was predominantly positively correlated with seedling underground biomass. It suggested that environmental differences arising from fertilization and planting patterns selectively promote microbial communities that contribute to organic carbon formation. In summary, the combination of biochar and organic fertilizers would enhance the improvement and adaptation of soil microbial communities, playing a crucial role in increasing forest soil organic carbon and promoting tree growth.

Malignant Transformation of Normal Oral Tissue to Dysplasia and Early Oral Squamous Cell Carcinoma: An In Silico Transcriptomics Approach

Background: Oral squamous cell carcinoma (OSCC) is a prevalent and aggressive form of head and neck cancer, often diagnosed at advanced stages. Elucidating the molecular mechanisms involved in the malignant transformation from normal oral tissue to oral preinvasive lesions (OPL) and primary OSCC could facilitate early diagnosis and improve therapeutic strategies. Methods: Differentially expressed genes (DEGs) were identified from the GSE30784 dataset by comparing normal oral tissue, oral dysplasia, and primary OSCC samples. Cross-validation was performed using an independent RNA-seq dataset, GSE186775. Protein-protein interaction (PPI) network analysis, gene ontology annotation, and pathway enrichment analysis were conducted on the common DEGs. Hub genes were identified, and their prognostic significance was evaluated using survival analysis. Transcription factor (TF) enrichment analysis, cross-validation, and immunohistochemistry analyses were also performed. Results: A total of 226 proteins and 677 interactions were identified in the PPI network, with 34 hub genes, including FN1, SERPINE1, PLAUR, THBS1, and ITGA6. Pathways such as "Formation of the cornified envelope," "Keratinization," and "Developmental biology" were enriched. Overexpression of SERPINE1, PLAUR, THBS1, and ITGA6 correlated with poor prognosis, while upregulation of CALML5 and SPINK5 was associated with favorable outcomes. NFIB emerged as the most significant TF-regulating hub genes. Immunohistochemistry validated ITGA6 overexpression in primary OSCC. Cross-validation using the RNA-seq dataset supported the involvement of critical genes in the malignant transformation process. Conclusion: This study identified vital genes, pathways, and prognostic markers involved in the malignant transformation from normal oral tissue to OPL and primary OSCC, providing insights for early diagnosis and targeted therapy development. Cross-validation with an independent RNA-seq dataset and immunohistochemistry reinforced the findings, supporting the robustness of the identified molecular signatures.

Perturbations to common gardens of anaerobic co-digesters reveal relationships between functional resilience and microbial community composition

We report the relationship between enrichment of adapted populations and enhancement of community functional resilience in methanogenic bioreactors. Although previous studies have shown the positive effects of acclimation, this work directly investigated the relationships between microbiome dynamics and performance of anaerobic co-digesting reactors in response to different levels of an environmental perturbation (loading of grease interceptor waste [GIW]). Using the methanogenic microbiome from a full-scale digester, we developed eight sets of microbial communities in triplicate using different feed sources. These substrate-specific microbiomes were then exposed to three independent disturbance events of low-, mid- and high-GIW loading rates. This approach allowed us to directly attribute differences in community responses to differences in community composition. Despite identical inocula, environment (digester operation, substrate loading rate, and feeding patterns) and general whole-community function (methane production and effluent quality) during the cultivation period, different substrates led to different microbial community assemblies. Lipid pre-acclimation led to enrichment of a pool of specialized populations, along with thriving of sub-dominant communities. The enrichment of these populations improved functional resilience and process performance when exposed to a low level of lipid-rich perturbation compared with less-acclimated communities. At higher levels of perturbation, the communities were not able to recover methanogenesis, indicating a loading limit to the resilience response. This study extends our current understanding of environmental perturbations, feed-specific adaptation, and functional resilience in methanogenic bioreactors.IMPORTANCEThis study demonstrates, for the first time for GIW co-digestion, how applying similar perturbations to different microbial communities was used to directly identify the causal relationships between microbial community, function, and environment in triplicate anaerobic microbiomes. We evaluated the impact of feed-specific adaptation on methanogenic microbiomes and demonstrated how microbiomes can be influenced to improve their functional (methanogenic) resilience to GIW inhibition. These findings demonstrate how an ecological framework can help improve a biological engineering application, and more specifically, increase the potential of anaerobic co-digestion for converting wastes to energy.

Soil microbiome characterization and its future directions with biosensing

Soil microbiome characterization is typically achieved with next-generation sequencing (NGS) techniques. Metabarcoding is very common, and meta-omics is growing in popularity. These techniques have been instrumental in microbiology, but they have limitations. They require extensive time, funding, expertise, and computing power to be effective. Moreover, these techniques are restricted to controlled laboratory conditions; they are not applicable in field settings, nor can they rapidly generate data. This hinders using NGS as an environmental monitoring tool or an in-situ checking device. Biosensing technology can be applied to soil microbiome characterization to overcome these limitations and to complement NGS techniques. Biosensing has been used in biomedical applications for decades, and many successful commercial products are on the market. Given its previous success, biosensing has much to offer soil microbiome characterization. There is a great variety of biosensors and biosensing techniques, and a few in particular are better suited for soil field studies. Aptamers are more stable than enzymes or antibodies and are more ready for field-use biosensors. Given that any microbiome is complex, a multiplex sensor will be needed, and with large, complicated datasets, machine learning might benefit these analyses. If the signals from the biosensors are optical, a smartphone can be used as a portable optical reader and potential data-analyzing device. Biosensing is a rich field that couples engineering and biology, and applying its toolset to help advance soil microbiome characterization would be a boon to microbiology more broadly.

Identification and validation of microbial biomarkers from cross-cohort datasets using xMarkerFinder

Microbial signatures have emerged as promising biomarkers for disease diagnostics and prognostics, yet their variability across different studies calls for a standardized approach to biomarker research. Therefore, we introduce xMarkerFinder, a four-stage computational framework for microbial biomarker identification with comprehensive validations from cross-cohort datasets, including differential signature identification, model construction, model validation and biomarker interpretation. xMarkerFinder enables the identification and validation of reproducible biomarkers for cross-cohort studies, along with the establishment of classification models and potential microbiome-induced mechanisms. Originally developed for gut microbiome research, xMarkerFinder's adaptable design makes it applicable to various microbial habitats and data types. Distinct from existing biomarker research tools that typically concentrate on a singular aspect, xMarkerFinder uniquely incorporates a sophisticated feature selection process, specifically designed to address the heterogeneity between different cohorts, extensive internal and external validations, and detailed specificity assessments. Execution time varies depending on the sample size, selected algorithm and computational resource. Accessible via GitHub ( https://github.com/tjcadd2020/xMarkerFinder ), xMarkerFinder supports users with diverse expertise levels through different execution options, including step-to-step scripts with detailed tutorials and frequently asked questions, a single-command execution script, a ready-to-use Docker image and a user-friendly web server ( https://www.biosino.org/xmarkerfinder ).

Gut microbiome diversity and composition in individuals with and without extended-spectrum β-lactamase-producing Enterobacterales carriage: a matched case-control study in infectious diseases department

OBJECTIVE

Little is known about the effect of gut microbial and extended-spectrum β-lactamase-producing Enterobacterales (ESBL-E) carriage, particularly in the general population. The aim of this study was to identify microbiota signatures uniquely correlated with ESBL-E carriage.

METHODS

We conducted a case-control study among individuals seeking care at the Sexual Health Clinic or Department of Infectious and Tropical Diseases, Saint-Antoine Hospital, Paris, France. Using coarsened exact matching, 176 participants with ESBL-carriage (i.e. cases) were matched 1:1 to those without ESBL-carriage (i.e. controls) based on sexual group, ESBL-E prevalence of countries travelled in <12 months, number of sexual partners in <6 months, geographic origin, and any antibiotic use in <6 months. 16S rRNA gene amplicon sequencing was used to generate differential abundances at the genus level and measures of α- and β-diversity.

RESULTS

Participants were mostly men (83.2%, n = 293/352) and had a median age of 33 years (interquartile range: 27-44). Nine genera were found associated with ESBL-E carriage: Proteus (p < 0.0001), Carnobacterium (p < 0.0001), Enterorhabdus (p 0.0079), Catonella (p 0.017), Dermacoccus (p 0.017), Escherichia/Shigella (p 0.021), Kocuria (p 0.023), Bacillus (p 0.040), and Filifactor (p 0.043); however, differences were no longer significant after Benjamini-Hochberg correction (q > 0.05). There were no differences between those with versus without ESBL-E carriage in measures of α-diversity (Shannon Diversity Index, p 0.49; Simpson Diversity Index, p 0.54; and Chao1 Richness Estimator, p 0.16) or β-diversity (Bray-Curtis dissimilarity index, p 0.42).

DISCUSSION

In this large carefully controlled study, there is lacking evidence that gut microbial composition and diversity is any different between individuals with and without ESBL-E carriage.

Deciphering the microbial map and its implications in the therapeutics of neurodegenerative disorder

Every facet of biological anthropology, including development, ageing, diseases, and even health maintenance, is influenced by gut microbiota's significant genetic and metabolic capabilities. With current advancements in sequencing technology and with new culture-independent approaches, researchers can surpass older correlative studies and develop mechanism-based studies on microbiome-host interactions. The microbiota-gut-brain axis (MGBA) regulates glial functioning, making it a possible target for the improvement of development and advancement of treatments for neurodegenerative diseases (NDDs). The gut-brain axis (GBA) is accountable for the reciprocal communication between the gastrointestinal and central nervous system, which plays an essential role in the regulation of physiological processes like controlling hunger, metabolism, and various gastrointestinal functions. Lately, studies have discovered the function of the gut microbiome for brain health-different microbiota through different pathways such as immunological, neurological and metabolic pathways. Additionally, we review the involvement of the neurotransmitters and the gut hormones related to gut microbiota. We also explore the MGBA in neurodegenerative disorders by focusing on metabolites. Further, targeting the blood-brain barrier (BBB), intestinal barrier, meninges, and peripheral immune system is investigated. Lastly, we discuss the therapeutics approach and evaluate the pre-clinical and clinical trial data regarding using prebiotics, probiotics, paraprobiotics, fecal microbiota transplantation, personalised medicine, and natural food bioactive in NDDs. A comprehensive study of the GBA will felicitate the creation of efficient therapeutic approaches for treating different NDDs.

Cabozantinib and nivolumab with or without live bacterial supplementation in metastatic renal cell carcinoma: a randomized phase 1 trial

Supplementation with CBM588, a bifidogenic live bacterial product, has been associated with improved clinical outcomes in persons with metastatic renal cell carcinoma (mRCC) receiving nivolumab and ipilimumab. However, its effect on those receiving tyrosine kinase inhibitor-based combinations is unknown. In this open-label, randomized, investigator-initiated, phase 1 study, 30 participants with locally advanced or mRCC with histological confirmation of clear cell, papillary or sarcomatoid component were randomized in a 2:1 fashion to receive cabozantinib (an inhibitor of vascular endothelial growth factor receptor, MET and AXL) and nivolumab (anti-programmed cell death protein 1) with or without CBM588 as first-line treatment. Metagenomic sequencing was performed on stool samples to characterize their gut microbiome at baseline and 13 weeks into treatment. The primary endpoint was a change in the relative abundance of Bifidobacterium spp.; secondary endpoints included objective response rate (ORR), progression-free survival (PFS) and toxicity profile. The primary endpoint of the study was not met and the addition of CBM588 to cabozantinib and nivolumab did not result in a difference in the relative abundance of Bifidobacterium spp. or alpha diversity (as measured by the Shannon index). However, ORR was significantly higher in participants treated with CBM588 compared to those in the control arm (14 of 19, 74% versus 2 of 10, 20%; P = 0.01). PFS at 6 months was 84% (16 of 19) and 60% (6 of 10) in the experimental and control arms, respectively. No significant difference in toxicity profile was seen between the study arms. Our results provide a preliminary signal of improved clinical activity with CBM588 in treatment-naive participants with mRCC receiving cabozantinib and nivolumab. Further investigation is needed to confirm these findings and better characterize the underlying mechanism driving this effect.ClinicalTrials.gov identifier: NCT05122546.

Challenges for pathologists in implementing clinical microbiome diagnostic testing

Recent research has established that the microbiome plays potential roles in the pathogenesis of numerous chronic diseases, including carcinomas. This discovery has led to significant interest in clinical microbiome testing among physicians, translational investigators, and the lay public. As novel, inexpensive methodologies to interrogate the microbiota become available, research labs and commercial vendors have offered microbial assays. However, these tests still have not infiltrated the clinical laboratory space. Here, we provide an overview of the challenges of implementing microbiome testing in clinical pathology. We discuss challenges associated with preanalytical and analytic sample handling and collection that can influence results, choosing the appropriate testing methodology for the clinical context, establishing reference ranges, interpreting the data generated by testing and its value in making patient care decisions, regulation, and cost considerations of testing. Additionally, we suggest potential solutions for these problems to expedite the establishment of microbiome testing in the clinical laboratory.

Soil keystone viruses are regulators of ecosystem multifunctionality

Ecosystem multifunctionality reflects the capacity of ecosystems to simultaneously maintain multiple functions which are essential bases for human sustainable development. Whereas viruses are a major component of the soil microbiome that drive ecosystem functions across biomes, the relationships between soil viral diversity and ecosystem multifunctionality remain under-studied. To address this critical knowledge gap, we employed a combination of amplicon and metagenomic sequencing to assess prokaryotic, fungal and viral diversity, and to link viruses to putative hosts. We described the features of viruses and their potential hosts in 154 soil samples from 29 farmlands and 25 forests distributed across China. Although 4,460 and 5,207 viral populations (vOTUs) were found in the farmlands and forests respectively, the diversity of specific vOTUs rather than overall soil viral diversity was positively correlated with ecosystem multifunctionality in both ecosystem types. Furthermore, the diversity of these keystone vOTUs, despite being 10-100 times lower than prokaryotic or fungal diversity, was a better predictor of ecosystem multifunctionality and more strongly associated with the relative abundances of prokaryotic genes related to soil nutrient cycling. Gemmatimonadota and Actinobacteria dominated the host community of soil keystone viruses in the farmlands and forests respectively, but were either absent or showed a significantly lower relative abundance in that of soil non-keystone viruses. These findings provide novel insights into the regulators of ecosystem multifunctionality and have important implications for the management of ecosystem functioning.

Emergent ecological patterns and modelling of gut microbiomes in health and in disease

Recent advancements in next-generation sequencing have revolutionized our understanding of the human microbiome. Despite this progress, challenges persist in comprehending the microbiome's influence on disease, hindered by technical complexities in species classification, abundance estimation, and data compositionality. At the same time, the existence of macroecological laws describing the variation and diversity in microbial communities irrespective of their environment has been recently proposed using 16s data and explained by a simple phenomenological model of population dynamics. We here investigate the relationship between dysbiosis, i.e. in unhealthy individuals there are deviations from the "regular" composition of the gut microbial community, and the existence of macro-ecological emergent law in microbial communities. We first quantitatively reconstruct these patterns at the species level using shotgun data, and addressing the consequences of sampling effects and statistical errors on ecological patterns. We then ask if such patterns can discriminate between healthy and unhealthy cohorts. Concomitantly, we evaluate the efficacy of different statistical generative models, which incorporate sampling and population dynamics, to describe such patterns and distinguish which are expected by chance, versus those that are potentially informative about disease states or other biological drivers. A critical aspect of our analysis is understanding the relationship between model parameters, which have clear ecological interpretations, and the state of the gut microbiome, thereby enabling the generation of synthetic compositional data that distinctively represent healthy and unhealthy individuals. Our approach, grounded in theoretical ecology and statistical physics, allows for a robust comparison of these models with empirical data, enhancing our understanding of the strengths and limitations of simple microbial models of population dynamics.

Spaceflight alters host-gut microbiota interactions

The ISS rodent habitat has provided crucial insights into the impact of spaceflight on mammals, inducing symptoms characteristic of liver disease, insulin resistance, osteopenia, and myopathy. Although these physiological responses can involve the microbiome on Earth, host-microbiota interactions during spaceflight are still being elucidated. We explore murine gut microbiota and host gene expression in the colon and liver after 29 and 56 days of spaceflight using multiomics. Metagenomics revealed significant changes in 44 microbiome species, including relative reductions in bile acid and butyrate metabolising bacteria like Extibacter muris and Dysosmobacter welbionis. Functional prediction indicate over-representation of fatty acid and bile acid metabolism, extracellular matrix interactions, and antibiotic resistance genes. Host gene expression described corresponding changes to bile acid and energy metabolism, and immune suppression. These changes imply that interactions at the host-gut microbiome interface contribute to spaceflight pathology and that these interactions might critically influence human health and long-duration spaceflight feasibility.

Oral Supplementation with the Short-Chain Fatty Acid Acetate Ameliorates Age-Related Arterial Dysfunction in Mice

Adverse changes in the gut microbiome with aging are an emerging mediator of arterial dysfunction, which contributes to cardiovascular disease (CVD) development. We investigated the therapeutic potential of enhancing the bioavailability of gut-derived short-chain fatty acids (SCFAs; produced from dietary fiber) for improving age-related arterial dysfunction. We performed gut microbial whole-genome sequencing in young (3 months) versus old (24 months) male C57BL/6N mice to explore changes in bacterial taxonomic abundance and functional pathways with aging and relations to arterial function. We then supplemented young and old mice with the SCFA acetate in drinking water versus controls and versus a high-fiber diet for 8-10 weeks to test the effects of these interventions on vascular function and explore potential mechanisms. Of the various differences in the gut microbiomes of old mice, lower SCFA-producing capacity (taxonomic abundance and functional pathways) stood out as a key feature related to worse arterial function after adjusting for age. Acetate supplementation and a high-fiber diet reversed ~30% of the age-related increase in aortic pulse wave velocity (stiffness) and fully restored carotid artery endothelium-dependent dilation (endothelial function) to young levels. Acetate and a high-fiber diet reduced age-related increases in systemic inflammation. We also found that improvements in endothelial function were likely mediated by suppressed early growth response-1 signaling using innovative siRNA-based knockdown in isolated arteries. There were no effects of the interventions in young mice. Acetate supplementation was comparably effective for ameliorating arterial dysfunction with aging as a high-fiber diet and thus shows promise for reducing CVD risk in older adults.

OCTOPUS: Disk-based, Multiplatform, Mobile-friendly Metagenomics Classifier

Portable genomic sequencers such as Oxford Nanopore's MinION enable real-time applications in clinical and environmental health. However, there is a bottleneck in the downstream analytics when bioinformatics pipelines are unavailable, e.g., when cloud processing is unreachable due to absence of Internet connection, or only low-end computing devices can be carried on site. Here we present a platform-friendly software for portable metagenomic analysis of Nanopore data, the Oligomer-based Classifier of Taxonomic Operational and Pan-genome Units via Singletons (OCTOPUS). OCTOPUS is written in Java, reimplements several features of the popular Kraken2 and KrakenUniq software, with original components for improving metagenomics classification on incomplete/sampled reference databases, making it ideal for running on smartphones or tablets. OCTOPUS obtains sensitivity and precision comparable to Kraken2, while dramatically decreasing (4- to 16-fold) the false positive rate, and yielding high correlation on real-word data. OCTOPUS is available along with customized databases at https://github.com/DataIntellSystLab/OCTOPUS and https://github.com/Ruiz-HCI-Lab/OctopusMobile.

The Effects of Aspirin Intervention on Inflammation-Associated Lingual Bacteria: A Pilot Study from a Randomized Clinical Trial

Several bacterial taxa enriched in inflammatory bowel diseases and colorectal cancer (CRC) are found in the oral cavity. We conducted a pilot study nested within a six-week aspirin intervention in a randomized placebo-controlled trial to test their response to aspirin intervention. Fifty healthy subjects, 50-75 years old, were randomized to receive 325 mg aspirin (n = 30) or placebo (n = 20) orally once daily for six weeks. Oral tongue swabs were collected at baseline and week six. We estimated the association between aspirin use and the temporal changes in the relative abundance of pre-specified genus level taxa from pre- to post-treatment. The temporal change in relative abundance differed for eight genus level taxa between the aspirin and placebo groups. In the aspirin group, there were significant increases in the relative abundances of Neisseria, Streptococcus, Actinomyces, and Rothia and significant decreases in Prevotella, Veillonella, Fusobacterium, and Porphyromonas relative to placebo. The log ratio of Neisseria to Fusobacterium declined more in the aspirin group than placebo, signaling a potential marker associated with aspirin intervention. These preliminary findings should be validated using metagenomic sequencing and may guide future studies on the role of aspirin on taxa in various oral ecological niches.

PM-profiler: a high-resolution and fast tool for taxonomy annotation of amplicon-based microbiome

Amplicon sequencing stands as a cornerstone in microbiome profiling, yet concerns persist regarding its resolution and accuracy. The enhancement of reference databases and annotations marks a new era for 16S rRNA-based profiling. Capitalizing on this potential, we introduce PM-profiler, a novel tool for profiling amplicon short reads. PM-profiler is implemented by C++-based advanced algorithms, such as pre-allocated hash for reference construction, hybrid and dynamic short-read matching, big-data-guided dual-mode hierarchical taxonomy annotation strategy, and full-procedure parallel computing. This tool delivers species-level resolution and ultrafast speed for large-scale microbiomes, surpassing alignment-based approaches and the Naïve-Bayesian model. Furthermore, recognizing the global uneven distribution of microbes, we delineate optimal annotation strategies for each sampling habitat based on microbial patterns over 270,000 microbiomes. Integrated with the established workflow of Parallel-Meta Suite and the latest curated reference databases, this endeavor offers a swift and dependable solution for high-precision microbiome surveys.IMPORTANCEOur study introduces PM-profiler, a new tool that deciphers the complexity of microbial communities. With advanced algorithms, flexible annotation strategies, and well-organized big-data, PM-profiler provides a faster and more accurate way to study on microbiomes, paving the way for discoveries that could improve our understanding of microbiomes and their impact on the world.

Precise antibiotic delivery to the lung infection microenvironment boosts the treatment of pneumonia with decreased gut dysbiosis

Bacterial pneumonia is a common disease with significant health risks. However, the overuse antibiotics in clinics face challenges such as inadequate targeting and limited drug utilization, leading to drug resistance and gut dysbiosis. Herein, a dual-responsive lung inflammatory tissue targeted nanoparticle (LITTN), designed for targeting lung tissue and bacteria, is screened from a series of prepared nanoparticles consisting of permanent cationic lipids, acid-responsive lipids, and reactive oxygen species-responsive and phenylboronic acid-modified lipids with different surface properties. Such nanoparticle is further verified to enhance the adsorption of vitronectin in serum. Additionally, the optimized nanoparticle exhibits more positive charge and coordination of boric acid with cis-diol in the infected microenvironment, facilitating electrostatic interactions with bacteria and biofilm penetration. Importantly, the antibacterial efficiency of dual-responsive rifampicin-loaded LITTN (Rif@LITTN) against methicillin-resistant staphylococcus aureus is 10 times higher than that of free rifampicin. In a mouse model of bacterial pneumonia, the intravenous administration of Rif@LITTN could precisely target the lungs, localize in the lung infection microenvironment, and trigger the responsive release of rifampicin, thereby effectively alleviating lung inflammation and reducing damage. Notably, the targeted delivery of rifampicin helps protect against antibiotic-induced changes in the gut microbiota. This study establishes a new strategy for precise delivery to the lung-infected microenvironment, promoting treatment efficacy while minimizing the impact on gut microbiota. STATEMENT OF SIGNIFICANCE: Intravenous antibiotics play a critical role in clinical care, particularly for severe bacterial pneumonia. However, the inability of antibiotics to reach target tissues causes serious side effects, including liver and kidney damage and intestinal dysbiosis. Therefore, achieving precise delivery of antibiotics is of great significance. In this study, we developed a novel lung inflammatory tissue-targeted nanoparticle that could target lung tissue after intravenous administration and then target the inflammatory microenvironment to trigger dual-responsive antibiotics release to synergistically treat pneumonia while maintaining the balance of gut microbiota and reducing the adverse effects of antibiotics. This study provides new ideas for targeted drug delivery and reference for clinical treatment of pneumonia.

A Standard Pipeline for Analyzing the Endometrial Microbiome

The endometrial microbiome is a rapidly advancing field of research, particularly in obstetrics and gynecology, as it has been found to be linked with obstetric complications and potential impacts on fertility. The diversity of microorganisms presents in the endometrium, along with their metabolites, can influence reproductive outcomes by modulating the local immune environment of the uterus. However, a major challenge in advancing our understanding of the endometrial microbiota lies in the heterogeneity of available studies, which vary in terms of patient selection, control groups, collection methods and analysis methodologies. In this study, we propose a detailed pipeline for endometrial microbiome analysis, based on the most comprehensive prospective of 64 studies that have investigated the endometrial microbiome up to the present. Additionally, our review suggests that a dominance of Lactobacilli in the endometrium may be associated with improved reproductive prognosis, including higher implantation rates and lower miscarriage rates. By establishing a standardized pipeline, we aim to facilitate future research, enabling better comparison and correlation of bacterial communities with the health status of patients, including fertility-related issues.

Considerations for performing companion animal skin microbiome studies

The microbiome field has grown significantly in the past decade, and published studies have provided an overview of the microorganisms inhabiting the skin of companion animals. With the continued growth and interest in this field, concerns have been raised regarding sample collection methods, reagent contamination, data processing and environmental factors that may impair data interpretation (especially as related to low-biomass skin samples). In order to assure transparency, it is important to report all steps from sample collection to data analysis, including use of proper controls, and to make sequence data and sample metadata publicly available. Whilst interstudy variation will continue to exist, efforts to standardise methods will reduce confounding variables, and allow for reproducibility and comparability of results between studies. Companion animal microbiome studies often include clinical cases, and small sample sizes may result in lack of statistical significance within small datasets. The ability to combine results from standardised studies through meta-analyses would mitigate the limitations of these smaller studies, providing for more robust interpretation of results which could then inform clinical decisions. In this narrative review, we aim to present considerations for designing a study to evaluate the skin microbiome of companion animals, from conception to data analysis.

Association of microbial community structure with gill disease in marine-stage farmed Atlantic salmon (Salmo salar); a yearlong study

BACKGROUND

Understanding the relationship between resident microbiota and disease in cultured fish represents an important and emerging area of study. Marine gill disorders in particular are considered an important challenge to Atlantic salmon (Salmo salar) aquaculture, however relatively little is known regarding the role resident gill microbiota might play in providing protection from or potentiating different gill diseases. Here, 16S rRNA sequencing was used to examine the gill microbiome alongside fish health screening in farmed Atlantic salmon. Results were used to explore the relationship between microbial communities and gill disease.

RESULTS

Microbial community restructuring was observed throughout the sampling period and linked to varied drivers of change, including environmental conditions and severity of gill pathology. Taxa with significantly greater relative abundance on healthier gills included isolates within genus Shewanella, and taxa within family Procabacteriaceae. In contrast, altered abundance of Candidatus Branchiomonas and Rubritalea spp. were associated with damaged gills. Interestingly, more general changes in community richness and diversity were not associated with altered gill health, and thus not apparently deleterious to fish. Gross and histological gill scoring demonstrated seasonal shifts in gill pathology, with increased severity of gill damage in autumn. Specific infectious causes that contributed to observed pathology within the population included the gill disorder amoebic gill disease (AGD), however due to the uncontrolled nature of this study and likely mixed contribution of various causes of gill disease to observed pathology results do not strongly support an association between the microbial community and specific infectious or non-infectious drivers of gill pathology.

CONCLUSIONS

Results suggest that the microbial community of farmed Atlantic salmon gills undergo continual restructuring in the marine environment, with mixed influences upon this change including environmental, host, and pathogenic factors. A significant association of specific taxa with different gill health states suggests these taxa might make meaningful indicators of gill health. Further research with more frequent sampling and deliberate manipulation of gills would provide important advancement of knowledge in this area. Overall, although much is still to be learnt regarding what constitutes a healthy or maladapted gill microbial community, the results of this study provide clear advancement of the field, providing new insight into the microbial community structure of gills during an annual production cycle of marine-stage farmed Atlantic salmon.

Updated perspectives on the contribution of the microbiome to the pathogenesis of mucositis using the MASCC/ISOO framework

Advances in the treatment of cancer have significantly improved mortality rates; however, this has come at a cost, with many treatments still limited by their toxic side effects. Mucositis in both the mouth and gastrointestinal tract is common following many anti-cancer agents, manifesting as ulcerative lesions and associated symptoms throughout the alimentary tract. The pathogenesis of mucositis was first defined in 2004 by Sonis, and almost 20 years on, the model continues to be updated reflecting ongoing research initiatives and more sophisticated analytical techniques. The most recent update, published by the Multinational Association for Supportive Care in Cancer and the International Society for Oral Oncology (MASCC/ISOO), highlights the numerous co-occurring events that underpin mucositis development. Most notably, a role for the ecosystem of microorganisms that reside throughout the alimentary tract (the oral and gut microbiota) was explored, building on initial concepts proposed by Sonis. However, many questions remain regarding the true causal contribution of the microbiota and associated metabolome. This review aims to provide an overview of this rapidly evolving area, synthesizing current evidence on the microbiota's contribution to mucositis development and progression, highlighting (i) components of the 5-phase model where the microbiome may be involved, (ii) methodological challenges that have hindered advances in this area, and (iii) opportunities for intervention.

Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar

Background

Tracking the spread of antibiotic resistant bacteria is critical to reduce global morbidity and mortality associated with human and animal infections. There is a need to understand the role that wild animals in maintenance and transfer of antibiotic resistance genes (ARGs).

Methods

This study used metagenomics to identify and compare the abundance of bacterial species and ARGs detected in the gut microbiomes from sympatric humans and wild mouse lemurs in a forest-dominated, roadless region of Madagascar near Ranomafana National Park. We examined the contribution of human geographic location toward differences in ARG abundance and compared the genomic similarity of ARGs between host source microbiomes.

Results

Alpha and beta diversity of species and ARGs between host sources were distinct but maintained a similar number of detectable ARG alleles. Humans were differentially more abundant for four distinct tetracycline resistance-associated genes compared to lemurs. There was no significant difference in human ARG diversity from different locations. Human and lemur microbiomes shared 14 distinct ARGs with highly conserved in nucleotide identity. Synteny of ARG-associated assemblies revealed a distinct multidrug-resistant gene cassette carrying dfrA1 and aadA1 present in human and lemur microbiomes without evidence of geographic overlap, suggesting that these resistance genes could be widespread in this ecosystem. Further investigation into intermediary processes that maintain drug-resistant bacteria in wildlife settings is needed.

Unassigning bacterial species for microbiome studies

The method of 16S rRNA marker gene sequencing has fueled microbiome research and continues to be relevant. A perceived weakness of the method is that taxonomic assignments are not possible to make at the rank of species. We show that by working to rule out bacterial or archaeal species membership, we can provide an answer that is more accurate and useful. The Unassigner software operates on 16S rRNA marker gene data and computes a rule-out probability for species membership using a beta-binomial distribution. We demonstrate that our approach is accurate based on full-genome comparisons. Our method is consistent with existing approaches and dramatically improves on them based on the percentage of reads it can associate with a species in a sample. The software is available at https://github.com/PennChopMicrobiomeProgram/unassigner.IMPORTANCEWhile existing methods do not provide reliable species-level assignments for 16S rRNA marker gene data, the Unassigner software solves this problem by ruling out species membership, allowing researchers to reason at the species level.

Comparative evaluation of 16S rRNA primer pairs in identifying nitrifying guilds in soils under long-term organic fertilization and water management

Compared with 454 sequencing technology, short-read sequencing (e.g., Illumina) technology generates sequences of high accuracy, but limited length (<500 bp). Such a limitation can prove that studying a target gene using a large amplicon (>500 bp) is challenging. The ammonia monooxygenase subunit A (amoA) gene of ammonia-oxidizing archaea (AOA), which plays a crucial part in the nitrification process, is such a gene. By providing a full overview of the community of a functional microbial guild, 16S ribosomal ribonucleic acid (rRNA) gene sequencing could overcome this problem. However, it remains unclear how 16S rRNA primer selection influences the quantification of relative abundance and the identification of community composition of nitrifiers, especially AOA. In the present study, a comparison was made between the performance of primer pairs 338F-806R, 515F-806R, and 515F-907R to a shotgun metagenome approach. The structure of nitrifier communities subjected to different long-term organic matter amendment and water management protocols was assessed. Overall, we observed higher Chao1 richness diversity of soil total bacteria by using 515F-806R compared to 338F-806R and 515F-907R, while higher Pielou's evenness diversity was observed by using 515F-806R and 515F-907R compared to 338F-806R. The studied primer pairs revealed different performances on the relative abundance of Thaumarchaeota, AOB, and NOB. The Thaumarchaeota 16S rRNA sequence was rarely detected using 338F-806R, while the relative abundances of Thaumarchaeota detected using 515F-806R were higher than those detected by using 515F-907R. AOB showed higher proportions in the 338F-806R and 515F-907R data, than in 515F-806R data. Different primers pairs showed significant change in relative proportion of NOB. Nonetheless, we found consistent patterns of the phylotype distribution of nitrifiers in different treatments. Nitrosopumilales (NP) and Nitrososphaerales (NS) clades were the dominant members of the AOA community in soils subject to controlled irrigation, whereas Ca. Nitrosotaleales (NT) and NS clades dominated the AOA community in soils subject to flooding irrigation. Nitrospira lineage II was the dominant NOB phylotype in all samples. Overall, ideal 16S rRNA primer pairs were identified for the analysis of nitrifier communities. Moreover, NP and NT clades of AOA might have distinct environmental adaptation strategies under different irrigation treatments.

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.

Baseline gut microbiota profiles affect treatment response in patients with depression

The role of the gut microbiota in the pathophysiology of depression has been explored in numerous studies, which have confirmed that the baseline gut microbial profiles of patients with depression differ from those of healthy individuals. The gut microbiome affects metabolic activity in the immune and central nervous systems and regulates intestinal ecology through the neuroendocrine system. Additionally, baseline changes in the gut microbiota differed among patients with depression who demonstrated varying treatment response. Currently, probiotics are an emerging treatment for depression; however, the efficacy of modulating the gut microbiota in the treatment of depression remains uncertain. Additionally, the mechanisms by which changes in the gut microbiota affect treatment response in patients with depression remain unclear. In this review, we aimed to summarize the differences in the baseline gut microbiota between the remission and non-remission groups after antidepressant therapy. Additionally, we summarized the possible mechanisms that may contribute to antidepressant resistance through the effects of the gut microbiome on the immune and nervous systems, various enzymes, bioaccumulation, and blood-brain barrier, and provide a basis for treating depression by targeting the gut microbiota.

Enteric Populations of Escherichia coli are Likely to be Resistant to Phages Due to O Antigen Expression

There is a surfeit of bioinformatic data showing that bacteriophages abound in the enteric microbiomes of humans. What is the contribution of these viruses in shaping the bacterial strain and species composition of the gut microbiome and how are these phages maintained over time? To address these questions, we performed experiments with Escherichia coli and phages isolated from four fecal microbiota transplantation (FMT) doses as representative samples of non-dysbiotic enteric microbiota and develop and analyze the properties of a mathematical model of the population and evolutionary dynamics of bacteria and phage. Our models predict and experiments confirm that due to production of the O antigen, E. coli in the enteric microbiome are likely to be resistant to infection with co-occurring phages. Furthermore, our modeling suggests that the phages can be maintained in the population due to the high rates of host transition between resistant and sensitive states, which we call leaky resistance. Based on our observations and model predictions, we postulate that the phages found in the human gut are likely to play little role in shaping the composition of E. coli at the strain level in the enteric microbiome in healthy individuals. How general this is for other species of bacteria in the enteric flora is not yet clear, although O antigen expression is common across many taxa.

Harnessing human microbiomes for disease prediction

The human microbiome has been increasingly recognized as having potential use for disease prediction. Predicting the risk, progression, and severity of diseases holds promise to transform clinical practice, empower patient decisions, and reduce the burden of various common diseases, as has been demonstrated for cardiovascular disease or breast cancer. Combining multiple modifiable and non-modifiable risk factors, including high-dimensional genomic data, has been traditionally favored, but few studies have incorporated the human microbiome into models for predicting the prospective risk of disease. Here, we review research into the use of the human microbiome for disease prediction with a particular focus on prospective studies as well as the modulation and engineering of the microbiome as a therapeutic strategy.

The root canal microbiome diversity and function. A whole-metagenome shotgun analysis

AIM

To evaluate the root canal microbiome composition and bacterial functional capability in cases of primary and secondary apical periodontitis utilizing whole-metagenome shotgun sequencing.

METHODOLOGY

Twenty-two samples from patients with primary root canal infections, and 18 samples obtained from previously treated teeth currently diagnosed with apical periodontitis were analysed with whole-metagenome shotgun sequencing at a depth of 20 M reads. Taxonomic and functional gene annotations were made using MetaPhlAn3 and HUMAnN3 software. The Shannon and Chao1 indices were utilized to measure alpha diversity. Differences in community composition were evaluated utilizing analysis of similarity (ANOSIM) using Bray-Curtis dissimilarities. The Wilcoxon rank sum test was used to compare differences in taxa and functional genes.

RESULTS

Microbial community variations within a community were significantly lower in secondary relative to primary infections (alpha diversity p = .001). Community composition was significantly different in primary versus secondary infection (R = .11, p = .005). The predominant taxa observed among samples (>2.5%) were Pseudopropionibacterium propionicum, Prevotella oris, Eubacterium infirmum, Tannerella forsythia, Atopobium rimae, Peptostreptococcus stomatis, Bacteroidetes bacterium oral taxon 272, Parvimonas micra, Olsenella profusa, Streptococcus anginosus, Lactobacillus rhamnosus, Porphyromonas endodontalis, Pseudoramibacter alactolyticus, Fusobacterium nucleatum, Eubacterium brachy and Solobacterium moorei. The Wilcoxon rank test revealed no significant differences in relative abundances of functional genes in both groups. Genes with greater relative abundances (top 25) were associated with genetic, signalling and cellular processes including the iron and peptide/nickel transport system. Numerous genes encoding toxins were identified: exfoliative toxin, haemolysins, thiol-activated cytolysin, phospholipase C, cAMP factor, sialidase, and hyaluronic glucosaminidase.

CONCLUSIONS

Despite taxonomic differences between primary and secondary apical periodontitis, the functional capability of the microbiomes was similar.

Microbial oases in the ice: A state-of-the-art review on cryoconite holes as diversity hotspots and their scientific connotations

Cryoconite holes, small meltwater pools on the surface of glaciers and ice sheets, represent extremely cold ecosystems teeming with diverse microbial life. Cryoconite holes exhibit greater susceptibility to the impacts of climate change, underlining the imperative nature of investigating microbial communities as an essential module of polar and alpine ecosystem monitoring efforts. Microbes in cryoconite holes play a critical role in nutrient cycling and can produce bioactive compounds, holding promise for industrial and pharmaceutical innovation. Understanding microbial diversity in these delicate ecosystems is essential for effective conservation strategies. Therefore, this review discusses the microbial diversity in these extreme environments, aiming to unveil the complexity of their microbial communities. The current study envisages that cryoconite holes as distinctive ecosystems encompass a multitude of taxonomically diverse and functionally adaptable microorganisms that exhibit a rich microbial diversity and possess intricate ecological functions. By investigating microbial diversity and ecological functions of cryoconite holes, this study aims to contribute valuable insights into the broader field of environmental microbiology and enhance further understanding of these ecosystems. This review seeks to provide a holistic overview regarding the formation, evolution, characterization, and molecular adaptations of cryoconite holes. Furthermore, future research directions and challenges underlining the need for long-term monitoring, and ethical considerations in preserving these pristine environments are also provided. Addressing these challenges and resolutely pursuing future research directions promises to enrich our comprehension of microbial diversity within cryoconite holes, revealing the broader ecological and biogeochemical implications. The inferences derived from the present study will provide researchers, ecologists, and policymakers with a profound understanding of the significance and utility of cryoconite holes in unveiling the microbial diversity and its potential applications.

Time of sample collection is critical for the replicability of microbiome analyses

As the microbiome field moves from descriptive and associative research to mechanistic and interventional studies, being able to account for all confounding variables in the experimental design, which includes the maternal effect1, cage effect2, facility differences3, as well as laboratory and sample handling protocols4, is critical for interpretability of results. Despite significant procedural and bioinformatic improvements, unexplained variability and lack of replicability still occur. One underexplored factor is that the microbiome is dynamic and exhibits diurnal oscillations that can change microbiome composition5-7. In this retrospective analysis of 16S amplicon sequencing studies in male mice, we show that sample collection time affects the conclusions drawn from microbiome studies and its effect size is larger than those of a daily experimental intervention or dietary changes. The timing of divergence of the microbiome composition between experimental and control groups is unique to each experiment. Sample collection times as short as only 4 hours apart can lead to vastly different conclusions. Lack of consistency in the time of sample collection may explain poor cross-study replicability in microbiome research. The impact of diurnal rhythms on the outcomes and study design of other fields is unknown but likely significant.

With a little help from my friends: the roles of microbial symbionts in insect populations and communities

To understand insect abundance, distribution and dynamics, we need to understand the relevant drivers of their populations and communities. While microbial symbionts are known to strongly affect many aspects of insect biology, we lack data on their effects on populations or community processes, or on insects' evolutionary responses at different timescales. How these effects change as the anthropogenic effects on ecosystems intensify is an area of intense research. Recent developments in sequencing and bioinformatics permit cost-effective microbial diversity surveys, tracking symbiont transmission, and identification of functions across insect populations and multi-species communities. In this review, we explore how different functional categories of symbionts can influence insect life-history traits, how these effects could affect insect populations and their interactions with other species, and how they may affect processes and patterns at the level of entire communities. We argue that insect-associated microbes should be considered important drivers of insect response and adaptation to environmental challenges and opportunities. We also outline the emerging approaches for surveying and characterizing insect-associated microbiota at population and community scales. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Comparative analysis of commercially available kits for optimal DNA extraction from bovine fecal samples

In the field of metagenomic research, the choice of DNA extraction methods plays a pivotal yet often underestimated role in shaping the reliability and interpretability of microbial community data. This study delves into the impact of five commercially available DNA extraction kits on the analysis of bovine fecal microbiota. Recognizing the importance of accurate DNA extraction in elucidating microbial community dynamics, we systematically assessed DNA yield, quality, and microbial composition across these kits using 16S rRNA gene sequencing. Notably, the FastDNA spin soil kit yielded the highest DNA concentration, while significant variations in quality were observed across kits. Furthermore, differential abundance analysis revealed kit-specific biases that impacted taxa representation. Microbial richness and diversity were significantly influenced by the choice of extraction kit, with QIAamp DNA stool minikit, QIAamp Power Pro, and DNeasy PowerSoil outperforming the Stool DNA Kit. Principal-coordinate analysis revealed distinct clustering based on DNA isolation procedures, particularly highlighting the unique microbial community composition derived from the Stool DNA Kit. This study also addressed practical implications, demonstrating how kit selection influences the concentration of Gram-positive and Gram-negative bacterial taxa in samples. This research highlights the need for consideration of DNA extraction kits in metagenomic studies, offering valuable insights for researchers striving to advance the precision and depth of microbiota analyses in ruminants.

Precision medicine for asthma treatment: Unlocking the potential of the epigenome and microbiome

Asthma is a leading worldwide biomedical concern. Patients can experience life-threatening worsening episodes (exacerbations) usually controlled by anti-inflammatory and bronchodilator drugs. However, substantial heterogeneity in treatment response exists, and a subset of patients with unresolved asthma carry the major burden of this disease. The study of the epigenome and microbiome might bridge the gap between human genetics and environmental exposure to partially explain the heterogeneity in drug response. This review aims to provide a critical examination of the existing literature on the microbiome and epigenetic studies examining associations with asthma treatments and drug response, highlight convergent pathways, address current challenges, and offer future perspectives. Current epigenetic and microbiome studies have shown the bilateral relationship between asthma pharmacologic interventions and the human epigenome and microbiome. These studies, focusing on corticosteroids and to a lesser extent on bronchodilators, azithromycin, immunotherapy, and mepolizumab, have improved the understanding of the molecular basis of treatment response and identified promising biomarkers for drug response prediction. Immune and inflammatory pathways (eg, IL-2, TNF-α, NF-κB, and C/EBPs) underlie microbiome-epigenetic associations with asthma treatment, representing potential therapeutic pathways to be targeted. A comprehensive evaluation of these omics biomarkers could significantly contribute to precision medicine and new therapeutic target discovery.

Pinpointing the microbiota of tardigrades: What is really there?

Microbiota are considered significant in the biology of tardigrades, yet their diversity and distribution remain largely unexplored. This is partly due to the methodological challenges associated with studying the microbiota of small organisms that inhabit microbe-rich environments. In our study, we characterized the microbiota of 31 species of cultured tardigrades using 16S rRNA amplicon sequencing. We employed various sample preparation strategies and multiple types of controls and estimated the number of microbes in samples using synthetic DNA spike-ins. We also reanalysed data from previous tardigrade microbiome studies. Our findings suggest that the microbial communities of cultured tardigrades are predominantly composed of bacterial genotypes originating from food, medium, or reagents. Despite numerous experiments, we found it challenging to identify strains that were enriched in certain tardigrades, which would have indicated likely symbiotic associations. Putative tardigrade-associated microbes rarely constituted more than 20% of the datasets, although some matched symbionts identified in other studies. We also uncovered serious contamination issues in previous tardigrade microbiome studies, casting doubt on some of their conclusions. We concluded that tardigrades are not universally dependent on specialized microbes. Our work underscores the need for rigorous safeguards in studies of the microbiota of microscopic organisms and serves as a cautionary tale for studies involving samples with low microbiome abundance.

Immunomodulation and inflammation: Role of GLP-1R and GIPR expressing cells within the gut

Glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are peptide hormones produced by enteroendocrine cells in the small intestine. Despite being produced in the gut, the leveraging of their role in potentiating glucose-stimulated insulin secretion, also known as the incretin effect, has distracted from discernment of direct intestinal signaling circuits. Both preclinical and clinical evidence have highlighted a role for the incretins in inflammation. In this review, we highlight the discoveries of GLP-1 receptor (GLP-1R)+ natural (TCRαβ and TCRγδ) and induced (TCRαβ+CD4+ cells and TCRαβ+CD8αβ+) intraepithelial lymphocytes. Both endogenous signaling and pharmacological activation of GLP-1R impact local and systemic inflammation, the gut microbiota, whole-body metabolism, as well as the control of GLP-1 bioavailability. While GIPR signaling has been documented to impact hematopoiesis, the impact of these bone marrow-derived cells in gut immunology is not well understood. We uncover gaps in the literature of the evaluation of the impact of sex in these GLP-1R and GIP receptor (GIPR) signaling circuits and provide speculations of the maintenance roles these hormones play within the gut in the fasting-refeeding cycles. GLP-1R agonists and GLP-1R/GIPR agonists are widely used as treatments for diabetes and weight loss, respectively; however, their impact on gut homeostasis has not been fully explored. Advancing our understanding of the roles of GLP-1R and GIPR signaling within the gut at homeostasis as well as metabolic and inflammatory diseases may provide targets to improve disease management.

The microbiome in recurrent pregnancy loss - A scoping review

Recurrent pregnancy loss (RPL) is a troubling condition that affects couples worldwide. Despite extensive research efforts, many RPL cases remain unexplained, highlighting the need for novel approaches to unravel its underlying mechanisms. Recent advances in microbiome research have shed light on the potential role of the microbiome in reproductive health and outcomes. Based on a systematic literature research, this review aims to comprehensively explore the current understanding of the microbiome's involvement in RPL, focusing on the vaginal, endometrial, and gut microbiomes. Evidence from the available studies is examined to explain the relationship between the microbiome and RPL. Furthermore, we discuss the diagnostic potential of the microbiome, therapeutic interventions, and future directions in microbiome research for RPL. Understanding the complex interactions between the microbiome and reproductive health holds promise for developing targeted interventions to help patients today diagnosed as unexplained.

New avenues for potentially seeking microbial responses to climate change beneath Antarctic ice shelves

The signs of climate change are undeniable, and the impact of these changes on ecosystem function heavily depends on the response of microbes that underpin the food web. Antarctic ice shelf is a massive mass of floating ice that extends from the continent into the ocean, exerting a profound influence on global carbon cycles. Beneath Antarctic ice shelves, marine ice stores valuable genetic information, where marine microbial communities before the industrial revolution are archived. Here, in this proof-of-concept, by employing a combination of single-cell technologiesand metagenomics, we have been able to sequence frozen microbial DNA (≈300 years old) stored in the marine ice core B15 collected from the Filchnner-Ronne Ice Shelf. Metagenomic data indicated that Proteobacteria and Thaumarchaeota (e.g., Nitrosopumilus spp.), followed by Actinobacteria (e.g., Actinomarinales), were abundant. Remarkably, our data allow us to "travel to the past" and calibrate genomic and genetic evolutionary changes for ecologically relevant microbes and functions, such as Nitrosopumilus spp., preserved in the marine ice (≈300 years old) with those collected recently in seawater under an ice shelf (year 2017). The evolutionary divergence for the ammonia monooxygenase gene amoA involved in chemolithoautotrophy was about 0.88 amino acid and 2.8 nucleotide substitution rate per 100 sites in a century, while the accumulated rate of genomic SNPs was 2,467 per 1 Mb of genome and 100 years. Whether these evolutionary changes remained constant over the last 300 years or accelerated during post-industrial periods remains an open question that will be further elucidated.

IMPORTANCE

Several efforts have been undertaken to predict the response of microbes under climate change, mainly based on short-term microcosm experiments under forced conditions. A common concern is that manipulative experiments cannot properly simulate the response of microbes to climate change, which is a long-term evolutionary process. In this proof-of-concept study with a limited sample size, we demonstrate a novel approach yet to be fully explored in science for accessing genetic information from putative past marine microbes preserved under Antarctic ice shelves before the industrial revolution. This potentially allows us estimating evolutionary changes as exemplified in our study. We advocate for gathering a more comprehensive Antarctic marine ice core data sets across various periods and sites. Such a data set would enable the establishment of a robust baseline, facilitating a better assessment of the potential effects of climate change on key genetic signatures of microbes.

Development of MetaXplore: An Interactive Tool for Targeted Metagenomic Analysis

Over the last decades, the analysis of complex microbial communities by high-throughput sequencing of marker gene amplicons has become routine work for many research groups. However, the main challenges faced by scientists who want to make use of the generated sequencing datasets are the lack of expertise to select a suitable pipeline and the need for bioinformatics or programming skills to apply it. Here, we present MetaXplore, an interactive, user-friendly platform that enables the discovery and visualization of amplicon sequencing data. Currently, it provides a set of well-documented choices for downstream analysis, including alpha and beta diversity analysis, taxonomic composition, differential abundance analysis, identification of the core microbiome within a population, and biomarker analysis. These features are presented in a user-friendly format that facilitates easy customization and the generation of publication-quality graphics. MetaXplore is implemented entirely in the R language using the Shiny framework. It can be easily used locally on any system with R installed, including Windows, Mac OS, and most Linux distributions, or remotely via a web server without bioinformatic expertise. It can also be used as a framework for advanced users who can modify and expand the tool.

The potential importance of the built-environment microbiome and its impact on human health

There is increasing evidence that interactions between microbes and their hosts not only play a role in determining health and disease but also in emotions, thought, and behavior. Built environments greatly influence microbiome exposures because of their built-in highly specific microbiomes coproduced with myriad metaorganisms including humans, pets, plants, rodents, and insects. Seemingly static built structures host complex ecologies of microorganisms that are only starting to be mapped. These microbial ecologies of built environments are directly and interdependently affected by social, spatial, and technological norms. Advances in technology have made these organisms visible and forced the scientific community and architects to rethink gene-environment and microbe interactions respectively. Thus, built environment design must consider the microbiome, and research involving host-microbiome interaction must consider the built-environment. This paradigm shift becomes increasingly important as evidence grows that contemporary built environments are steadily reducing the microbial diversity essential for human health, well-being, and resilience while accelerating the symptoms of human chronic diseases including environmental allergies, and other more life-altering diseases. New models of design are required to balance maximizing exposure to microbial diversity while minimizing exposure to human-associated diseases. Sustained trans-disciplinary research across time (evolutionary, historical, and generational) and space (cultural and geographical) is needed to develop experimental design protocols that address multigenerational multispecies health and health equity in built environments.